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Last updated on November 15, 2020. This conference program is tentative and subject to change
Technical Program for Tuesday November 17, 2020
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TuA21 |
L-1 |
C1: Circuits and Systems |
Regular Session |
Chair: Onoye, Takao | Osaka University |
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11:00-11:15, Paper TuA21.1 | |
A Fault Detection Scheme for Reversible Circuits Using -Ve Control K-CNOT Based Circuit |
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Handique, Mousum | Assam University, Silchar-788011, Assam, India |
Deka, Jantindra Kumar | Indian Institute of Technology Guwahati, Guwahati-781039, Assam, |
Biswas, Santosh | Indian Institute of Technology Bhilai, Chhattisgarh 492015, Ind |
Keywords: Circuits and Systems
Abstract: The reversible
logic circuit is a prominent research area for its low-power design, and
also quantum computing. The development of synthesis and optimization
is a well-known problem in the reversible circuits. For ensuring the
high reliability and integrity performance of these circuits, the proper
testing technique will be required to detect and locate the faults. In
this paper, we consider the problem of reversible circuit testing,
specifically targeting the fault detection for the missing-gate fault
model in the k-CNOT based reversible circuit. It has been shown that n
number of test vectors is sufficient for the detection of all single
missing-gate faults (SMGFs), repeated-gate faults (RGFs), and partial
missing-gate faults (PMGFs) of the proposed fault detection scheme in a
reversible circuit with n inputs. Finally, we provide our experimental
results based on several benchmark circuits and also show the
comparative analysis with existing methods.
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11:15-11:30, Paper TuA21.2 | |
Single VDTA Based Grounded Memristor Model and Its Applications |
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Singh, Ankur | Indian Institute of Information Technology Guwahati, Assam, Indi |
Borah, Shekhar Suman | Indian Institute of Information Technology Guwahati, Assam, Indi |
Ghosh, Mourina | Indian Institute of Information Technology Guwahati, Assam, Indi |
Keywords: Circuits and Systems
Abstract: An
application-based memristor prototype by employing only a single Voltage
Difference Transconductance Amplifier (VDTA) as an active device and
one grounded MOS-capacitor is reported in this research article. The
transient analysis, pinched hysteresis loop for various frequencies
along with serial and parallel combinations of the memristor are also
examined. This grounded memristor design can suitably operate up-to MHz
ranges. As an application of the stated memristor prototype,
demodulation of grounded memristor-based Binary Frequency Shift Keying
(BFSK), Amplitude Demodulation and a realization of Schmitt trigger
configurations are shown. Moreover, the layout of this memristor is
performed which occupies an effective area of 1432μm2. The simulation
and layout of the entire design are implemented using Analog Design
Environment (ADE) tool of the Cadence Virtuoso.
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11:30-11:45, Paper TuA21.3 | |
CMOS CDBA Based 6th Order Inverse Filter Realization for Low-Power Applications |
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Borah, Shekhar Suman | Indian Institute of Information Technology Guwahati, Assam, Indi |
Singh, Ankur | Indian Institute of Information Technology Guwahati, Assam, Indi |
Ghosh, Mourina | Indian Institute of Information Technology Guwahati, Assam, Indi |
Keywords: Circuits and Systems
Abstract: This article
describes a realization of higher-order Inverse Band Pass Filter
(SO-IBPF) configuration for low-power applications based on Current
Differencing Buffered Amplifier (CDBA) as active elements and a few
passive components. The proposed structure is proficient to operate with
0.6V supply voltage, 0.45V bias voltage and dissipates 0.918mW power.
To justify the practicability of the proposed design, frequency and
phase response outputs are produced through PSPICE simulation using
0.18牛 TSMC CMOS process parameters. The other performance
investigations such as sensitivity, non-ideality, input-output noise
analysis, temperature variations, Monte-Carlo analysis and percentage of
total harmonic distortion (%THD) are also examined. Moreover, the
proposed configuration is experimentally tested using commercially
available IC AD844AN to verify the theoretical propositions and
simulation results. The layout of the proposed structure is also
realized with Analog Design Environment tool (ADE) of Cadence/ spectre
environment.
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11:45-12:00, Paper TuA21.4 | |
Construction of Obstacle-Avoiding Delay-Driven GNR Routing Tree |
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Yan, Jin-Tai | Tainan National University of the Arts |
Huang, Po-Yuan | Chung-Hua University |
Wang, Chien-Yi | Chung-Hua University |
Keywords: Circuits and Systems
Abstract: It is known
that graphene nanoribbon (GNR) based devices and interconnects can be
treated to be better alternative in nano-scale designs. In this paper,
given a source pin and a set of target pins inside a GNR routing plane
with a set of rectangular obstacles, based on the selection of the
possible obstacle-avoiding delay-driven routing paths on the target
pins, an efficient routing algorithm can be proposed to construct an
obstacle-avoiding delay-driven GNR routing tree with minimizing the
total wirelength for the target pins. Compared with Das痴 algorithm with
obstacle avoidance on total wirelength and maximum source-to-target
delay, the experimental results show that our proposed routing algorithm
only uses 7.87% of the extra wirelength to reduce 23.42% of the maximum
delay in the construction of an obstacle-avoiding delay-driven GNR
routing tree for 6 tested examples on the average.
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12:00-12:15, Paper TuA21.5 | |
Investigation of Analog Single Event Transient on Low Noise Amplifier in X and Ka Bands |
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Periyasamy, Rajendiran | Ssn College of Engiineering, Anna University |
Raj, Srinivasan | Ssn College of Engiineering, Anna University |
Keywords: Circuits and Systems, Devices, Materials & Processing, Wireless Communications & Networks
Abstract: In this paper,
we have analyzed the analog single event transient (ASET) performance of
MOSFET based LNA circuits at two different frequencies (one in X band
and another in Ka-band) to study the frequency dependency. The ASET
impact is analyzed in the time and frequency domains under two
scenarios, (i) absence of the RF input signal and (ii) the Presence of
the RF input signal. In the first case, the collected charge (Qc) is
taken as metric in the time domain and the second case, the spectrogram
is used to analyze the disturbing presence in the fundamental frequency
due to radiation strike. Based on the QC, the LNA used in X-band is more
vulnerable compared to LNA used in Ka-band. The spectrogram results
show that the LNA output spectrum in the X-band is disturbed more and
stronger to the radiation strike compared to the LNA used in Ka-band
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TuA22 |
L-2 |
B1: Biomedical Engineering |
Regular Session |
Chair: Huang, Ming | NAIST |
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11:00-11:15, Paper TuA22.1 | |
Automatic
Fetal Head Candidate Localization from 2D Ultrasound Images Using Haar
Cascade Classifier and Enhanced Localization Algorithm |
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Rismonita, Tessya | Bandung Institute of Technology |
Handayani, Astri | Bandung Institute of Technology |
Avalokita, Devi Tara | Bandung Institute of Technology |
Setiawan, Agung W. | Institut Teknologi Bandung |
Keywords: Biomedical Engineering
Abstract: Fetal head
circumference (HC) is one of the fetal biometrics that is often used to
determine gestational age and monitor the fetal growth in the womb.
Nowadays, head circumference measurement from ultrasound images is
performed manually by a doctor or sonographer by drawing a line or
forming an ellipse to surround the fetal head. However, manual
annotations are prone to human error and intra-observer as well as
inter-observer variabilities. In this research, an automatic fetal head
candidate localization was implemented using Haar Cascade Classifier
(HCC) and further optimized by Enhanced Localization Algorithm (ELA).
The combination of HCC and ELA was evaluated on 703 ultrasound images of
the second trimester and 141 ultrasound images of the third trimester
using the Jaccard Index (JI), Dice Similarity Coefficient (DSC), and
Overlapped Area Ratio (OAR). The localization results showed that the
HCC + ELA produced an average JI of 90.5%, DSC of 94.58%, OAR of 97.77%
for the second trimester and an average JI of 88.17%, DSC of 93.33%, OAR
of 96.97% for the third trimester. Based on the three evaluation
parameters, we analyzed the factors affecting the accuracy of the
localization algorithm and the correspondence of the localization
results with the ellipse fitting outcome as the final process to
determine the fetal head circumference.
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11:15-11:30, Paper TuA22.2 | |
Predicting Short-Term Changing Blood GlucoseLevel of Diabetes Patients Using Noninvasive Data |
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Balasooriya, Kasuri | University of Moratuwa |
Nanayakkara, Nuwan D. | University of Moratuwa |
Keywords: Biomedical Engineering
Abstract: Diabetes is a
chronic disease in which the blood glucose level stays high over a
prolonged period. Uncontrolled diabetes put patients into critical
conditions when the blood glucose level moves outside the clinically
accepted range. Knowing the trend of the blood glucose level changes in
advance will give the ability to take corrective actions to maintain it
within the recommended levels. Continuous glucose monitoring (CGM)
devices with an associated prediction model integrated into insulin
pumps implanted in type 1 diabetic patients are able to predict the
future glucose level in real time. A few different techniques for
short-time glucose prediction have been reported incorporating past CGM
readings, insulin dosage and meals. However, future glucose level
predictions for patients without implanted insulin pumps are not
available. This paper presents a machine learning algorithm to implement
a short-term prediction model using non-invasive data; a past glucose
level (measured or previously predicted), drugs dosage, food
consumption, and life styles of diabetes patients. A deep learning time
series forecasting based Long short-term memory (LSTM) model is used to
predict the blood glucose level 30 minutes in the future. The model used
data from diabetic patients to predict the short-term blood glucose
levels with an accuracy level of 79.97%. The proposed model was able to
predict blood glucose levels 30-min in advance with an average daily
glucose levels error of 22.2 mg/dl.
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11:30-11:45, Paper TuA22.3 | |
Automatic Fetal Head Circumference Measurement in 2D Ultrasound Images Based on Optimized Fast Ellipse Fitting |
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Avalokita, Devi Tara | Bandung Institute of Technology |
Rismonita, Tessya | Bandung Institute of Technology |
Handayani, Astri | Bandung Institute of Technology |
Setiawan, Agung W. | Bandung Institute of Technology |
Keywords: Biomedical Engineering
Abstract: Gestational age
(GA) monitoring from fetal ultrasound imaging is one method to observe
pre-birth risk factors and to prepare early treatment for neonatal
problems. There are several parameters in an ultrasound image that can
be used to estimate GA, one of which is the fetal head circumference
(HC). However, fetal HC measurement is prone to error since it relies on
manual annotation by sonographer or obstetrician. This research aims to
design an algorithm to automatically calculate the fetal HC based on
optimized ellipse fitting on a localized region of interest (RoI)
previously defined as fetal head candidate area. Our optimization method
consists of pre-processing steps to exclude noise within the RoI and to
select the optimum representation of fetal head pixels to be processed
by the ellipse fitting algorithm. We managed to perform ellipse fitting
on 699 and 141 ultrasound images representing respectively the second
and third trimester pregnancies; with the average dice similarity
coefficient (DSC) of 95.27%ア6.25%, hausdorff distance (HD) of 3.51
mmア5.54 mm, a difference in fetal HC (DF) of -3.42 mmア13.66 mm, and an
absolute difference in fetal HC (ADF) of 6.53 mmア12.5 mm. The results
demonstrated that the presented method performed comparably to other
systems published in the literature. Moreover, our results represent an
evaluation of a significantly larger number of data compared to most of
the previous works.
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11:45-12:00, Paper TuA22.4 | |
Computer Aided Classification of Benign and Malignant Breast Lesions Using Maximum Response 8 Filter Bank and Genetic Algorithm |
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Bhowmick, Chiranjib | IIT Kharagpur |
Dutta, Pranab Kumar | IIT Kharagpur |
Mahadevappa, Manjunatha | IIT Kharagpur |
Keywords: Biomedical Engineering
Abstract: Breast Cancer
has very low survival rate when detected at later stages. Hence,
Computer Aided Diagnostic Models can assist the medical practitioners by
diagnosing reports without human intervention. In this paper the sample
size considered is 401(200 benign and 201 malignant images) and has
been acquired from the Digital Database for Screening Mammography. This
paper propose a novel method to detect breast malignancies using texton
based analysis. The filter bank that has been used here to obtain the
texton based response is the Maximum Response 8 Filter Bank. Further
Haralick's features from the Gray Level Co-occurence Matrix , histogram
based features from Local Binary Pattern and statistical features namely
skewness and kurtosis are extracted from each filter response. Genetic
Algorithm and Linear Discriminant Analysis has been used for feature
selection and feature reduction respectively. Classification is
performed using three classifiers namely Naive bayes, Logistic
Regression and Linear SVM. The proposed algorthm exhibit an Accuracy of
87.5% and Area under Curve of 0.95 using Logistic Regression classifier.
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12:00-12:15, Paper TuA22.5 | |
Effects of Myocardial Fat痴 Thickness and Myocardial Impedance on Bipolar Radiofrequency Cathode Ablation |
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Sun, Yao | The University of Aizu |
Zhu, Xin | The University of Aizu |
Nakamura, Keijiro | Toho University Ohashi Medical Center |
Keywords: Biomedical Engineering, Devices, Materials & Processing
Abstract: Radiofrequency
cathode ablation is an effective tool for the treatment of cardiac
arrhythmia. Bipolar ablation may provide a more localized lesion and
therefore prevent side effects and complications caused by cathode
ablation. However, myocardial impedance and heart fat痴 thickness may
have significant influence on the performance of bipolar ablation. In
this study, we perform computer simulation to study the influence of
myocardial impedance and heart fat痴 thickness on bipolar and unipolar
cathode ablation. Through computer simulation, we obtain and compare the
treatment effects under different configurations of cathode ablation.
The simulation results are generally consistent with experiment results.
Through our simulation, when the fat layer痴 thickness increases, the
bipolar ablation痴 heating effect decreases, but the final ablation
effect is still better than that of unipolar ablation. The ablation
performance is improved when myocardial impedance decreases. However,
the heating effect of the bipolar configuration is more sensitive to the
variation of myocardial impedance and fat layersthickness compared
with that of the unipolar configuration.
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TuA23 |
L-3 |
ML1: Machine Learning, Cloud and Data Analytics |
Regular Session |
Chair: Cheng, Junqiang | Beijing University of Posts and Telecommunications |
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11:00-11:15, Paper TuA23.1 | |
Tumor Budding Detection in H&E-Stained Images Using Deep Semantic Learning |
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Banaeeyan, Rasoul | Multimedia University |
Ahmad Fauzi, Mohammad Faizal | Multimedia University |
Chen, Wei | The Ohio State University Wexner Medical Center |
Knight, Debbie | The Ohio State University Wexner Medical Center |
Hampel, Heather | The Ohio State University Wexner Medical Center |
Frankel, Wendy L | The Ohio State University Wexner Medical Center |
Gurcan, Metin N | Wake Forest School of Medicine |
Keywords: Biomedical Engineering, Machine Learning, Cloud and Data Analytics, Signal and Image Processing
Abstract: Tumor buddings
(TB), a special formation of cancerous cells that bud from the tumor
front, are fast becoming the key indicator in modern clinical
applications where they play a significant role in prognostic and
evaluation of colorectal cancers in histopathological images. Recently,
computational methods have been rapidly evolving in the domain of
digital pathology, yet the literature lacks computerized approaches to
automate the localization and segmentation of TBs in hematoxylin and
eosin (H&E) stained images. This research addresses this very
challenging task of tumor budding detection in H&E images by
presenting different deep learning architectures designed for semantic
segmentation. The proposed design for a new Convolutional Neural Network
(CNN) incorporates convolution filters with different factors of
dilations. Multiple experiments based on a newly constructed colorectal
cancer histopathological image collection provided promising
performances. The best average intersection over union (IOU) for TB of
0.11, IOU for non-TB of 0.86, mean IOU of 0.49 and weighted IOU of 0.83
were observed.
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11:15-11:30, Paper TuA23.2 | |
ResCovNet: A Deep Learning-Based Architecture for COVID-19 Detection from Chest CT Scan Images |
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Dastider, Ankan Ghosh | Bangladesh University of Engineering and Technology |
Subah, Mohseu Rashid | Bangladesh University of Engineering and Technology |
Sadik, Farhan | Bangladesh University of Engineering and Technology |
Mahmud, Tanvir | Bangladesh University of Engineering and Technology |
Fattah, Shaikh Anowarul | Bangladesh University of Engineering and Technology |
Keywords: Biomedical Engineering, Disasters and Humanitarian Technology, Machine Learning, Cloud and Data Analytics
Abstract: Automatic
disease detection using machine learning-based techniques from X-ray and
computed tomography (CT) can play a major role in the frontline to
assist medical professionals during the current outbreak of COVID-19.
Fast diagnosis of the disease is the key to reduce the uncontrollable
spread of this life-threatening disease, where machine learning-based
applications can contribute greatly by predicting the situation of
patients so that professionals can decide accordingly. The major
drawbacks of detecting COVID-19 are its similarities with different
types of pneumonia, and the absence of properly labeled data.
Considering the ResNet152V2 as a backbone network, an efficient
architecture, namely ResCovNet is proposed to detect COVID-19 accurately
from chest CT scan images by separating it from three types of
pneumonia and normal cases. Otsu's thresholding is applied in the
pre-processing step to strengthen the features for the classification
network. With the use of proposed architecture, a very satisfactory
classification accuracy of 88.1% is achieved to separate COVID-19 from
all other four classes. Evaluating the performance of this study by
3-fold cross-validation, and comparison with related works prove that
this adroit algorithm provides an effective way to be implemented as a
diagnostic tool in the COVID-19 screening.
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11:30-11:45, Paper TuA23.3 | |
Leukemia Detection Mechanism through Microscopic Image and ML Techniques |
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Hossain, Mohammad Akter | United International University |
Sabik, Mubtasim Islam | United International University |
Muntasir, Ikramuzzaman | United International University |
Islam, AKM Muzahidul Islam | United International University |
Islam, Salekul | United International University |
Ahmed, Ashir | Kyushu University |
Keywords: Biomedical Engineering, Machine Learning, Cloud and Data Analytics
Abstract: This paper
focuses on Acute Lymphocytic Leukemia (ALL) as this is the most common
type of Leukemia in Bangladesh. It is common knowledge among
oncologists, that cancer is much easier to treat if it is detected in
the early stages. Thus the treatment needs to begin as early as
possible. We propose a hands-on approach in detecting the irregular
blood components (e.g., Neutrophils, Eosinophils, Basophils, Lymphocytes
and Monocytes) that are typically found in a cancer patient. In this
work, we first identify 14 attributes to prepare the dataset and
determine 4 major attributes that play a significant role in determining
a Leukemia patient. We have also collected 256 primary data from
Leukemia patient. The data is then processed using microscope to obtain
images and fetch into Faster-RCNN machine learning algorithm to predict
the odds of cancer cells forming. Here we have applied two loss
functions to both the RPN (Region Convolutional Neural Network) model
and the classifier model to detect the similar blood object. After
identifying the object, we have calculated the corresponding object and
based on the count of the corresponding object we finally detect
Leukemia. The mean average precision observed are 0.10, 0.16 and 0,
where the epochs are 40, 60 and 120, respectively.
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11:45-12:00, Paper TuA23.4 | |
Smart Wake up Stroke Alert System |
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Boppana, B.Lakshmi | National Institute of Technology |
Kuppuru, Bharat Kumar | National Institute of Technology, Warangal |
Nerella, Krishna Karteek | National Institute of Technology, Warangal |
Kovvada, Sharmila | National Institute of Technology |
Keywords: Biomedical Engineering, Machine Learning, Cloud and Data Analytics, Circuits and Systems
Abstract: Wake-up stroke
refers to a kind of ischemic stroke where a person wakes up with
symptoms of stroke that are not present before going to sleep. These
symptoms may include muscle weakness, drowsiness, walking difficulties,
face drooping among others. Risk factors for ischemic strokes are
Diabetes, Hypertension, Obesity, age, tobacco use, etc. From the
Statistical Findings, 8-28 percent of all brain ischemic strokes consist
of Wake-up strokes. The main method of treating an ischemic stroke is
tissue Plasminogen Activator (tPA), the use of which is approved for
3-4.5 hours from the onset time of stroke. As the onset time in wake-up
strokes is difficult to determine, the person may not be eligible for
tPA treatment. This paper presents the development of a prototype to
detect the wake-up stroke using the appropriate sensors to obtain
physiological data and Internet of things technology to issue an alert
signal to the concerned people of the patient. In India, various factors
causes the delay of the patient痴 arrival to the hospital. The proposed
device helps the people to take the patient to the hospital within time
to reduce the risk of permanent disabilities like paralysis and memory
loss.
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12:00-12:15, Paper TuA23.5 | |
Cells Detection and Segmentation in ER-IHC Stained Breast Histopathology Images |
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Jamaluddin, Mohammad Fareed | Multimedia University |
Ahmad Fauzi, Mohammad Faizal | Multimedia University |
Abas, Fazly Salleh | Multimedia University |
Lee, Jenny T H | Sarawak General Hospital |
Khor, See Yee | Queen Elizabeth Hospital |
Teoh, Kean Hooi | University Malaya |
Looi, Lai-Meng | University Malaya |
Keywords: Biomedical Engineering, Machine Learning, Cloud and Data Analytics, Signal and Image Processing
Abstract: In this paper,
we present our recent work on cells detection and segmentation in
estrogen receptor immuno-histochemistry (ER-IHC)-stained breast
carcinoma images. The proposed cell detection and segmentation is very
useful in the predictive scoring of hormone receptor status in ER-IHC
stained whole-slide images, which helps pathologists to decide whether a
patient should be offered hormonal therapy or other treatments. The
proposed method is based on deep convolutional neural network, followed
by watershed-based post-processing. The cell detection results are
compared and evaluated objectively against the ground truth provided by
our collaborating pathologists. The cell segmentation results, on the
other hand, are evaluated visually by overlaying the computer segmented
boundaries on the ER-IHC images for comparison. The automated cell
detection algorithm recorded precision and recall rates of 95% and 91%
respectively. The very promising performances for both the detection and
segmentation paves the way for an automated system for hormone receptor
scoring in ER-IHC stained whole-slide breast carcinoma images.
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TuA24 |
L-4 |
DMP1: Devices, Materials & Processing |
Regular Session |
Chair: Okada, Minoru | Nara Institute of Science and Technology |
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11:00-11:15, Paper TuA24.1 | |
Quantum
Transport of Edge States in Zigzag Graphene NanoRibbon in the Presence
of an Abrupt Structure Change Due to Missing Atoms |
|
Amin, Nazmul | Bangladesh University of Engineering and Technology |
Alam, Mahbub | Bangladesh University of Engineering and Technology |
Keywords: Devices, Materials & Processing
Abstract: In this
article, the edge transport of Zigzag Graphene NanoRibbon (ZGNR) in the
presence of an abrupt structure change due to missing atoms, which we
define as 'cut' is studied through Non-Equilibrium Green's Function
formalism. Interesting results are found that are notably different for
difference in the width of the 'cut'. For ZGNR, depending on the width
of the 'cut', the electrons can be fully transmitted (T=1) or fully
blocked (T=0) in the device scattering region.
|
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11:15-11:30, Paper TuA24.2 | |
Glancing Angle Synthesised MnO2 Nanowire Array Based Fast Response Schottky Detector |
|
Lynrah, Stacy A | National Institute of Technology Nagaland |
P., Chinnamuthu | National Institute of Technology Nagaland |
Keywords: Devices, Materials & Processing
Abstract: In this paper,
vertically aligned MnO2 nanowire (NW) array were fabricated on silicon
(Si) by using glancing angle deposition (GLAD). Successful formation of
the NW can be confirmed from the field emission scanning electron
microscope (FESEM). Optical absorption shows the absorption in visible
region which corresponds with the bandgap of MnO2. From Tauc plot, the
optical bandgap was found to be 2.7 eV and 1.8 eV. Under light
illumination, there is a dramatic increase of photocurrent due to the
electric field formed between Gold (Au) and MnO2 NW. The photoresponse
measurement shows that the rise time(tr) and fall time (tf) of the NW
are 0.18 s and 0.16 s respectively. MnO2 NW proves to be a good
candidate for optoelectronics application.
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|
11:30-11:45, Paper TuA24.3 | |
Evaluation of Electrical Discharge by Ge2Sb2Te5 on Different Substrates for Optoelectronic Applications |
|
Srivastava, Vibhu | Indian Institute of Information Technology Allahabad |
Bajpai, Tulika | Indian Institute of Information Technology Allahabad |
, Sunny | Indian Institute of Information Technology Allahabad |
Keywords: Devices, Materials & Processing, Photonics
Abstract: In this paper,
we report the electrical discharge by crystalline and amorphous
Ge2Sb2Te5 (GST) in lateral metal-semiconductor-metal form (MSM) on
different substrates through design and simulation. This is an extension
to a previous work where optical analysis with same structure and
platforms were performed. Silicon, silicon dioxide and metal (Au) are
used as semiconducting, insulating and conducting substrates,
respectively, beneath the GST material. The electron, hole and total
current behaviors are analyzed and optimized for incident light
wavelength and dimension for every substrate platform. The analyses are
performed for the optical spectrum ranging from 650 nm to 2500 nm (the
NIR range and a portion of visible radiation) under a moderate range of
external biasing from -5 V to +5 V at the electrode. Crystalline-GST
(CGST) on Si is found suitable for 1550 nm wavelength range, which is
optical fiber communication wavelength, with 130 nm optimized thickness
and <0.1 A of current. CGST is found to have maximum current at lower
thicknesses for all substrate types whereas amorphous-GST (AGST)
exhibits higher current with SiO2 platform at comparatively lower
wavelength, making both AGST/CGST suitable for other Si/SOI based NIR
range optoelectronic devices. The photo-current to the dark-current
ratio is almost 1000 for all platforms which inferred to the low
noise/intensity detection systems.
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11:45-12:00, Paper TuA24.4 | |
A Concentric Double-Ring Resonator Based Plasmonic Refractive Index Sensor with Glucose Sensing Capability |
|
Hassan, Md. Farhad | Islamic University of Technology |
Tathfif, Infiter | Islamic University of Technology |
Radoan, Mohammed | Islamic University of Technology |
Sagor, Rakibul Hasan | Islamic University of Technology |
Keywords: Photonics, Devices, Materials & Processing
Abstract: This paper
presents a refractive index sensor that includes two horizontal MIM
(Metal-Insulator-Metal) waveguides coupled with a rectangular ohmic
cavity and a Concentric Double-Ring Resonator (CDRR). The cavities
contain the Material Under Sensing (MUS), while the surrounding area is
filled with silver. The designed model is simulated using the Finite
Element Method (FEM). Results from simulation show a linear shift of the
resonant peaks for variations in the MUS refractive index. Therefore,
unknown MUS is identified through peak shifts. The sensor achieves a
maximum sensitivity of 1070 nm/RIU with the most sensitive geometry
obtained from the simulations. Moreover, the ability to identify glucose
concentration levels in the human blood samples makes the proposed
sensor an attractive choice for bio-sensing applications
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TuA25 |
L-5 |
W1: Wireless Communications & Networks |
Regular Session |
Chair: Chen, Na | Nara Institute of Science and Technology |
|
11:00-11:15, Paper TuA25.1 | |
A Context Information Enhanced Multilevel Beam Search Procedure for mmWave Bands |
|
S, Anandu | National Institute of Technology, Rourkela |
Mati, Gyana Ranjan | National Institute of Technology, Rourkela |
Das, Susmita | National Institute of Technology, Rourkela |
Keywords: Wireless Communications & Networks
Abstract: The mmWave band
with its broad unused spectrum finds its way into the 5th generation
(5G) of communication networks to tackle the traffic demand and need for
higher data rates. However, the mmWaves are subjected to high levels of
attenuation and this loss can be compensated by making use of highly
directional transmissions, this leads to delays that are incurred in
searching for the appropriate narrow beam transmission which involves
scanning the cell area with narrow directional beams. This paper deals
with a beam search algorithm that makes use of user location information
in reducing the time taken for obtaining the optimum beam
configuration. We investigate the performance of the proposed algorithm
in a scenario with location inaccuracies. We also evaluate how the
algorithm fare in scenarios involving obstructions in the transmission
path.
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|
11:15-11:30, Paper TuA25.2 | |
Traffic Aware Sleeping Strategies for Small-Cell Base Station in the Ultra Dense 5G Small Cell Networks |
|
Kuna, Venkateswararao | National Institute of Technology, Goa |
Swain, Pravati | National Institute of Technology, Goa |
Keywords: Wireless Communications & Networks
Abstract: The 5G
ultra-dense small cell network plays a key role in the future generation
of mobile networks. It provides high data rate, seamless coverage and
reliable services for wireless communication in an ultra-dense network.
The dense deployment of small cells is needed to control forthcoming
traffic demands which leads to enhance the operational cost and reduces
the energy efficiency. One way to improve the energy efficiency is by
using the sleeping strategy of small cell by transferring the traffic
load of a small cell to other small cells. This work proposes an Initial
Connection algorithm for establishing an initial association between
the UEs and small base stations (s-BSs) while considering the UE
preference. The Initial Connection algorithm creates a connected
network. Moreover, the proposed Load Sharing Based Sleep Approach
(LSBSA) algorithm performs small cells sleeping on the connected network
which results in the deployment of s-BSs. The proposed Initial
Connection and LSBSA algorithms are implemented and evaluated in MATLAB
for different mobile data traffic. Also, various UEs distribution
scenarios are are considered. The results are demonstrated that the
proposed approaches improve network performance in terms of energy
efficiency of the small cell network by deploying the optimal number of
active s-BSs.
|
|
11:30-11:45, Paper TuA25.3 | |
Transmit Power Minimization in Intelligent Reflecting Surfaces-Aided Uplink Communications |
|
Wu, Jiao | Seoul National University |
Shim, Byonghyo | Seoul National University |
Keywords: Wireless Communications & Networks
Abstract: Employing
intelligent reflecting surfaces (IRSs) is emerging as a green
alternative to improve the signal quality and suppress interference for
massive antenna systems. Specifically, IRS is a planar surface
consisting of a large number of low-cost and passive elements each being
able to reflect the incident signal independently with an adjustable
phase shift. In this paper, we study the power control problem at the
user for an IRS-aided uplink system under the quality of service (QoS)
constraints. Our goal is to minimize the total transmit power at the
user by jointly optimizing the phase shifts of passive elements at the
IRS and the receiving beamforming at the BS, subject to the
signal-to-noise ratio (SNR) constraint at the user. To solve the
resulting non-convex optimization problem, we develop an efficient
algorithm, called the manifold-based alternating optimization (M-AO).
Simulation results show that the proposed algorithm significantly saved
the transmit power.
|
|
11:45-12:00, Paper TuA25.4 | |
Highly
Precise Prediction of 28 GHz Indoor Radio Wave Propagation
Characteristics in an Office Environment for Design of 5G Wireless
Networks |
|
Nagamoto, Sango | Hokkaido University |
Omiya, Manabu | Hokkaido University |
Keywords: Wireless Communications & Networks, Antenna & Microwave
Abstract: The commercial
service of fifth generation mobile communication system started in the
spring of 2020 in Japan. This paper discusses a highly precise
prediction of 28 GHz millimeter wave indoor propagation characteristics
in an office environment by using a large-scale electro-magnetic field
simulation based on the finite difference time domain technique. The
computer simulations are carried out using the high-performance computer
system operated in Information Initiative Center, Hokkaido University.
They give us a detail of electromagnetic field distributions in an FDTD
problem space including targets at once although they require a lot of
computer resources and a long running time in general. The paper
compares calculated path loss model parameters such as path loss
exponents, shadow factors and cross-polarization discriminations in the
LOS environment with the measured ones demonstrated by the other
research groups to confirm the effectiveness of numerical results and
the accurate prediction of path loss model parameters.
|
|
12:00-12:15, Paper TuA25.5 | |
Device-To-Device Communication in Terahertz Frequency Band: Enhancement of Energy Efficiency |
|
Tultul, Nafisa Azad | Brac University |
Farah, Subrin | Brac University |
Hossain, Syed Shafquat | Brac University |
Hossain, MD Akbar | Manukau Institute of Technology |
Sabuj, Saifur Rahman | Hanbat National University |
Keywords: Wireless Communications & Networks
Abstract: The increasing
demand for higher data rates pushes the boundaries of the currently used
radio spectrum. The terahertz (THz) frequency band (0.1-10 THz) is
widely considered by scientific community to address spectrum scarcity.
In this paper we developed a theoretical model for device-to-device
(D2D) communication operating in THz band. We also derived a close form
formula of data rates, outage probability, and energy efficiency. Our
simulation results show an improvement of data rates and energy
efficiency while decreasing the outage probability of D2D communication
in THz. For instance, there is 86% of increase in energy efficiency when
the transmission power is 19dBm. Finally, the improvement of energy
efficiency is 87% using optimal transmission power due to 50 resource
blocks.
|
|
TuA26 |
L-6 |
P1: Power & Energy |
Regular Session |
Chair: Duong, Quang-Thang | Nara Institute of Science and Technology |
|
11:00-11:15, Paper TuA26.1 | |
Improvement of Energy Efficiency and Effectiveness of Cooking in Solar Electric Slow Cooker for Tropical Countries |
|
Md. Muhaymin Hasan, Rayed | Brac University |
Nahian, Islam | BRAC University |
Siam, Mehrab Azam Khan | Brac University |
Amin, Sams Shafiul | Brac University |
Azad, AKM Abdul | Brac University |
Keywords: Power & Energy, Social Implications of Technology
Abstract: Cooking system
has been evolving for a long time. From the parabolic system to solar
cooking. Every method had its unique concepts. Attempts towards solar
cooking have always been proven beneficent and successful. Solar cooking
is a system where energy comes from the photovoltaic solar panel which
is powered by sunlight. We have designed a system where solar energy
will be stored in a pack of battery which can be used in the absence of
the sun. Combination of PV panels and batteries will provide the
required power during sun time. A full-time main grid back- up is also
present in the system
|
|
11:15-11:30, Paper TuA26.2 | |
Novel
Optimistic Approach for Design of a UHV AC Transmission Line in India
from View Point of Maximum Permissible Exposure Values of Fields |
|
Vyas, Kaustubh | Research Scholar, Department of Electrical Engineering, Pandit D |
Jamnani, Jitendra | Department of Electrical Engineering, Pandit Deendayal Petroleum |
Keywords: Power & Energy, Software & Database Systems
Abstract: Along the
transmission corridor, overhead transmission lines require a portion of
land which is to be reserved as right-of-ways (ROW). Main criteria to
obtain suitable value of ROW is effects produced by static electric
field, magnetic fields and effects due to corona phenomena. A tough need
therefore exists to determine the distribution of these fields,
especially electric fields throughout the corridor along the length of
transmission lines. Determination of the maximum value of the electric
and magnetic fields produced by transmission lines close to ground
surface has thus become significant. The present research work deals
with estimation of electric and magnetic field distribution along with
corona effects all the way through the length of an ultra-high voltage
transmission line corridor. Analysis is carried out by making use of
newly developed computer software that uses MATLAB as programming
platform. Charge simulation method (CSM) has been used for computation
whereas Maxwell痴 potential coefficient theory forms the fundamental
base of computations. Results for 1200 kV Ultra High Voltage AC line are
presented here. Single circuit horizontal line configuration has been
considered for analysis. Profiles of all the fields are plotted in 3D
environment to find maximum possible value of the fields considering
effects of sag through catenary model. Optimization is carried out
through a recently developed objective function with the help of Genetic
Algorithm.
|
|
11:30-11:45, Paper TuA26.3 | |
Comparisons of Instability in Device Characteristics at High Temperature for Thin-Film SOI Power N and P Channel MOSFETs |
|
Kaneda, Yoshimasa | Kyushu Institute of Technology |
Ariyoshi, Kazuma | Kyushu Institute of Technology |
Matsumoto, Satoshi | Kyushu Institute of Technology |
Keywords: Devices, Materials & Processing, Power & Energy
Abstract: This paper
investigate instability in device characteristics related to the hot
carrier effect, Negative Bias Temperature Instability (NBTI) and
Positive Bias Temperature (PBTI) under DC stress for n- and p-channel
thin-film Silicon on Insulator (SOI) power MOSFET at high temperature.
The threshold voltage shift increases as the temperature rises due to
PBTI for n-MOSFET and NBTI for p-MOSFET. Drain Avalanche Hot Carrier
(DAHC) occurs when the gate stress voltage is near the threshold voltage
and Channel Hot Carrier (CHC) occurs when the gate voltage is high. The
threshold voltage shift and the degradation rate of on-resistance of
the n-MOSFET is larger than that of the p-MOSFET due to the difference
in the impact ionization coefficient between electrons and holes.
|
|
11:45-12:00, Paper TuA26.4 | |
Numerical Simulation of CsSnI3-Based Perovskite Solar Cells: Influence of Doped-ITO Front Contact |
|
Rahman, Md Sazzadur | University of Asia Pacific |
Miah, Suman | University of Asia Pacific |
Marma, Ma Sing Wang | University of Asia Pacific |
Ibrahim, Mohammad | University of Asia Pacific |
Keywords: Devices, Materials & Processing, Power & Energy
Abstract: The environmental friendliness and excellent thermal stability proves Cesium Tin Iodide ( CsSnI3) as one of the promising materials for the commercialization of the perovskite solar cells. However, CsSnI3 solar cells suffer from poor efficiency due to having low open circuit voltage, VOC
attributed to poor absorber film quality as well as energy level
mismatch at the interfaces between different layers like transparent
front contact (typically used Indium Tin Oxide, ITO) carrier transport
layer interface. In order to improve the energy matching between ITO
hole transport layer (HTL) interface, a typical inverted planar
perovskite solar cell (ITO/HTL/ CsSnI3/ETL) is
numerically simulated (Finite difference time domain, FDTD analysis
followed by electrical simulation) here, with various types of doped ITO
layers having higher workfuctions (≥ 5eV), replacing the typical
undoped ITO material having lower workfunction (≤4.7eV). The simulation
results illustrate that, utilizing the higher workfunction and optical
transparency of available doped ITO materials the VOC of a typical CsSnI3
cell can be increased from 0.5V up to 1.1V which will make it possible
to achieve power conversion efficiency as high as 11% (which is 3.3%
with undoped ITO), without adopting complex modification of the absorber
layer.
|
|
12:00-12:15, Paper TuA26.5 | |
Power System Stability of Offshore Wind with an Energy Storage to Electrify O&G Platform |
|
Tee, Jing Zhong | University of Glasgow |
Lim, Idris Li Hong | University of Glasgow |
Yang, Jin | University of Glasgow |
Choo, Ciel. T | Sembcorp Marine Ltd |
Anaya-Lara, Olimpo | University of Strathclyde |
Chui, Chee Kong | National University of Singapore |
Keywords: Marine and Offshore Engineering, Power & Energy
Abstract: The Capital
Expenditure (CapEx) of offshore floating wind turbine generation (WTG)
and battery energy storage system (BESS) are declining over the years.
This can mitigate gas turbine power generation in offshore oil and gas
(O&G) platforms with lower cost impact. This paper proposes
integrated systems consisting a WTG and O&G production platforms
with BESS onboard to meet the load demand. Cost analysis shows that this
integrated system paradigm with BESS can lower overall cost in CapEx
and Operational Expenditure (OpEx) compared with typical system.
Moreover, transient stability in simulation shows that the system 2 has a
significant reduction in term of both voltage and frequency transient
deviation, with transient recovery time that could meet the IEC
standards 61892-1 for O&G platforms.
|
|
Tu120 |
L-0 |
Plenary Talk - 1: Applications of KNApSAcK Database and DPClus Algorithm:
Plants to Metabolites to Target Proteins in the Context of Jamu
Medicines and IBD Gene Prediction (by Md. Altaf-Ul-Amin) |
Plenary Session |
Chair: Okada, Minoru | Nara Institute of Science and Technology |
|
13:30-14:30, Paper Tu120.1 | |
Applications
of KNApSAcK Database and DPClus Algorithm: Plants to Metabolites to
Target Proteins in the Context of Jamu Medicines and IBD Gene Prediction |
|
Altaf-Ul-Amin, Md. | Nara Institute of Science and Technology |
Keywords: Biomedical Engineering, Machine Learning, Cloud and Data Analytics
Abstract: Initially, we
developed KNApSAcK as a species-metabolite relational database and
subsequently, inspired by its popularity we extended it to KNApSAcK
family databases by adding different types of omics data together with
data regarding edible plants and traditional medicines mainly focusing
human health care and ecology. Previously we also developed graph
clustering algorithms DPClus and DPClusO, which we and many other
researchers applied to analysis of versatile omics data. In the present
talk, first, I will briefly focus on the KNApSAcK database and the
DPClus algorithm. Then I will discuss a new method to predict the
relation between plant and disease using network analysis and supervised
clustering based on Jamu formulas. Jamu is the common name of
Indonesian traditional medicines. Next, I will extend the talk on the
analysis for predicting Jamu efficacy based on metabolite composition
and identifying important metabolites by applying various machine
learning techniques and algorithms including support vector machine
(SVM) and random forest. I will then focus on prediction of target
proteins by Jamu metabolites. Finally, I will discuss application of
DPClusO algorithm in finding inflammatory bowel disease related genes.
|
|
TuB21 |
L-1 |
C2: Circuits and Systems |
Regular Session |
Chair: Mitsuyama, Yukio | Kochi University of Technology |
|
14:45-15:00, Paper TuB21.1 | |
Implementation and Performance Evaluation of Novel Line Adder Architecture for Portable Systems |
|
Janwadkar, Sudhanshu | Sardar Vallabhbhai National Institute of Technology, Surat |
Dhavse, Rasika | Sardar Vallabhbhai National Institute of Technology, Surat |
Keywords: Circuits and Systems
Abstract: In this paper,
we propose design and implementation of novel line adder architecture
capable of adding multiple addends in a single step. The architecture is
derived based on addition algorithm from Shuddha system of vedic
mathematics. The adder architecture is particularly suitable for a class
of applications, such as FIR filter, where multiple operands are
required to be added. The implementation is particularly suited for
portable systems where area and power consumption are highly
constrained. We then quantitatively compare proposed adder architecture
against popular Parallel-prefix adder architectures for different
wordlengths (N = 4, 8, 16 and 32 bits). All the architectures are
implemented on Genesys2 board(Xilinx part number xc7k325t-2ffg900c)
using VHDL coding and Xilinx Vivado 2016.2 platform. Standard
performance metrics such as FPGA device utilisation (number of slices
and logic LUTs), Power Consumption and Performance are considered for
comparison. Results indicate that proposed vedic adder occupies 35.12 %
lesser logic LUTs and 28.71 % lesser slices than any other adder
architectures, under consideration, while at the same time, there is an
improvement of 9.1 % in on-chip FPGA power consumption than all other
adder architectures. The performance of vedic adder architecture draws
parallel with that of fastest prefix adder being considered.
|
|
15:00-15:15, Paper TuB21.2 | |
Time Domain Analysis of Class-D Amplifier Driving Series-Series and Series-Parallel Circuits |
|
Sarkar, Sayan | HKUST |
Ki, Wing Hung | HKUST |
Keywords: Circuits and Systems, Biomedical Engineering, Power & Energy
Abstract: A class-D power
amplifier (PA) driving a pair of resonant coils is studied. Time-domain
analysis of the inductor currents of the primary and the secondary
sections with series-series (SS) and series-parallel (SP) resonance are
derived, with either resistor or rectifier loads. Both the ripple and
rectified output voltage of the secondary section are analyzed. Results
are validated through extensive SPICE simulations. Analytical and
simulated results are matched with better than 90% accuracy.
|
|
15:15-15:30, Paper TuB21.3 | |
Defect Tolerant Approach for Reliable Majority Voter Design Using Quadded Transistor Logic |
|
Mukherjee, Atin | NIT Rourkela |
Keywords: Circuits and Systems, Computer Architecture & Systems
Abstract: In this paper,
we have proposed a new fault tolerant design technique for majority
voter that is used in selection of final output for fault-tolerant
methods like N-tuple modular redundancy (NMR) and N-tuple interwoven
redundancy (NIR). The common assumption that majority voters are robust
and hence does not affect the final reliability of a system, is false
for most of the practical applications. We have used redundancy at
transistor level combined with redundancy at gate level to design a
defect tolerant majority voter that provides notable improvement in
reliability over conventional triple modular redundancy technique using
traditional non-reliable voters and other existing methods.
|
|
15:30-15:45, Paper TuB21.4 | |
Adaptive BFS Based Fault Tolerant Routing Algorithm for Network on Chip |
|
Ashish, Kumar Yadav | IIT Bhilai |
Singh, Kunwer Mrityunjay | Iit Guwahati |
Biswas, Santosh | IIT Bhilai |
Keywords: Circuits and Systems, Computer Architecture & Systems
Abstract: In modern-day
deep sub-micron technology various cores and components are integrated
on a single chip called System on Chip (SOC). To assure performance of
SOC, intracore communication must be efficient and accurate. Network on
Chip (NOC) plays a vital role in communication among cores, memory,
input-output, and other components. Increased density of components
on-chip enhances the probability of failure. Failure can be due to
faulty components, link failure, deadlock, livelock, starvation,
congestion, etc. To avoid failure in communication, e need an efficient
algorithm that must have properties like deadlock-free, livelock free,
highly adaptive, fault-tolerant, minimal etc. In this paper, we propose a
novel fault-tolerant, deadlock-free, livelock free, fully adaptive, and
minimal breadthfirst search (BFS) based routing algorithm which routes a
packet from source to destination efficiently. The simulation results
depict that our algorithm can route packets in the presence of faulty
links or faulty components. It also gives the alternate routes while
facing faults.
|
|
15:45-16:00, Paper TuB21.5 | |
An Efficient Dadda Multiplier Using Approximate Adder |
|
Pathak, Ketki | Sarvanjanik College of Engineering & Technology |
Sarvaiya, Jignesh | SVNIT, Surat |
Darji, Anand | SVNIT, Surat |
Bhatt, Zinal | Sarvanjanik College of Engineering & Technology |
Diwan, Shreya | Sarvanjanik College of Engineering & Technology |
Patel, Azba | Sarvanjanik College of Engineering & Technology |
Gangadwala, Anjali | Sarvanjanik College of Engineering & Technology |
Keywords: Circuits and Systems, Computer Architecture & Systems
Abstract: In most
multimedia applications, human beings can gather useful information from
approximate outputs. The approximation concept is dominating in the
field of digital signal processing and multimedia applications as it
allows the reduction of area and power significantly with some loss of
accuracy. Little inaccuracy does not affect the visual quality as it
seems unnoticeable in the perception of a human eye. As an advantage,
this technique is to reduce the device utilization for such
applications, which will eventually lead to a reduction in terms of
power as well as transmission speed. Finally, the redundant bit, as well
as the storage required to store the data, will be reduced. The
approximation of arithmetic circuits is useful for reducing its
computational complexity without a significant impact on its coding
performance. In the end, the proposed approximate almost full adder
based dada multiplier utilizes less power, delay, and device
utilization. In this paper, analysis of various multipliers using
approximate almost full adder is evaluated.
|
|
16:00-16:15, Paper TuB21.6 | |
Maximizing Yield through Retesting of Rejected Circuits Using Approximation Technique |
|
Jena, Sisir Kumar | Indian Institute of Technology Guwahati |
Biswas, Santosh | Indian Institute of Technology, Bhilai |
Deka, Jatindra Kumar | Indian Institute of Technology, Guwahati (IITG) |
Keywords: Circuits and Systems, Computer Architecture & Systems
Abstract: The maximizing
yield concept ensures a semiconductor manufacturing structure towards
recognizing, diminishing, and avoiding yield-related defects and
contamination. According to the current scenario of technology scaling,
manufacturing yield is measured in terms of the number of perfect chips
produced. However, in this paper, an imperfect chip producing a
good-enough result like Approximate Circuit (AxIC) can also be
considered and helps enhance the yield. Hence, this paper's primary
objective is to identify those acceptable circuits (AcICs) through
retesting, which indirectly increases the effective yield. The basic
idea is to divide the testing process into two phases. In the first
phase, we follow a conventional test flow architecture and collect the
rejected circuits. In the second phase, all the rejected circuits that
are tested imperfect in the first phase are retested by applying the
test patterns. During this phase, the circuit may produce wrong results
for some test patterns, but we should ignore and continue the test until
all the test patterns are applied. The test patterns for which the
circuit produces a wrong result (error) are quantified and checked
against the golden output for deviation. If the amount of deviation is
nominal and does not affect the circuit's overall performance, then the
circuit is accepted as an AxIC. Though the circuit does not precisely
follow the definitions of AxICs, it can significantly contribute to the
yield enhancement and termed as
|
|
TuB22 |
L-2 |
SS-1: Special Session - Recent Advances on Autonomous Mobile Robots |
Invited Session |
Chair: Xie, Yuanlong | Huazhong University of Science and Technology |
Organizer: Xie, Yuanlong | Huazhong University of Science and Technology |
Organizer: Wang, Shuting | Huazhong University of Science and Technology |
|
14:45-15:00, Paper TuB22.1 | |
Modified MRAS-Based Algorithm for Inertia Estimation of Mobile Robotic Chassis Drive Systems (I) |
|
Yang, Chengbo | Huazhong University of Science and Technology |
Song, Bao | Huazhong University of Science and Technology |
Tang, Xiaoqi | Huazhong University of Science and Technology |
Xie, Yuanlong | Huazhong University of Science and Technology |
Zhou, Xiangdong | Huazhong University of Science and Technology |
Keywords: Robotics, Control Systems & Theory, Power & Energy
Abstract: Permanent
magnet synchronous motor (PMSM) is typically used to drive the mobile
robotic chassis system. In this paper, a modified model reference
adaptive system (MRAS) based algorithm is proposed to estimate the
moment of inertia of the PMSM drive system. First, an extended state
observer (ESO) technique is introduced to reconstruct the adjustable
model so that the adverse effects of nonlinear dynamics on its accuracy
are removed. Thus, the estimation precision of the moment of inertia can
be enhanced. Then, a novel sliding-mode adaptive law is designed to
replace the PI adaptive law, which avoids complicated PI parameters
adjustment and improves the dynamic estimation performance. The
existence and the reachability of the sliding mode are proved with
aiding from the Lyapunov function. Experimental results verify the
effectiveness of the proposed method.
|
|
15:00-15:15, Paper TuB22.2 | |
Path Planning of Composite Trackless AGV Considering Map Preprocessing (I) |
|
Li, Yaozhong | Huazhong University of Science and Technology |
Wang, Shuting | Huazhong University of Science and Technology |
Jiang, Liquan | Huazhong University of Science and Technology |
Xie, Yuanlong | Huazhong University of Science and Technology |
Meng, Jie | Huazhong University of Science & Technology |
Wu, Hao | Huazhong University of Science and Technology |
Keywords: Robotics, Control Systems & Theory
Abstract: With mounted
robot arm, the compound trackless automatic guided vehicle (AGV) has
strong flexibility and adaptability in industrial environments. However,
due to the space constraints of the robot arm, the path planning in
complex large scenes is hard to achieve high efficiency, and it is easy
for falling into local minimum and stagnation. In this paper, a novel
AGV path planning algorithm is proposed on the basis of map
preprocessing to improve the planning efficiency and guarantee the
operating safety. First, by integrating the multiple constraints
including the obstacles and robotic position/posture, the preprocessing
method of the environmental map is proposed utilizing obstacle expansion
and Delaunay triangulation. Then, to achieve better convergence and
global optimization capacity, the global path searching is modified by
(1) constructing the OpenList with priority queues; (2) exploring the
adaptive rules for step size and dynamic weighted heuristic function.
Finally, combining linearization and cubic hermite interpolation method,
the planned path is smoothed to enhance the movement stability and
energy consumption rate. Simulation analysis and experimental results
verify the feasibility, efficiency and superiority of the proposed path
planning method.
|
|
15:15-15:30, Paper TuB22.3 | |
Asymmetric Barrier Function-Based Adaptive Control of a Four-Wheel-Steering Mobile Robot (I) |
|
Xie, Yuanlong | Huazhong University of Science and Technology |
Jiang, Liquan | Huazhong University of Science and Technology |
Meng, Jie | Huazhong University of Science & Technology |
Wang, Shuting | Huazhong University of Science and Technology |
Zheng, Shiqi | China University of Geosciences |
Wu, Hao | Huazhong University of Science and Technology |
Keywords: Robotics, Control Systems & Theory
Abstract:
Four-wheel-steering mobile robots (FMR) are widely-adopted in industrial
manufacturing applications. However, the robust trajectory tracking of
FMR is hard to achieve due to the unknown disturbances and
uncertainties. To address this challenge, this paper presents an
asymmetric barrier function-based adaptive control (ABFAC) method for
obtaining a robust direct yaw moment control scheme for the FMR. The
praiseworthy features of the proposed ABFAC method are twofold: (a) It
does not need the information concerning the upper bound of the
disturbances; (b) By introducing the barrier function, the output
signals are guaranteed to be within the desired neighborhood since the
sliding mode gains will grow once the disturbance derivatives increase.
In this context, the proposed ABFAC method makes the control signal
follows the absolute value of the disturbance, ensuring robust
closed-loop responses. The stability of the resultant system is ensured
by the Lyapunov theory. Finally, experimental results of real-time FMR
are given to show the effectiveness and practicability of the proposed
ABFAC method
|
|
15:30-15:45, Paper TuB22.4 | |
Improved Double-Tree RRT* Algorithm for Efficient Path Planning of Mobile Robots (I) |
|
Jiang, Liquan | Huazhong University of Science and Technology |
Wang, Shuting | Huazhong University of Science and Technology |
Meng, Jie | Huazhong University of Science & Technology |
Zhang, Xiaolong | Huazhong University of Science and Technology |
Xie, Yuanlong | Huazhong University of Science and Technology |
Keywords: Robotics, Control Systems & Theory, Circuits and Systems
Abstract: With a modified
form of the rapidly- exploring random tree (RRT), RRT* algorithm is an
important and effective tool for sampling-based path planning. However,
the partial extension and low efficiency of the traditional RRT* make it
very difficult to satisfy specific constraints or real-time
requirements of mobile robotic scenarios. Based on the double tree
structure expansion, a double-tree RRT* (D-RRT*) algorithm is proposed
in this paper with the ability to improve space collision detection and
search the feasible connection area using constrained nodes. The
proposed method can effectively utilize the fast preprocessing ability
of a double-tree structure and reduce the implementation of iterations.
Meanwhile, node filtering and regression are designed to reduce the node
numbers and prevent over space searching. Through the validation
examples of mobile robots, it is shown that the proposed D-RRT* method
can search for a global safe path with enhanced efficiency and
convergence as compared with conventional methods.
|
|
TuB23 |
L-3 |
ML2: Machine Learning, Cloud and Data Analytics |
Regular Session |
Chair: Okada, Minoru | Nara Institute of Science and Technology |
|
14:45-15:00, Paper TuB23.1 | |
Deep Learning Approach for Dermototis Identification |
|
Boppana, B.Lakshmi | National Institute of Technology |
Kulkarni, Minal | National Institute of Technology |
Katrevula, Divya | National Institute of Technology |
Daruri, Harshita | National Institute of Technology |
Keywords: Machine Learning, Cloud and Data Analytics, Biomedical Engineering
Abstract: The
advancements in Computer Vision with Deep Learning are playing an
essential role in aiding Healthcare Organizations to offer better
patient care while reducing costs and improving efficiencies. The
medical industry has seen a sharp growth since the past few decades and
it has benefited thousands of living beings. Skin being the largest part
of human beings,it has never been given the proper care nor importance,
hence widely resulting in the ignorance of skin infections or cancers.
Despite the diagnosis of several such diseases being detected at the
later or critical stages, there is a little to no scope of detection
where the affected people can identify the symptoms immediately and
could reach a physician. In this paper, we present the development of a
model using deep learning approach to identify the specific dermatitis
and a mobile application that functions in a way to detect the disease
when a picture of the symptomatic part is taken and uploaded. This
scheme assists the medical professionals and patients during pandemic
situations like COVID 19. This application is user friendly and very
much useful for the people living in rural areas and hilly area where it
takes long time and expenditure to reach hospital
|
|
15:00-15:15, Paper TuB23.2 | |
Prediction of Total Body Water Using Scaled Conjugate Gradient Artificial Neural Network |
|
Rosales, Marife | De La Salle University |
Palconit, Maria Gemel | De La Salle University |
Bandala, Argel | De La Salle University |
Vicerra, Ryan Rhay | De La Salle University |
Dadios, Elmer | De La Salle University |
Calinao Jr., Hilario | De La Salle University |
Keywords: Machine Learning, Cloud and Data Analytics, Biomedical Engineering
Abstract: The study aims
to design an intelligent total body water measuring device which will
help to determine the total body water level or percentage of an
individual using ultrasonic sensor, load cell and bioelectric impedance
analysis (BIA). The system utilized the Scaled Conjugate Gradient
Artificial Neural Network (ANN) as the machine learning algorithm. The
system used the dataset splitting of 70%-15%-15% for training,
validation and testing. Different hidden neurons were used and compared
during neural network training and found out that using 10 neurons will
provide the lowest mean square error (MSE) with best value of Pearson痴
correlation (R). Based on the results, using 10 neurons, Scaled
Conjugate Gradient algorithm has better performance as compared to
Levenberg-Marquardt algorithm with MSE equal to 0.180033, 0.118954,
0.529157 while the R value is equal to 0.997887, 0.997488, 0.99644 for
training, validation and testing.
|
|
15:15-15:30, Paper TuB23.3 | |
A Development of Medication Assist Device Based on Multi-Object Recognition |
|
Lin, Yu-Sheng | Department of Mechanical Engineering, Southern Taiwan University |
Tsai, Chia-Ching | Medical Device Innovation Center, National Cheng Kung University |
Chang, Kai-Ming | Medical Device Innovation Center, National Cheng Kung University |
Shih, Pao-Chin | Department of Pharmacy, National Cheng Kung University Hospital |
Cheng, Ching-Lan | Department of Pharmacy, National Cheng Kung University Hospital |
Keywords: Machine Learning, Cloud and Data Analytics, Biomedical Engineering, Engineering Management
Abstract: When the human
population is experiencing a decline but the turnover rate of
pharmacists in general hospitals is gradually increasing, department of
pharmacy starts to import more modern technologies including automation
and artificial intelligence to aid in the workflow. One of the lengthy
and routine work is to count the number of remaining medications of each
ward, which requires many pharmacists and technicians depends on the
size of hospital. This study thereby introduces a design of a medication
assist device with an integration of the machine vision and multiple
object recognition algorithm. The work can be divided into hardware
design, data collection, training and validation, respectively. The
recognition algorithm is based on deep learning Faster RCNN, which can
successfully identify 7 classes of the anesthetics often used with an
accuracy of 99.03%. This pilot study presents the capability of
medication recognition, and the potential to expand numbers of
medication.
|
|
15:30-15:45, Paper TuB23.4 | |
Non-Intrusive Diabetes Pre-Diagnosis Using Fingerprint Analysis with Multilayer Perceptron |
|
Cruz, Denzel Theo | FAITH Colleges |
Ibo, Arles Vincent | FAITH Colleges |
Talavera, John Meldwin | FAITH Colleges |
Santos, Adonis | FAITH Colleges |
Malabanan, Francis | FAITH Colleges |
Tabing, Jay Nickson | FAITH Colleges |
Escarez, Christopher | FAITH Colleges |
Keywords: Machine Learning, Cloud and Data Analytics, Biomedical Engineering, Signal and Image Processing
Abstract: In the Western
Pacific, the Philippines ranks fifth in the number of diagnosed
diabetics. According to Philippine Statistics Authority痴 2016 report,
Diabetes Mellitus ranks sixth as the cause of death in the country
comprising of 5.7% of the total deaths. With the increasing
urbanization, the number of diabetics in the country is expected to
grow, but with the recent technological advancements, artificial
intelligence could be used to facilitate and diagnose the people who
could potentially suffer from the said disease. This study focuses on
the implementation of Multilayer Perceptron with Histogram of Oriented
Gradient to classify different fingerprint patterns, namely arch, loops,
and whorls and lastly Logistic Regression to predict whether a person
has a high or low chance of having a diabetes. The system is implemented
using a 64-bit Windows operating system through Python, java
programming languages, and U.are.U fingerprint scanner for the input
images.
|
|
15:45-16:00, Paper TuB23.5 | |
Diabetic Retinopathy Classification Using a Hybrid and Efficient MobileNetV2-SVM Model |
|
Taufiqurrahman, Shidqie | Biomedical Engineering Program, School of Electrical Engineering |
Handayani, Astri | Biomedical Engineering Program, School of Electrical Engineering |
Hermanto, Beni | Biomedical Engineering Program, School of Electrical Engineering |
Mengko, Tati | Biomedical Engineering Program, School of Electrical Engineering |
Keywords: Machine Learning, Cloud and Data Analytics, Biomedical Engineering, Signal and Image Processing
Abstract: Deep learning
has been proposed as one of the automated solutions for diabetic
retinopathy (DR) severity classification problem. However, most of the
successful deep learning models are based on large convolutional neural
network (CNN) architectures, requiring a vast volume of training data as
well as dedicated computational resources. In this study, we used
MobileNetV2 architecture, which was considered a small-scale
architecture (4.2 million trainable parameters), to perform DR
classification task in APTOS 2019 dataset (3662 color retinal images).
We used the generic MobileNetV2 pre-trained weights from ImageNet as
initialization and implemented data augmentation and resampling during
training. We further optimized our model by combining it with an SVM
classifier, resulting a hybrid and computationally efficient deep
learning model, MobileNetV2-SVM. This model obtained quadratic weighted
kappa score of 0.925, 85% accuracy, and area under receiving operating
characteristic (AUROC) of 1.00, 0.82, 0.94, 0.94, 0.93 for normal, mild,
moderate, severe, and proliferative DR classes, respectively; which is
better or at least comparable with the larger architecture performance
on the same dataset. Our result shows that with proper optimization
strategy, a relatively small and generic CNN architecture, can achieve
promising DR classification performance, and even outperform the
performance of CNN model with larger architecture.
|
|
16:00-16:15, Paper TuB23.6 | |
Deep Learning Based Approach for Malaria Detection in Blood Cell Images |
|
Joshi, Amogh Manoj | Vivekanand Education Society痴 Institute of Technology, Mumbai |
Das, Ananta Kumar | International Institute of Information Technology, Bangalore |
Dhal, Subhasish | Indian Institute of Information Technology Guwahati |
Keywords: Machine Learning, Cloud and Data Analytics, Biomedical Engineering, Signal and Image Processing
Abstract: Malaria, a
life-threatening disease, develops due to the bite of female Anopheles
mosquito. It spreads the plasmodium parasites in human blood, killing
hundreds of millions of people every year. Modern scientific
advancements play a pivotal role to combat the disease, along with
biomedical research by the medical experts to possibly eradicate this
disease from all parts of the world. With the significant development in
deep learning research, faultless identification of medical imaging has
become an important factor in medical diagnosis and decision-making. To
this end, we present a deep learning based approach using a
convolutional neural network for detecting malaria from microscopic cell
images using image classification. The proposed CNN model implemented
using 5-fold cross validation approach outperforms all the existing
methods in terms of accuracy and other evaluation metrics, thus
achieving the best results till date in malaria detection using deep
learning.
|
|
TuB24 |
L-4 |
SIP1: Signal and Image Processing |
Regular Session |
Chair: Subudhi, Badri Narayan | Indian Institute of Technology |
|
14:45-15:00, Paper TuB24.1 | |
Rational Graph Filter Design Using Spectral Transformation and IIR Digital Filter |
|
Tseng, Chien-Cheng | National Kaohsiung University of Science and Technology |
Keywords: Signal and Image Processing
Abstract: In this paper,
rational graph filters are designed by using conventional IIR digital
filters and spectral transformation. First, the specification of the
rational graph filter design is converted to that of IIR digital filter
by using a spectral transformation. Then, conventional IIR digital
filter design methods are directly employed to design converted digital
filter without needing to develop new design algorithms. Next, the
coefficients of rational graph filter are obtained from those of the
designed digital filter by using Chebyshev polynomials and spectral
transformation. Finally, one design example is demonstrated to show the
effectiveness of the proposed method, and the application to temperature
data denoising illustrates the usefulness of graph filter to practical
problem.
|
|
15:00-15:15, Paper TuB24.2 | |
Edge Preserving Image Fusion Using Intensity Variation Approach |
|
Panda, Manoj Kumar | Indian Institute of Technology |
Subudhi, Badri Narayan | Indian Institute of Technology |
Veerakumar, Thangaraj | National Institute of Technology |
Gaur, Manoj Singh | Indian Institute of Technology |
Keywords: Signal and Image Processing
Abstract: In this
article, a novel edge preserving image fusion method is proposed by
merging multiple images captured from different imaging sensors. The
objective of this paper is to highlight the informative contents of
multiple images into a single fused image. Fusion of data from multiple
sensors is a difficult task as the imaging modality are different and
sensors capturing the data may be affected by sensors noise. As the
images captured from multiple sensors possess uncertainty within a pixel
due to the multi-valued level of brightness. It is obvious that a
deterministic method of fusion may not give a better results. Hence, it
is required to explore the use of fuzzy sets theoretic approaches in
this regard. The proposed scheme follow three stages. In the first stage
of the algorithm, a resultant image is obtained by setting the maximum
value between the pixel intensity of visible and infrared sub-images
considered within a small spatial neighborhood. The edges of the visible
image are preserved in the second stage of the algorithm using a Fuzzy
edge technique. Finally the fused image is obtained by combining the
obtained resultant image and the edges of the visible image. In order to
evaluate the performance of the proposed method quantitatively, and
qualitatively experiments were carried out on publicly available
benchmark database, 典NO-database The proposed method is compared with
those of eight state-of-the-arts techniques. The experimental results
of the proposed method
|
|
15:15-15:30, Paper TuB24.3 | |
Aboveground Biomass Estimation of Mangroves Using Sentinel-1 Image and Ifsar Data: A Comparison |
|
Santillan, Meriam | Caraga State University |
Bolastig, Charlene | Caraga State University |
Handayan, Jodijane | Caraga State University |
Keywords: Signal and Image Processing
Abstract: Mangrove forest
plays an important role in ecosystem and the need to conserve this is
essential in our time as global warming was realized. One way to monitor
this forest is to estimate its aboveground biomass (AGB). This study
aims to estimate the AGB of the largest single mangrove forest in the
Philippines located in the municipality of Del Carmen, Siargao Islands
using remotely sensed Interferometric Synthetic Aperture Radar (IfSAR)
datasets and Sentinel-1 image. There were three predictor variables
derived from the Sentinel -1 image used for modeling the AGB: the
backscatter value from VV polarization, backscatter value from VH
polarization, and the combination of the backscatter values from VV and
VH polarizations. Also, the predictor variable from IfSAR dataset that
was used is the canopy height. Linear regression between the
field-measured AGB and the predictor variables was used to generate AGB
model, and the coefficient of determination (r2) and root mean square
error (RMSE) were determined. The results show that the model derived
from IfSAR data obtained a coefficient of determination of 0.42 and RMSE
of 19.39 Mg/ha. However, the combination of the two polarizations
derived from Sentinel-1 image was more accurate in estimating AGB since
it obtained the highest r2 of 0.43 and lowest RMSE of 12.65 Mg/ha. Based
on the best model the estimated above ground biomass of whole mangrove
forest ranged from 73.37 Mg/ha to 225.51 Mg/ha with an average of 140.2
Mg/ha.
|
|
15:45-16:00, Paper TuB24.5 | |
FPGA-Based Features Extraction Sensor for Lettuce Crop |
|
Adonis, Maverick Jonas | University of the Philippines |
Forteza, Renzo | Electrical and Electronics Engineering Institute, University Of |
Ramos, Alaine Richelle | University of the Philippines Diliman |
Alvarez, Anastacia | University of the Philippines |
De Leon, Maria Theresa | University of the Philippines |
Hizon, John Richard | University of the Philippines, Diliman |
Sabino, Maria Patricia Rouelli | University of the Philippines Diliman |
Santos, Christopher | University of the Philippines |
Rosales, Marc | University of the Philippines |
Keywords: Signal and Image Processing, Circuits and Systems, Devices, Materials & Processing
Abstract: 輸 method for
extracting lettuce phenotypic features using an ARTY A7-35T FPGA
platform is proposed. Image acquisition is done by interfacing an OV7670
CMOS camera with FPGA and saving image data on DDR3 memory. The image
processing techniques firstly involve color model conversion for
saturation enhancement. Then, binarization is done as an initial step in
background discrimination, using a threshold value on the green channel
of image. To construct a solid figure for foreground, morphological
transformations are implemented. Then, pixel count of foreground white
pixels are used as an argument in the computation of lettuce canopy
area. The FPGA implementation consumes 85.89% of total LUTs resources of
the chosen FPGA board with errors as low as 1.28% on the computed
canopy area value compared with a MATLAB benchmark. Power consumption
reached up to 1.73W, with a total calculated latency of 596.51 ms from
image acquisition to canopy area value.
|
|
16:00-16:15, Paper TuB24.6 | |
Modelling of Human Vocal Folds and Systematic Investigation of Their Vibrations from Kymogram |
|
R, Sandhanakrishnan | Sri Sivasubramaniya Nadar College of Engineering, Kalavakkam, Ch |
Jain, Rhea | Drexel University, Pennsylvania, USA |
Sukumar, Suhashine | Sri Sivasubramaniya Nadar College of Engineering, Kalavakkam, Ch |
R P, Subramanian | Sri Sivasubramaniya Nadar College of Engineering, Kalavakkam, Ch |
S, Arun Karthick | Sri Sivasubramaniya Nadar College of Engineering, Kalavakkam, Ch |
S, Pravin Kumar | Sri Sivasubramaniya Nadar College of Engineering, Kalavakkam, Ch |
Keywords: Signal and Image Processing, Devices, Materials & Processing, Biomedical Engineering
Abstract: The systematic
investigation of the vocal foldsphysical phenomenon and corresponding
kymographic vibratory patterns can establish clinically important
relationships which are vital in the diagnosis of laryngeal disorders.
The routine investigation is often done clinically through the in-vivo
examination of human vocal folds using laryngoscopes. Physical modelling
of human vocal folds overcomes the accessibility limitations of the
laryngoscopes in imaging the medial and coronal parts of the vocal folds
in-vivo, thus allowing investigation of mucosal wave propagation for
different geometrical configurations of the vocal folds. Here, the
modelled vocal folds are fabricated using flexible silicone compounds,
which can closely reproduce the vibratory characteristics of human vocal
folds. The kymogram, generated by recording the vibration pattern of
the vocal folds, is useful in the analysis of its functional
characteristics. The systematic investigation involves quantification of
the vibratory parameters from the kymogram of the modelled vocal folds
and establishing its relationship with the physical phenomenon. From the
quantification, the important parameters: amplitude, open quotient,
closed quotient, speed quotient and skewness are analysed. The
quantified parameters reflect the influence of physical parameters on
the vibratory characteristics of the vocal folds.
|
|
TuB25 |
L-5 |
W2: Wireless Communications & Networks |
Regular Session |
Chair: Higashino, Takeshi | Nara Institute of Science and Technology |
|
14:45-15:00, Paper TuB25.1 | |
On ASER Performance of M-Ary QAM Schemes Over DF Coordinated-NOMA |
|
Bisen, Shubham | IIT Indore |
Shaik, Parvez | IIT Indore |
Bhatia, Vimal | IIT Indore |
Keywords: Wireless Communications & Networks
Abstract: In this work,
we investigate the performance of a power domain based downlink decode
and forward coordinated-non-orthogonal multiple access (NOMA) system
with two users and one relay node. The system is considered to operate
in half-duplex mode over a Rayleigh faded channel, where the weak user
is heavily shadowed with no direct link. Framework for average symbol
rate error (ASER) and asymptotic ASER of generalized M-ary QAM for both
weak and strong user is developed. Further, the impact of various power
levels over different QAM schemes for users is analyzed. Furthermore,
the impact of symmetric and asymmetric constellations for the users is
also considered and their impact over the system is detailed and useful
insights drawn. The derived analytical expressions are verified through
Monte-Carlo simulations and compared with non-coordinated NOMA.
|
|
15:00-15:15, Paper TuB25.2 | |
Fuzzy Power Control for Non-Linear Distortion Suppression in MIMO-OFDM Systems |
|
Principe, Genesis Marr | De La Salle University |
Vicerra, Ryan Rhay | De La Salle University |
Bandala, Argel | De La Salle University |
Keywords: Wireless Communications & Networks
Abstract: The
hybridization of MIMO-OFDM systems became one of the most used wireless
communication model for broadband, mobile, and multimedia applications
because of its high bandwidth efficiency, bandwidth capacity, and
robustness to fading. However, it suffers from the underlying
disadvantage of OFDM system which is having a high peak-to-average-power
ratio (PAPR) due to large envelope variations. These variations cause
non-linear distortion when the OFDM signal is amplified for
transmission. Hence, in order to eliminate the non-linear distortion
effects of the high power amplifier in MIMO-OFDM systems, the input
signal power must have an appropriate power level to satisfy an optimal
input back off (IBO) value that also contributes to an amplifier痴
maximum efficiency. A Fuzzy Logic Controller is used to control the IBO
of the system as well as the signal power level. Results shows that
using the proposed Single-Input Single-Output (SISO) Fuzzy Power
Controller reduces the bit error rate (BER) significantly compared to
the traditional scheme.
|
|
15:15-15:30, Paper TuB25.3 | |
Forcible Search with Mixed Gibbs Sampling Massive MIMO Detection |
|
Yamazaki, Kenji | Keio University |
Sanada, Yukitoshi | Keio University |
Keywords: Wireless Communications & Networks
Abstract: In this paper,
mixed Gibbs sampling multiple-input multiple-output (MIMO) detection
with forcible search is proposed. In conventional Gibbs sampling MIMO
detection, the problem of stalling occurs under high signal-to-noise
ratios (SNRs) which degrades the detection performance. Mixed GS (MGS)
is one solution to this problem. In the MGS, random sampling is carried
out with a constant probability without judging if a current search is
at a local minimum. In the proposed scheme, combined with MGS, multiple
candidate symbols are forcibly changed when the search is captured by a
local minimum. The search restarts away from the local minimum which
effectively enlarges the search area in a solution space. Numerical
results obtained through computer simulation show that the proposed
scheme achieves better performance in a large scale MIMO system with
QPSK signals.
|
|
15:30-15:45, Paper TuB25.4 | |
Design and Analysis of Low-Complexity Terahertz Receiver |
|
Sharma, Vaishali | Indian Institute of Technology Indore |
Bhatia, Vimal | IIT Indore |
Sharma, Sanjeev | Indian Institute of Technology BHU, Varanasi |
Keywords: Wireless Communications & Networks
Abstract: Terahertz (THz)
band communication is considered as a promising technology for 6G
wireless technology due to availability of large bandwidth at THz bands.
Most receivers for symbol detection need channel state information
(CSI), however estimating CSI is complex for THz bands. Hence, in this
paper, we design and analyze low complexity THz receiver without
considering the CSI for symbol detection. The rate adaptation for THz
communication systems is also analysed for the distance attenuation.
Since, at THz the performance is sensitive to distance. We consider
modified transmitted-reference (MTR) pulsed and optimal lth-order energy
detector (OED) based THz communication system. Simulations are carried
out to show effectiveness of MTR and OED for pulse-based THz band
wireless systems by considering the effect of distance, data rate, and
absorption by molecular gases.
|
|
15:45-16:00, Paper TuB25.5 | |
Reducing Collision Probability in Sensing-Based SPS Algorithm for V2X Sidelink Communications |
|
Lee, Tsern-Huei | National Chiao Tung University |
Lin, Chieh-Fu | National Chiao Tung University |
Keywords: Wireless Communications & Networks
Abstract: Sensing-based
semi-persistent scheduling algorithm was developed by 3GPP as the
standard for distributed resource selection in V2X sidelink
communications. Sensing before resource selection largely reduces
collision probability. However, we found that considerable collisions
can happen if user equipments use different resource reservation
intervals. An enhancement is proposed in this paper to prevent
collisions. The proposed enhancement requires only simple computation
and does not need additional information to be transmitted in sidelink
control information. Simulations are conducted and results show that the
improvement is significant. For our simulation scenario, the collision
probability can be reduced by more than 77% under perfect channel
condition. When channel condition is taken into consideration, the
packet reception ratio can be improved by more than 6.41%.
|
|
16:00-16:15, Paper TuB25.6 | |
Paradigm Shift in Public Warning Systems : A Two-Tier Approach towards Broadcasting |
|
Gandotra, Pimmy | IIT Delhi |
Bhatia, Vimal | IIT Indore |
Lal, Brejesh | IIT Delhi |
Keywords: Wireless Communications & Networks
Abstract: With the recent
outbreak of COVID-19 and other pandemics, improving the public safety
communication is essential for efficient communication in the 5G and
beyond wireless communication networks. The key requirements shall be
lower delays, improved coordination and efficient resource utilization,
to achieve higher efficiency in the network performance in an
emergency/pandemic situation. Since deployment costs and scarce resource
availability are major constraints in the network functioning, looking
forward to a new network solution, a heterogenous network (HetNet)
architecture has been proposed in this paper, for an efficient broadcast
network set up during emergency situations. This paper proposes a
two-tier heterogenous network (HetNet) architecture, with the macro base
station (MBS) tier being Tier 1 and the small cell tier (SCT) being
Tier 2. Here the SCT is mostly involved in setting up of a public
warning communication system. The HetNets also intend to promote
device-to-device (D2D) communication links, in case of absence of
connectivity to the user via the MBT or the SCT. Use of small cells and
D2D links shall improve the overall system performance. Certain research
challenges however persist, and are stated in the paper.
|
|
TuB26 |
L-6 |
P2: Power & Energy |
Regular Session |
Chair: Au, Ngoc Duc | Soongsil University |
|
14:45-15:00, Paper TuB26.1 | |
Multi-Objective
Optimization of Parabolic Trough Concentrated Solar Power with Thermal
Energy Storage Plant Parameters Using Elitist Nondominated Sorting
Genetic Algorithm |
|
Alvar, Ryan Francis | University of the Philippines Los Bas |
Aguirre, Rodolfo Jr. | University of the Philippines Los Bas |
Manzano, John Paul | University of the Philippines Los Bas |
Keywords: Power & Energy
Abstract: Large-scale
concentrated solar power (CSP) with thermal energy storage (TES) is the
most viable option in a centralized generation for a sustainable energy
system. To have a successful CSP-TES plant operation, selecting the best
plant configuration is deemed necessary. Thus, this study presented a
flexible method to determine the optimal plant parameters while
considering the electricity demand curve of the location. Modeling and
performance simulation were done in the System Advisor Model. Elitist
Nondominated Sorting Genetic Algorithm of MATLAB was used to solve
multi-objective optimization problem. Results showed the optimal
performance of the plant in terms of its energy, economic, and
environmental aspects. Also, it was established that the parabolic
trough CSP-TES plant can provide high electrical output to meet peak
demands during nighttime.
|
|
15:00-15:15, Paper TuB26.2 | |
Optimal Operation Planning for Renewable Energy and CCHP in Smart City |
|
Yabiku, Tetsuya | University of the Ryukyus |
Sugimura, Makoto | University of the Ryukyus |
Mandal, Paras | University of Texas at El Paso |
Senjyu, Tomonobu | University of Ryukyus |
Hemeida, Ashraf | Aswan University |
Takahashi, Hiroshi | Fuji Electric Co, Ltd |
Keywords: Power & Energy
Abstract: This study
proposes the problem of optimizing the annual operation, equipment
configuration and capacity in a smart city with renewable energy and
Combined Cooling Heating and Power (CCHP). The effectiveness of this
study is demonstrated by comparing the case where renewable energy and
CCHP are introduced and the case where only electricity purchased from
the electric utility is used.
|
|
15:15-15:30, Paper TuB26.3 | |
EV Charging Optimization Based on Day-Ahead Pricing Incorporating Consumer Behavior |
|
Zhang, Qun | National University of Singapore |
Raman, Gururaghav | National University of Singapore |
Peng, Jimmy Chih-Hsien | National University of Singapore |
Keywords: Power & Energy
Abstract: With the
increasing penetration of electric vehicles (EVs) into the automotive
market, the electricity peak demand would increase significantly due to
residential EV charging. This paper tackles this problem by defining an
'ideal' EV consumption profile, from which a day-ahead pricing scheme is
derived. Based on historical residential EV-use data ranging over a
year, we demonstrate that the proposed optimization process results in a
pricing profile that achieves a dual objective of minimizing the total
electricity cost as well as the peak aggregate system demand.
Importantly, the proposed formulation is simple, and accounts for the
tradeoff between consumer convenience in terms of the number of
available charging slots during a day and the reduction in the total
electricity cost. This technique is demonstrated to be scalable with
respect to the size of the community whose EV charging demands are being
optimized.
|
|
15:30-15:45, Paper TuB26.4 | |
Voltage Stability Enhancement by Coordinated Design of FACTS Devices by Particle Swarm Optimization Algorithm |
|
Jamnani, Jitendra | Pandit Deendayal Petroleum University |
Pandya, Maulikkumar | Kadi Sarva Vishwavidyalaya |
Keywords: Power & Energy
Abstract: The grow of
electrical energy utilization and day by day increment of nonlinear
loads in power system forced for high electrical power and better
stability. Flexible AC Transmission System (FACTS) is a key solution for
power system performance enhancement. Based on that, a particle swarm
optimization (PSO) algorithm is applied to design the coordinated
parameters of static VAR compensator (SVC) and Thyristor Controlled
Series Capacitor (TCSC). A self-sufficient model of IEEE fourteen bus
system has been taken and voltage stability analysis is done by
considering load changing at a bus and change of power factor at load.
PSO applied here is built on searching the values of L and C of SVC. PSO
is available with few modification like change in PSO range &
number, difference in selection criteria technique, control technique
etc, with due respect to normalize PSO. From the results, it is found
that coordination of FACTS devices with each other promises the
efficiency of the suggested method for enhancement of voltage stability.
|
|
15:45-16:00, Paper TuB26.5 | |
Prediction of AC Breakdown Voltage of Mineral Oil Nanofluid |
|
S, Sarov Mohan | National Institute of Technology Calicut |
P, Preetha | National Institute of Technology Calicut |
Keywords: Power & Energy
Abstract: AC breakdown
strength is a critical parameter in the performance of an insulating
liquid. Developing a method to predict the breakdown strength of
dielectric liquid makes it possible to predetermine the voltage
withstand capability of materials. Prediction of breakdown voltage of
nanofluids (NFs) has great significance to the optimization of filler
loading concentration of NFs. Based on the electric field distribution
inside the dielectric liquid samples, this paper proposes a prediction
method for AC breakdown voltage (BDV) using curve fitting technique. By
analyzing various statistical parameters of electric field distribution
such as average, standard deviation, variance, skewness, and kurtosis
along with AC breakdown voltage values of NFs, a relationship connecting
these parameters and breakdown voltage is formed. Using this relation
and statistical parameters of electric field distribution obtained from
simulation model, breakdown voltage is predicted for another set of NFs.
TiO2 NFs are used for framing the equations and breakdown voltage is
predicted for Al2O3 NFs. It is observed that AC breakdown strength is
predicted with least error by using kurtosis as the statistical
parameter. Test results show that the relative errors between predicted
values and actual values are all less than 8%, which indicates the
accuracy and reliability of this method.
|
|
16:00-16:15, Paper TuB26.6 | |
Evaluation of Performance and Reliability Indices of a Micro-Grid with Distributed Generation |
|
Sultana, Gousia | PES University |
B.K, Keshavan | PES University |
Keywords: Power & Energy
Abstract: In the present
trend, the more importance has been given for the power generation using
renewable energy sources (RES). Worldwide research is going on for the
power generation near the load side with fewer losses and better
efficiency using RES. In this regard, distributed generation (DG) and
micro-grids are the two major areas of research. Distributed generation
is nothing but the small-to-medium power generating plants located at or
near the loads with or without connection with the main Grid. In this
paper, reliability evaluation of RBTS bus-2 system has been carried out
with and without considering distributed generation in Grid connected
mode. The reliability has been evaluated feeder wise, each feeder is
considered as separate micro-Grid with grid connected mode. Also the
sizing and siting of Distributed Generation in considered in the
reliability evaluation. The Analytical technique has been used to obtain
the load point indices and total system reliability indices. The
results obtained with and without distributed generation have been
compared.
|
|
TuC21 |
L-1 |
C3: Circuits and Systems |
Regular Session |
Chair: Onoye, Takao | Osaka University |
|
16:30-16:45, Paper TuC21.1 | |
Automatic Identification System Receiver for Small Fishing Vessels |
|
Cruz, Febus Reidj G. | Mapua University |
Ordiales, Jeremiah A. | Mapua University |
Reyes, Malvin Angelo C. | Mapua University |
Salvanera, Pinky T. | Mapua University |
Keywords: Circuits and Systems, Wireless Communications & Networks, Marine and Offshore Engineering
Abstract: Municipal
fishermen experience collisions and being rammed by larger marine
vessels. Automatic Identification System (AIS) can be a solution for
them, if not for its high cost. Likewise, in emergency situations, due
to limited cellular coverage at sea, fishermen do not have the means to
communicate with each other and request for assistance. Therefore, this
design addresses these concerns with a low-cost AIS receiver embedded
with intercommunication using microcomputer and software-defined radio.
|
|
16:45-17:00, Paper TuC21.2 | |
A 0.5-5 GHz 0.3-mW 50% Duty-Cycle Corrector in 65-Nm CMOS |
|
Zhang, Jiaqi | Sun Yat-Sen University |
Meng, Xiangyu | Sun Yat-Sen University |
Keywords: Circuits and Systems, Wireless Communications & Networks, Power & Energy
Abstract: A Duty Cycle
Corrector (DCC) with wide operation frequency band, wide duty-cycle
correction range, high duty accuracy and low power consumption
performance is proposed in this paper. A dual feedback loop with
differential input clock is added to reduce the impact of charge pump
imbalance on circuit performance. The chopping technique is also
introduced to improve the loop gain meanwhile suppress the DC offset in
the feedback loop. Furthermore, a novel duty-cycle adjuster (DCA) with
configurable load capacitance is presented to maintain the duty-cycle
correction range in a wide frequency range. The proposed DCC is
implemented in 65-nm CMOS process with 1V supply voltage.
Post-simulation results indicate that the DCC corrects the input duty
cycle with a range from 20% to 80% to 50ア0.7% in the 0.5-5 GHz frequency
range. The maximum power consumption of the DCC is 0.32 mW when the
input clock frequency is set to 5 GHz.
|
|
17:00-17:15, Paper TuC21.3 | |
Study of Cardiorespiratory and Sweat Monitoring Wearable Architecture for Coal Mine Workers |
|
Sarkar, Sayan | Wecare Medservice Llp |
Ghosh, Aayushman | Wecare Medservice LLP |
Ghosh, Shiuli Subhra | Jindal Stainless Limited |
Keywords: Biomedical Engineering, Circuits and Systems, Engineering Management
Abstract: In an
industrial environment, there is always a surging demand for a wearable
device to cope up with the increasing degree of automation and reduced
manual intervention. The requirement of the wearable is related to the
employee's health and well-being. Safety remains a prime concern despite
other large-scale availability of personal protective equipment (PPE)
and the adoption of strict safety measures. The wearable can be an
essential component of the worker's toolkit, as its application is
increasingly demanding. We have developed an integrated
cardiorespiratory & sweat monitoring wearable and performed
extensive experiments in an operational underground mine in different
conditions. The appearance of a wearable platform with biochemical
analysis, physiological parameters monitoring along with ambient
environment sensors has enabled the observation of critical indicators
of performance as well as the stress of mineworkers.
|
|
17:15-17:30, Paper TuC21.4 | |
An Electromyography-Aided Robotics Hand for Rehabilitation a Proof-Of-Concept Study |
|
Suppiah, Ravi | Newcastle University Upon Tyne |
Abidi, Khalid | Newcastle University |
Kim, Noori | Newcastle University in Singapore |
Sharma, Anurag | Newcastle University in Singapore |
Alkaff, Ahmad | National University of Singapore |
Keywords: Biomedical Engineering, Circuits and Systems, Robotics, Control Systems & Theory
Abstract: The
conventional rehabilitation process has benefited in aiding a patient痴
recovery significantly. However, for a typical traditional
rehabilitation session to occur, a medical professional is required to
present alongside the patient. With the advancement of technology,
robotics is now being integrated into the rehabilitation process to
provide significant benefits to the rehabilitation environment. The
objective of this project is to develop a Rehabilitative Robotics System
that assists stroke patients with the recovery of their hand movements.
A hand exoskeleton is integrated with an Electromyography (EMG) sensor,
a linear actuator, a microcontroller, and a screen. The EMG input is
used to detect a patient痴 intention to open or close his/her arm with
the assistance of the linear actuator. The screen will display the
options which allow the patient to select the mode of the rehabilitation
process. The results of the session are then recorded in the computer
for further analysis by the medical professionals. The system is aimed
to design a portable, lightweight device that can be mobile with the
patient without a secondary assistant. This paper presents the
literature review alongside the development of the hand exoskeleton
design, hardware components and design, software implementation, and
system implementations.
|
|
17:30-17:45, Paper TuC21.5 | |
Automated Aquaponics System and Water Quality Monitoring with SMS Notification for Tilapia Industry |
|
Autos, Ma. Jenica | Pamantasan Ng Cabuyao |
Falculan, Samantha Kaye | Pamantasan Ng Cabuyao |
Fortin, John Jeremy | Pamantasan Ng Cabuyao |
Mendoza, June | Pamantasan Ng Cabuyao |
Sigue, Anna-liza | Pamantasan Ng Cabuyao |
Beano, Mary Grace | Pamantasan Ng Cabuyao |
Medina, Oliver | Pamantasan Ng Cabuyao |
Tuazon, DonJuan | Pamantasan Ng Cabuyao |
Keywords: Devices, Materials & Processing, Circuits and Systems, Robotics, Control Systems & Theory
Abstract: This paper
introduces the development of monitoring and maintaining optimal water
quality in an aquaponics system. The design is based on the hydroponics
system痴 Nutrient Film Technique (NFT) in which plant roots are being
exposed to a thin layer of nutrient water in a long narrow channel. The
design used a developmental and experimental type with the use of
microprocessors and sensors for enhanced monitoring and error-correcting
within the aquaponics system where standard data was obtained from
different reliable sources. Various sensors are calibrated for different
measurements to provide accurate and reliable readings of water
temperature, pH level, dissolved oxygen, total dissolved solids, water
flow, and temperature and humidity. The Arduino Mega reads and analyzes
data collected by various sensors, and instructs actuators such as
aquarium heater, cooling fan, aerator, grow light, and water pump. The
data gathered appears on the built-in LCD screen and will be sent to the
owner's mobile phone regarding the condition of the system. Also, the
system has a fish feeder that automatically dispenses food at a given
time. The device can be controlled wirelessly using a mobile phone and
manually using a 4x4 keypad. Also, the owner can monitor the way each
actuator was controlled.
|
|
17:45-18:00, Paper TuC21.6 | |
Quick Response Code Attendance System with SMS Location Tracker |
|
Soriano, Aldrin | Pamantasan Ng Cabuyao |
Quiambao, Christine Rose | Pamantasan Ng Cabuyao |
Fordan, Matthew | Pamantasan Ng Cabuyao |
Casunuran, Jehriel Joseph | Pamantasan Ng Cabuyao |
Bea, Mary Grace | Pamantasan Ng Cabuyao |
Domingo, Bernie | Pamantasan Ng Cabuyao |
Mandayo, Ericson | Pamantasan Ng Cabuyao |
Keywords: Software & Database Systems, Devices, Materials & Processing, Circuits and Systems
Abstract: Over the years,
the manual checking of attendance has been carried across most of the
educational institutions. Manual attendance monitoring results in a lot
of time consumed. To overcome the problem for manual attendance, the
researchers proposed a Quick Response (QR) Code Attendance System with
SMS Location Tracker that can provide information about the student痴
arrival and departure time in school. The main purpose of the study is
to design a QR Code Attendance System to improve the manual/traditional
attendance and to provide a Global Positioning System (GPS) that can
track the location of the students. The researchers used an Incremental
Methodology to approach the study. It is a method in which the product
is incrementally designed, implemented, and evaluated until the product
is complete. The design project was tested and evaluated by 50 users and
10 experts. Based on the series of testing the system can provide an
easier and more convenient recording and checking of attendance using
the QR Code Scanner, it is also capable of providing the information
about attendance by sending a text message and can provide location by
requesting on the Android Application.
|
|
TuC22 |
L-2 |
SS-2: Special Session - Recent Advances on Autonomous Mobile Robots |
Invited Session |
Chair: Xie, Yuanlong | Huazhong University of Science and Technology |
Organizer: Xie, Yuanlong | Huazhong University of Science and Technology |
Organizer: Wang, Shuting | Huazhong University of Science and Technology |
|
16:30-16:45, Paper TuC22.1 | |
An Efficient and Robust Approach to Solve the Kidnapped Robot Problem Considering Time Variation (I) |
|
Meng, Jie | Huazhong University of Science & Technology |
Wang, Shuting | Huazhong University of Science and Technology |
Li, Gen | Guangzhou Institute of Advanced Technology, Chinese Academy of S |
Jiang, Liquan | Huazhong University of Science and Technology |
Xie, Yuanlong | Huazhong University of Science and Technology |
Sun, Haodong | Huazhong University of Science and Technology |
Liu, Chao | Huazhong University of Science and Technology |
Keywords: Robotics, Control Systems & Theory, Signal and Image Processing
Abstract: This paper
proposes an efficient and robust localization recovery method
considering time variation for Monte Carlo localization (MCL), which can
handle the kidnapped robot problem (KRP) with improved recovery speed
and success rate. The presence of particles near the real robot痴 pose
is necessary for the localization recovery of MCL. Therefore, the
generation number and position of random particles are the vital factors
to solve KRP. It is generally assumed that the robot cannot move
instantaneously, so the size of the search space where robot may appear
should be time-dependent after the KRP occurs. Given these
considerations, a restricted search space is firstly constructed as a
set subject to a time-varying normal distribution, which can effectively
narrow the search space and estimate the probability that the robot may
appear. In addition, a short-long term random particle generation
strategy considering time variation is designed to availably determine
the number of random particles according to the change of the likelihood
and time. And then, the random particles are spread into the restricted
search space. Finally, the above particle set is integrated into the
MCL for localization recovery. The effectiveness of the proposed method
is verified through real scene experiments.
|
|
16:45-17:00, Paper TuC22.2 | |
Stability Analysis of RV Reducers of Mobile Manipulator System (I) |
|
Jiang, Ning | Huazhong University of Science and Technology |
Xie, Xianda | Huazhong University of Science and Technology |
Wen, Zizhang | Huazhong University of Science and Technology |
Wang, Shuting | Huazhong University of Science and Technology |
Keywords: Robotics, Control Systems & Theory, Devices, Materials & Processing
Abstract: RV reducers are
widely recognized in mobile manipulators due to their advantages, such
as high efficiency, high reduction ratio, and high precision. However,
for different types of reducers under different working conditions,
there is no fast quantitative method for determining the dynamic
characteristics of new materials and structures yet, so, this paper
deals with the study of system stability by combining contact mechanics,
kinematics, and Lyapunov exponents. First, kinematics analysis of
one-stage cycloid reducer is performed, and the kinematics equations
have been solved using the fourth-order Runge-Kutta numerical method,
then, Lyapunov exponent is used to analyzing the motion smoothness
characteristics of the system with various parameters. Also, the
numerical experiment for the single stage cycloid pin gear system is
given and the diagrams are obtained, showing the resulting translation,
corresponding velocity, dynamic force, and Lyapunov exponent in terms of
time. Research shows that a quantitative analysis index of RV reducer
is of great significance for its nonlinear dynamic performance
evaluation.
|
|
17:00-17:15, Paper TuC22.3 | |
Fast and Reliable Global Localization Using Reflector Landmarks (I) |
|
Liu, Chao | Huazhong University of Science and Technology |
Li, Gen | Guangzhou Institute of Advanced Technology, Chinese Academy of S |
Huang, Yu | Huazhong University of Science and Technology |
Zhang, Xiaolong | Huazhong University of Science and Technology |
Xie, Yuanlong | Huazhong University of Science and Technology |
Meng, Jie | Huazhong University of Science & Technology |
Jiang, Liquan | Huazhong University of Science and Technology |
Keywords: Robotics, Control Systems & Theory
Abstract: Abstract揚lobal
localization is essential for pose initialization and pose recovery.
However, for the lack of prior information, global localization is
always unreliable and time consuming, especially in featureless and
dynamic industry environment. To alleviate the negative influence of
such environment, this paper uses reflector as landmarks. Then, several
maps including labeled occupancy grid map and multi-resolution
likelihood field are proposed to model the positions of landmarks as
well as ordinary obstacles. Furthermore, a branch and bound method is
employed to achieve fast global search based on those proposed maps.
Through experiments in a real industry application, the reliability and
efficiency of our proposed global localization method is verified.
|
|
TuC23 |
L-3 |
ML3: Machine Learning, Cloud and Data Analytics |
Regular Session |
Chair: Okada, Minoru | Nara Institute of Science and Technology |
|
16:30-16:45, Paper TuC23.1 | |
Machine Learning Analysis for Remote Prenatal Care |
|
Bautista, John Mark | Ateneo De Manila University |
Quiwa, Quiel Andrew I. | Ateneo De Manila University |
Reyes, Rosula | Ateneo De Manila University |
Keywords: Machine Learning, Cloud and Data Analytics, Biomedical Engineering, Software & Database Systems
Abstract: The lack of
health professionals, quality health care, and accessible health centers
in rural and isolated communities have resulted in high maternal and
fetal mortality rates in the Philippines, especially since quality
maternal and child healthcare services are concentrated in more
developed urban areas. This study proposes applying the Telemedicine
framework as a helping tool for doctors and health professionals. The
implemented Telemedicine approach on prenatal care followed a set-up
that included patient information input, a mobile application used for
both data input and visualization, a cloud-based server for the
database, and a machine learning system which analyzed data from the
patient profile. With a dataset of 97 samples, four algorithms were
implemented for the development of the machine learning system
Decision Tree, Random Forest Decision Tree, K-Nearest Neighbor, and
Support Vector Machine. The performance of each algorithm was tested in
terms of accuracy, precision, recall, and the F1 score or the weighted
average of precision and recall. Based on these parameters, the most
effective algorithm was the Random Forest Decision Tree with the highest
train score (0.987) and test score (0.900). The results of this
algorithm were visualized in an Android mobile application that
displayed whether the patient was a positive or negative case with
respect to the possibility of having a high-risk pregnancy.
|
|
16:45-17:00, Paper TuC23.2 | |
Design of a Nutrient Film Technique Hydroponics System with Fuzzy Logic Control |
|
Puno, John Carlo | De La Salle University |
Haban, Jenskie Jerlin | De La Salle University |
Alejandrino, Jonnel | De La Salle University |
Bandala, Argel | De La Salle University |
Dadios, Elmer | De La Salle University |
Keywords: Machine Learning, Cloud and Data Analytics, Circuits and Systems, Robotics, Control Systems & Theory
Abstract: This study
presents the design and development of a nutrient film technique
hydroponics system for lettuce. Hydroponics is a method of cultivating
crops with the use of water with nutrient solutions as medium. This
nutrient film technique hydroponics system was built as an alternative
to traditional farming that requires a lot of space. This system can
produce a good number of crops without consuming large land area. The
system also features monitoring of the key parameters needed for by the
crop to survive. A fuzzy logic control will also be used to maintain the
level of the parameters. Data from the sensors for measuring electrical
conductivity, pH, and as well as the water level of the mixing tank
will be the input of the fuzzy logic and will control the pumps of fresh
water and nutrient concentrate reservoir, and the drain of the mixing
tank. The optimum values for electrical conductivity, pH, water flow
rate, and temperature were all based on the existing studies that also
cultivate lettuce as their primary crop.
|
|
17:00-17:15, Paper TuC23.3 | |
Hardware Accelerators for Edge Enabled Machine Learning |
|
Suresh, Arjun | RV College of Engineering |
Reddy, Bhargava N | PES University |
Chodavarapu, Renu Madhavi | RV College of Engineering |
Keywords: Machine Learning, Cloud and Data Analytics, Computer Architecture & Systems
Abstract: The
proliferation of IoT devices in recent years has resulted in an
exponential increase in data being transmitted over the internet. The
traffic is slated for further increase in the coming years and will
result in excessive network congestion and high latency. To alleviate
this problem, an alternate approach needs to be considered. A prominent
option would be to move the computing domain to the edge device. This
option is constrained due to reduced computing, storage and power
available on the edge. A novel approach combining both software and
hardware solutions is required to perform analytics at the edge. This
paper proposes an architecture for analysing data on the edge, combining
hardware and software solutions. The proposed methodology explores
machine learning algorithms for edge computing combined with the use of
hardware accelerators to achieve truly intelligent edge devices. A
qualitative and quantitative comparison of performance of various
algorithms on CPU, GPU, FPGA platforms is carried out. A machine
learning model for predicting Remaining Useful Life (RUL) for a
multivariate time series dataset is developed and its deployment on the
edge is discussed. The results of the experiments carried out are
promising and hold potential for further research.
|
|
17:15-17:30, Paper TuC23.4 | |
Assessment of the Relative Importance of Different Hyper-Parameters of LSTM for an IDS |
|
Sewak, Mohit | Microsoft, India; BITS Pilani, India |
Sahay, Sanjay K. | BITS Pilani, Goa, India |
Rathore, Hemant | BITS Pilani, Goa, India |
Keywords: Machine Learning, Cloud and Data Analytics, Computer Architecture & Systems, Signal and Image Processing
Abstract: Recurrent deep
learning language models like the LSTM are often used to provide
advanced cyber-defense for high-value assets. The underlying assumption
for using LSTM networks for malware-detection is that the op-code
sequence of a malware could be treated as a language representation.
There are differences between any spoken-language and the
machine-language. In this paper we demonstrate that due to these
inherent differences, an LSTM model with its default configuration as
tuned for a spoken-language, may not work well to detect malware unless
the network's essential hyper-parameters are tuned appropriately. In the
process, we also determine the relative importance of all the different
hyper-parameters of an LSTM network as applied to malware detection
using their op-code sequence representations. We experimented with
different configurations of LSTM networks, and altered hyper-parameters
like the embedding-size, number of hidden-layers, number of LSTM-units
in a hidden layers, pruning/padding-length of the input-vector,
activation-function, and batch-size. We discovered that owing to the
enhanced complexity of the malware/machine-language, the performance of
an LSTM network configured for an Intrusion Detection System, is very
sensitive towards the number-of-hidden-layers, input sequence-length and
the choice of the activation-function. We also assess how sequential DL
architectures compares against their non-sequential counterparts for
the purpose of malware-detection.
|
|
17:30-17:45, Paper TuC23.5 | |
Convolutional Neural Network Based Traffic-Sign Classifier Optimized for Edge Inference |
|
B B, Shabarinath | National Institute of Technology, Warangal |
P., Muralidhar | National Institute of Technology, Warangal |
Keywords: Machine Learning, Cloud and Data Analytics, Computer Architecture & Systems
Abstract: Traffic-Sign
Classification is a major task in self-driving cars as well as modern
driving assisting systems can be deployed as an inference engine on the
Field Programmable Gate Array (FPGA) combined with host processor-based
edge device like Zynq Platform considering the property of dynamic
reconfigurability of FPGA adoptable to architectural innovation. Hence
this paper proposes an optimized Convolutional Neural Network (CNN)
architecture based on VGGNet combined with image-preprocessing
techniques. The proposed methodology utilizes pruning combined with
post-training quantization-based optimization and obtains an accuracy
loss of less than 1%. The architecture is trained, tested and validated
using German Traffic Sign Detection Benchmark (GTSDB) with Google痴
TensorFlow framework obtaining a validation accuracy of 99.2% and test
accuracy of 100% for novel input inference. The experimental results
show the reduction in memory footprint of CNN model readily
implementable on FPGA.
|
|
17:45-18:00, Paper TuC23.6 | |
Evaluation of Neural Network Models for Performance Prediction of Scientific Applications |
|
Mankodi, Amit | Dhirubhai Ambani Institute of Information and Communication Tech |
Bhatt, Amit | Dhirubhai Ambani Institute of Information and Communication Tech |
Chaudhury, Bhaskar | Dhirubhai Ambani Institute of Information and Communication Tech |
Keywords: Machine Learning, Cloud and Data Analytics, Computer Architecture & Systems
Abstract: Performance
prediction is an important and active research area. In particular,
several research efforts have built empirical models using machine
learning algorithms for performance prediction. These models enable us
to understand the dependence on hardware components for algorithm
execution, system痴 scaling capabilities, cross-platform prediction in
multi-core systems, and many others. The user community can use this
knowledge to select hardware configurations best suited for executing a
given software. In recent times, neural network-based models are widely
used to build empirical models that understand complex relations between
independent and dependent variables of an unknown data set. This paper
has studied one-layer and multi-layer neural network models for
performance prediction of three algorithms with different computations
and memory-access patterns. We have shown that the multi-layer model
outperforms the one-layer model, especially for computationally
intensive algorithms. We have also shown that computationally intensive
algorithms having a higher variance in runtime due to manufacturer
variability require a higher number of neurons for convergence than
memory-intensive algorithms. Our multi-layer neural network with optimal
configuration has a prediction accuracy of about 88% for
computationally intensive algorithms and about 95% for the
memory-intensive algorithm.
|
|
TuC24 |
L-4 |
SIP2: Signal and Image Processing |
Regular Session |
Chair: Nakai-Kasai, Ayano | Kyoto University |
|
16:30-16:45, Paper TuC24.1 | |
Segmentation of Aquaculture Underwater Scene Images Based on SLIC Superpixels Merging-Fast Marching Method Hybrid |
|
Almero, Vincent Jan | De La Salle University |
Alejandrino, Jonnel | De La Salle University |
Bandala, Argel | De La Salle University |
Dadios, Elmer | De La Salle University |
Keywords: Signal and Image Processing, Machine Learning, Cloud and Data Analytics
Abstract: Segmentation is
a challenging task for the complex and low-quality underwater images,
as this is prerequisite to advanced tasks in fish monitoring such as
fish detection and classification. A demand exists for underwater image
segmentation algorithms that can robustly segment fish from its
background. A competitive approach is the integration of
states-of-the-art image segmentation algorithms: SLIC superpixels
merging by KAZE Keypoints clustering and Fast Marching Method (FMM) to a
single framework. The combination of these established methods offers
robustness towards underwater images of different visual qualities.
First, a locally acquired underwater image is represented as
superpixels. Then, the KAZE features of an underwater image is
extracted. Such features are utilized by the k-means clustering to group
superpixels which contains fish pixels into a region. Lastly, the
merged region is further segmented with Fast Marching Method and
corresponding morphological processes. The study presents the viability
of the integration of different image segmentation techniques for
localized application. The number of superpixels, KAZE Keypoint score
threshold and FMM threshold are identified to affect the performance of
the proposed algorithm. Qualitative observations and quantitative
measures validate the robustness of this generated algorithm to address
this difficult and persistent task.
|
|
16:45-17:00, Paper TuC24.2 | |
Visual Classification of Lettuce Growth Stage Based on Morphological Attributes Using Unsupervised Machine Learning Models |
|
Alejandrino, Jonnel | De La Salle University |
Concepcion, Ronnie II | De La Salle University |
Lauguico, Sandy | De La Salle University |
Almero, Vincent Jan | De La Salle University |
Tobias, Rogelio Ruzcko | De La Salle University |
Puno, John Carlo | De La Salle University |
Bandala, Argel | De La Salle University |
Dadios, Elmer | De La Salle University |
Flores, Ramon | Laguna State Polytechnic University |
Keywords: Signal and Image Processing, Machine Learning, Cloud and Data Analytics
Abstract: Food shortage
is a serious problem facing the world and is prevalent in urban areas.
The scarcity of food is mainly caused by crop failure. Environmental
factors offered by the rural areas determine the condition of crops to
be produced. This scenario pomps, the explication of urban farming.
However, urban farming requires all-out monitoring and control. This
study specifically solves the predicament of identifying the
developmental growth of plants from seed leaf to amend the techniques of
plant science and cultivation management. With a view to this, the
paper shows coupled color-based superpixels and multifold watershed
transformation in segmenting the lettuce image from the background. To
fathom it out, a comparative analysis of three unsupervised machine
learning algorithms: Self Organizing Map (SOM), Hierarchical, and K -
means algorithms were conducted. These were done by modeling each
algorithm from the features extracted from morphological computations of
the lettuce images raised in a smart aquaponics setup. Each of the
models was optimized to increase cross and hold-out validations. The
results showed that K means algorithm having the parameters of
algorithm = 疎uto copyx= 禅rue init = 銭-means++ maxiter = 000
nclusters = ninit = 5 n_jobs = precompute_distance =
疎uto random_state = 0 tol = .000001 verbose = leaf_size =
0was the most effective model for the given dataset, yielding a
high precision and recall unsupervis
|
|
17:00-17:15, Paper TuC24.3 | |
Steering Kernel-Based Guided Image Filter for Single Image Dehazing |
|
Yadav, Sumit Kr. | Department of Electronics Engineering, IIT (BHU), Varanasi, INDI |
Sarawadekar, Kishor | Department of Electronics Engineering, IIT (BHU), Varanasi, INDI |
Keywords: Signal and Image Processing, Machine Learning, Cloud and Data Analytics
Abstract: The guided
image filter (GIF) technique is used for haze removal. It reduces the
gradient reversal artifact as well as preserves the edge information
precisely in smooth (flat) region only. However, it fails to avoid halo
artifact and edge-smoothing effect in sharp regions. So, to mitigate
this problem, we propose an adaptive haze removal algorithm using a
steering kernel-based guided image filter (SKGIF). Steering kernel
determines the edge-direction in guidance image more adequately. The
edge-direction is an essential feature of guidance image, and it helps
to determine more edge-preserving information in flat as well as sharp
regions. Experimental outcomes on different hazy images prove the
effectiveness of the proposed algorithm.
|
|
17:15-17:30, Paper TuC24.4 | |
Concept Drift Adaptation for Acoustic Scene Classifier Based on Gaussian Mixture Model |
|
Daqiqil Id, Ibnu | Okayama University |
Abe, Masanobu | Okayama University |
Hara, Sunao | Okayama University |
Keywords: Signal and Image Processing, Machine Learning, Cloud and Data Analytics
Abstract: In
non-stationary environments, data might change over time, leading to
variations in the underlying data distributions. This phenomenon is
called concept drift and it negatively impacts the performance of scene
detection models due to them being trained and evaluated on data with
different distributions. This paper presents a new algorithm for
detecting and adapting to concept drifts based on combining the existing
and new components Gaussian mixture model then merging it. The
algorithm is equipped with a drift detector based on kernel density
estimation enabling the algorithm to adapt to new data and generalize
over old and new concepts well.
|
|
17:30-17:45, Paper TuC24.5 | |
Swapping Face Images Based on Augmented Facial Landmarks and Its Detection |
|
Sadu, Chiranjeevi | Rajiv Gandhi University of Knowledge Technologies |
Das, Pradip K. | Indian Institute of Technology Guwahati |
Keywords: Signal and Image Processing, Machine Learning, Cloud and Data Analytics
Abstract: Facial landmark
points that are precisely extracted from the face images improve the
performance of many applications in the domains of computer vision and
graphics. Face swapping is one of such applications. With the
availability of sophisticated image editing tools and the use of deep
learning models, it is easy to create swapped face images or face swap
attacks in images or videos even for non-professionals. Face swapping
transfers a face from a source to a destination image, while preserving
photo realism. It has potential applications in computer games, privacy
protection, etc. However, it could also be used for fraudulent purposes.
In this paper, we propose an approach to create face swap attacks and
detect them from the original images. The augmented 81-facial landmark
points are extracted for creating the face swap attacks. The feature
descriptors Weighted Local Magnitude Patterns (WLMP) and Support Vector
Machines (SVM) are utilized for the swapped face images detection. The
performance of the proposed approach is demonstrated by different types
of SVM classifiers on a real-world dataset. Experimental results show
that the proposed system effectively does face swapping and detection
with an accuracy of 95%.
|
|
17:45-18:00, Paper TuC24.6 | |
Gender Recognition Using In-Built Inertial Sensors of Smartphone |
|
Meena, Tanushree | RESEARCH SCHOLAR |
Sarawadekar, Kishor | Department of Electronics Engineering, Indian Institute of Techn |
Keywords: Signal and Image Processing, Machine Learning, Cloud and Data Analytics
Abstract: The research
work on user authentication using biometric parameters like face, iris,
fingerprint, and gait, have been vastly carried out over the last few
decades. Also, the researchers are putting great efforts in the field of
gender recognition of a person. Predicting the gender of a person by
considering the biometric parameters described above has been the topic
of interest in many areas like security, forensic, e-commerce
applications, investigation, and some smart automation systems. In this
paper, we have presented an analytical approach for gender recognition
based on the information of human gait obtained from the inertial
sensors of a smartphone, and the comparative analysis of various machine
learning classification and regression algorithms on the recognition
performance. The overall aim of our research is to provide an insight
and to improve the preciseness of the gender recognition system.
Moreover, the proposed system can enhance the processing speed of the
biometric recognition systems by determining the gender of the person at
the initial stage to reduce the search area. We have achieved the state
of the art performance and obtained an accuracy of 96.3% using the
proposed method.
|
|
TuC25 |
L-5 |
W3: Wireless Communications & Networks |
Regular Session |
Chair: Vu, Thanh Tung | The University of Newcastle |
|
16:30-16:45, Paper TuC25.1 | |
An Improved Codebook Training Procedure Using Compressed Sensing in mmWave Hybrid Beamforming |
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Mati, Gyana Ranjan | National Institute of Technology, Rourkela |
Das, Susmita | National Institute of Technology, Rourkela |
Keywords: Wireless Communications & Networks, Antenna & Microwave, Signal and Image Processing
Abstract: Millimeter Wave
(mmWave) communication with the advantage of high spectrum availability
is a key technology to offer several gigabits per second data rates for
future 5G and beyond applications. Limited power availability and
smaller coverage area are some critical issues in it due to its high
attenuation and atmospheric absorption. Beamforming has become a
skillful technique to keep track of the angle of arrival (AoA) and angle
of departure (AoD) by directing the steering vector along with these
phases with the least beam-width. Providing an optimal power allocation
towards a user's location through beamforming has become an efficient
technique to direct beam along the angle of departure (AoD) of the
transmitted wave with the smallest beam-width. In a multi-input and
multi-output (MIMO) channel, the channel state information (CSI) of a
large dimension array leads to a considerable feedback overhead. The
sparse nature of the MIMO channel has been exploited by researchers
using compressed sensing, where, the resulting precoder indices can be
sent back to the transmitter in order to reduce the feedback overhead.
The precoder and combiner are updated with their estimated AoA and AoD
during the training period. However, the training time goes enormously
high as the number of antennas become too large. To overcome such
limitation, an improved codebook training procedure (CTP) incorporated
with hybrid beamforming (HBF) has been suggested in this research. The
proposed scheme will e
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16:45-17:00, Paper TuC25.2 | |
Power and Area Oriented Implementations of Lightweight Cryptographic Algorithms for Wireless Sensor Networks |
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Torreno, Alexis Czezar | University of the Philippines Diliman |
De Leon, Maria Theresa | University of the Philippines |
Rosales, Marc | University of the Philippines |
Alvarez, Anastacia | University of the Philippines |
Keywords: Wireless Communications & Networks, Circuits and Systems
Abstract: Security is a
concern in wireless sensor networks, which are inherently prone to third
party attacks. As such, cryptography is used to make a secure mode of
communication among nodes and/or between nodes and base stations.
However, conventional algorithms are resource-hungry and therefore not
fit for small devices, hence the creation of a new category of
cryptography known as Lightweight Cryptographic Algorithms. These
algorithms are still continuously being improved to fit in the
decreasing sizes of small scale devices like FPGA-based wireless sensor
networks. In this study, we quantify the effects of Data Width
Reduction, and Round Unrolling on area, and power consumption. These are
tested on three lightweight ciphers: LiCi, ANUII, and QTL. Data Width
Reduction reduces area by using only a fraction of the original
datapath. It was however found to be ineffective for the chosen ciphers,
increasing area by 5.64%, 6%, and 9.2% in LiCi, ANUII, and QTL,
respectively. Round Unrolling reduces latency which lessens the
contribution of static power for each computation. Results show that
round unrolling improves power efficiency by 25.97%, 3%, and 14% in
LiCi, ANUII, and QTL, respectively. This comes at 299%, 414%, and 52%
increase in area. The results allow newer and better lightweight ciphers
to be further improved for small scale devices.
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17:00-17:15, Paper TuC25.3 | |
MELM-GRBFNN:
A Modified Extreme Learning Machine Trained Gaussian Radial Basis
Function Neural Network Model for Estimating Blocking Probability of OBS
Network |
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Chakraborty, Srija | National Institute of Technology, Rourkela |
Turuk, Ashok Kumar | National Institute of Technology, Rourkela |
Sahoo, Bibhudatta | National Institute of Technology, Rourkela |
Keywords: Wireless Communications & Networks, Machine Learning, Cloud and Data Analytics, Photonics
Abstract: Neural networks
are extensively used for determining different characteristics of
optical burst switching networks. The main disadvantage of optical burst
switching network is burst drop and burst contention, which occurs
because of burst getting blocked. Using neural network approaches,
blocking probability can be pre-determined for the upcoming traffic. In
this paper, Log-incremental modified extreme learning machine trained
generalized radial basis function neural network (MELM-GRBFNN) model is
used for training and predicting burst contention or burst blocking
probability. From the obtained results, it is inferred that the
prediction accuracy of our proposed model is more accurate and faster
than the contemporary approaches. It is observed that our proposed
method is competent in predicting the burst blocking probability with
higher accuracy and indicates a reduction in the burst loss. Thus, it
will help network designers to have a preliminary idea about the
performance of the network model under specific configurations.
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17:15-17:30, Paper TuC25.4 | |
Improving Single Reference Indoor Positioning Accuracy through Machine Learning |
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Santos, Rochelle Xenia Mendoza | Institute for Infocomm Research, A*STAR |
Krishnan, Sivanand | Institute for Infocomm Research, A*STAR |
Keywords: Wireless Communications & Networks, Machine Learning, Cloud and Data Analytics, Signal and Image Processing
Abstract: Indoor
Positioning Systems (IPSs) are able to provide information on the
location of personnel and assets in various indoor environments such as
offices, warehouses and factories. Using the position data from the IPS,
Location Based Services (LBS) can be offered to personnel in offices.
Also, various productivity improvement measures such as bottleneck
identification, cutting wastage in searching for assets and floor layout
optimization can be carried out in industry spaces like factories and
warehouses. The widespread adoption of IPS is however currently hindered
by insufficient positioning accuracy and the high infrastructure cost
of installing and maintaining several reference nodes. This paper
therefore proposes using just a single reference node and map matching
for positioning along pre-determined routes. Furthermore, by employing
Machine Learning, it is shown through simulation that the solution can
be less complex and yet more accurate than traditional map matching,
even in challenging indoor environments.
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17:30-17:45, Paper TuC25.5 | |
Performance Analysis of OTFS Over Mobile Multipath Channels for Visible Light Communication |
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Sharma, Anupma | Indian Institute of Technology Indore |
Jain, Sandesh | Indian Institute of Technology Indore |
Mitra, Rangeet | 父ole De Technologie Sup駻ieure, University of Quebec, Montreal |
Bhatia, Vimal | IIT Indore |
Keywords: Wireless Communications & Networks, Photonics, Signal and Image Processing
Abstract: Visible light
communication (VLC) is eco-friendly and low-cost supplement to the
existing radio frequency (RF) based communication system. However, the
performance of VLC based system is limited by dispersive characteristics
of the VLC channel which leads to inter-symbol-interference (ISI) and
inter-carrier-interference (ICI). To alleviate the ISI and ICI,
orthogonal time frequency space (OTFS) modulation has been proposed in
the literature for both RF and millimeter wave communication systems.
However, the performance analysis of OTFS over mobile multipath VLC
channels is still an open area to investigate. This paper investigates
the performance of OTFS over mobile multipath channels for the VLC
system. Simulations performed over the realistic mobile multipath VLC
channel indicate that OTFS with message passing detector exhibit better
bit error rate over the conventional orthogonal frequency division
multiplexing scheme with minimum mean square error based detector.
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17:45-18:00, Paper TuC25.6 | |
MIMO Detection with Block Parallel Gibbs Sampling and Maximum Ratio Combining |
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Tomura, Kosuke | Keio University |
Sanada, Yukitoshi | Keio University |
Yutaro, Kobayashi | Keio University |
Keywords: Wireless Communications & Networks, Signal and Image Processing
Abstract: In this paper,
block parallel Gibbs sampling (BPGS) multiple-input multiple-output
(MIMO) detection is proposed. In a conventional Gibbs sampling scheme,
MIMO detection is carried out sequentially symbol-by-symbol. The
proposed scheme divides a symbol vector to blocks and updates candidate
transmit symbols in parallel in a block so that the total number of
iterations in a unit period increases. Furthermore, maximum ratio
combining (MRC) is adopted to BPGS to improve accuracy in this paper.
Numerical results obtained through computer simulations show that bit
error rate performance under high bit-energy-to-noise-spectrum-density
conditions improves with the proposed scheme. It is also shown that the
block size of three achieves the best performance when number of
antennas is 16times16 and the number of iterations is 50.
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TuC26 |
L-6 |
P3: Power & Energy |
Regular Session |
Chair: Au, Ngoc Duc | Soongsil University |
|
16:30-16:45, Paper TuC26.1 | |
Modelling of Electric Vehicle Charging and Discharging Profile to Mimic Real Life Scenario at Charging Stations |
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Aqib, Muhammad | University of Auckland |
Ukil, Abhisek | University of Auckland |
Keywords: Power & Energy
Abstract: Agent-based
models(ABM)are a kind of micro scale model that imitate the simultaneous
operations and interactions of multiple agents in an attempt to
re-create and predict the appearance of complex process. Netlogo is a
real time simulation software tool to design this model with the help of
programming and coding. This paper identifies decision variables based
on electric vehicles (EVs) charging statistics and the heuristic
decisions in EVs charging at public charging stations, commercial place
and offices are converted into constraints of (ABM). This unique model is
the version of real time charging scenario at the charging stations.
With the help of programmed model in Netlogo, the behavior of EVs user
under different real life scenarios are observed and recorded. The
proposed system is implemented and designed in Netlogo to test the
results.
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16:45-17:00, Paper TuC26.2 | |
Voltage
Profile Improvement in Autonomous AC Microgrid Operated at Constant
Frequency and Equivalent Parallel Operation of Inverters |
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Zhang, Daming | University of New South Wales |
Tang, Xiuhui | University of New South Wales |
John, Fletcher | University of New South Wales |
Keywords: Power & Energy
Abstract: For an
autonomous microgrid operated at constant frequency, the main power
quality issue is the voltage profile. In this paper, a fine-tuning of a
control coefficient for real power reference generation is proposed.
Matlab/Simulink real-time fixed-time-step modelling has been conducted
to carry out validation of such proposal. It is found that by taking
proper tuning, the terminal voltage at each DG can be kept within
voltage limit. Furthermore different conventions for denoting reactive
power in inverter have been summarized in this paper.
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17:00-17:15, Paper TuC26.3 | |
Unknown Parameter Estimation of a Detailed Solar PV Cell Model |
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Huynh, Duy | Ho Chi Minh City University of Technology (HUTECH) |
Ho, Loc | Ho Chi Minh City University of Technology (HUTECH) |
Dunnigan, Matthew | Heriot-Watt University |
Keywords: Power & Energy
Abstract: This paper
proposes a novel technique for unknown parameter estimation of a
detailed solar photovoltaic (PV) cell model based on the artificial bee
colony (ABC) algorithm and particle swarm optimization (PSO) algorithm.
This combination allows to balance between the exploration and
exploitation abilities of each algorithm for achieving a good
optimization performance. The detailed solar PV cell model is the
double-diode model with seven unknown parameters which are estimated by
using the hybrid ABC-PSO algorithm. The numerical results of the
parameter estimation using the hybrid ABC-PSO algorithm are compared
with those using the PSO, advanced PSO and ABC algorithms showing that
the convergence speed and value of the hybrid ABC-PSO algorithm are
always better than the PSO, advanced PSO and ABC algorithms.
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17:15-17:30, Paper TuC26.4 | |
Reviewing the Economics of Using LPG vs. Electricity for Household Cooking in Sri Lanka |
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Jayasekara, Shalitha | Sri Lanka Institute of Information Technology |
Fernando, Yasiru | Sri Lanka Institute of Information Technology |
Keywords: Power & Energy
Abstract: Cooking is an
essential activity in the households in Sri Lanka. Sri Lankan households
utilize several types of fuel to produce heat for their daily cooking
needs. The most commonly used energy sources are Liquid Petroleum Gas
(LPG) and Electricity. Therefore, it is essential to investigate the
economic aspects of using each of these energy sources. This research
aims to use existing data on several cooking appliances along with LPG
and Electricity charges in Sri Lanka to calculate the costs of using
each of the energy sources. With the total monthly cost of LPG at
Rs.560/= and Electricity at Rs.1150/= as of March 2020, this study
suggests that LPG is the most suitable energy source for cooking in Sri
Lankan households.
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17:30-17:45, Paper TuC26.5 | |
A High Gain Flyback DC-DC Converter for PV Applications |
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Hasan, Rasedul | University of Sydney |
Hassan, Waqas | University of Sydney |
Xiao, Weidong | University of Sydney |
Keywords: Power & Energy
Abstract: This paper
proposes a high voltage gain flyback DC-DC converter for PV
applications. The flyback converter is composed of a voltage-doubler
circuitry that is designed to reduce the turn ratio of the flyback
converter. This enhance the gain of the converter and hence reduce the
voltage and current stresses of the power semiconductor devices.
Moreover, a resonant active-clamp circuit is employed in the primary
that limits the voltage stress and provides zero voltage switching (ZVS)
turn-on of the power switches. The resonant operation of the switches
reduces the conduction loss and switching turn-off loss as well. The
soft switching operation and low stresses in the switches make the
overall efficiency high. The simulation result of the proposed converter
has been analysed and the experiment of the prototype is done to verify
the result.
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17:45-18:00, Paper TuC26.6 | |
Modeling and Estimation of Run-Of-River Hydropower Potential through Integrated GIS and SWAT Interface in Agusan River Basin |
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Tiongson, Riza Mae | Caraga State University |
Bolanio, Kendel | Caraga State University |
Keywords: Power & Energy, Aerospace Technology
Abstract: The
Philippines, specifically Agusan, is rich in water resources but lacks
the reliable information in terms of its potential. Therefore, this
study estimates the theoretical ROR hydro potential of Agusan River
Basin which passes from Davao de Oro and throughout Agusan del Norte. A
30-m spatial resolution elevation of SRTM-DEM, Climate Forecast System
Reanalysis, Global Land Cover Characteristics Database v 2, and
Harmonized World Soil Database v 1.2 have been gathered to make the
assessment possible using GIS-based spatial tool and SWAT (Soil and
Water Assessment Tool) hydrological model Interface. Simulated head drop
and flow rate of 111 delineated stream networks were generated
considering the meteorological data of 2001 to 2014. The estimated total
theoretical run-of-river hydro potential of the basin is 74.49 MW at
annual mean flow. Issues like polluting energy sources and pivoting
power outages within the territories and provinces of Mindanao can be
aided by this hydropower potential associated with geographic and
hydrographic modelling.
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