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2nd IEEE International Conference on Distributed Computing and electrical Circuits and Electronics, ICDCECE 2023

作者： Chaturvedi, Abhay Rohan, J. Saktheeswaran, Murali Samson Isaac, J. Kathan, Ambujam Sekhar, G.G. Raja Gla University Department of Electronics and Communication Engineering Mathura India Kpr Institute of Engineering and Technology Department of Chemical Engineering Coimbatore India Velammal College of Engineering and Technology Department of Computer Science and Engineering Madurai India Karunya Institute of Technology and Sciences Department of Biomedical Engineering Coimbatore India Akt Memorial College of Engineering and Technology Department of Electronics and Communication Engineering Kallakurichi India Koneru Lakshmaiah Education Foundation Department of Electrical and Electronics Engineering Guntur India

ISBN: (纸本)9798350347456

Coronavirus infection is caused by one of the global issues of a deadly virus. The letters 'CO' stands for different types of symptoms, 'VI' for infection easily spread, and 'D' for everybody. Detection and diagnosis are based on various symptoms, and because the virus primarily affects the lung area of the human body, most people test their health condition using CT scans (Computed Tomography). The existing method Support Vector Machine Classifier (SVM)-based image processing technique, identifies CT (Computed Tomography) lung images from patients, which has drawbacks such as a lower positive rate and a less accurate affecting region. So, in the proposed method, the lung CT (Computed Tomography) image is used to classify deep learning. Preprocessing, Segmentation, and Classification are all steps in the digital image processing process. The first step image is obtained by taking the input CT (Computed Tomography) image and processing it into various regions while obtaining the deep level of the specified area using preprocessing bilateral filter. The second step is segmentation using K-means clustering the image segments into different regions or objects like effect and normal regions. This main object is removing the unwanted area. The third step Classification method is based on deep learning. The image is classified with different mathematical functions and identified as the extract part of the lung image. Output results are distinguished sickness and non-illness areas in the lung. The difference in the dark level of each locale is recorded and used as a highlight to identify infection areas identified by low fluctuation contrast with non-COVID-19 affected areas. Simulation is used to validate the proposed method's performance. The proposed method has an accuracy of 84.35% and a false rate of 15.65%. © 2023 IEEE.

关键词： COVID-19

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Mechanism of Threshold Voltage Instability in Double Gate α-IGZO Nanosheet TFT under Bias and Temperature Stress

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IEEE Journal of the Electron Devices Society 2024年 12卷 464-471页

作者： Aslam, Muhammad Chang, Shu-Wei Chen, Yi-Ho Lee, Yao-Jen Li, Yiming Lee, Wen-Hsi Parallel and Scientific Computing Laboratory National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electrical Engineering National Cheng Kung University Tainan City701401 Taiwan Institute of Pioneer Semiconductor Innovation Industry Academic Innovation School National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Communications Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan

Amorphous indium gallium zinc oxide (a-IGZO)-based thin film transistors (TFTs) are increasingly becoming popular because of their potential in futuristic applications, including CMOS technology. Given the demand for CMOS-compatible, ultra-scaled, reliable, and high-performing devices, we fabricate and analyze scaled-channel a-IGZO-TFTs with an optimal double-gate structure, a thin nanosheet-based channel, and an effective high- κ dielectric namely HfO2. The reliably reported double gate IGZO nanosheet TFTs (DG-IGZO-NS-TFTs) are tested under positive and negative bias stress at variant temperatures, and the resulting modulations are analyzed critically. The reported DG-IGZO-NSTFTs exhibit a negative side threshold voltage shift (Δ Vth) accompanied by an increase in Ion/Ion(0) under negative bias temperature stress (NBTS) at elevated temperatures, which indicates the presence of additional charges. An anomalous negative side shifting of the Vth is observed under positive bias temperature stress (PBTS), where diffused hydrogen atoms are identified as introducing excess n-type carriers into the channel and causing the observed Δ Vth. The spectroscopic analysis is performed to establish evidence for the assumed mechanisms, and the role of individual gates is investigated in the context of performance variance under temperature-bias stress. Moreover, the partial reversibility of the stress-induced degradation is experimentally established and methodically discussed. Overall, the reported results offer a comprehensive understanding of scaled-channel DG-NS-IGZO-TFTs, which help shape performance-enhancement strategies, control degradation mechanisms, and define appropriate application scenarios. © 2013 IEEE.

关键词： Thin film transistors

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Optimal service station design for traffic mitigation via genetic algorithm and neural network

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IFAC-PapersOnLine 2023年第2期56卷 1528-1533页

作者： Carlo Cenedese Michele Cucuzzella Adriano Cotta Ramusino Davide Spalenza John Lygeros Antonella Ferrara Department of Information Technology and Electrical Engineering ETH Zürich Zurich Switzerland Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy

This paper analyzes how the presence of service stations on highways affects traffic congestion. We focus on the problem of optimally designing a service station to achieve beneficial effects in terms of total traffic congestion and peak traffic reduction. We propose a genetic algorithm based on the recently proposed Cell Transmission Model with service station (CTM-s), that efficiently describes the dynamics of a service station. Then, we leverage the algorithm to train a neural network capable of solving the same problem, avoiding to implement the CTM-s. Finally, we validate the performance of our algorithms by using real data from Dutch highways.

关键词： genetic algorithm neural network traffic control management service station design smart mobility

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Interferometric Approaches for Accurate Location and Displacement Measurement Using Passive Frequency-Doubling Reflectennas

Interferometric Approaches for Accurate Location and Displac...

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Microwave, MTT-S International Symposium

作者： Ismail H. Uluer Jeff Frolik Thomas M. Weller School of Electrical Engineering and Computer Science Oregon State University USA Department of Electrical and Biomedical Engineering University of Vermont USA

ISBN: (数字)9798350375046

ISBN: (纸本)9798350375053

This paper presents a novel localization and displacement sensing approach that uses a pair of passive sensors and a mobile interrogator. One of the potential applications of this approach is structural health monitoring, where the sensors are embedded in environments such as concrete or soil. The interferometric technique provides location and displacement information via the destructive and constructive interference pattern of the signals returned from the two sensors as the interrogator moves. The measurement results with two sensors reveal that the location information can be obtained with approximately 5 times greater accuracy compared to using a single sensor. The experimental results are in good agreement with analytical calculations.

关键词： Microwave measurement Location awareness Accuracy Soil measurements Displacement measurement Interference Soil

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DrugEL: Ensemble Learning Model for Identification of Druggable Proteins

DrugEL: Ensemble Learning Model for Identification of Drugga...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Md. Mamun Ali Kawsar Ahmed Francis M. Bui Fang-Xiang Wu Division of Biomedical Engineering University of Saskatchewan Saskatoon Canada Department of Electrical and Computer Engineering University of Saskatchewan Saskatoon Canada Department of Mechanical Engineering and Department of Computer Science Division of Biomedical Engineering University of Saskatchewan Saskatoon Canada

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Druggable proteins are defined as proteins that can interact with drugs to modulate certain biological activity. The identification of druggable proteins holds significant clinical importance, directly impacting the development of targeted therapies for diseases like cancer and metabolic disorders. Identifying druggable proteins involves various methods, including computational prediction models, mass spectrometry (MS), and biochemical assays, but achieving high accuracy remains a challenge. This study proposes DrugEL, an ensemble learning model that uses Bayesian inference to integrate predictions from multiple algorithms: Random Forest (RF), K-Nearest Neighbor (KNN), LightGBM (LGBM), and Decision Tree (DT) with seven feature extraction methods (LSA, AAC, PAAC, GAAC, NMBroto, AAIndex, and KNN). The results show that DrugEL outperforms existing models in terms of accuracy (0.9758), MCC (0.9515), AUC (0.9758), sensitivity (0.9742) and specificity (0.9774), particularly excelling with the LSA method.

关键词： Proteins Analytical models Accuracy Sensitivity Biological system modeling Computational modeling Nearest neighbor methods Predictive models Ensemble learning Random forests

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Designing Enhanced Monte Carlo Power Depletion Simulation in PSPICE

Designing Enhanced Monte Carlo Power Depletion Simulation in...

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IEEE International Conference on Electro-Information Technology

作者： Peiqiao Wu Xingguo Xiong Xuan Zhang Bhushan Dharmadhikari Department of Biomedical Engineering University of Bridgeport Bridgeport CT Department of Electrical Engineering Department of Computer Science and Engineering University of Bridgeport Bridgeport CT Electrical & Computer Engineering & Technology Minnesota State University Mankato MN

ISBN: (数字)9798350330649

ISBN: (纸本)9798350330656

PSPICE is a member of the SPICE family and is widely used for simulating different types of circuits in various applications. To accurately measure average power consumption, Monte Carlo simulation is often used as an indirect method. This involves integrating an auxiliary power testing circuit into the PSPICE simulation. However, voltage drops may occur unexpectedly at stable states and boundaries during simulations of CMOS and pass transistor logic (PTL) circuits, even though power consumption should always be positive. This discrepancy occurs because the auxiliary power testing circuit is only connected to the power source V dd , ignoring the contribution of input signals to the circuit’s overall electric energy. This oversight becomes significant, especially in cases where input signals are complex. As a solution, we propose a modified Monte Carlo model where an auxiliary power testing circuit is incorporated into each individual input source to account for power consumption accurately. After comparing and analyzing the simulation results between the conventional and modified Monte Carlo methods, we observed the elimination of unexpected voltage drops and a significant improvement in result accuracy with the modified design.

关键词： Monte Carlo methods Accuracy Power demand Power measurement Simulation Circuits SPICE

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Parameters Determination for Ill-Defined Edge Detection Using Particle Swarm Optimization

Parameters Determination for Ill-Defined Edge Detection Usin...

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2023 International Technical Conference on Circuits/Systems, computers, and Communications, ITC-CSCC 2023

作者： Panwong, Pannawit Auephanwiriyakul, Sansanee Theera-Umpon, Nipon Chiang Mai University Faculty of Engineering Computer Engineering Department Chiang Mai Thailand Graduate School Chiang Mai University Chiang Mai Thailand Biomedical Engineering Institute Chiang Mai University Chiang Mai Thailand Electrical Engineering Department Faculty of Engineering Chiang Mai University Chiang Mai Thailand

ISBN: (纸本)9798350326413

Segmentation process is one of the preprocess steps in object detection. To achieve segmentation, edge detection is a possible choice. However, if there is noise in image, edge might be ill-defined. Our algorithm for ill-defined edge detection is enhanced in this paper. In particular, we utilized the particle swarm optimization (PSO) in finding optimal parameters in the algorithm, rather than using manual settings as in the original work. There are two data sets, i.e., synthetic and carpal bone data sets, used in the experiment. We found that the intersection over union (IOU) on the blind test data set of the synthetic data set is 0.9200\pm 0.0144. The result on the blind test carpal bone data set is 0.9228\pm 0.0592. For the carpal bone data set, we compare the result with that from the original algorithm. The result shows that the enhanced method performs better than the original one. However, there is still a problem in misleading edge direction because of gradient and edge map generation. © 2023 IEEE.

关键词： Swarm intelligence

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10-point connector formed by two snap buttons

10-point connector formed by two snap buttons

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2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Yang, Chang-Ming Wu, Shu-Cing Kao, Rally Liao, Kuo-Cheng Wu, Ze-We Chen, Shih-Hung Chen, Chi-Chun Ming Young Biomedical Corp Miaoli Taiwan National Chin-Yi University of Technology Program Prospective Technology of Electrical Engineering and Computer Science Taichung Taiwan Bonanza Biotechnology Co.Ltd National Chin-Yi University of Technology Dept. of Computer Science and Information Engineering Taichung Taiwan National Chin-Yi University of Technology Dept. of Electronic Engineering Taichung Taiwan

ISBN: (纸本)9798350324136

With the rapid advancement of electronic textiles, the design and integration of connectors have emerged as pivotal challenges. This study emphasizes the development of a connection solution that amalgamates miniaturization, efficiency, and reliability, specifically tailored for Flexible Conductive Silicone Circuits. A diversified connection scheme is proposed, incorporating elements such as snaps, Pogo pins, and conductive hook-and-loop fasteners, thereby achieving an innovative and pragmatic design. Through meticulous manufacturing processes, including the utilization of hot-melt adhesive, PET films, conductive fabric, and other multilayer materials, a connection system with low impedance and commendable conductivity was successfully engineered. Impedance test outcomes have indicated that the resistance at each connection point is less than 0.7 ohms, substantiating its superior electrical properties. In terms of assembly, this research demonstrates the precise interconnection of the controller and conductive fabric circuit, ensured by metal pin technology, leading to connection stability. This solution not only furnishes appropriate connection technology for specific application scenarios but also opens new avenues and directions for connection design within the domain of electronic textiles. © 2024 IEEE.

关键词： Connectors E-Textiles Flexible Conductive Silicone Circuit PET films

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Expanding chiral metamaterials for retrieving fingerprints via vibrational circular dichroism

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Light(Science & Applications) 2023年第7期12卷 1401-1414页

作者： Cheng Xu Zhihao Ren Hong Zhou Jingkai Zhou Chong Pei Ho Nan Wang Chengkuo Lee Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Center for Inteligent Sensors and MEMS(CISM) National University of SingaporeSingapore 117608Singapore institute of Microelectronics(IME) Agency for ScienceTechnology and Research(A*STAR)Singapore 138634Singapore NUS Graduate School for Integrative Science and Engineering Program(ISEP) National University of SingaporeSingapore 117456Singapore

Circular dichroism(CD)spectroscopy has been widely demonstrated for detecting chiral ***,the determination of chiral mixtures with various concentrations and enantiomeric ratios can be a challenging *** solve this problem,we report an enhanced vibrational circular dichroism(VCD)sensing platform based on plasmonic chiral metamaterials,which presents a 6-magnitude signal enhancement with a selectivity of chiral *** by coupled-mode theory,we leverage both in-plane and out-of-plane symmetry-breaking structures for chiral metamaterial design enabled by a two-step lithography process,which increases the near-field coupling strengths and varies the ratio between absorption and radiation loss,resulting in improved chiral light-matter interaction and enhanced molecular VCD ***,we demonstrate the thin-film sensing process of BSA andβ-lactoglobulin proteins,which contain secondary structures a-helix andβ-sheet and achieve a limit of detection down to zeptomole ***,we also,for the first time,explore the potential of enhanced VCD spectroscopy by demonstrating a selective sensing process of chiral mixtures,where the mixing ratio can be successfully differentiated with our proposed chiral *** findings improve the sensing signal of molecules and expand the extractable information,paving the way toward label-free,compact,small-volume chiral molecule detection for stereochemical and clinical diagnosisapplications.

关键词： chiral vibrational circular

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Design and simulation of a 2-D array flexible ultrasound transducer system for tissue characterization-A pilot study

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Medicine in Novel Technology and Devices 2022年第1期13卷 59-64页

作者： Zhihua Gan Brian Guo Jiqi Cheng Yi-Xian Qin Department of Biomedical Engineering Stony Brook UniversityStony BrookNY11794USA Department of Electrical and Computer Engineering Stony Brook UniversityStony BrookNY11794USA

Noninvasive diagnosis of bone density and mechanical properties using non-radiation imaging modality is an emerging area with promising in early prediction of osteopenia and treatment effectiveness in the clinic and functional disuse,i.e.,long-term bedrest and space *** in quantitative ultrasound have shown advantages in measuring both bone density and mechanical strength,non-radiation,imaging capability,and easy to *** challenge that remained is the poor penetration of ultrasound signals passing through trabecular and cortical bones and acoustic energy scattering.A new scanning confocal ultrasound technology is developed in this lab to detect the alteration of bone to provide diagnostic results in bone density and structure properties.A software-controlled flexible ultrasound system with 2-D dual array transducer is developed and proposed for the purpose of noninvasive bone density diagnosis and assessment of bone ***(Tx)transducer elements are divided into sub-blocks to excite the ultrasound signals in sequence to decrease the system complexity while maintaining beam pattern properties by the signal processing procedure at receiving(Rx)*** is also applied to reduce acoustic side lobes and to make the resolution in the ultrasound field of view(FOV)more *** study may provide basic understanding of modulated confocal ultrasound beam forming for tissue characterization,such as trabecular bone structual and strength properties.

关键词： Flexible ultrasound system Noninvasive diagnostic imaging Sub-block triggering Ultrasound imaging resolution Apodization Quantitative ultrasound Trabecular bone property Scanning ultrasound Bone density and strength

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