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10th IEEE Global Conference on Consumer Electronics, GCCE 2021

作者： Muchtar, Kahlil Saddami, Khairun Bintang, Akhyar Cenggoro, Tjeng Wawan Pardamean, Bens Lin, Chih-Yang Ernita, Tia Universitas Syiah Kuala Department of Electrical And Computer Engineering Aceh Indonesia Universitas Syiah Kuala Department of Electrical And Computer Engineering Aceh Indonesia Bina Nusantara University School of Computer Science Bina Nusantara University Bioinformatics And Data Science Research Center Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program-Master of Computer Science Program Bina Nusantara University Bioinformatics And Data Science Research Center Computer Science Department Jakarta Indonesia Yuan-Ze University Department of Electrical And Engineering Taoyuan Taiwan

ISBN: (纸本)9781665436762

In this paper, we propose a novel approach to locate and detect moving pedestrians in a video. Our proposed method first locates the region of interest (ROI) using a background subtraction algorithm based on guided filtering. This novel background subtraction algorithm allows our method to also filter unexpected noises at the same time, which could benefit the performance of our proposed method. Subsequently, the pedestrians are detected using YOLOv3 within the provided ROI. Our experiments showed that the proposed method has a competitive performance in the CDNET2014 dataset with a fast-processing time. © 2021 IEEE.

关键词： Convolutional neural networks

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2D Polynomial Regression Modeling for Predictive Analysis of Glucose Concentration in NP-Model Fractal Microwave Sensor Using Frequency and Transmission Coefficient Disparities

2D Polynomial Regression Modeling for Predictive Analysis of...

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13th International electrical engineering Congress, iEECON 2025

作者： Nantapanich, Nutyada Mahatthanajatuphat, Pisit Wongsin, Norakamon Lee, Wilaiporn Rajamangala University of Technology Thanyaburi Faculty of Engineering Department of Electronics and Telecommunication Engineering Pathum Thani Thailand Yothinburana School Regular Program in Mathematics-Science Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand

ISBN: (纸本)9798331543952

The article introduces a two-dimensional polynomial regression model for the predictive analysis of glucose concentration in a fractal microwave sensor NP model, utilizing frequency and transmission coefficient differences to examine their correlation with glucose concentration levels. The sensor employed in this investigation is fabricated on an economical FR-4 substrate to minimize costs. The sensor structure is developed with the fractal structure reduction method established by the NP model to operate at a frequency of roughly 2.97 GHz. The CST Studio software is utilized to analyze the findings from the simulation of the suggested sensor structure. Furthermore, the proposed sensor is integrated into a test apparatus comprising a sensor platform and a liquid tube constructed from PPA material. The liquid under examination is a glucose and water mixture at varying concentrations. It was analyzed using a VNA instrument to evaluate its frequency response and the magnitude of the alteration in the transmission coefficient. The values are utilized to create a two-dimensional polynomial regression model. The experiments demonstrated that the proposed sensor model possesses an Adjusted R² value of 0.99499 and an average error of approximately 3.57% for glucose concentration analysis throughout the range of 5% to 30%, with sensitivities of 0.00879 dB/% for insertion loss and 0.092 MHz/% for frequency variation, facilitating accurate glucose concentration prediction analysis. © 2025 IEEE.

关键词： Polynomial regression

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Effective Dimension Aware Fractional-Order Stochastic Gradient Descent for Convex Optimization Problems

arXiv

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arXiv 2025年

作者： Partohaghighi, Mohammad Marcia, Roummel Chen, YangQuan Electrical Engineering and Computer Science graduate program University of California Merced United States Department of Applied Mathematics University of California Merced MercedCA United States Lab Department of Mechanical Engineering School of Engineering University of California MercedCA95343 United States

Fractional-order stochastic gradient descent (FOSGD) leverages a fractional exponent to capture long-memory effects in optimization, yet its practical impact is often constrained by the difficulty of tuning and stabilizing this exponent. In this work, we introduce 2SED Fractional-Order Stochastic Gradient Descent (2SEDFOSGD), a novel method that synergistically combines the Two-Scale Effective Dimension (2SED) algorithm with FOSGD to automatically calibrate the fractional exponent in a data-driven manner. By continuously gauging model sensitivity and effective dimensionality, 2SED dynamically adjusts the exponent to curb erratic oscillations and enhance convergence rates. Theoretically, we demonstrate how this dimension-aware adaptation retains the benefits of fractional memory while averting the sluggish or unstable behaviors frequently observed in naive fractional SGD. Empirical evaluations across multiple benchmarks confirm that our 2SED-driven fractional exponent approach not only converges faster but also achieves more robust final performance, suggesting broad applicability for fractional-order methodologies in large-scale machine learning and related domains. © 2025, CC BY.

关键词： Convex optimization

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Global distortions from local rewards: neural coding strategies in path-integrating neural systems 24

Global distortions from local rewards: neural coding strateg...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Francisco Acosta Fatih Dinc William T. Redman Manu Madhav David Klindt Nina Miolane Department of Physics UC Santa Barbara CNC Program Stanford University Applied Physics Laboratory Johns Hopkins University Biomedical Engineering University of British Columbia NeuroAI CSHL Electrical & Computer Engineering UC Santa Barbara

ISBN: (纸本)9798331314385

Grid cells in the mammalian brain are fundamental to spatial navigation, and therefore crucial to how animals perceive and interact with their environment. Traditionally, grid cells are thought support path integration through highly symmetric hexagonal lattice firing patterns. However, recent findings show that their firing patterns become distorted in the presence of significant spatial landmarks such as rewarded locations. This introduces a novel perspective of dynamic, subjective, and action-relevant interactions between spatial representations and environmental cues. Here, we propose a practical and theoretical framework to quantify and explain these interactions. To this end, we train path-integrating recurrent neural networks (piRNNs) on a spatial navigation task, whose goal is to predict the agent's position with a special focus on rewarded locations. Grid-like neurons naturally emerge from the training of piRNNs, which allows us to investigate how the two aspects of the task, space and reward, are integrated in their firing patterns. We find that geometry, but not topology, of the grid cell population code becomes distorted. Surprisingly, these distortions are global in the firing patterns of the grid cells despite local changes in the reward. Our results indicate that after training with location-specific reward information, the preserved representational topology supports successful path integration, whereas the emergent heterogeneity in individual responses due to global distortions may encode dynamically changing environmental cues. By bridging the gap between computational models and the biological reality of spatial navigation under reward information, we offer new insights into how neural systems prioritize environmental landmarks in their spatial navigation code.

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Growing Our PEARLS and ASSETS Through a Support Ecosystem for Low-Income Academically Talented Students 54

Growing Our PEARLS and ASSETS Through a Support Ecosystem fo...

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： Lopez Del Puerto, Carla Jimenez, Manuel Alfaro, Monica Bellido, Carmen Cafaro, Matias J. Univ. of Puerto Rico Mayaguez Civil Engineering Department Mayaguez00681-9000 Puerto Rico Univ. of Puerto Rico Mayaguez Electrical & Computer Eng. Department Mayaguez00681-9000 Puerto Rico Univ. of Puerto Rico Mayaguez Biology Department Mayaguez00681-9000 Puerto Rico Teacher Preparation Program Univ. of Puerto Rico Mayaguez Mayaguez00681-9000 Puerto Rico

ISBN: (纸本)9798350351507

This research to practice paper describes two NSF-funded projects: The 'program for engineering Access, Retention, and LIATS Success' (PEARLS) and the 'Academic and Socioemotional Support Ecosystem for Talented low-income STEM Students' (ASSETS). These initiatives aim to support low-income, academically talented students pursuing STEM degrees, offering academic, socio-emotional, and financial assistance. Both projects provide mentoring, workshops, mental health services, and scholarships. Outcomes have shown increased engagement, retention, and graduation rates among participants compared to non-participants. Retention and persistence rates among PEARLS participants reached 97% and 96.3% respectively, showcasing the model effectiveness in keeping students focused on their studies. Graduation rates saw remarkable improvements, with on-time graduation rates soaring to 4.17 times that of non-participating students. The paper presents a robust framework for an integrated support ecosystem, emphasizing scalability and replicability across diverse institutions. By addressing the challenges faced by underprivileged students during environmental crises, this framework aims to foster equity and inclusion in higher education, ensuring all students have the support they need to succeed. © 2024 IEEE.

关键词： Students

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The Impact of Hot Carrier Injection-Induced Device Degradation for Lower-Power FinFETs

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Journal of Electronic Materials 2023年第2期52卷 1391-1399页

作者： Chen, Yu-Lin Yeh, Wen-Kuan Hsu, Heng-Tung Chen, Ke-Horng Lien, Der-Hsien Lin, Wen-Chin Yu, Tien-Han Chiu, Yu-Sheng Godwinraj, D. Godfrey, D. Wu, Chien-Hung International College of Semiconductor Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Electronics National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Microelectronics National Cheng Kung University Tainan Taiwan Department of ECE Amal Jyothi College of Engineering Kerala Kottayam India Department of Optoelectronics and Materials Engineering Chung Hua University Hsinchu Taiwan Department of Electronics and Communication Engineering Dayananda Sagar University Bengaluru India National Applied Research Laboratories Hsinchu Taiwan

The impact of hot carrier injection (HCI) on the performance of standard and low-VT FinFETs are investigated and benchmarked with each other. For this investigation, these FinFETs were fabricated with various gate lengths (L) from 16 to 36 nm. HCI-induced transconductance degradation in standard devices for gate length variations of 36 nm down to 16 nm was 75%, while it was 35% for low-VT devices. Similarly, the degradation of threshold voltage in standard devices for gate length variations of 36 nm down to 16 nm was 39%, while it was 36% for low-VT device. In this work, as the device is subject to HCI, we found that: (1) short-channel devices cause severe degradation on the threshold voltage and transconductance (gm) compared to long-channel devices, owing to the higher electric field for short-channel devices at the gate edge, (2) standard devices exhibit a more stable threshold voltage than that of low-VT power devices, since the TiN barrier layer prevents Al atom diffusion into the HfO2 layer, and (3) the transconductance efficiency of standard devices is better than that of low-VT power devices. Further, the lower-VT devices show lower transconductance degradation than standard devices. However, the transconductance degradation of the long-channel standard and low-VT devices are the same. Compared to short-channel low-VT devices, extended-channel standard devices are more immune to the HCI effect. © 2022, The Minerals, Metals & Materials Society.

关键词： Threshold voltage

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Epilayer on NEAT Grown GaN Schottky Diodes for Radiation Detection

Epilayer on NEAT Grown GaN Schottky Diodes for Radiation Det...

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2023 Transactions of the American Nuclear Society Annual Meeting and Technology Expo, ANS 2023

作者： Remy, Jarod Zhang, Yuxuan Talesara, Vishank Zhao, Hongping Lu, Wu Hashimoto, Tadao Cao, Lei R. Nuclear Engineering Program Department of Mechanical and Aerospace Engineering 281 W. Lane Ave. ColumbusOH43210 United States Department of Electrical and Computer Engineering 281 W. Lane Ave ColumbusOH43210 United States Department of Material Science and Engineering The Ohio State University 281 W. Lane Ave ColumbusOH43210 United States SixPoint Materials Inc 37 Industrial Way STE 106 BuelltonCA United States

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Fuzzy Logic Approach for Power Transformer Condition Assessment Using Health Index

Fuzzy Logic Approach for Power Transformer Condition Assessm...

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2022 International Conference on Power, Energy and Innovations, ICPEI 2022

作者： Dorji, Tashi Suwanasri, Thanapong Poonnoy, Nitchamon Suwanasri, Cattareeya EPE Program The Sirindhorn International Thai-German Graduate School of Engineering KMUTNB 1518 Pracharat 1 Rd. Bangsue Bangkok Thailand Department of Teacher Training in Electrical Engineering Faculty of Technical Education KMUTNB 1518 Pracharat 1 Rd. Bangsue Bangkok Thailand Department of Electrical and Computer Engineering Faculty of Engineering KMUTNB 1518 Pracharat 1 Rd.Bangsue Bangkok Thailand

ISBN: (数字)9781665460194

ISBN: (纸本)9781665460194

This paper presents a realistic power transformer condition assessment and Health Index (HI) determination technique. The real-time operating data of twenty-seven power transformers of Bhutan Power Corporation Limited in transmission substations are used for condition evaluation. The diagnostic test data are combined into nine diagnostic groups for condition assessment. The conventional method of scoring and weighting average and the fuzzy logic methods are adopted for the condition assessment of power transformers. The excel program was developed for the conventional method for seamless evaluation. All the parameters harmonies the estimation and classification of the transformer operating condition. Then, this paper proposed new procedures for validating the conventional system of HI determination by the fuzzy logic method. © 2022 IEEE.

关键词： Power transformers

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A WEARABLE GRAPHENE TRANSISTOR-BASED BIOSENSOR FOR MONITORING IL-6 BIOMARKER 25

A WEARABLE GRAPHENE TRANSISTOR-BASED BIOSENSOR FOR MONITORIN...

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25th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2021

作者： Laliberte, Kaitlyn E. Scott, Patrick Khan, Niazul I. Mahmud, Md Shaad Song, Edward Department of Electrical and Computer Engineering University of New Hampshire United States Materials Science Program University of New Hampshire United States

ISBN: (纸本)9781733419031

Graphene field-effect transistor (GFET) is becoming an increasingly popular biosensing platform for monitoring health conditions through biomarker detection. Moreover, the graphene's 2-dimensional geometry makes it ideal for implementing flexible wearable devices. In this work, we present a printable graphene transistor-based biosensor that can be used as a wearable sensor to detect a protein biomarker Interleukin-6 (IL-6). Our device contains a voltage control, a current meter, and a power source all integrated into a single miniaturized platform making it a truly skin-mounted wearable device. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

关键词： Graphene transistors

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A Position Control System for a Single-port Laparoscopic Manipulating Robot

A Position Control System for a Single-port Laparoscopic Man...

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2022 International electrical engineering Congress, iEECON 2022

作者： Sonsilphong, Amornthep Sonsilphong, Suphachoke Soemphol, Chaiyong Hormdee, Daranee Khampitak, Kovit Rajamangala University of Technology Isan Department of Electrical Engineering Khon Kean Thailand Khon Kaen University Data Science Health Informatics Program Faculty of Medicine Khon Kaen Thailand Mahasarakham University Faculty of Engineering Department of Electrical Engineering Mahasarakham Thailand Khon Kaen University Embedded System RD Group Computer Engineering Faculty of Engineering Khon Kaen Thailand Khon Kean University Faculty of Medicine Department of Obstetrics and Gynecology Khon Kean Thailand

ISBN: (纸本)9781665402064

The research herein proposes a position control system, designed for a single-port surgical robot, based on the lockup table method. The programmable logic controller (PLC) was implemented to move the single- port surgical robot and handle laparoscope and surgical instruments with feedback control. The output responses of the desired angle were investigated under several conditions. The rotating angle allows movement of the laparoscope in the range of -10o to +10o. The error of the desired position of the designed system was less than approximately ± 0.1o. Moreover, the output data from several experiments may be employed to improve the open-loop control systems. This system is also capable of providing computer vision task implementation, enabling semi- automatic or automatic surgery in the future. © 2022 IEEE.

关键词： Laparoscopy

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