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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Rikos, Apostolos I. Jiang, Wei Charalambous, Themistoklis Johansson, Karl H. Artificial Intelligence Thrust of the Information Hub Guangzhou China The Hong Kong University of Science and Technology Department of Computer Science and Engineering Clear Water Bay Hong Kong Aalto University School of Electrical Engineering Department of Electrical Engineering and Automation Espoo Finland University of Cyprus School of Engineering Department of Electrical and Computer Engineering Nicosia1678 Cyprus Kth Royal Institute of Technology Division of Decision and Control Systems StockholmSE-100 44 Sweden

ISBN: (纸本)9798350316339

In realistic distributed optimization scenarios, individual nodes possess only partial information and communicate over bandwidth constrained channels. For this reason, the development of efficient distributed algorithms is essential. In our paper we addresses the challenge of unconstrained distributed optimization. In our scenario each node's local function exhibits strong convexity with Lipschitz continuous gradients. The exchange of information between nodes occurs through 3-bit bandwidth-limited channels (i.e., nodes exchange messages represented by a only 3 -bits). Our proposed algorithm respects the network's bandwidth constraints by leveraging zoom-in and zoom-out operations to adjust quantizer parameters dynamically. We show that during our algorithm's operation nodes are able to converge to the exact optimal solution. Furthermore, we show that our algorithm achieves a linear convergence rate to the optimal solution. We conclude the paper with simulations that highlight our algorithm's unique characteristics. © 2024 IEEE.

关键词： Bandwidth

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An Efficiency-Enhanced LCC-S Based Inductive Power Transfer Converter Throughout Battery Constant Current Charging Process 32

An Efficiency-Enhanced LCC-S Based Inductive Power Transfer ...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Luo, Yuying Iam, Io-Wa Ding, Zhaoyi Chan, Pak-Ian Lam, Chi-Seng University of Macau Institute of Microelectronics China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering China

ISBN: (纸本)9798350399714

Constant current (CC) charging is a dominant charging process before the battery can be fully charged and the battery is considered as an equivalent resistance with a wide range variation during the process. However, a wide load range variation causes the transfer efficiency of inductive power transfer (IPT) converter to deviate from the optimum point. Therefore, transfer efficiency optimization measures are required during battery CC charging process with IPT converter. Herein, this paper proposed a suitable bivariate control method for a single-stage IPT converter based on inductor-capacitor-capacitor-series (LCC-S) compensation topology, which keeps the converter output current constant and improves transfer efficiency. The newly adopted bivariate control method includes two control variables, the conduction angle of the voltage-controlled semi-active rectifier (VCSAR) and the operating frequency of the inverter. The equivalent load of the VCSAR is adjusted by controlling the conduction angle, and at the same time, the operating frequency of the inverter is controlled to ensure constant current output. Finally, simulation results are presented to verify the effectiveness of the bivariate control method for the LCC-S compensated IPT converter. In addition, zero-voltage switching (ZVS) can be realized in both sides of the converter. © 2023 IEEE.

关键词： Zero voltage switching

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Development and Evaluation of a Secure Patient Health Monitoring Internet of Things Mobile Application

Development and Evaluation of a Secure Patient Health Monito...

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2024 IEEE SmartBlock4Africa, SmartBlock4Africa 2024

作者： Shoewu, Oluwagbemiga Omotayo Akinwole, Bukola Hannah Akinyemi, Lateef Adesola Computer Engineering Lagos State University Lagos Nigeria University of Port-Harcourt Department of Electrical and Electronic Engineering Rivers Nigeria CSET University of South Africa Department of Compt. Science and Electrical Engineering Johannesburg South Africa

ISBN: (纸本)9798350376838

Despite advancements in medical technology, healthcare practitioners face challenges in continuous patient monitoring, leading to delayed diagnoses, chronic disease progression and increased healthcare costs. The integration of the Internet of Things (IoT) technology in healthcare enables real-time remote monitoring of patients and connected medical devices, facilitating timely interventions. This study presents a secure IoT-based mobile application (app) for patient health monitoring and evaluates its effectiveness in improving healthcare outcomes and efficiency. The proposed system utilizes various sensors to track vital signs, including heart rate, blood oxygen levels, body temperature and electrocardiograms in real-time. It features a smart notification system that displays critical data in red when thresholds are exceeded, alerting healthcare professionals to urgent issues. The system employs a microcontroller and sensors to securely collect and transmit patient data to an online server, accessible to authorized healthcare professionals via a unique login. Results show high accuracy in monitoring vital signs, with error rates consistently below 3% compared to existing IoT systems. Specifically, the highest error rates were 2.857% for heart rate, 2.174% for blood oxygen levels, and 1.701 % for body temperature, while the lowest error rates were 1.075% for 1.031 % and 0.168%, respectively. The mean squared errors (MSE) were 2.80%, 2.35%, and 0.054°C. These findings confirm the system's reliability and effectiveness in patient health monitoring. Moreover, the system empowers individuals to proactively manage their health, ultimately facilitating the transition to data-driven precision medicine. © 2024 IEEE.

关键词： Electrocardiograms

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IoT-Enabled Solar-Powered Water Trash Collector with Conveyor Belt 8th

IoT-Enabled Solar-Powered Water Trash Collector with Conveyo...

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8th International Conference on Information and Communication Technology for Competitive Strategies, ICTCS 2023

作者： Devapriya, S. Krishna, M. K. Nandana Gondi, Bhavika Vinuha, Chinta Pandi, V. Ravikumar Sathyan, Soumya Valsan, Vipina Suresh, Kavya Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India Department of Electrical and Electronics Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9789819994854

This study presents a novel solution in the form of a solar-powered water trash collector, designed specifically for deployment in backwaters and smaller water bodies, to address the critical issues of water pollution and waste management. Focusing on the challenges faced by national rivers, including hazardous polymers, plastic waste, and decaying organic matter, the collector operates under IoT-enabled Bluetooth control using mobile application, incorporating a conveyor belt mechanism for efficient waste collection, particularly targeting prevalent plastic debris in freshwater environments. A notable feature of this solution is its integration of solar power, ensuring self-sustained operation and reduced environmental impact, aligning with the imperative for eco-friendly waste management technologies. Bluetooth control enhances adaptability for smaller water bodies, crucial for precise navigation. The core objective is to provide an effective solar-powered water trash collector tailored for backwaters, addressing the escalating waste production due to population growth. Additionally, a comprehensive waste management approach is proposed, facilitated by an Android application for seamless navigation of integrated trash bins. In conclusion, this study offers an innovative approach to tackle water pollution and waste management, introducing a solar-powered collector uniquely equipped to address backwater ecosystems’ specific challenges while promoting sustainability and environmental well-being. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Bluetooth

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A Machine Learning Approach to Motif Finding for LncRNA Sub-cellular Localization

A Machine Learning Approach to Motif Finding for LncRNA Sub-...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Yi, Weijun Miller, Jason R Hu, Gangqing Adjeroh, Donald A. West Virginia University Computer Science and Electrical Engineering MorgantownWV United States Hood College Computer Science and Information Technology FrederickMD United States Wvu School of Medicine Microbiology Immunology and Cell Biology MorgantownWV United States

ISBN: (纸本)9798350386226

Motifs are functional elements in DNA, RNA, and protein sequences. Motif finding in molecular sequences is well studied. However, applying machine learning techniques specifically integrating cytoplasmic/nuclear relative concentration index (CN-RCI) of genes across multiple cell lines to uncover motifs associated with lncRNA subcellular localization is still a new area of study. In this work, we start with the CN-RCI values from genes in multiple cell lines to develop a machine learning approach for identifying lncRNA motifs that are associated with lncRNA subcellular localization. The reliability of the approach is analyzed, first by using the identified motifs in experiments on classification of lncRNA subcellular localization, and then by comparison of the motifs against a library of known localization-related sequence fragments. © 2024 IEEE.

关键词： Adversarial machine learning

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Vertically Stackable Memcapacitor Crossbar Array based on NAND Flash Array Structure

Vertically Stackable Memcapacitor Crossbar Array based on NA...

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2024 IEEE International Electron Devices Meeting, IEDM 2024

作者： Yu, Junsu Hwang, Hwiho Kim, Hyungjin Choi, Woo Young Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Division of Materials Science and Engineering Department of Semiconductor Engineering Hanyang University Seoul04763 Korea Republic of

ISBN: (纸本)9798350365429

In this work, a vertically stackable 4F2 memcapacitor crossbar array based on charge trap flash (CTF) is experimentally demonstrated with a TiN-Al2O3- Si3N4-SiO2-Si (TANOS) gate stack. 4-bit multi-level operation of the fabricated 24 × 48 array is verified with more than 10 years of retention and no read/write disturbance. Also, vector-matrix multiplication (VMM) operations with an error of 0.227 % are validated, along with read operations using a sensing circuit. Based on the measurement data of the planar array, the capability of performing read/write operations with a vertically stacked 3-D structure is verified through TCAD simulations. A weight transfer procedure is also provided to enhance VMM accuracy in a scaled-down vertical structure, resulting in significantly suppressed VMM errors. © 2024 IEEE.

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DynFS: dynamic genotype cutting feature selection algorithm

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Journal of Ambient Intelligence and Humanized Computing 2023年第12期14卷 16477-16490页

作者： Fister, Dušan Fister, Iztok Karakatič, Sašo Faculty of Economics and Business University of Maribor Razlagova 14 Maribor2000 Slovenia Faculty of Electrical Engineering and Computer Science University of Maribor Koroška cesta 46 Maribor2000 Slovenia

Large information datasets often impose an immense number of features where many are found redundant and thus inessential for statistical analysis. In the past, a data preprocessing phase was formalized to cope with the problem and take appropriate remedial measures. Traditionally, this was a fixed and stationary process that suffered from a lack of transparency and high susceptibility to input variations. This paper presents a novel and fully automated meta-heuristic nature-inspired wrapper-based feature selection framework DynFS with dynamically cutting search space. The experiments show that the DynFS statistically significantly overcomes a fixed feature selection framework and allows for a high level of robustness and stability. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Swarm intelligence

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A Lightweight Drone Simulator 10

A Lightweight Drone Simulator

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10th International Conference on Software Defined Systems, SDS 2023

作者： Blake Putnam, Evan Nihal Senarath, Dylan Ramirez Urquijo, Giselle Tunc, Cihan Bryce, Renee California State Polytechnic University Humboldt Department of Computer Science ArcataCA United States California State Polytechnic University Pomona Department of Electrical and Computer Engineering PomonaCA United States University of North Texas Department of Computer Science and Engineering DentonTX United States

ISBN: (纸本)9798350382235

Drones are valuable assets across industries for a variety of purposes, including but not limited to surveillance, transportation, delivery, smart agriculture, etc. However, drone-related studies may require significant costs to purchase, configure, and deploy to study algorithms and how drones interact with each other. Alternatively, drone simulators can provide a lower-cost option to investigate drones and related algorithms. Nevertheless, drone simulators on the market today tend to be computationally heavy, have a steep learning curve, and may be overwhelming for abstract problem-solving studies. There is a need for an inexpensive and easy testing alternative for researchers and for high-level algorithm development. In this paper, we present a lightweight and easy-to-use drone simulator that allows the definition of multiple drones with their sensors, actuators, speed, and battery limit as well as their communication among themselves. The simulator also allows the definition of the simulation world using small blocks that can be defined using different parameters. We presented two scenarios, such as package delivery and survey area coverage, to show the capabilities of the simulator. The simulator information can be achieved from our group website. © 2023 IEEE.

关键词： Drones

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Assessment of processing time and measurement accuracy of different phase compensation methods in Quantitative Phase Imaging via Digital Holographic Microscopy applied to Biological Specimens Holographic Microscopy

Assessment of processing time and measurement accuracy of di...

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3D Image Acquisition and Display: Technology, Perception and Applications, 3D 2024 - Part of Optica Imaging Congress

作者： Obando-Vásquez, Sofía Doblas, Ana Trujillo, Carlos Applied optics group School of Applied Science and Engineering Universidad EAFIT Medellín Colombia Department of Electrical and Computer Engineering University of Massachusetts DartmouthMA United States

Six different methods for phase compensation in Digital Holographic Microscopy are compared using a calibrated test target and a Toxocara canis larva sample regarding processing time, measurement accuracy, and usefuln...

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Hybrid Xception-ResNext BiLSTM Model with Attention and Visual Synchronization for Robust Deepfake Detection

Hybrid Xception-ResNext BiLSTM Model with Attention and Visu...

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2024 International Conference on System, Computation, Automation and Networking, ICSCAN 2024

作者： Suresh, M. Raghavan, J.Vijaya Roy, Abhisek Das, Swet Snigdha Srm Institute of Science and Technology Department of Computing Technologies Chennai India Manakula Vinayagar Institute of Technology Department of Electrical and Electronics Engineering Pondicherry India Computer Science Engineering Srm Institute of Science and Technology Chennai India

ISBN: (纸本)9798331510022

Deepfake technology has become a significant problem since it allows for the creationof compelling manipulated videos. This research presents a novel hybrid deepfake detection system that combines the Xception and ResNext networks with a Bidirectional Long Short-Term Memory (BiLSTM) model and Convolutional Block Attention Module (CBAM). Apart from focusing on the temporal and spatial anomalies of deepfakes, our model also includes visual synchronization analysis and physiological signal detection. Extensive experiments are conducted across several datasets, exhibiting cutting-edge performance across various manipulation scenarios. The proposed method achieves good generalization, as they are in real-world circumstances. © 2024 IEEE.

关键词： Gallium nitride

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