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4th International Conference on Artificial Intelligence and Electromechanical Automation, AIEA 2023

作者： Sun, BenBen Guan, WanBing Wang, JianXin Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China Key Laboratory of Advanced Fuel Cells and Electrolyzers Cell Technology of Zhejiang Province Ningbo Institute of Materials Technology & Engineering Chinese Academy of Sciences Ningbo China

ISBN: (纸本)9781510666412

Solid oxide fuel cells (SOFCs) have the advantages of high conversion efficiency, low working noise, and environmental protection. Thus, they are widely used in large-scale power generation, combined heat power, peak load-regulating energy storage, and other fields. In the actual working process of SOFCs, the battery performance will decline sharply due to extreme conditions such as overtemperature and peroxide, and the service life will be terminated. Remote monitoring of fuel cells can detect problems in time and restore the battery’s performance by restoring the battery, thereby extending its service life. The data generated by fuel cells during operation have a strong temporal correlation. To discover the future state of fuel cells in time and solve the problem that a large number of codes are needed for monitoring, this paper designs a remote monitoring system of fuel cells with low-code based on Node-RED and Ali Cloud. The output current of fuel cells is predicted by using the improved back propagation neural network based on Levenberg-Marguardt (LM-BPNN) algorithm. The test result of LM-BPNN shows that the test samples have a root mean square error of 0.172, a mean absolute percentage error of 3.85%, and a coefficient of determination of 0.998. © 2023 SPIE.

关键词： Digital storage

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Evaluating Power Demand Dynamics at a Rural U.S. Highway DC-Fast Charging Station

Evaluating Power Demand Dynamics at a Rural U.S. Highway DC-...

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2023 IEEE Industry Applications Society Annual Meeting, IAS 2023

作者： Stenstadvolden, Anders Zhao, Long Kapourchali, Mohammad Heidari Zhou, Yuhao South Dakota School of Mines and Technology Dept. Electrical Engineering and Computer Science Rapid City United States University of Alaska Anchorage Dept. Electrical Engineering Anchorage United States University of Texas at Arlington Dept. Electrical Enginering Arlington United States

ISBN: (纸本)9798350320169

The proliferation of electric vehicles (EVs) and EV charging infrastructure along the U.S. Interstate Highway System poses significant challenges to the power grid. To address these challenges, it is necessary to develop a comprehensive understanding of the power demand characteristics for existing EV charging stations along interstates. This study presents an analysis of the charging trends and demand behaviors of a level-3 DC-fast EV charging station on the U.S. interstate using two years of actual 15-minute smart meter data. The rural location of the EV charging station provides representative charging trends and behaviors for EV charging stations along the U.S. Interstate Highway System in the rural region. The analysis investigates demand trends for both years based on different time periods, such as month, season, and weekday, and introduces a new index term, Charging Behavior (CB), to analyze the similarities in the charging demand behavior at the EV charging station between both years of demand. Additionally, the study investigates the seasonal impact of EV traffic density. The findings of this study can inform power professionals and researchers in preparing for the increase in EVs and EV infrastructure along the U.S. Interstate Highway System. © 2023 IEEE.

关键词： Electric power utilization

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Cloud-Enabled Patient Acuity Prediction Utilizing Decision Trees in Smart ICU Nurse Assignment Systems 4

Cloud-Enabled Patient Acuity Prediction Utilizing Decision T...

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4th International Conference on Sustainable Expert Systems, ICSES 2024

作者： Arul Prasath, A. Saravanan, S. Monikapreethi, S.K. Brindha, G. Maheshwari, S. Srinivasan, C. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Muthayammal Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Namakkal India Rajalakshmi Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Meenakshi College of Engineering Department of Electronics and Instrumentation Engineering Tamil Nadu Chennai India Sri Sai Ranganathan Engineering College Department of Information Technology Tamil Nadu Coimbatore India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331540364

This research introduces a new method for improving Intensive Care Units (ICUs) nurse assignment using cloud computing and Decision Trees (DTs )-based patient acuity prediction models. Effective and timely care delivery is dependent on the efficient allocation of nursing resources, which is becoming more important due to the growing complexity of patients' situations in ICUs. To integrate patient data from many sources seamlessly the proposed system uses cloud infrastructure to process and analyze data in real-time. To proactively identify high-risk situations, use DTs algorithms to forecast patient acuity levels using a variety of clinical indicators. Optimizing staffing levels and improving patient outcomes which incorporates these predictions into the nurse assignment process. Through a case study performed in a real-world ICUs improves nurse efficiency and the quality of patient care. The findings of this study highlight the promise of decision support systems hosted in the cloud for improving the delivery of healthcare in ICUs. © 2024 IEEE.

关键词： Nursing

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Design, Simulation and Performance Analysis of S-Band Microstrip Patch Antenna for Wireless Applications 4

Design, Simulation and Performance Analysis of S-Band Micros...

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4th IEEE Global Conference for Advancement in technology, GCAT 2023

作者： Sohel Rana, Md. Joy, Sanjay Kumar Jubaer Nazmul, Md. Soriful Islam Sourav, Md. Jakaria Hassan, Md. Naheen Khurshid, Md. Rabiul Islam, Sheikh Md. Department of Electrical and Electronic Engineering Northern University of Business and Technology Khulna Khulna9100 Bangladesh Department of Computer Science and Engineering Bangladesh University of Professionals Mirpur Cantonment Dhaka Bangladesh Department of Electronics and Communication Engineering Khulna University of Engineering and Technology Khulna9203 Bangladesh

ISBN: (纸本)9798350305258

This research described above includes the planning, simulation, and examination of a microstrip patch antenna operating at a frequency of 2.5 GHz. This antenna is designed for use in wireless applications that work in the S-band. Because of its low loss tangent and high dielectric permittivity, the Rogers RO3006 material was chosen to serve as the substrate for the antenna. The dielectric permittivity of this material is 6.5. The entire antenna was developed with computer simulation technology (CST) software, which was also utilized for simulation purposes;Origin Pro software was used to display the graphs. The simulated antenna had a return loss of -42.476 dBi, a gain of 6.1 dBi, a voltage standing wave ratio (VSWR) of 1.01, and a directivity of 7.1 dBi, according to the results of the simulation. The fundamental purpose of the research paper is to achieve a standard VSWR by reducing the return loss of the antenna, increasing the gain and directivity of the antenna, and improving the antenna's efficiency. Because of this, the antenna will be able to function more effectively. © 2023 IEEE.

关键词： 2.5GHz CST return loss Rogers RO3006 VSWR

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Safety Case Conversion from Goal Structuring Notation to Structured Assurance Case Metamodel 31

Safety Case Conversion from Goal Structuring Notation to Str...

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31st International Scientific Conference Electronics, ET 2022

作者： Buysse, Laure Vanoost, Dries Vankeirsbilck, Jens Boydens, Jeroen Pissoort, Davy Faculty of Engineering Technology Department of Electrical Engineering Bruges8200 Belgium Ku Leuven Bruges Campus Faculty of Engineering Technology Department of Computer Science Bruges8200 Belgium

ISBN: (数字)9781665498784

ISBN: (纸本)9781665498784

Assurance cases are a valuable tool in communicating arguments for the justification of system properties. Graphical notations provide a clear way to presents these arguments. However, many commercial tools fail to implement recent standards and provide no support to the transition between notations. This paper presents an assurance case tool fit to the most recent guidelines, providing support for multiple notations with the abiliy to convert a safety case to a different notation. © 2022 IEEE.

关键词： Safety Standards Guidelines

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Survey of Covid Vaccine Hesitancy 15

Survey of Covid Vaccine Hesitancy

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Tripathi, Kirti Carter, Vivian Fergerson, An'Darius Prakash, Duraisamy Dutt, Varun Lloyd Institute of Engineering and Technology Electronics and Communication Engineering Uttar Pradesh India Tuskegee University Department of Psychology & Sociology AL United States University of Wisconsin-Green Bay Department of Computer Science WI United States Indian Institute of Technology Mandi School of Computing and Electrical Engineering Himachal Pradesh India

ISBN: (纸本)9798350370249

Vaccination serves as vital for strengthening immunity to illnesses and diseases that occurred amid the COVID-19 pandemic. There is a significant reluctance on the part of the general public as well as medical professionals to get vaccinated despite the affordability and availability of numerous licensed vaccines. This reluctance mainly causes worries about possible problems and negative effects. The keyword 'Vaccine hesitancy during COVID-19' was the primary search keyword on the Google Scholar platform. Seventeen studies that were published recently on the COVID19 pandemic that reported vaccine reluctance were found via our search, and these have been included in this review. During this survey, we found that the acceptance or rejection of vaccines was influenced by several criteria, such as income, education, gender, age, politics, religion, work position, and ethnicity. The vaccine was frequently refused for several reasons, which involve a general dislike of vaccinations, safety concerns or the belief that a rapidly developed vaccine may be too risky, the belief that immunity already exists or that the vaccine is unnecessary because COVID-19 is relatively harmless, a general lack of trust, doubts about the vaccine's efficacy, and distrust about the vaccine's origin. This review emphasizes the factors influencing COVID-19 vaccine acceptance and participation in clinical trials globally. It also presents strategies to enhance attitudes toward vaccination drives in the future. Additionally, governments and health authorities need to improve communication efforts and build public confidence. © 2024 IEEE.

关键词： Covid-19 Ethnicity Healthcare Vaccine Acceptance Vaccine Hesitancy

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Turning to Information Theory to Bring in-Memory Computing into Practice

IEEE BITS the Information Theory Magazine

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IEEE BITS the Information Theory Magazine 2023年第3期3卷 64-77页

作者： Dupraz, Elsa Leduc-Primeau, Francois Cai, Kui Dolecek, Lara Lab-STICC UMR CNRS IMT Atlantique Brest29238 France Polytechnique Montreal Department of Electrical Engineering MontrealQCH3T 1J4 Canada Singapore University of Technology and Design Science Mathematics and Technology Cluster Singapore487372 Singapore UCLA Department of Electrical and Computer Engineering Los AngelesCA90095 United States

This article explores the emerging field of in-memory computing, which has the potential to significantly improve energy efficiency in many signal processing and machine learning applications. In-memory computing systems are impacted by various sources of noise and perturbations that can affect their computation accuracy. Therefore, this article aims to identify the key challenges to be addressed from an information-theoretic point of view in this area. It first identifies relevant computation structures and noise models from the literature of hardware implementation, and then reviews existing works in information theory and error-correction for in-memory computing. Finally, it identifies key open avenues for establishing information-theoretic foundations of in-memory computing systems, and for providing insightful design rules leading to highly energy-efficient computing systems. © 2021 IEEE.

关键词： Error correction

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Collision Avoidance for AGV Navigation Using the Time Elastic Band Algorithm

Collision Avoidance for AGV Navigation Using the Time Elasti...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Hsu, Pei-En Lin, Cheng-Hung He, Jyun-Hong Chiang, Hsin-Han National Taiwan Normal University Dept. Electrical Engineering Taipei Taiwan National Taipei University of Technology Dept. Computer Science and Information Engineering Taipei Taiwan National Taipei University of Technology Dept. Vehicle Engineering Taipei Taiwan

ISBN: (纸本)9798350324174

This paper presents a design and implementation of an automated guided vehicle (AGV) that addresses the dynamic obstacle avoidance problem in navigation. We employ the TEB path planner, which is based on laser range sensors, as the algorithm for dynamic obstacle avoidance. In the development process, the Stage simulation is previously conducted to obtain suitable parameters. The environment used in the Stage simulation is a flat map of the real vehicle verification site, and the robot specifications and sensors used are the same as those of the actual vehicle. Finally, we apply the parameters obtained from the simulation to the real AGV for validation. © 2023 IEEE.

关键词： Navigation

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Wi-Fi RTT Range Offset and Multi-Band Analysis: Challenges and Opportunities for Indoor Localization

Wi-Fi RTT Range Offset and Multi-Band Analysis: Challenges a...

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IEEE Symposium on Position Location and Navigation (PLANS)

作者： Sultan Al Sulami Tarig Ballal Muhammad Moinuddin Tareq Al-Naffouri Electrical and Computer Engineering Dept King Abdulaziz University Jeddah Saudi Arabia Electrical and Computer Engineering Dept King Abdullah University of Science and Technology Thuwal Saudi Arabia

ISBN: (数字)9798331523176

ISBN: (纸本)9798331523183

Indoor localization has emerged as a critical research area, driven by the growing need for accurate positioning in environments where Global Navigation Satellite Systems (GNSS) are unavailable. Wi-Fi Round-Trip Time (RTT) has shown promise for precise indoor positioning, but the presence of systematic offsets across frequency bands poses significant challenges to its accuracy and reliability. These offsets, arise with factors such as device heterogeneity, multipath propagation, and environmental interference, not only degrade RTT performance but also complicate its integration with RTT multi-band and other measurement sources . This study presents a comprehensive analysis of RTT range offset across the 2.4 GHz, 5 GHz, and 6 GHz frequency bands, identifying it as limiting factor in achieving high-precision indoor positioning. Furthermore, we investigate the potential of multi-band fusion to mitigate these offsets and explore the associated challenges in realizing accurate localization systems. Our findings offer insights into integration of RTT-multi-band to overcome the practical limitations of RTT technology.

关键词： Location awareness Global navigation satellite system Time-frequency analysis Accuracy Systematics Limiting Correlation Calibration Frequency measurement Wireless fidelity

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Analysis of Google Play Store's Sentiment Review on Indonesia's P2P Fintech Platform

Analysis of Google Play Store's Sentiment Review on Indonesi...

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2022 IEEE Delhi Section Conference, DELCON 2022

作者： Amrie, Syahrul Kurniawan, Sandy Windiatmaja, Jauzak Hussaini Ruldeviyani, Yova Universitas Indonesia Faculty of Computer Science Department of Information Technology Jakarta Indonesia Universitas Indonesia Faculty of Computer Science Department of Computer Science Jakarta Indonesia Universitas Indonesia Faculty of Engineering Department of Electrical Engineering Jakarta Indonesia Universitas Indonesia Faculty of Computer Science Department of Computer Science Depok Indonesia

ISBN: (纸本)9781665458832

Nowadays there are so many mobile phone-based investment applications, ranging from mutual funds, stocks, and P2P lending. While these investment applications are gaining huge attraction among the general masses, sometimes selecting the right platform still becomes a hot issue. This research aimed to analyze the sentiment on P2P lending applications and to determine the user's response due to the increase in the number of funds distribution during the COVID-19 pandemic. By doing so, this research could give some insight into the new and existing user. Data was obtained through assessment reviews on the Play store platform for the P2P A, P2P B, and P2P C applications. Assessment reviews were classified by using a data mining approach, TF-IDF feature extraction, and Naïve-Bayes classification method. This research showed that P2P A got 77% positive sentiment and 23% negative sentiment, P2P B got 36% positive sentiment and 64% negative sentiment, and P2P C got 68% positive sentiment and 32% negative sentiment. From the results of the study, it was found that P2P A got better results than both P2P B and P2P C. those were 77% positive sentiment with 23% negative sentiment in finance topic, 56% positive sentiment with 44 % negative sentiment in account verification topic, 79% positive sentiment with 21% negative sentiment in apps review, and 99% positive sentiment with 1% negative sentiment in referral topic. © 2022 IEEE.

关键词： Sentiment analysis

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