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2024 International Conference on Information Technology and Computing, ICITCOM 2024

作者： Alita, Debby Ahmad, Imam Jafar Rumandan, Rhaishudin Erkamim, Moh Widyasmoro Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandarlampung Indonesia Institut Agama Islam Negeri Ambon Islamic Education Management Study Program Ambon Indonesia Universitas Tunas Pembangunan Smart City Information Systems Study Program Surakarta Indonesia Universitas Muhammadiyah Yogyakarta Faculty of Engineering Department of Electrical Engineering Yogyakarta Indonesia

ISBN: (纸本)9798350379839

Stunting in toddlers is a chronic nutritional issue that affects the physical and cognitive development of children, with serious long-term consequences such as reduced cognitive function and an increased risk of chronic diseases in adulthood. Therefore, early identification and prevention efforts for stunting are crucial. Classifying toddlers into categories of at-risk for stunting or not is essential to provide timely and appropriate interventions. This study employs data mining techniques using the decision tree algorithm to expedite the stunting detection process and improve the accuracy of nutritional status classification in children. The results indicate that the constructed decision tree model can classify children's nutritional status with an accuracy of 83.26%. The decision tree achieves high accuracy in classifying stunting in toddlers due to its ability to handle complex data and identify significant patterns within the data. © 2024 IEEE.

关键词： Classification Data Mining Decision Tree Stunting

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Frequency Stability Improvement of Integrated Micro-Grid Using Battery Storage System Based Distribution Static Compensator (BESS-DSTATCOM)

Frequency Stability Improvement of Integrated Micro-Grid Usi...

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2024 IEEE Global Energy Conference, GEC 2024

作者： Imtiaz, Saqif Munir, Mudassir Ali, Maqsood Kilic, Heybet Altimania, Mohammad R. Yilmaz, Musa Yang, Lijun School of Electrical Engineering Yanshan University Qinhuangdao066004 China Department of Electrical Engineering Sukkur IBA University Sukkur65200 Pakistan Department of Electric Power and Energy Systems Dicle University Diyarbakir21280 Turkey Electrical Engineering Department University of Tabuk Tabuk47512 Saudi Arabia Bourns College of Engineering University of California at Riverside RiversideCA92521 United States

ISBN: (纸本)9798331532611

Dynamic instability challenges can be encountered in microgrids (MG), especially frequency fluctuations generated at the point of common coupling (PCC), leading to an unreliable microgrid. A novel method of improving frequency stability of the wind based microgrid is proposed in this study through the integration of a Battery Energy Storage System (BESS) with a Distribution Static Compensator (DSTATCOM). A BESS-DSTATCOM with a six pulse regulated control scheme that manages reactive power while mitigating frequency instabilities, especially in fault event scenarios becomes part of the system. Prolonged frequency disturbances at the PCC due to faults are critical to MG stability and need to be addressed for reliable MG operation. Through the proposed BESS DSTATCOM approach, reactive power management is optimized to maintain system frequency as consistent as possible. The proposed method was developed, tested, and verified in MATLAB, showing that this approach successfully improves frequency stability in the microgrid under various operating conditions. The simulation results show the effectiveness of the BESS DSTATCOM strategy on MG operation. ©2024 IEEE.

关键词： Frequency stability

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A Novel Compact Ultrawideband Microstrip Patch Antenna for Satellite Communications System 8th

A Novel Compact Ultrawideband Microstrip Patch Antenna for S...

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8th International Conference on Space Science and Communication, IconSpace2023

作者： Rahman, Md. Afzalur Al‑Bawri, Samir Salem Islam, Mohammad Tariqul Singh, Mandeep Jit Rahman, Md. Asifur Bangi43600 Malaysia Department of Electrical Electronic and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia UKM Selangor Bangi43600 Malaysia Department of Electrical and Electronic Engineering School of Science and Engineering United International University UIU United City Madani Ave Dhaka1212 Bangladesh

ISBN: (纸本)9789819701414

The present study outlines the development and execution of a unique, condensed, ultrawideband microstrip patch antenna through the utilization of CST Microwave Studio software. The aforementioned antenna, with dimensions of 15 × 18.30 × 1.6 mm3, has been designed with a particular focus on its utility in the context of satellite communication applications. The substrate utilized in its construction is Rogers RT5880 material. The antenna exhibits a noteworthy characteristic of achieving a wide range of bandwidth coverage, estimated to be around 140.39%. The system exhibits versatility in fulfilling diverse communication needs as it functions through three distinct frequency bands, specifically the C, X, and Ku bands. The antenna demonstrates exceptional transmission capabilities, achieving maximum efficiency of 93%. Remarkably, the antenna demonstrates a noteworthy gain of 4.8 dBi, indicating its exceptional ability to amplify signals, despite its diminutive size. The device’s expansive frequency range, condensed physical dimensions, and noteworthy amplification render it appropriate for a diverse array of wireless implementations. Given these characteristics, the aforementioned antenna presents itself as a highly appropriate option for applications in satellite communication. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Bandwidth

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Optimizing Energy Efficiency in Smart Buildings Through Intelligent HVAC Control systems 8

Optimizing Energy Efficiency in Smart Buildings Through Inte...

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8th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024

作者： Cengiz, Korhan Biruni University Department of Electrical-Electronics Engineering Istanbul Turkey University of Jordan Faculty of Information Technology and Systems Jordan

ISBN: (纸本)9798350354423

This work explores the optimization of HVAC systems in smart buildings through the integration of advanced methodologies, including machine learning algorithms. Specif-ically, we investigate the application of neural networks, and genetic algorithms to enhance energy efficiency and user comfort. Through a comprehensive experimental evaluation, we validated of our proposed approach over existing optimization strategies, as evidenced by improvements in predictive accuracy, user satisfaction, and energy consumption reduction. Our findings highlight the efficacy of leveraging advanced optimization techniques in addressing the complex challenges of HVAC control in modern building infrastructures. © 2024 IEEE.

关键词： Smart homes

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Variable Speed Control of Wound Rotor Synchronous Motor with MTPA Technique

Variable Speed Control of Wound Rotor Synchronous Motor with...

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2023 International Aegean Conference on electrical Machines and Power Electronics and 2023 International Conference on Optimization of electrical and Electronic Equipment, ACEMP-OPTIM 2023

作者： Guldan, Mehmet Mert Akgul, Kadir Tap, Alper Ergene, Lale T. Istanbul Technical University Department of Electrical Engineering Istanbul Turkey AVL Research & Engineering E-Drive Systems Istanbul Turkey

ISBN: (纸本)9798350311495

In today's world, electrical machines are essential in various industries and our daily lives. The popular choice is the permanent magnet synchronous machine (PMSM), however it has some drawbacks. Since PMSMs require rare-earth elements (or other special alloys), a magnet-free alternative motor called wound rotor synchronous machine (WRSM) used to reduce reliance on foreign industries. The field current of a WRSM passing through the rotor windings generates the magnetic field which offers flexibility in flux linkage. The WRSMs have also some disadvantages compared to PMSMs such as increased rotor losses because of the field winding, and larger size. This study presents a modeling and control methods of WRSMs, highlighting the differences in the control algorithm. The control methods for WRSMs are similar to PMSMs like zero d-axis current (ZDC) control and maximum torque per ampere (MTPA) control. But the independent control of the field current allows for more flexible field-oriented control in high-speed applications of a WRSM. © 2023 IEEE.

关键词： Permanent magnets

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Physical Understanding of HfZrO2/Si FeFET Memory and Its AI Applications

Physical Understanding of HfZrO2/Si FeFET Memory and Its AI ...

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13th Symposium on Semiconductor Process Integration, held at the 244th Meeting of The Electrochemical Society

作者： Takagi, Shinichi Toprasertpong, Kasidit Cai, Zuocheng Nako, Eishin Nakane, Ryosho Takenaka, Mitsuru Department of Electrical Engineering and Information Systems The University of Tokyo Tokyo Japan

ISBN: (纸本)9781607685395

Si-friendly HfO2-based FeFETs have been well recognized as a technology booster for future integrated memory applications, which are expected to enhance the energy efficiency of AI computation. In this paper, we present our recent studies on the understanding of the coupling between polarization, inversion-layer charges, and carrier traps in HfZrO2 (HZO)/Si FeFET memory. Discrimination of polarization, inversion carriers, and trapped carriers is realized by combining P-V, quasi-split C-V, and Hall measurements of FeFETs. Polarization and electron/hole-trap interactions significantly affect the performance and characteristics of HZO/Si FeFETs. A large number of electron traps can enhance polarization and the memory window of n-FeFETs, while there are almost no hole traps, leading to the smaller memory window of p-FeFETs. We have also proposed a new scheme of physical reservoir computing with parallel data processing for speech recognition by using HZO/Si FeFETs. A high classification accuracy of 95.9 % has been experimentally demonstrated in the task to classify the audio waveforms of '0' to '9' spoken digits. © The Electrochemical Society.

关键词： Polarization

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A Hierarchical Multi-Step DERMS Framework for Day-Ahead Scheduling in Distribution Networks Hosting Soft Open Points

A Hierarchical Multi-Step DERMS Framework for Day-Ahead Sche...

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2024 IEEE/PES Transmission and Distribution Conference and Exposition, T and D 2024

作者： Baghbannovin, Salar Gavgani, Pouya Pourghasem Mohseni-Bonab, Seyed Masoud Kamwa, Innocent Université Laval Electrical Engineering Department Québec Canada Hydro-Québec/IREQ Digital Systems Department Varennes Canada

ISBN: (纸本)9798350316377

This work proposes a hierarchical control framework for the day-ahead scheduling of distribution networks (DNs). In the proposed framework, the set points of the network elements are achieved through a bi-level optimization. At the lower level, the aggregator-type distributed energy resources management system (DERMS) aggregates the distributed energy resources of the network and performs an economic dispatch (ED). At the higher level, initialized setpoints of the aggregated DERs are represented to the utility DERMS for security checks and decision-making. Besides, the distribution system operator (DSO) acts as the coordinator for the whole DN and facilitates the power supply of the network utilizing advanced power electronic devices namely soft open points (SOPs). The effective collaboration of the DSO and DERMS in networks hosting SOPs reduces the computational burden and improves the economy and security of the network. © 2024 IEEE.

关键词： Electric power distribution

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Optimizing Power Consumption in Data Centers Through Intelligent Load Balancing Algorithms 8

Optimizing Power Consumption in Data Centers Through Intelli...

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8th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024

作者： Cengiz, Korhan Biruni University Department of Electrical-Electronics Engineering Istanbul Turkey University of Jordan Faculty of Information Technology and Systems Jordan

ISBN: (纸本)9798350354423

Efficiently managing energy consumption, optimizing resource allocation, and improving computational performance are crucial objectives in contemporary data processing environments. This paper presents a novel methodology designed to address these challenges effectively. This paper introduces a novel methodology aimed at enhancing energy efficiency, optimizing resource utilization, and improving computational performance in data processing tasks. Through rigorous experimentation and analysis, our approach showcases substantial advancements over existing methods by achieving notable reductions in power consumption, achieving balanced resource allocation, and optimizing response times. The experimental findings underscore the efficacy of our methodology in tackling the intricate challenges inherent in contemporary data processing environments, thereby offering promising prospects for the development of sustainable and scalable computing infrastructures. © 2024 IEEE.

关键词： Computational Performance Data Processing Energy Efficiency Optimization Resource Utilization

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An Adaptive Framework for Classification and Detection of Android Malware

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2024年第21期18卷 59-73页

作者： Al Sharah, Ashraf Alrub, Yousef Abu Owida, Hamza Abu Elsoud, Esraa Abu Alshdaifat, Nawaf Khtatnaha, Hamzah Department of Electrical Engineering College of Engineering Technology Al-Balqa Applied University Amman Jordan Department of Computer Information Systems Faculty of Prince Al-Hussein Bin Abdallah II for Information Technology The Hashemite University Zarqa Jordan Department of Medical Engineering Faculty of Engineering Al-Ahliyya Amman University Amman Jordan Department of Computer Science Faculty of Information Technology Zarqa University Zarqa Jordan Faculty of Information Technology Applied Science Private University Amman Jordan

The hardware and software of a computer are controlled by its operating system (OS), which performs essential tasks such as input and output processing, file and memory management, and the management of peripheral devices such as disk drives and printers. Application software refers to programs designed for specific purposes, these applications, often freely available and open source, contribute to the rising number of downloads. In the third quarter of 2022, combined downloads from the Apple App Store and Google Play Reached an estimated 35.3 billion. However, the prevalence of insecurity in these applications and technologies heightens the potential for cybercrimes. Protection against unauthorized intruders is crucial in identifying malicious applications. Machine learning (ML) serves as a promising avenue for detecting malware attacks, offering potential solutions to bolster cybersecurity measures. We propose a novel approach utilizing ML to enhance malware detection accuracy by segmenting datasets into distinct groups. Our research employs supervised ML techniques on the CICMaldroid2020 dataset, which includes comprehensive information such as intent actions, permissions, and sensitive APIs. The dataset was partitioned into four groups, each containing 150 features, and analyzed across four experiments to distinguish between attack and benign classes. Our proposed model demonstrated exceptional performance, with the random forest algorithm achieving an accuracy of 98.6% and a precision of 98.75%. These results highlight the effectiveness of our segmentation approach and its significant contribution to advancing malware detection in Android applications, offering a promising direction for future cybersecurity solutions. © 2024 by the authors of this article.

关键词： Android malware

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A Design and Implementation of Stationery Product Recognition Method Using Two-Stage YOLO v8 Model 12

A Design and Implementation of Stationery Product Recognitio...

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12th International Conference on Information and Education Technology, ICIET 2024

作者： Zhou, Xudong Funabiki, Nobuo Jing, Yanhui Xiao, Yanqi Kao, Wen-Chung Okayama University Department Of Information And Communication Systems Okayama Japan National Taiwan Normal University Department Of Electrical Engineering Taipei Taiwan

ISBN: (纸本)9798350371772

A company typically maintains a lot of stationery products, such as ball-pens, glue-sticks, and erasers, for daily use in the operations. However, their accurate managements will cost a lot or often be impossible. Currently, YOLO is a very popular model for object recognition using images due to high capabilities. In this paper, we present a design and implementation of a stationery product recognition method using the latest YOLO v8 model at two stages. The first-stage model recognizes the category of the target object from the given image. The second-stage model selects the specific product in the category. For evaluations, we prepare 795 images of 45 stationery products in 9 categories and train the two-stage YOLO models using NVIDIA's RTX-3060 GPU. Then, we measure the training time and the recognition accuracy of the proposal. The results show the effectiveness of the proposal. © 2024 IEEE.

关键词： Object recognition

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