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2020 International Conference on Smart Technology and Applications, ICoSTA 2020

作者： Amirullah Soeprijanto, Adi Adiananda Penangsang, Ontoseno Universitas Bhayangkara Surabaya Electrical Engineering Study Program Faculty of Engineering Surabaya Indonesia Institut Teknologi Sepuluh Nopember Department of Electrical Engineering Surabaya Indonesia

ISBN: (纸本)9781728130835

This paper presents an analysis of the Unified Power Quality Conditioner-Photovoltaic (UPQC-PV) system under sag and interruption voltage with variable irradiance. The PV is connected to a three-phase three-wire (3P3W) distribution system with 380 volts (L-L) and a frequency of 50 hertz, through UPQC-DC link. This system is used to maintain and supply sensitive loads. This paper shows that in the sag voltage and irradiance levels of 200 W/m2 to 1200 W/m2, the 3P3W system uses UPQC-PV with proportional-integral (PI) still able to maintain the active load power above 3714 W. However, in the interruption voltage and same irradiance level, the load active power drops to between 2560 W and 2805 W. This research also shows that in the sag voltage and same irradiance levels, the 3P3W system uses UPQC-PV with PI still able to generate PV power between 500 W to 920 W. In the interruption voltage and same irradiance levels, the power that can be generated by PV increases between 1300 W to 1635 W. Otherwise, at 250 C and 1000 W/m2, the increase in PV power on interruption voltage has not been able to meet the load active power consumption, so it finally drops to 2650 W. This paper is simulated using Matlab/Simulink. © 2020 IEEE.

关键词： Energy transfer

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Development of teaching materials for improving motivation to learn electromagnetics using ict

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IEEJ Transactions on Fundamentals and Materials 2020年第4期140卷 171-178页

作者： Ohtaki, Yu Ohchi, Masashi Master's Program in Electrical Electronics and Computer Engineering Graduate School of Engineering Chiba Institute of Technology 2-17-1 Tsudanuma Narashino275-0016 Japan Department of Electrical and Electronic Engineering Faculty of Engineering Chiba Institute of Technology 2-17-1 Tsudanuma Narashino275-0016 Japan

In this research, we have been developed teaching materials for electromagnetics that demonstrate theories using real-world actual applications (capacitors, coils, piezoelectric elements, Wireless Power Transfer(WPT), WiFi, direct-current motor, etc.) presented as animations and video data via Web services. Hypertext Markup Language (HTML) and JavaScript were used to create the Web services for teaching materials. Recently, the lack of academic ability of Japanese engineering course students has become a large social problem at Japanese higher education. In particular, in the field of electrical engineering education, the visualization and mathematical abilities of students have been declining remarkably. In addition, today's teaching materials for educational institutions in Japan tend to reply primarily on rote learning. However, we consider that rote learning is not the primary method for university education. We tested our new developed materials on students learning motivation of electromagnetics and evaluated their effectiveness with some questionnaires. It was clear that the new teaching method has effectiveness for increasing learning motivation of Electromagnetics. © 2020 The Institute of electrical Engineers of Japan.

关键词： Web services

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Twenty years of e-learning in health science: A bibliometric 7

Twenty years of e-learning in health science: A bibliometric

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7th International Conference on Computer Science and Computational Intelligence, CSCI 2022

作者： Maulana, Fairuz Iqbal Febriantono, M. Aldiki Raharja, Dwi Risza Budi Khaeruddin Herasmara, Ridho Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Diploma III Electronic Technology Vocational Study Program University of Muhammadiyah Malang Indonesia Electrical Engineering Faculty of Science and Technology Raden Rahmat Islamic University Malang Indonesia

Education about health sciences has historically been limited in the curriculum of health professionals and largely inaccessible to the public. In practice, most of the health science education is still running conventionally. Supposedly with the advancement of technology and the use of the internet everywhere, learning such as e-learning can be important, especially in the health sector. Until this research was conducted, only 514 academic documents about e-learning in health sciences were found for 20 years from 2001 to 2020, obtained in searching on the Scopus database. This study presents a comprehensive overview of studies related to E-learning in the Health Sciences sector. This study uses bibliometric analysis and indexed digital methods to map scientific publications throughout the world. This research employs the Scopus database to gather information, as well as the Scopus online analysis tool and Vosviewer to show the bibliometric network. The method consists with five stages: determining search keywords, initial search results, refinement of search results, initial compilation, and data analysis. Among the most published and indexed articles by Scopus, papers published by researchers in the United States have the highest number of publications (80), followed by United Kingdom (63) and Australia with 45 academic publications. The processed data shows the pattern and trend of increasing the number of international publications in E-learning in Health Sciences field, which Scopus index. © 2022 Elsevier B.V.. All rights reserved.

关键词： Publishing

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Long short-term memory (LSTM) model-based reinforcement learning for nonlinear mass spring damper system control

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Procedia Computer Science 2023年 216卷 213-220页

作者： Santo Wijaya Yaya Heryadi Yulyani Arifin Wayan Suparta Lukas Computer Science Department BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta 55281 Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta 12930 Indonesia

The Neural Networks (NN) model which is incorporated in the control system design has been studied, and the results show better performance than the mathematical model approach. However, some studies consider that only offline NN model learning and does not use the online NN model learning directly on the control system. As a result, the controller's performance decreases due to changes in the system environment from time to time. The Reinforcement Learning (RL) method has been investigated intensively, especially Model-based RL (Mb-RL) to predict system dynamics. It has been investigated and performs well in making the system more robust to environmental changes by enabling online learning. This paper proposes online learning of local dynamics using the Mb-RL method by utilizing Long Short-Term Memory (LSTM) model. We consider Model Predictive Control (MPC) scheme as an agent of the Mb-RL method to control the regulatory trajectory objectives with a random shooting policy to search for the minimum objective function. A nonlinear Mass Spring Damper (NMSD) system with parameter-varying linear inertia is used to demonstrate the effectiveness of the proposed method. The simulation results show that the system can effectively control high-oscillating nonlinear systems with good performance.

关键词： Model-based Reinforcement Learning Random-Shooting Policy LSTM MPC Nonlinear System

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AI In Healthcare: Using Bayesian Networks To Predict Response To Immune Checkpoint Blockades

AI In Healthcare: Using Bayesian Networks To Predict Respons...

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National Conference on Radio Science (NSRC)

作者： Ahmed H. Saadawy Aly F. Hissam Eman Badr Omar M. Fahmy Biomedical Sciences Program Zewail City of Science and Technology Giza Egypt Faculty of Computers and Artificial Intelligence Cairo University Giza Egypt Omar Mamdouh Fahmy Electrical Engineering Dept. Badr University in Cairo Giza Egypt

Cancer remains a leading cause of death worldwide, with its heterogeneous and patient-specific nature complicating treatment. Immunotherapy, especially immune checkpoint blockades (ICB), shows promising potential by reactivating the immune system to detect and destroy cancer cells. However, their effectiveness largely depends on the patient’s clinical and molecular characteristics, making them unsuitable for everyone. This highlights the importance of developing predictive and interpretable models that could distinguish potential responders from non-responders. This study aims to utilize gene expression data to predict patients’ responses to ICB and identify key genes whose expression is associated with treatment outcome using probabilistic Bayesian networks (BNs). To address the high-dimensional nature of gene expression data, we propose and compare the use of machine learning-based feature selection (FS) and clustering by weighted gene co-expression network analysis (WGCNA). To our knowledge, this is the first study to apply BNs along with FS and WGCNA dimensionality reduction techniques to tackle ICB response using transcriptomic data. We achieved a maximal classification accuracy of 75% and identified eight genes and two gene clusters directly influencing ICB response. These results may offer more biological insights and mechanisms underlying ICB response. The proposed pipeline will contribute to guiding treatment decisions, minimizing harmful side effects, and reducing the financial costs associated with ineffective treatments.

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Electronic and Structural Insights into Boron Nitride Counterparts of Net-(Y,W)

SSRN

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SSRN 2024年

作者： Lima, Kleuton Antunes Lopes dos Santos, Emanuel José Alexandrino de Mendonça, Fábio Lúcio Lopes da Silva, Daniel Alves Giozza, William Ferreira Ribeiro, Luiz Antonio Institute of Physics University of Brasília Brasília70910-900 Brazil Computational Materials Laboratory LCCMat Institute of Physics University of Brasília Brasília70910-900 Brazil Department of Electrical Engineering Faculty of Technology University of Brasília Brasília Brazil Professional Postgraduate Program in Electrical Engineering - PPEE University of Brasília Brasília Brazil

Computational materials play a crucial role in comprehending various material classes and their properties, offering valuable insights for predicting novel structures and complementing experimental approaches. Net-(C,Y,W) has emerged as stable two-dimensional carbon allotropes of 4-6-8 carbon rings within this framework. This study uses density functional theory calculations and ab initio molecular dynamics simulations to explore the structural, electronic, optical, and mechanical properties of their boron nitride counterparts, named NetBN-W and NetBN-Y, with NetBN-C already investigated. The electronic analysis reveals an insulating characteristic for NetBN-W and a potential wide band gap semiconducting nature for NetBN-Y, with values of 5.12 eV and 3.71 eV, respectively. Optical properties examination indicates UV activity for these materials, accompanied by optical anisotropy between the x and y directions. Evaluation of mechanical properties also uncovers significant anisotropy in both materials, with Young's moduli reaching 417.58 GPa for NetBN-W and 433.31 GPa for NetBN-Y when stretched in the y-direction of the basal plane. The nearly zero Young's modulus for NetBN-Y in the x-direction signifies its substantial instability under tension due to nitrogen bonds parallel to the strain direction. These findings offer valuable insights into the fundamental properties of NetBN-W and NetBN-Y and their potential applications. © 2024, The Authors. All rights reserved.

关键词： Density functional theory

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Prediction of Internet Broadband Connectivity Classification in West Java Indonesia using Machine Learning

Prediction of Internet Broadband Connectivity Classification...

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Artificial Intelligence Robotics, Signal and Image Processing (AIRoSIP), International Conference on

作者： Wahyu Haris Kusuma Atmaja Yaya Heryadi Ilvico Sonata Lukas Wayan Suparta Computer Science Department Binus Graduate Program - Computer Science Bina Nusantara University West Jakarta Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Engineering Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

ISBN: (数字)9798350327472

ISBN: (纸本)9798350327489

A location's Take-up Rate was significantly influenced by its Internet connectivity and availability. The purpose of this research is to answer concerns about internal Internet Service Provider issues that affect Internet connectivity in clusters of West Java, Indonesia. It also aims to evaluate the results of models that forecast how these internal factors will affect internet connectivity. According to the research findings, the FTTH Cluster has eight significant Internet predictor connectivity out of 18 elements. Activation delay and Administration Documentation of Activation with Connectivity were the two major parameters modeled out of the 18 components. Artificial Neural Network (ANN), Support Vector Machine (SVM), and Decision Tree (DT) models were used to predict Internet Broadband Connectivity Classification based on the two most important variables. According to the study, ANN is the best model, with 99% accuracy and 99.6% precision when compared to SVM and DT. Furthermore, it exceeds previous studies that used the ANN model and achieved 97.92% accuracy.

关键词： Support vector machines Java Accuracy Web and internet services Artificial neural networks Predictive models Internet Broadband communication Optical fiber subscriber loops Robots

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What Role Do Aggregators Play in Power System Security and Resilience?

What Role Do Aggregators Play in Power System Security and R...

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Resilience Week (RWS)

作者： Reiko Matsuda-Dunn Laura Leddy Eliza Hotchkiss Mukesh Gautam Michael Abdelmalak National Renewable Energy Laboratory Golden CO USA Advanced Energy Systems PhD Program Colorado School of Mines Colorado School of Mines Golden CO USA Department of Electrical and Biomedical Engineering University of Nevada at Reno Reno NV USA

Barriers to the participation of distributed energy resources (DERs) in wholesale electricity markets have limited the use of DERs for power system security and resilience. In September 2020, the Federal Energy Regulatory Commission (FERC) approved an order to reduce these barriers. FERC Order No. 2222 enables the participation of DER aggregators in wholesale electricity markets. DERs include renewable generation and technologies that support the integration of renewable generation by increasing grid flexibility and resilience. Requiring wholesale energy markets to allow DER aggregator participation provides a path for DERs to become competitive in these markets. As the contribution from aggregated DERs continues to increase, the aggregator's role in supporting grid security and resilience will become more critical. This paper reviews work that demonstrates how DER aggregators can provide resilience support through technical capabilities, operational strategies, and secure communication architectures. Socioeconomic influences and impacts of aggregators, including implications for social resilience, are presented. In surveying the current state-of-the-art across different but interconnected topics, we illustrate how aggregators can be power system participants that enhance grid security. There is no one-size-fits-all approach to enhancing resilience in a power grid that includes a growing cohort of DER aggregators, but there are many options for aggregators to contribute to a more resilient and secure power grid.

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Electronic and Electrochemical Properties of Novel Cathode Material NaFeSO4OH by First-Principle Calculations

Electronic and Electrochemical Properties of Novel Cathode M...

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International Conference on Renewable Energy and E-mobility, ICREEM 2022

作者： Idrus, Aqeel Badrudin, Fadhlul Wafi Shaffee, Siti Nur Amira Hassan, Oskar Hasdinor Sazman, Fatin Nabilah Zaki, Nur Hamizah Mohd Zolkiffly, Mohd Zaid Ali, Ab Malik Marwan Ahmad, Shahrul Izwan Baharom, Rahimi Taib, Mohamad Fariz Mohamad Zu Azhan Yahya, Muhd Faculty of Defence Science and Technology Universiti Pertahanan Nasional Malaysia Kuala Lumpur57000 Malaysia Centre for Defence Foundation Studies Universiti Pertahanan Nasional Malaysia Kuala Lumpur57000 Malaysia Renewables Technology Program PETRONAS Group Research and Technology Jln Ayer Hitam Kawasan Institusi Bangi Selangor Bandar Baru Bangi43000 Malaysia Faculty of Arts and Design Universiti Teknologi MARA Selangor Shah Alam40450 Malaysia Institute of Science Universiti Teknologi MARA Selangor Shah Alam40450 Malaysia Faculty of Electrical Engineering Universiti Teknologi MARA Selangor Shah Alam40450 Malaysia

ISBN: (纸本)9789819959457

We reported first-principle calculations on the structural and electronic properties of layered sodium iron(II) hydroxysulfate, NaFeSO4OH as a potential cathode for sodium-ion battery. Layered NaFeSO4OH was virtually derived from the experimentally reported layered LiFeSO4OH by replacing Li with Na. A redox voltage of 3.00 V was computed along with the theoretical capacity of 140 mAh/g, yielding an energy density of 420 Wh/kg. The electronic band gap is predicted to be similar to the Li counterpart of the material. This material has some valuable positive attributes, including high capacity and energy density, sturdy host structure as well as being made up of abundant elements. © Institute of Technology PETRONAS Sdn Bhd (Universiti Teknologi PETRONAS) 2024.

关键词： Electronic properties

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Meaningful human control: actionable properties for AI system development

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AI and Ethics 2022年第1期3卷 241-255页

作者： Cavalcante Siebert, Luciano Lupetti, Maria Luce Aizenberg, Evgeni Beckers, Niek Zgonnikov, Arkady Veluwenkamp, Herman Abbink, David Giaccardi, Elisa Houben, Geert-Jan Jonker, Catholijn M. van den Hoven, Jeroen Forster, Deborah Lagendijk, Reginald L. AiTech Interdisciplinary Research Program on Meaningful Human Control Delft University of Technology Delft The Netherlands Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft The Netherlands Faculty of Industrial Design Engineering Delft University of Technology Delft The Netherlands Faculty of Mechanical Maritime and Materials Engineering Delft University of Technology Delft The Netherlands Faculty of Technology Policy and Management Delft University of Technology Delft The Netherlands

How can humans remain in control of artificial intelligence (AI)-based systems designed to perform tasks autonomously? Such systems are increasingly ubiquitous, creating benefits - but also undesirable situations where moral responsibility for their actions cannot be properly attributed to any particular person or group. The concept of meaningful human control has been proposed to address responsibility gaps and mitigate them by establishing conditions that enable a proper attribution of responsibility for humans; however, clear requirements for researchers, designers, and engineers are yet inexistent, making the development of AI-based systems that remain under meaningful human control challenging. In this paper, we address the gap between philosophical theory and engineering practice by identifying, through an iterative process of abductive thinking, four actionable properties for AI-based systems under meaningful human control, which we discuss making use of two applications scenarios: automated vehicles and AI-based hiring. First, a system in which humans and AI algorithms interact should have an explicitly defined domain of morally loaded situations within which the system ought to operate. Second, humans and AI agents within the system should have appropriate and mutually compatible representations. Third, responsibility attributed to a human should be commensurate with that human’s ability and authority to control the system. Fourth, there should be explicit links between the actions of the AI agents and actions of humans who are aware of their moral responsibility. We argue that these four properties will support practically minded professionals to take concrete steps toward designing and engineering for AI systems that facilitate meaningful human control.

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