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IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Burak Dindar Can Berk Saner Hüseyin Kemal Çakmak Veit Hagenmeyer Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany Department of Electrical and Computer Engineering National University of Singapore Singapore

ISBN: (数字)9798350318098

ISBN: (纸本)9798350318104

The integration of distributed generators (DGs) into the electrical grid has introduced new dimensions in power system management: Enhancing efficiency and operational flexibility of the grid requires taking into account the DGs located at the distribution level in dispatch decisions, while also considering the operational constraints of both distribution and transmission levels. However, the centralization of cooperation between transmission system operators (TSOs) and distribution system operators (DSOs) is troublesome due to privacy concerns of both parties. In present paper, we introduce a Machine Learning-Based Privacy-Preserving Optimal Power Flow (MLB-PP-OPF) framework. This method enables the seamless inclusion of DGs at the distribution level in optimal power flow calculations, all while adhering to the operational limits of both systems and maintaining data privacy. The proposed approach leverages three machine learning models to map the distribution system variables to active and reactive power flows at the point of common coupling, and to determine the feasible operating region of the distribution system in a privacy-preserving manner. Comparative case studies, performed on the coupled IEEE 30-bus transmission and 33-bus distribution test systems, demonstrate that the results achieved using MLB-PP-OPF align almost perfectly with those obtained through classical OPF, while maintaining data privacy.

关键词： Couplings Data privacy Reactive power Privacy Machine learning Generators Data models

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Transformer-Based Embeddings for Greek Language Categorization

Transformer-Based Embeddings for Greek Language Categorizati...

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International Conference on computer and Information Science (ACIS)

作者： Charalampos M. Liapis Konstantinos Kyritsis Isidoros Perikos Michael Paraskevas Mathematics Dept. University of Patras Computer Technology Institute & Press “Diophantus” Patras Greece Electrical and Computer Engineering Dept. University of Peloponnese Patras Greece Computer Engineering and Informatics Department Electrical and Computer Engineering Dept. University of Patras University of Peloponnese Computer Technology Institute and Press “Diophantus” Patras Greece Electrical and Computer Engineering Dept. University of Peloponnese Computer Technology Institute and Press “Diophantus” Patras Greece

ISBN: (数字)9798350376647

ISBN: (纸本)9798350376654

The Greek School Network (GSN) provides support to students, teachers, and school units in secondary education across Greece. Handling numerous user queries manually can be challenging, necessitating the development of an automated system for accurate categorization of these queries. This paper presents a comparative study of various transformer-based models for multi-class text categorization of Greek language queries submitted to the GSN helpdesk. We introduce a new experimental balanced dataset and extract vector representations from eleven transformer-based models. These representations are evaluated using ten classic machine learning classifiers. Our findings highlight the superior performance of the Multilingual E5 Text Embeddings model, particularly when paired with the extreme gradient-boosting classifier. This combination demonstrates a clear advantage in accurately categorizing user queries, paving the way for more efficient automated helpdesk systems.

关键词： Information science Accuracy Computational modeling Text categorization Education Machine learning Transformers Vectors

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Enhancing Early Childhood Literacy: A Technological Aid for Letter Learning

Enhancing Early Childhood Literacy: A Technological Aid for ...

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Information and Communication technology for Development for Africa (ICT4DA), International Conference on

作者： D. I. De Silva K. S. N. Athukorala Department of Information Technology Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Science and Informatics Uva Wellassa University Badulla Sri Lanka

ISBN: (数字)9798331527792

ISBN: (纸本)9798331527808

Children generally learn at a slower pace than adults, necessitating additional practice, especially during early education stages. Mastery of the alphabet is crucial as it forms the foundation of any language, making it imperative for children to learn it first. Each child possesses a distinct learning style, and the duration required to grasp new concepts can vary considerably among individuals. To address this, the Sinhala Alphabet Learning Tool has been developed, offering preschoolers an interactive platform that enhances engagement and facilitates their learning experience. This research employs the K-Nearest Neighbors algorithm combined with image processing techniques to accurately predict letters input by preschoolers. A substantial dataset comprising 56,000 entries was meticulously collected directly from preschool participants. The data were systematically organized into folders based on letter classification, subsequently used to train the K-Nearest Neighbors model, known for its simplicity and effectiveness in pattern recognition tasks. The tool enables users to input Sinhala letters and immediately receive feedback on the correctness of their entries. The system evaluates the shape of the letters and provides feedback with an impressive accuracy rate of 87%, ensuring that preschoolers receive reliable insights into their learning progress. While previous studies have primarily focused on recognizing Sinhala characters using Optical Character Recognition integrated with machine learning algorithms, the proposed approach diverges by capturing letter inputs through a graphical user interface developed using Tkinter. This design significantly enhances the interactivity and user-friendliness of the tool, making it more suitable and appealing for preschool-aged children.

关键词： Training Systematics Shape Supervised learning Nearest neighbor methods Prediction algorithms Vectors Classification algorithms Character recognition Reliability

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Participatory Design Workshop to Create a Virtual Reality Musical Instrument Based on Tumbuk Kalang 8th

Participatory Design Workshop to Create a Virtual Reality Mu...

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8th International Visual informatics Conference, IVIC 2023

作者： Baharin, Hanif Norowi, Noris Saffian, Khatriza Ahmad Sim, Yap Eng Institute of Visual Informatics Universiti Kebangsaan Malaysia Selangor UKM Bangi43600 Malaysia Faculty of Computer Science and Information Technology Universiti Putra Malaysia Selangor Serdang43400 Malaysia Conservatory of Music College of Creative Arts University Teknologi MARA Selangor Shah Alam40450 Malaysia

ISBN: (纸本)9789819973385

This paper describes a participatory design workshop to design a virtual reality musical instrument based on Tumbuk Kalang. Originating as a performance for rice harvesting festivals, Tumbuk Kalang as a traditional musical instrument consists of a mortar and pestles. Several players, each holding a pestle will coordinate their movements to pound on the same mortar to create rhythmic sounds whilst singing. These days, Tumbuk Kalang is no longer associated with rice harvest but has been innovated in cultural performances that include songs, dances, and other musical instruments. As machines take over rice production, pestles and mortars are out of use and the tradition of Tumbuk Kalang may be lost. Thus, this research proposes to create a Virtual Reality (VR) Tumbuk Kalang so that it can be preserved and played by future musicians. However, instead of recreating Tumbuk Kalang in VR, we suggest that innovation should be introduced in the design of the new VR Tumbuk Kalang. Hence, we have conducted a participatory design workshop with 12 musicians to design the new VR Tumbuk Kalang. The findings from the workshop produces six new designs of VR musical instruments based on Tumbuk Kalang. The contributions of this paper include the new designs of VR Tumbuk Kalang and the participatory design method used which may be replicated by other researchers who are aiming to preserve traditional musical instruments in the form of VR. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Virtual reality

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Wital: A COTS WiFi Devices Based Vital Signs Monitoring System Using NLOS Sensing Model

arXiv

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arXiv 2023年

作者： Zhang, Xiang Gu, Yu Yan, Huan Wang, Yantong Dong, Mianxiong Ota, Kaoru Ren, Fuji Ji, Yusheng The School of Computer and Information Hefei University of Technology China I+ Lab School of Computer Science and Engineering University of Electronic Science and Technology of China China The Dept. of Sciences and Informatics Muroran Institute of Technology Japan The National Institute of Informatics Tokyo101-8430 Japan

Vital sign (breathing and heartbeat) monitoring is essential for patient care and sleep disease prevention. Most current solutions are based on wearable sensors or cameras;however, the former could affect sleep quality, while the latter often present privacy concerns. To address these shortcomings, we propose Wital, a contactless vital sign monitoring system based on low-cost and widespread commercial off-the-shelf (COTS) Wi-Fi devices. There are two challenges that need to be overcome. First, the torso deformations caused by breathing/heartbeats are weak. How can such deformations be effectively captured? Second, movements such as turning over affect the accuracy of vital sign monitoring. How can such detrimental effects be avoided? For the former, we propose a non-line-of-sight (NLOS) sensing model for modeling the relationship between the energy ratio of line-of-sight (LOS) to NLOS signals and the vital sign monitoring capability using Ricean K theory and use this model to guide the system construction to better capture the deformations caused by breathing/heartbeats. For the latter, we propose a motion segmentation method based on motion regularity detection that accurately distinguishes respiration from other motions, and we remove periods that include movements such as turning over to eliminate detrimental effects. We have implemented and validated Wital on low-cost COTS devices. The experimental results demonstrate the effectiveness of Wital in monitoring vital signs. © 2023, CC BY.

关键词： Wireless local area networks (WLAN)

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Automated Estimation of Left Myocardial Strain from Cine CTA: A Comparison with Cine MRI

Automated Estimation of Left Myocardial Strain from Cine CTA...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Sun, An-Yu Hsu, Li-Yueh Chang, Lin-Ching Bandettini, W Patricia Chen, Marcus Y. National Institutes of Health National Heart Lung and Blood Institute BethesdaMD United States Catholic University of America Department of Electrical Engineering and Computer Science WashingtonDC United States National Institutes of Health Clinical Center BethesdaMD United States New Jersey Institute of Technology Department of Informatics NewarkNJ United States

ISBN: (纸本)9798350362480

Cardiovascular disease, the leading cause of death in the U.S., affects both the heart and blood vessels. Contrast-enhanced cardiac computed tomography angiography (CTA) is a prominent imaging modality for assessing heart and coronary artery morphology, aiding in the diagnosis of cardiovascular disease. Cine CTA, which captures multiple 3D heart images throughout the cardiac cycle, is particularly useful for evaluating nonischemic cardiomyopathy, a common cause of heart failure unrelated to coronary artery disease. Key biomarkers, such as left ventricular ejection fraction, which measures the amount of blood pumped from the heart's lower chambers per contraction, and myocardial strain, which evaluates the deformation of the heart muscle during contraction and relaxation, are vital for assessing heart function. We developed an automated artificial intelligence (AI) framework to segment various cardiac structures across all image volumes representing different phases of the cardiac cycle. The framework also automatically extracts three short-axis slices to calculate the myocardial strain in the left ventricle. The results are compared with strain measurements obtained from cardiovascular magnetic resonance (CMR) cine imaging. Our study shows both radial and circumferential strains from cine CTA are comparable to those from cine CMR. The proposed AI framework facilitates a comprehensive evaluation of myocardial function throughout the cine CTA, supporting improved diagnostic accuracy. © 2024 IEEE.

关键词： computerized tomography

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Feature Analysis and Selection for BGP Anomaly Detection

Feature Analysis and Selection for BGP Anomaly Detection

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International Conference on Intelligence in Next Generation Networks (ICIN)

作者： Rifqy Hakimi Martin J. Reed School of Computer Science and Electronic Engineering University of Essex Colchester United Kingdom School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

ISBN: (数字)9798331542399

ISBN: (纸本)9798331542405

Automated incidence reporting requires accurate and timely anomaly detection. This paper considers this in the context of the Border Gateway Protocol (BGP). BGP is crucial for Internet routing but is vulnerable to attacks due to a lack of widespread authentication. While rare, BGP disruptions can be highly detrimental to Internet performance and security. Detecting BGP anomalies helps network operators protect their networks and improve Internet reliability. In this work, we investigate and develop anomaly detection for BGP using Machine-Learning. We extract relevant features of BGP control plane messages from RIPE RIS and RouteViews public datasets. After extracting features, we employ various feature selection algorithms to extract the most relevant features and explore balancing the datasets. Finally, we explore detection latency, an important operating parameter for automated anomaly detection. The results show that BGP anomalies can be detected in the order of seven minutes when using real attack data and that the observation point for the BGP data has a significant effect on anomaly detection.

关键词： Technological innovation Soft sensors Machine learning Feature extraction Routing Border Gateway Protocol Security Reliability Anomaly detection Faces

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Chat Application Utilizing Automatic Translation Built on The Microsoft Azure Platform 9th

Chat Application Utilizing Automatic Translation Built on Th...

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9th International Conference on computer Science and Computational Intelligence, ICCSCI 2024

作者： Prabowo, Yulius Denny Putra, Raymond Wangsa Maslim, Martinus BINUS Online Learning Computer Science Department Bina Nusantara University Jakarta11480 Indonesia Institute of Information Management School of Management National Cheng Kung Unversity Tainan Taiwan Informatics Department Faculty of Industrial Technology Universitas Atma Jaya Yogyakarta Daerah Istimewa Yogyakarta Indonesia

Language serves as a means of interpersonal communication. There exist various categories of language, such as 'dialect,' 'slang,' 'jargon,' and 'lingo.' In addition to linguistic proficiency, it is essential to possess fundamental language skills to effectively utilize a language for communication purposes. The four skills include listening, speaking, reading, and writing. With the advancement of technology, we utilize many media to communicate in different languages. The most fundamental form of communication involves speaking and listening, whereas other mediums such as smartphones require the ability to read and write to send and receive messages. Only a select few individuals can proficiently perform four different abilities simultaneously at an advanced level. In addition to that, there is also a linguistic barrier, requiring the use of translation software. If someone engages in conversation with another person who faces a language barrier, they will require two essential tools: translation software and a means of communication. Therefore, this study aims to explore the development of a chat program that can effectively eliminate language barriers. Consequently, this software was effectively constructed utilizing the Microsoft Azure platform and offers three language options as the basis for translation. © 2024 The Authors.

关键词： Program translators

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A Fused Machine Learning Approach for Intrusion Detection System

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computers, Materials & Continua 2023年第2期74卷 2607-2623页

作者： Muhammad Sajid Farooq Sagheer Abbas Atta-ur-Rahman Kiran Sultan Muhammad Adnan Khan Amir Mosavi School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam 31441Saudi Arabia Department of CIT The Applied CollegeKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Software Gachon UniversitySeongnam13120Korea John von Neumann Faculty of Informatics Obuda UniversityBudapest1034Hungary Institute of Information Engineering Automation and MathematicsSlovak University of Technology in BratislavaBratislava81107Slovakia Faculty of Civil Engineering TU-DresdenDresden01062Germany

The rapid growth in data generation and increased use of computer network devices has amplified the infrastructures of *** interconnectivity of networks has brought various complexities in maintaining network availability,consistency,and *** learning based intrusion detection systems have become essential to monitor network traffic for malicious and illicit *** intrusion detection system controls the flow of network traffic with the help of computer *** deep learning algorithms in intrusion detection systems have played a prominent role in identifying and analyzing intrusions in network *** this purpose,when the network traffic encounters known or unknown intrusions in the network,a machine-learning framework is needed to identify and/or verify network *** Intrusion detection scheme empowered with a fused machine learning technique(IDS-FMLT)is proposed to detect intrusion in a heterogeneous network that consists of different source networks and to protect the network from malicious *** proposed IDS-FMLT system model obtained 95.18%validation accuracy and a 4.82%miss rate in intrusion detection.

关键词： Fused machine learning heterogeneous network intrusion detection

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Advancing Online Education: An Interactive Framework for Aligning Teaching Methods with Learning Styles

Advancing Online Education: An Interactive Framework for Ali...

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Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), International Conference on

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

This research develops an innovative method for enhancing existing distance education by adjusting the teaching process to students' learning styles. The study investigates the relationship between teachers' teaching styles and learners' preferences, refining Grasha's teaching style model to better suit students' needs. As a result, an online system was created that enabled teachers to modify their strategies during lessons, thereby improving student participation and performance. Furthermore, a mobile solution was also implemented to address the need for portable and easy-to-use options. To evaluate the adoption of the system, university students were administered questionnaires aimed primarily at determining their main learning styles. Based on the analysis, lecturers were trained to modify their teaching methods accordingly. The findings revealed significant improvements in student satisfaction and academic performance after the alignment of teaching methods with learning preferences. Cronbach's Alpha values confirmed the high reliability of the results, highlighting increased engagement and satisfaction among students. The contribution of this study lies in its practical approach to improving online education through personalized teaching methods. The platform provides educators with a real-time feedback loop, enabling dynamic adjustment of teaching strategies to optimize student engagement. The research demonstrates technical soundness, supported by rigorous data analysis, and has the potential to revolutionize online learning environments globally.

关键词： Feedback loop Data analysis Education Refining Electric variables measurement Real-time systems Time measurement Mobile applications Reliability Artificial intelligence

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