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5th International Conference on Energy Conservation and Efficiency, ICECE 2022

作者： Mussadiq, Usman Kausar, Tasleem Ahmed, Saeed Kim, Su Min Mirpur University of Science and Technology Dept. of Electrical Engineering Azad Kashmir Pakistan Must Dept. of Electrical Engineering Mirpur Azad Kashmir Pakistan Korea Polytechnic University Dept. of Electronics Engineering Siheung Korea Republic of

ISBN: (纸本)9781728186801

The population growth, rising energy demand, economic drain, and carbon emissions result in the massive infiltration of renewable energy resources (RER) at consumption. The active users that produce and consume energy are termed as prosumers. However, the use of RER without energy storage systems (ESS) is not practical due to intermittent and uncertain supply. To this end, this paper investigates the impact of the hybrid energy storage system (HESS) in terms of a lifetime, and ESS cost to share and manage the energy within the prosumer community. For HESS, a parallel combination of ultra-capacitors (UC) and lead-Acid batteries are used at the prosumer end along with the central storage unit (CSU) to maintain the state of charge (SOC) within the safe limits. The power transients are managed by UC which ultimately improves the battery life. Simulation results show there are 36% and 37.5% HESS-based cost reductions for prosumer-1 and prosumer-2, respectively. © 2022 IEEE.

关键词： Renewable energy resources

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Comparative Analysis of RSSI Values at WLAN Bands in Obstructed Wireless Communication Path 18

Comparative Analysis of RSSI Values at WLAN Bands in Obstruc...

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18th IEEE International Conference on Emerging Technologies, ICET 2023

作者： Khan, Muhammad Altaf Hussain Asim, Muhammad Aatif, Muhammad Naseer, Muhammad University of Engineering and Technolgy Dept. of Telecommunication Eng. Peshawar Pakistan Cecos Univ. of Information Technology and Emerging Science Dept. of Electrical Eng. Peshawar Pakistan

ISBN: (纸本)9798350328172

The performance of the direct Line of Sight wireless communication is remarkably influenced by multiple reflections in addition to scattering and diffraction propagation effects. The geometric and dielectric properties of the objects acting as obstacles to wireless signals vary to a large extent. Hence, it is required to model signal propagation accurately. In this work, measurements of WLAN signal strengths are made in a typical university corridor. The first Fresnel zone was blocked completely, using metal sheet of relevant size. The received signal strength values with and without blockage of Fresnel Zone were recorded through multiple reading sets in both the indoor and outdoor scenarios. For recording signal strength values, Homedale software was used. Validation of the proposed scenario is done through Tamograph simulator. This work quantifies the blockage effects in different scenarios and showing considerable reduction in signal strength by the blockage of first Fresnel zone. The power losses are significant are more detrimental in outdoor scenario than indoor. © 2023 IEEE.

关键词： Sheet metal

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Handcrafted and Deep features based Classification of Scoliosis 2

Handcrafted and Deep features based Classification of Scolio...

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2nd International Conference on Digital Futures and Transformative Technologies, ICoDT2 2022

作者： Fatima, Joddat Mohsan, Mashood M. Qaisar, Muhammad Umair Hamza, Muhammad Tahir, Muhammad Zeshan Zaman, Ghazzal Bahria University Dept. of Computer Science Islamabad Pakistan National University of Sciences & Technology Dept. of Computer & Software Engineering Rawalpindi Pakistan

ISBN: (纸本)9781665498197

The Spinal cord acts as the central transmission line connecting the Brain with all other body organs. Vertebrae are 33 uneven bones stacked over one another that holds the whole skeleton structure. Scoliosis is the three-dimensional spinal deformity which commonly occurs during the growing age and erupts before puberty. It is further classified in two Shapes C and S. Our research work has two stages, in first stage we segment out the vertebral column using Mask-RCNN. The segmented column is used for features extraction and in stage two feature based classification is done for normal, C and S shape of scoliosis using AASCE2019 dataset. A comparative study on multiple image classification networks is also conducted and based on results EfficientNet-B4 is selected for formulation of hybrid feature set. The accuracy achieved using Random forest classifier, for handcrafted and deep features was up to 94.32% and 89.66%. Hybrid feature set formulated with combination of deep and handcrafted features attained accuracy up to 94.45%. © 2022 IEEE.

关键词： Decision trees

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Attention-Based AdaptSepCX Network for Effective Student Action Recognition in Online Learning

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Procedia computer Science 2024年 233卷 164-174页

作者： Arnab Dey Anubhav Anand Subhajit Samanta Bijay Kumar Sah Samit Biswas Dept. of Computer Science and Technology Indian Institute of Engineering Science and Technology Shibpur Howrah 711103 India

In the realm of online learning and distance education, the issue of inadequate supervision looms large, posing a significant obstacle. This paper delves into the challenges posed by the lack of supervision in online learning environments and proposes an innovative solution to understand and recognize students’ behaviors. This study's primary objective is to detect and recognize students’ actions in images captured through webcam. This task distinguishes itself from the well-established video-based student action recognition domain, which relies on temporal cues. Recognizing student actions from images intensifies the complexity of the problem. To meet this challenge, a novel deep learning model named AdaptSepCX Attention, specifically designed for student action recognition in online learning environments, is introduced. The proposed method exhibits exceptional performance with 92.73% validation accuracy on the Student Online Action Image dataset (SOAId), a carefully curated collection comprising 2029 student-centric images. The proposed model outperforms well-established models such as DenseNet121, NASNet Mobile, Con-vXNet, DELVS1 and MobileNetV2 in student action recognition. Action recognition for students has broader implications beyond the online classroom. It has the potential to revolutionize educational technology, making online learning more interactive and engaging. Enabling machines to understand and respond to student actions enhances education, personalizes learning, and supports students’ academic success and well-being. This research enhances the understanding of student involvement in online learning and offers an effective solution for recognizing actions from images.

关键词： Students Action Recognition Action Recognition Online Learning Attention Adaptive Seperable Convolution Network

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Blockchain-Enhanced Framework for Secure Third-Party Vendor Risk Management and Vigilant Security Controls

Blockchain-Enhanced Framework for Secure Third-Party Vendor ...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Gupta, Deepti Elluri, Lavanya Jain, Avi Moni, Shafika Showkat Aslan, Omer Texas A&m University - Central Texas Dept. of Computer Information Systems TX United States College of Business University of Tampa FL United States Embry-Riddle Aeronautical University Dept. of Electrical Engineering and Computer Science FL United States Bandirma Onyedi Eylül University Department of Software Engineering Bandirma Turkey

ISBN: (纸本)9798350362480

In an era of heightened digital interconnectedness, businesses increasingly rely on third-party vendors to enhance their operational capabilities. However, this growing dependency introduces significant security risks, making it crucial to develop a robust framework to mitigate potential vulnerabilities. This paper proposes a comprehensive secure framework for managing third-party vendor risk, integrating blockchain technology to ensure transparency, traceability, and immutability in vendor assessments and interactions. By leveraging blockchain, the framework enhances the integrity of vendor security audits, ensuring that vendor assessments remain up-to-date and tamperproof. This proposed framework leverages smart contracts to reduce human error while ensuring real-time monitoring of compliance and security controls. By evaluating critical security controls - such as data encryption, access control mechanisms, multi-factor authentication, and zero-trust architecture - this approach strengthens an organization's defense against emerging cyber threats. Additionally, continuous monitoring enabled by blockchain ensures the immutability and transparency of vendor compliance processes. In this paper, a case study on iHealth's transition to AWS Cloud demonstrates the practical implementation of the framework, showing a significant reduction in vulnerabilities and marked improvement in incident response times. Through the adoption of this blockchain-enabled approach, organizations can mitigate vendor risks, streamline compliance, and enhance their overall security posture. Our findings highlight the importance of employing blockchain to enforce security controls and maintain compliance with healthcare regulations such as HIPAA. In this paper, we present a comprehensive set of security controls and demonstrate how blockchain technology enhances their effectiveness, ensuring greater transparency, accountability, and automation in vendor assessments. By reducing human error, e

关键词： Smart contract

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Models of Virtual Battery Systems and Electric Grid Networks to Support a National Energy Trading Platform and Prosumer Integration 12

Models of Virtual Battery Systems and Electric Grid Networks...

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12th International electrical engineering Congress, iEECON 2024

作者： Bumrungkun, Prachya Sudta, Panaya Patanacharoenwong, Wanchalerm Rajamangala University Of Technology Faculty Of Agriculture And Technology Dept. Of Electrical Technology Surin Thailand School Of Environment Resource And Development Asian Institute Of Technologyn Dept. Of Energy Pathum Thani Thailand Engineering And Services Session Customer Service Division Provincial Electricity Authority Pea Lop Buri Thailand

ISBN: (纸本)9798350383591

This article's purpose aligns with the Thai government's policy to enhance the power quality and stability of the electricity production and utility distribution systems. Such improvements are essential to boost investor confidence and better serve the country's citizens. This undertaking complements the increasing incorporation of renewable energy sources and the integration of prosumers into the electrical grid as part of Distributed Generation (DG). These efforts are in line with the state's objective to achieve 25% renewable energy usage of the total energy consumption by 2024 and are connected to the National Energy Trading Platform (NETP), which is focused on preparing the electrical distribution system to accommodate the whole system. In response to these developments, this article presents a strategic approach for the distribution utility system to develop electrical grid networks and virtual battery systems. These innovations support a centralized energy trading platform and facilitate the integration of prosumers. The approach combines the planning and management of electrical grid networks with the operational strategies of virtual battery storage systems (VBSS). The benefits of this initiative extend beyond immediate improvements;they equip electrical utility with the necessary knowledge and tools to enhance and control its future electrical distribution systems and to stay adaptive amidst disruptive changes in the energy business model and market. © 2024 IEEE.

关键词： Energy utilization

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Unsupervised Anomaly Detection Framework for Coronary Artery Lesions in CTCA 22

Unsupervised Anomaly Detection Framework for Coronary Artery...

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22nd IEEE International Symposium on Biomedical Imaging, ISBI 2025

作者： Kang, Dongwoo Choi, Jaewon Woo, Jonghye Kuo, C.-C. Jay School of Electronic and Electrical Engineering Hongik University Seoul Korea Republic of Massachusetts General Hospital Harvard Medical School Dept. of Radiology BostonMA United States University of Southern California Dept. of Electrical and Computer Engineering Los AngelesCA United States

ISBN: (纸本)9798331520526

Coronary artery disease is a leading cause of mortality world-wide, emphasizing the need for accurate and efficient detection methods. Current deep learning approaches for coronary lesion detection in computed tomography coronary angiog-raphy (CTCA) rely on large labeled datasets for supervised learning, limiting scalability. This study proposes an unsu-pervised framework for coronary lesion detection in CTCA. Using vessel linearization, we generated small linear volume patches from CTCA and trained a deep autoencoder model, MemAE, exclusively on normal patches to detect anomalies based on reconstruction error without lesion location labels. Results on a public dataset demonstrate high accuracy, achieving 97.5% on per-patient average reconstruction error and 85% using the number of patches with high reconstruction error, offering a scalable and accessible solution. © 2025 IEEE.

关键词： Semi-supervised learning

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Diving into Brain Complexity: Exploring Functional and Effective Connectivity Networks 18

Diving into Brain Complexity: Exploring Functional and Effec...

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18th IEEE International Conference on Emerging Technologies, ICET 2023

作者： Siddique, Abu Bakar Khalid, Hassan Bin Ali, Raja Hashim University of Europe for Applied Sciences Dept. of Technology & Software Engineering Berlin Germany Gik Institute of Engg. Sciences & Technology Faculty of Computer Science & Engineering Topi Pakistan

ISBN: (纸本)9798350328172

The human brain's intricate functions are under-pinned by a vast network of synapses that enable chemical impulses between neurons. Neuroscientists employ two key approaches, functional and effective connectivity, to understand the brain's complexity, focusing on its operations, cognition, and behavior. While both methods utilize graph theory for network analysis, functional connectivity, which investigates associated brain activity, has seen more substantial research efforts than effective connectivity, which examines information processing's inter-regional impacts. In this research paper, we aim to present an extensive examination of the emerging discipline that combines graph theory with the analysis of brain characteristics, shedding light on how these characteristics arise from the interactions among different groups of neurons. Our primary focus lies in exploring the diverse cognitive and neurological applications that leverage functional Magnetic Resonance Imaging (fMRI) as a tool. Additionally, we offer a comprehensive overview of the methods employed to construct brain networks based on functional and efficient connections. Throughout the discussion, we emphasize the advantages and limitations associated with these approaches. © 2023 IEEE.

关键词： Graph theory

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Enhancing VANET Efficiency with ACRR Technique for Improved Traffic Management and Network Scalability

Enhancing VANET Efficiency with ACRR Technique for Improved ...

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Science, technology, engineering and Management (ICSTEM), International Conference on

作者： K Karthick Praveen Talari Nishadevi V R Krishna Prakash R. Asokan Velusamy A Dept. of Computer Science and Engineering Kongunadu College of Engineering and Technology Trichy Tamilnadu Dept. of Computer Science and Engineering Vignan Bharathi institute of technology Hyderabad Telangana Dept. of Computer Science and Engineering Mahendra College of Engineering Salem Tamilnadu Dept. of Information Technology Sona College of Technology Salem India Dept. of Electronics and Communication Engineering Kongunadu College of Engineering and Technology Trichy Tamilnadu

ISBN: (数字)9798350376913

ISBN: (纸本)9798350388473

The role of Vehicular Ad Hoc Networks (VANETs) is crucial in enabling Intelligent Transportation System (ITS) technologies such as safe financial transactions, media applications, and effective traffic control. As traffic increases, the topology of vehicular networks is in constant flux, and the sparse distribution of vehicles, particularly on highways, presents challenges for network scalability. This situation makes it difficult for cars to keep consistent routes inside the network, which affects the stability of the network. To address these challenges, the developed Adaptive-ant Colony based Randomized Recommendation (ACRR) technique emerges as a unique solution for enhancing VANETs by reducing travel time. In instances of high traffic density on busy roads, the ACRR algorithm is effectively utilized to group vehicles. Leveraging data collected from these densely populated road segments, the system identifies congestion-prone areas and formulates optimal vehicle routes based on customized vehicle groupings. The framework's performance evaluation encompasses various parameters, including packet loss, message transmission rate, energy consumption, and average cluster growth. The proposed VANET framework, empowered by the ACRR algorithm, achieves an impressive message transmission rate of approximately 80%. In comparison, alternative methods like Re-RouTE exhibit a limited transmission rate of 70%, while others such as Net Run Rate (NRR), DIVERT 30, and DIVERT-60 demonstrate rates below 20%. Furthermore, the framework's parcel loss is significantly reduced to only 33% of that observed in the standard VANET framework. As a result, the ACRR algorithm integrated into the VANET framework demonstrates notable efficiency when compared to other approaches. It is crucial to recognize that, even with a refined technique, managing traffic congestion remains challenging if drivers disregard the recommended routing suggestions. Overall, this research offers insights into the p

关键词： Performance evaluation Roads Scalability Vehicular ad hoc networks Clustering algorithms Packet loss Routing

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P-68: Oxide Semiconductor Thin-Film Transistor-Based Micro-LED Pixel Circuit with External Current Setting System

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SID Symposium Digest of Technical Papers 2024年第1期55卷 1647-1649页

作者： Hye-Won Woo Hwarim Im Kook Chul Moon Yong-Sang Kim Dept. of Display Convergence Engineering Sungkyunkwan University Suwon Korea 16419 Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea 16419

We propose an oxide semiconductor thin-film transistor-based micro light-emitting diode pixel circuit with external current setting system. The proposed circuit achieved stable operation using pulse width modulation w... 详细信息

关键词： Micro light-emitting diode (µ LED) pixel circuit external current setting system

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