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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Wijayaraja, Jaliya L. Abhayasinghe, Nimsiri Wellalage, Sasini Sliit Faculty of Computing Department of Computer Systems Engineering Malabe Sri Lanka Sliit Faculty of Engineering Department of Electrical and Electronic Engineering Malabe Sri Lanka

ISBN: (纸本)9798350331820

Enhancing the performance and extending the life-cycle of older vehicles through retrofitting with improved systems presents an alluring opportunity. However, achieving accurate sensing of crucial parameters, such as engine revolutions per minute (RPM), poses challenges due to the need for mechanical manipulation and some designs, which may result in diminished accuracy in adverse settings. This study proposes using the primary ignition pulse signal to accurately determine engine speed without mechanical manipulation. We investigate the effectiveness of signal processing methods, including the RC filter, 2nd and 6th order Butterworth filter, to improve the accuracy of the readings. Our proposed method successfully collects data from conventional internal combustion engines, with simulated signal processing methods producing accurate detection of RPM and reduced fluctuations. The proposed method eliminated the noise, leading to accurate RPM measurements, while the maximum standard deviation observed for the RC filter implementation was 38.74. By accurately sensing key parameters, older vehicles can be retrofitted with improved systems, leading to enhanced performance and an extended lifecycle. The introduced methods can be practically implemented using custom electronics or embedded systems and can contribute to future research on automotive retrofitting. © 2023 IEEE.

关键词： Life cycle

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Reliability-aware swarm based multi-objective optimization for controller placement in distributed SDN architecture

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Digital Communications and Networks 2024年第5期10卷 1245-1257页

作者： Abeer A.Z.Ibrahim Fazirulhisyam Hashim Aduwati Sali Nor K.Noordin Keivan Navaie Saber M.E.Fadul Department of Computer and Communication Systems Engineering Faculty of EngineeringUniversiti Putra MalaysiaSerdang43400Malaysia Wireless and Photonics Networks Research Centre(WiPNET) Faculty of EngineeringUniversiti Putra MalaysiaSerdang43400Malaysia Department of Communication and Computer Engineering College of Engineering and Medical SciencesKhartoum11111Sudan School of Computing and Communications Lancaster UniversityLancasterLA14YWUnited Kingdom Department of Electrical and Electronics Engineering Faculty of EngineeringUniversiti Putra MalaysiaSerdang43400Malaysia

The deployment of distributed multi-controllers for Software-Defined Networking(SDN)architecture is an emerging solution to improve network scalability and ***,the network control failure affects the dynamic resource allocation in distributed networks resulting in network disruption and low ***,we consider the control plane fault tolerance for cost-effective and accurate controller location models during control plane *** fault-tolerance strategy has been applied to distributed SDN control architecture,which allows each switch to migrate to next controller to enhance network *** this paper,the Reliable and Dynamic Mapping-based Controller Placement(RDMCP)problem in distributed architecture is framed as an optimization problem to improve the system reliability,quality,and *** considering the bound constraints,a heuristic state-of-the-art Controller Placement Problem(CPP)algorithm is used to address the optimal assignment and reassignment of switches to nearby controllers other than their regular *** algorithm identifies the optimal controller location,minimum number of controllers,and the expected assignment costs after failure at the lowest effective cost.A metaheuristic Particle Swarm Optimization(PSO)algorithm was combined with RDMCP to form a hybrid approach that improves objective function optimization in terms of reliability and *** effectiveness of our hybrid RDMCP-PSO was then evaluated using extensive experiments and compared with other baseline *** findings demonstrate that the proposed hybrid technique significantly increases the network performance regarding the controller number and load balancing of the standalone heuristic CPP algorithm.

关键词： Software defined networking Dynamic mapping Particle swarm optimization Reliability Multi-objective optimization Evolutionary

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A Survey on Usage of Multimedia Databases for Emotion Elicitation: A Quantitative Report on How Content Diversity Can Improve Performance 46

A Survey on Usage of Multimedia Databases for Emotion Elicit...

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46th ICT and Electronics Convention, MIPRO 2023

作者： Horvat, M. Jercic, P. University of Zagreb Faculty of Electrical Engineering and Computing Department of Applied Computing Zagreb Croatia Graz University of Technology Institute of Interactive Systems and Data Science Graz Austria

ISBN: (纸本)9789532331042

Affective picture databases provide a standardized set of images to elicit controlled and consistent emotional responses in research participants. They are a valuable tool for studying various emotion-related phenomena across several research domains. These domains include emotion perception, emotion regulation, and the neural basis of emotion. However, affective picture databases have diverse schemas, structures, and content, making them difficult to use. Searching and retrieving optimal pictures relevant to affective stimulation may be challenging and time-consuming. In this context, we surveyed domain experts about their practices and experiences working with affective multimedia databases such as IAPS, NAPS, OASIS, GAPED, and others. The survey identified a need for novel data observatory software. This finding motivates the authors' intention to develop and validate such software platform that relies on AI. Such a platform would describe better, retrieve, and integrate various semi-structured affective multimedia datasets. The results prominently indicate the overwhelming dissatisfaction regarding stimuli content diversity and cultural bias, specifically regarding emotional and semantic context. The main driver of satisfaction from users of existing automated retrieval software is the quality of semantic descriptors available. This points to the direction AI should take in novel data observatory software. This survey follows up on a similar survey conducted ten years ago and explores the differences in researchers' opinions and experiences during that time. The complete aggregated results are publicly available at https://***/mhorvat/stimdbsurvey. © 2023 MIPRO Croatian Society.

关键词： Database systems

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Profitable Investment in PV and BES Integrated with EV Charging Stations in Croatia - Myth or Reality? 7

Profitable Investment in PV and BES Integrated with EV Charg...

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7th International Conference on Smart and Sustainable Technologies, SpliTech 2022

作者： Grzanic, Mirna Hrga, Alen Capuder, Tomislav Faculty of Electrical Engineering and Computing Department of Energy and Power Systems Zagreb Croatia

ISBN: (纸本)9789532901160

The increasing number of electric vehicles (EVs) poses a challenge to the power system operation and manage-ment. To deal with the growing consumption together with the uncertainty related to the time of arrival at the charging station and EV state of energy, the paper investigates the profitability of investment in different low-carbon (LC) technologies in the EV charging stations based on real-EV-data optimization. The model considers several real-life charging points in Croatia at different location (high-way, parking lot in the capital city and parking lot at the sea-side). Analyses show that the investment in PV and BES is profitable under current retail market options resulting in 3% to 70% cost reduction wit different LC technology options, while recently introduced EV charging reimbursement shortens the period of investment in LC technology for 8 years. © 2022 University of Split, FESB.

关键词： Solar panels

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Deep Learning in Medical Image Registration: Magic or Mirage? 38

Deep Learning in Medical Image Registration: Magic or Mirage...

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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Jena, Rohit Sethi, Deeksha Chaudhari, Pratik Gee, James C. Computer and Information Science United States Electrical and Systems Engineering United States Radiology United States Penn Image Computing and Science Laboratory United States

Classical optimization and learning-based methods are the two reigning paradigms in deformable image registration. While optimization-based methods boast generalizability across modalities and robust performance, learning-based methods promise peak performance, incorporating weak supervision and amortized optimization. However, the exact conditions for either paradigm to perform well over the other are shrouded and not explicitly outlined in the existing literature. In this paper, we make an explicit correspondence between the mutual information of the distribution of per-pixel intensity and labels, and the performance of classical registration methods. This strong correlation hints to the fact that architectural designs in learning-based methods is unlikely to affect this correlation, and therefore, the performance of learning-based methods. This hypothesis is thoroughly validated with state-of-the-art classical and learning-based methods. However, learning-based methods with weak supervision can perform high-fidelity intensity and label registration, which is not possible with classical methods. Next, we show that this high-fidelity feature learning does not translate to invariance to domain shift, and learning-based methods are sensitive to such changes in the data distribution. We reassess and recalibrate performance expectations from classical and DLIR methods under access to label supervision, training time, and its generalization capabilities under minor domain shifts. © 2024 Neural information processing systems foundation. All rights reserved.

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DaC-GANSAEBF:Divide and Conquer-Generative Adversarial Network-Squeeze and Excitation-Based Framework for Spam Email Identification

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Computer Modeling in engineering & Sciences 2025年第3期142卷 3181-3212页

作者： Tawfeeq Shawly Ahmed A.Alsheikhy Yahia Said Shaaban M.Shaaban Husam Lahza Aws I.Abu Eid Abdulrahman Alzahrani Department of Electrical Engineering Faculty of Engineering at RabighKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical Engineering College of EngineeringNorthern Border UniversityArar91431Saudi Arabia Center for Scientific Research and Entrepreneurship Northern Border UniversityArar73213Saudi Arabia Department of Information Technology College of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information and Communication Technology College of Computing StudiesArab Open UniversityKuwait BranchKuwait City13033Al-SafatState of Kuwait Department of Information Systems and Technology College of Computer Science and EngineeringUniversity of JeddahJeddah23218Saudi Arabia

Email communication plays a crucial role in both personal and professional contexts;however,it is frequently compromised by the ongoing challenge of spam,which detracts from productivity and introduces considerable security *** spam detection techniques often struggle to keep pace with the evolving tactics employed by spammers,resulting in user dissatisfaction and potential data *** address this issue,we introduce the Divide and Conquer-Generative Adversarial Network Squeeze and Excitation-Based Framework(DaC-GANSAEBF),an innovative deep-learning model designed to identify spam *** framework incorporates cutting-edge technologies,such as Generative Adversarial Networks(GAN),Squeeze and Excitation(SAE)modules,and a newly formulated Light Dual Attention(LDA)mechanism,which effectively utilizes both global and local attention to discern intricate patterns within textual *** approach significantly improves efficiency and accuracy by segmenting scanned email content into smaller,independently evaluated *** model underwent training and validation using four publicly available benchmark datasets,achieving an impressive average accuracy of 98.87%,outperforming leading methods in the *** findings underscore the resilience and scalability of DaC-GANSAEBF,positioning it as a viable solution for contemporary spam detection *** framework can be easily integrated into existing technologies to enhance user security and reduce the risks associated with spam.

关键词： Email spam fraud light dual attention squeeze and excitation divide and conquer-generative adversarial network-squeeze and excitation-based framework security

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A self-adaptive multi-objective harmony search based fuzzy clustering technique for image segmentation

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Journal of Ambient Intelligence and Humanized computing 2023年第11期14卷 14943-14958页

作者： Wan, Changjing Yuan, Xiaofang Dai, Xiangshan Zhang, Ting He, Qian College of Electrical and Information Engineering Hunan University Changsha410082 China Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology Guilin541004 China

Image segmentation can be considered as a problem of clustering since the pixels in the digital image are clustered in term of some evaluation criteria. Generally, clustering technique in image segmentation employs a single objective which can not reach ideal result for various kinds of images. Moreover, fuzzy c-means (FCM) algorithms which determine the fuzzy partition matrix of the data set by solving the clustering problem with conditional constraints and obtain the clustering output, have been verified effective and efficient for image segmentation. In fact, these FCM algorithms still have some shortcomings including: being sensitive to outliers and noise, key parameters need to be adjusted with experience. In view of this, a self-adaptive multi-objective harmony search based fuzzy clustering (SAMOHSFC) technique for image segmentation is proposed in this paper. SAMOHSFC technique encodes several cluster centers in one harmony vector and optimizes multiple objectives. In addition, we consider the spatial information of the image as an attribute of the input data set besides the attribute of gray information of input image in the SAMOHSFC. Superiority of the proposed algorithm over three classic segmentation algorithms has been verified for a synthetic and two real images from quantitative and visual aspect. In the experiment, the effect of different kinds of spatial information on the segmentation performance of the SAMOHSFC is analyzed. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Multiobjective optimization

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Distribution Transformer Losses Analysis due to Photovoltaic-Induced Current Harmonics 1

Distribution Transformer Losses Analysis due to Photovoltaic...

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1st IEEE International Conference on Advanced Power engineering and Energy, APEE 2024

作者： Wazir, Muhammad Haziq Mohd Said, Dalila Mat Sapari, Norazliani Md Yunus, Mohamed Shahriman Mohamed Yassin, Zaris Izzati Mohd Abidin, Muhammad Zahid Zainul Universiti Teknologi Malaysia Centre of Electrical Energy Systems Faculty of Electrical Engineering Johor Bahru Malaysia Cawangan Kejuruteraan Elektrik Jabatan Kerja Raya Malaysia Kuala Lumpur Malaysia School of Engineering and Computing Mila University Electrical and Electronic Department Nilai Malaysia

ISBN: (纸本)9798350360936

Harmonic distortion is one of the monumental power quality disturbances in an electrical distribution system, which originates from power electronic assets such as power electronic devices from consumers and renewable energy integration. Harmonics adversely affect distribution transformers by elevating losses in their components, leading to the reduction of their lifespan. The impact on the transformer losses is a crucial attention especially considering the integration of photovoltaic systems (PV) into distribution network. Therefore, this paper examined the relationship between current harmonics from various photovoltaic penetration towards load losses generated in an oil-immersed distribution transformer in three-phase distribution network with the presence of unbalanced harmonic loads. The simulation was carried out using MATLAB Simulink 2021a software, during which the current distortion was compared evaluated and compared in accordance with a specified standard. As a result, the rise in PV penetration has been demonstrated to lead to increased losses in distribution transformer. © 2024 IEEE.

关键词： Distribution transformers

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ETAG: An Energy-Neutral Ear Tag for Real-Time Body Temperature Monitoring of Dairy Cattle 23

ETAG: An Energy-Neutral Ear Tag for Real-Time Body Temperatu...

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29th Annual International Conference on Mobile computing and Networking, MobiCom 2023

作者： Vu, Hien Chung, Hanwook Choi, Christopher Kim, Younghyun Department of Electrical and Computer Engineering College of Engineering Wisconsin Embedded Systems and Computing Laboratory University of Wisconsin-Madison MadisonWI60032179 United States

ISBN: (纸本)9781450399906

Heat stress, caused by a warming climate and the increasingly high milk-producing dairy cattle, is one of the major threats to the well-being of dairy cattle as well as the economic, environmental, and social sustainability of dairy farming around the world. Timely identification of cows under heat stress is crucial to improving animal welfare, preventing milk production losses, and preserving water and energy for *** paper presents a smart ear tag, named eTag, and an associated system that can read a passive microchip temperature sensor subcutaneously injected into the animal with minimal discomfort. It features a lightweight design using a single coil shared for microchip scanning and wireless charging. eTag is autonomously recharged by a wireless charger over the head during daily milking sessions, enabling perpetual operation without battery replacement after deployment. The real-world performance of the proposed system was examined intensively in a three-week deployment on seven lactating Holstein cows. We demonstrate that eTag can reliably collect accurate body temperature in real time while maintaining a positive energy flow. The deployment of eTag will enable the timely detection of heat stress and facilitate precision control of barn cooling systems. © 2023 ACM.

关键词： Energy harvesting

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Identification of Equivalent Circuit Model Parameters for a Li-ion Battery Cell 11

Identification of Equivalent Circuit Model Parameters for a ...

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11th IEEE International Conference on systems and Control, ICSC 2023

作者： Rukavina, Filip Leko, Dorijan Matijašić, Matija Bralić, Ivan Ugalde, Juan M. Vašak, Mario University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Renewable Energy Systems Zagreb Croatia Rimac Technology D.o.o. Battery Systems Engineering Sveta Nedelja Croatia

ISBN: (纸本)9798350304886

Batteries raise issues in electric vehicles because of their limited range and lifespan. They can however be extended by implementing smart, accurate and computationally inexpensive control algorithms. Herein, a lithium-ion battery cell is modelled with an equivalent circuit model which is complex enough to track the output voltage of the cell while remaining simple enough to be used in a control algorithm. This work presents the identification procedure of equivalent circuit model parameters for a lithium-ion battery cell by applying high currents to the cell. Consequently, high accuracy was achieved for the whole range of possible currents. The parameters were identified on a dataset with high currents, while the model was evaluated on a different dataset acquired from a real electric vehicle usage data. Metrics from both the identification and the validation datasets are similar meaning that the model generalises well. © 2023 IEEE.

关键词： Equivalent circuits

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