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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Kadhim, Aqeel Kamil Najim, Ali Hamza Ali Alheeti, Khattab M. Mohd Satar, Nurhizam Safie Abdallah Hashim, Aisa Hassan Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq Department of Computer Technical Engineering Baghdad Iraq Department of Computer Technical Engineering Al-Diwaniyah Iraq College of Computer and Information Technology Computer Networking Systems Department University of Anbar Anbar Iraq Center for Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

In VANETs, the important and effective applications of vehicle localization include safety and communication applications. Thus, it is difficult to get very accurate localization in the dynamic and often very fluctuating environment of VANET. This research responds to this challenge with a keen thrust on improving vehicle localization using the Mobility Data Verification process. The primary goal of this work is to achieve high accuracy of vehicle positioning within VANET by checking the coherence of mobility data of moving vehicles. Hence, we present a concept that builds upon Mobility Data Verification to provide real-time location details from vehicles. Both GPS and onboard sensors feed this method, which uses a multi-level verification to flag out or eliminate the errors of deliberately spoofed data points. We use simulations to evaluate and validate the effectiveness of the proposed verification approach. As the proposed system, our previously developed and fine-tuned weighted localization (OWL) strategy does so. The performance evaluation results suggest that our proposed solution is feasible to distinguish automobiles that are not trustworthy and improve the performance of the localization algorithm. © 2024 IEEE.

关键词： Vane pumps

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Efficient Resubstitution-Based Approximate Logic Synthesis

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IEEE Transactions on computer-Aided Design of Integrated Circuits and systems 2024年第6期44卷 2040-2053页

作者： Meng, Chang Mishchenko, Alan Qian, Weikang Micheli, Giovanni De École Polytechnique Fédérale De Lausanne Integrated Systems Laboratory Switzerland University Of California Department Of Electrical Engineering And Computer Sciences Berkeley United States Shanghai Jiao Tong University University Of Michigan-Shanghai Jiao Tong University Joint Institute MoE Key Laboratory Of Artificial Intelligence China

Approximate computing is an emerging paradigm for designing error-resilient applications. It reduces circuit area, power, and delay at the cost of allowingintroducing errors. This paper introducesproposes a powerful technique, termed Approximate Resubstitution (AppResub), to approximately simplify the circuit. AppResub re-expressesreplaces a node's function with a simpler approximate function onusing existing nodes in the circuit, by replacing it with a simpler approximate function to reduce the hardware cost. Leveraging AppResub, an efficient flow for approximate logic synthesis (ALS) is developed by iteratively applying a set of promising AppResubs for circuit simplification. To evaluate errors caused by a set of AppResubs, a novel error model capable of efficiently computing an error upper bound is used to smartly apply AppResubs in the ALS flow. The experimental results demonstrate that, compared to a state-of-the-art method, the proposed flow further reduces 20.9% area and 21.7% delay under the mean error distance constraint, making itwhile being 400× faster. The code of our flow is open-source. © 1982-2012 IEEE.

关键词： Delay circuits

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Design and Modeling of a Two-stage PV Inverter for Single Phase and Three Phase Applications

Design and Modeling of a Two-stage PV Inverter for Single Ph...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Shen, Yidi Ghaderloo, Reza Asrar Singhabahu, Chanaka Resalayyan, Rakesh Khaligh, Alireza Maryland Power Electronics Laboratory Department of Electrical and Computer Engineering The Institute for Systems Research University of Maryland College ParkMD20742 United States

ISBN: (纸本)9798350316445

This paper presents the modeling and design of a 1kW two-stage photovoltaic (PV) inverter compatible with both single phase and three phase grid. The topology consists of a cascade of dual-active-bridge (DAB) based dc-dc stage and a two-level voltage source inverter (VSI) stage. Two-level VSI based dc-ac stage is designed and the modulation schemes are compared considering operation for both single phase and three phase output connection. A 3 leg interleaved hybrid pulse width modulation (3 leg-IHPWM) is proposed for single phase operation to reduce power loss and current total harmonic distortion (THD) with full utilization of the third switching leg. Sizing of dc link capacitance is analyzed for both single phase power decoupling and three phase load unbalance. Circuit design and component selection are conducted including dc link voltage selection, output filter sizing, DAB dc-dc stage transformer sizing and modulation optimization for zero-voltage-switching (ZVS) ability and control flexibility. The proposed design is verified through hardware prototype and experimental testing. © 2023 IEEE.

关键词： Single Phase Three Phase Two-stage Inverter Voltage Source Inverter

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Detection and Mitigation of Subtle Feature-map Attacks in Pseudo Parallel Collaborative CNN Models for Distributed Edge Intelligence 100

Detection and Mitigation of Subtle Feature-map Attacks in Ps...

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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Patel, Parth Hasan, Syed Rafay Rahman, Mohammad Ashiqur Homsi, Soamar Tennessee Tech University Department of Electrical and Computer Engineering United States Florida International University Department of Computer Science United States AirForce Research Laboratory Information Warfare Division United States

ISBN: (纸本)9798331517786

Although Collaborative Deep Neural Network (CDNN) promises to be an alternative mechanism to mitigate the effects of the untrusted cloud, this approach is susceptible to other kinds of adversarial attacks, which arise from one or more untrusted devices in CDNN acting maliciously. However, since each untrusted node in the CDNN contains only partial information of the complete DNN model, it is worth investigating whether the attacker can still muster a viable threat to CDNN or not. This led to the investigation of attack scenarios and their effects on convolutional neural networks (CNN) used for image classification in the CDNN environment. In this research, we are investigating the shortcomings of existing attacks on CDNN, that lead to non-subtle attack to the defender who is on look out against such attacks. Our research showed that sparse nature of feature maps (FMs) due to the ReLU function lead to many existing attacks more obvious to the attacker. Next, we investigated how one can detect the existing attacks if the defender has some previous knowledge of the complete CNN's FMs. Our results show minimal detection overhead of about 2%, with an accuracy of 95% and F1 score of above 0.97. © 2024 IEEE.

关键词： Convolutional neural networks

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Bi-level Optimal Planning of Voltage Regulator in Distribution systems Considering Maximization of Incentive-based Photovoltaic Energy Integration

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CSEE Journal of Power and Energy systems 2023年第6期9卷 2008-2017页

作者： Xu Xu Youwei Jia Chun Sing Lai Minghao Wang Zhao Xu Department of Electrical and Electronic Engineering Southern University of Science and TechnologyShenzhenChina Department of Electrical Engineering The Hong Kong Polytechnic UniversityHung HomHong Kong SARChina Department of Electrical and Electronic Engineering University Key Laboratory of Advanced Wireless Communications of Guangdong ProvinceSouthern University of Science and TechnologyShenzhen 515100China Department of Electronic and Computer Engineering Brunel Institute of Power SystemsBrunel University LondonLondonUB83PH United Kingdom Department of Electrical Engineering Shenzhen Research InstituteThe Hong Kong Polytechnic UniversityHung HomHong Kong SARChina

This paper focuses on optimal voltage regulator(VR)planning to maximize the photovoltaic(PV)energy integration in distribution *** describe the amount of dynamic PV energy that can be integrated into the power system,the concept of PV accommodation capability(PVAC)is introduced and modeled with *** proposed planning model is formulated as a Benders decomposition based bi-level stochastic optimization *** the upper-level problem,VR planning decisions and PVAC are determined via mixed integer linear programming(MILP)before considering *** in the lower-level problem,the feasibility of first-level results is checked by critical network constraints(*** magnitude constraints and line capacity constraints)under uncertainties considered by time-varying loads and PV *** this paper,these uncertainties are represented in the form of operational scenarios,which are generated by the Gaussian copula theory and reduced by a well-studied backward-reduction *** modified IEEE 33-node distribution grid is utilized to verify the effectiveness of the proposed *** results demonstrate that a PV energy integration can be significantly enhanced after optimal voltage regulator planning.

关键词： Bi-level stochastic optimization problem critical network constraints photovoltaic energy integration uncertainties voltage regulator planning

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Reduced Sensor Control Approach for Active Power Decoupling Circuit in PV Microinverter Application

Reduced Sensor Control Approach for Active Power Decoupling ...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Shen, Yidi Zakzewski, Daniel Hasnain, Arafat Resalayyan, Rakesh Khaligh, Alireza University of Maryland Maryland Power Electronics Laboratory Department of Electrical and Computer Engineering The Institute for Systems Research College ParkMD20742 United States

ISBN: (纸本)9798350316445

Active power decoupling (APD) circuit is of great importance in single-phase photovoltaic (PV) inverter systems for eliminating the fluctuating power drawn from the PV panel. The control of APD circuit is the key to the power decoupling performance and maximum power point tracking (MPPT) efficiency. This paper proposes a control approach for parallel boost type APD circuit with a single sensor, reducing the count of sensors compared to the conventional APD control approach. Operation of the APD circuit with control approach utilizing only the readings from the decoupling capacitor voltage sensor is analyzed in this work. Specifically, controller design for the APD circuit with reduced sensor applicable to a 40 V, 400 W microinverter is presented and experimentally verified with a GaN-based prototype. © 2023 IEEE.

关键词： Active Power Decoupling Microinverter PV Reduced Sensor

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A New Approach for Quantum Phase Estimation Based Algorithms for Machine Learning 8th

A New Approach for Quantum Phase Estimation Based Algorithm...

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8th International Conference on Smart City Applications, SCA 2023

作者： Ouedrhiri, Oumayma Banouar, Oumayma El Hadaj, Salah Raghay, Said Department of Computer Science and Mathematics University of Quebec at Trois-Riviéres Trois-Riviéres Canada Faculty of Sciences and Techniques Laboratory of Computer Science Engineering and Systems Marrakesh Morocco

ISBN: (纸本)9783031543753

One of the greatest developments in computer science is undoubtedly quantum computing. It has demonstrated to give various benefits over the classical algorithms, particularly in the significant reduction of processing time, due to the parallelism and entanglement properties. One of the most crucial quantum computing algorithms is quantum phase estimation (QPE). It is called the eigenvalue finding module for unitary operators. It has helped to solve the order finding and the factoring problem, and to calculate the eigenvalues of unitary matrices and quantum sampling methods. In this paper, we study recent improved versions for the QPE procedure, their advantages and experimentation. We also propose a new approach for QPE based algorithms for machine learning (ML). These algorithms are the Harrow-Hassidim-Lloyd (HHL) algorithm for solving linear systems, the quantum singular value thresholding (QSVT) algorithm for matrix completion in recommender systems, and the quantum principal components analysis (QPCA) for data visualization. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Machine learning

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Adaptive Droop Control in VSC-Based MT-MVDC Distribution systems Considering ESS Participation

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IEEE Transactions on Energy Conversion 2024年第2期40卷 761-772页

作者： Sun, Pingyang Pinthurat, Watcharakorn Li, Gen Khalid, Muhammad Town, Graham Konstantinou, Georgios UNSW Sydney School of Electrical Engineering and Telecommunications NSW2052 Australia Rajamangala University of Technology Tawan-Ok Department of Electrical Engineering Chanthaburi Thailand Energy Technology and Computer Science Section Department of Engineering Technology Ballerup2750 Denmark King Fahd University of Petroleum and Minerals Electrical Engineering Department Interdisciplinary Research Center for Sustainable Energy Systems Dhahran31261 Saudi Arabia Macquarie University School of Engineering NSW2019 Australia

This paper proposes a novel adaptive droop (ADC) control for voltage source converter (VSC)-based multiterminal medium-voltage direct current (MT-MVDC) distribution systems with heterogeneous energy storage system (ESS) participation. The proposed ADC scheme can achieve MVDC bus voltage management and power sharing between VSCs with overloading operation, solving the issue that all VSCs on the rectifier/inverter side reach their power limits concurrently after a large system disturbance. This is accomplished by factoring in the real-time power/voltage values at VSC stations along with an extended power component. This component is contingent on the actual operational state of the ESSs and inversely correlated with the power delivered/absorbed by the ESSs. Moreover, the controllers of the battery and ultracapacitor systems incorporate two additional control loops, a novel VSC excess power reduction (VEPR) loop as well as inner expanded excess power reduction (EEPR) loop, to obtain the power reference values. The two loops ensure all VSCs operate within individual power limits after the engagement of the ESS. The effectiveness of proposed ADC strategy is confirmed through real-time simulations in a hybrid AC/MT-MVDC system. © 1986-2012 IEEE.

关键词： Charge storage

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Bi-Directional MS Lesion Filling and Synthesis Using Denoising Diffusion Implicit Model-based Lesion Repainting

Bi-Directional MS Lesion Filling and Synthesis Using Denoisi...

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Medical Imaging 2025: Image Processing

作者： Zhang, Jinwei Zuo, Lianrui Liu, Yihao Remedios, Samuel Landman, Bennett A. Prince, Jerry L. Carass, Aaron Image Analysis and Communications Laboratory Department of Electrical and Computer Engineering Johns Hopkins University BaltimoreMD21218 United States Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN37235 United States Department of Computer Science Johns Hopkins University BaltimoreMD21218 United States

ISBN: (纸本)9781510685901

Automatic magnetic resonance (MR) image processing pipelines are widely used to study people with multiple sclerosis (PwMS), encompassing tasks such as lesion segmentation and brain parcellation. However, the presence of lesion often complicates these analyses, particularly in brain parcellation. Lesion filling is commonly used to mitigate this issue, but existing lesion filling algorithms often fall short in accurately reconstructing realistic lesion-free images, which are vital for consistent downstream analysis. Additionally, the performance of lesion segmentation algorithms is often limited by insufficient data with lesion delineations as the training labels. In this paper, we propose a novel approach leveraging Denoising Diffusion Implicit Models (DDIMs) for both MS lesion filling and synthesis based on image inpainting. Our modified DDIM architecture, once trained, enables both MS lesion filing and synthesis of lesioned tissues. Specifically, it can generate lesion-free T1-weighted or FLAIR images from those containing lesions;Or it can add lesions to T1-weighted or FLAIR images of healthy subjects. The former is essential for downstream analyses that require lesion-free images, while the latter is valuable for augmenting training datasets for lesion segmentation tasks. We validate our approach through initial experiments in this paper and demonstrate promising results in both lesion filling and synthesis, paving the way for future work. © 2025 SPIE.

关键词： Image segmentation

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Historical Arabic Images Classification and Retrieval Using Siamese Deep Learning Model

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computers, Materials & Continua 2022年第7期72卷 2109-2125页

作者： Manal M.Khayyat Lamiaa A.Elrefaei Mashael M.Khayyat Computer Science Department Umm Al-Qura UniversityMakkahSaudi Arabia Computer Science Department King Abdulaziz UniversityJeddahSaudi Arabia Electrical Engineering Department Faculty of Engineering at ShoubraBenha UniversityCairoEgypt Department of Information Systems and Technology College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia

Classifying the visual features in images to retrieve a specific image is a significant problem within the computer vision field especially when dealing with historical faded colored ***,there were lots of efforts trying to automate the classification operation and retrieve similar images *** reach this goal,we developed a VGG19 deep convolutional neural network to extract the visual features from the images ***,the distances among the extracted features vectors are measured and a similarity score is generated using a Siamese deep neural *** Siamese model built and trained at first from scratch but,it didn’t generated high evaluation ***,we re-built it from VGG19 pre-trained deep learning model to generate higher evaluation ***,three different distance metrics combined with the Sigmoid activation function are experimented looking for the most accurate method formeasuring the similarities among the retrieved *** that the highest evaluation parameters generated using the Cosine distance ***,the Graphics Processing Unit(GPU)utilized to run the code instead of running it on the Central Processing Unit(CPU).This step optimized the execution further since it expedited both the training and the retrieval time *** extensive experimentation,we reached satisfactory solution recording 0.98 and 0.99 F-score for the classification and for the retrieval,respectively.

关键词： Visual features vectors deep learning models distance methods similar image retrieval

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