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A Recurrent Neural Network for Multimodal Anomaly Detection by Using Spatio-Temporal Audio-Visual Data

computers, Materials & Continua 2024年第11期81卷 2493-2515页

作者： Sameema Tariq Ata-Ur-Rehman Maria Abubakar Waseem Iqbal Hatoon S.Alsagri Yousef A.Alduraywish Haya Abdullah AAlhakbani Department of Electrical Engineering University of Engineering and TechnologyLahore54890Pakistan Department of Electrical Engineering National University of Science and TechnologyNational University of Sciences and TechnologyIslamabad24090Pakistan Department of Business and Computing Ravensbourne University LondonRavensbourne UniversityLondonSE100EWEngland Electrical and Computer Engineering Department College of EngineeringSultan Qaboos UniversityMuscat123Oman College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11673Saudi Arabia

In video surveillance,anomaly detection requires training machine learning models on spatio-temporal video ***,sometimes the video-only data is not sufficient to accurately detect all the abnormal ***,we propose a novel audio-visual spatiotemporal autoencoder specifically designed to detect anomalies for video surveillance by utilizing audio data along with video *** paper presents a competitive approach to a multi-modal recurrent neural network for anomaly detection that combines separate spatial and temporal autoencoders to leverage both spatial and temporal features in audio-visual *** proposed model is trained to produce low reconstruction error for normal data and high error for abnormal data,effectively distinguishing between the two and assigning an anomaly *** is conducted on normal datasets,while testing is performed on both normal and anomalous *** anomaly scores from the models are combined using a late fusion technique,and a deep dense layer model is trained to produce decisive scores indicating whether a sequence is normal or *** model’s performance is evaluated on the University of California,San Diego Pedestrian 2(UCSD PED 2),University of Minnesota(UMN),and Tampere University of technology(TUT)Rare Sound Events datasets using six evaluation *** is compared with state-of-the-art methods depicting a high Area Under Curve(AUC)and a low Equal Error Rate(EER),achieving an(AUC)of 93.1 and an(EER)of 8.1 for the(UCSD)dataset,and an(AUC)of 94.9 and an(EER)of 5.9 for the UMN *** evaluations demonstrate that the joint results from the combined audio-visual model outperform those from separate models,highlighting the competitive advantage of the proposed multi-modal approach.

关键词： Acoustic-visual anomaly detection sequence-to-sequence autoencoder reconstruction error late fusion regularity score

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Fully Soft Switched Bridgeless Buck Power Factor Correction Converter 16

Fully Soft Switched Bridgeless Buck Power Factor Correction ...

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16th Annual Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2025

作者： Kaviani, Kosar Maghsoudi, Mohammad Farzanehfard, Hosein Isfahan University of Technology Department of Electrical and Computer Engineering Isfahan Iran

ISBN: (纸本)9798331533946

In this paper, a bridgeless buck PFC structure is presented. To Fulfill soft switching for the main switches an auxiliary circuitry is utilized. The main switches of the proposed structure operate under ZVS condition and the auxiliary switch operate under ZCS condition. The introduced topology operates at Discontinuous conduction mode (DCM) leading to intrinsic PFC capability. A 120 W, 100 kHz prototype is designed and simulated to validate theoretical analysis using PSIM software. The results show 97% efficiency and fully soft switching operation. © 2025 IEEE.

关键词： Buck converter

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Strategic Renewable Energy Resource Selection Using a Fuzzy Decision-Making Method

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Intelligent Automation & Soft Computing 2023年第2期35卷 2117-2134页

作者： Anas Quteishat M.A.A.Younis Electrical Engineering Department Faculty of Engineering TechnologyAl-Balqa Applied UniversityAl-SaltJordan Department of Electrical and Computer Engineering Sohar UniversitySultanate of Oman

Renewable energy is created by renewable natural resources such as geothermal heat,sunlight,tides,rain,and *** resources are vital for all countries in terms of their economies and *** a result,selecting the optimal option for any country is critical in terms of energy *** country is nowadays planning to increase the share of renewable energy in their universal energy sources as a result of global *** the present work,the authors suggest fuzzy multi-characteristic decision-making approaches for renew-able energy source selection,and fuzzy set theory is a valuable methodology for dealing with uncertainty in the presence of incomplete or ambiguous *** study employed a hybrid method for order of preference by resemblance to an ideal solution based on fuzzy analytical network process-technique,which agrees with professional assessment scores to be linguistic phrases,fuzzy numbers,or crisp *** hybrid methodology is based on fuzzy set ideologies,which calculate alternatives in accordance with professional functional requirements using objective or subjective *** best-suited renewable energy alternative is discovered using the approach presented.

关键词： Multi characteristic decision making framework fuzzy sets fuzzy theory renewable energy energy resource selection

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Outdoor navigation for visually impaired people using YOLOv5 and Transfer learning: an analytical study

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Multimedia Tools and Applications 2024年 1-20页

作者： Shariatinezhad, Monir Molaeezadeh, Seyyedeh Fatemeh Gholami, Mohammad Department of Electrical and Computer Engineering Jundi-Shapur University of Technology Po.Box: 64615-334 Dezful Iran

This study introduces an obstacle detection system for visual impairment rehabilitation in visually impaired individuals, leveraging YOLOv5 and transfer learning. The methodology comprises four main phases. First phase is sidewalk dataset generation, involving creating our customized PESID dataset and a proprietary dataset. Second phase is image annotation into eight essential obstacle classes. We pay special attention to edges, slopes, and holes—often overlooked in existing sidewalk datasets. These aspects are crucial for ensuring the safety of visually impaired individuals. Third phase is model pretraining with the large-scale COCO dataset. Last phase is fine-tuning using transfer learning on specialized datasets. The evaluated models for obstacle detection include YOLOv3, YOLOv5s, YOLOv5l, YOLOv5x, YOLOv5n, MobilenetSSDv2, Detectron2, RetinaNet, and Faster RCNN. On the customized PESID dataset, YOLOv5s, YOLOv5x, YOLOv5m, and YOLOv5l outperform other models in terms of Mean Average Precision at an Intersection of Union (IOU) of 0.5 (MAP0.5) and detection speed. On our proprietary dataset, the YOLOv5l model achieves a MAP0.5 of 84.5% and 77 frames per second. Notably, the MAP0.5 scores for edges, slopes, and holes are 77%, 85%, and 84%, respectively. Additionally, improving image annotation quality significantly enhances model accuracy by more than 10% for two datasets. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image annotation

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Artificial visual perception neural system using a solution-processable MoS_(2)-based in-memory light sensor

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Light(Science & Applications) 2023年第8期12卷 1583-1594页

作者： Dayanand Kumar Lana Joharji Hanrui Li Ayman Rezk Ammar Nayfeh Nazek El-Atab Smart Advanced Memory Devices and Applications(SAMA)LaboratoryElectrical and Computer Engineering ProgramComputer Electrical Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955Kingdom of Saudi Arabia Department of Electrical Engineering and Computer Science Khalifa UniversityAbu Dhabi 127788United Arab Emirates

Optoelectronic devices are advantageous in in-memory light sensing for visual information processing,recognition,and storage in an energy-efficient ***,in-memory light sensors have been proposed to improve the energy,area,and time efficiencies of neuromorphic computing *** study is primarily focused on the development of a single sensing-storage-processing node based on a two-terminal solution-processable MoS2 metal-oxide-semiconductor(MOS)charge-trapping memory structure—the basic structure for charge-coupled devices(CCD)—and showing its suitability for in-memory light sensing and artificial visual *** memory window of the device increased from 2.8 V to more than 6V when the device was irradiated with optical lights of different wavelengths during the program ***,the charge retention capability of the device at a high temperature(100 ℃)was enhanced from 36 to 64%when exposed to a light wavelength of 400 *** larger shift in the threshold voltage with an increasing operating voltage confirmed that more charges were trapped at the Al_(2)O_(3)/MoS_(2) interface and in the MoS_(2) layer.A small convolutional neural network was proposed to measure the optical sensing and electrical programming abilities of the *** array simulation received optical images transmitted using a blue light wavelength and performed inference computation to process and recognize the images with 91%*** study is a significant step toward the development of optoelectronic MOS memory devices for neuromorphic visual perception,adaptive parallel processing networks for in-memory light sensing,and smart CCD cameras with artificial visual perception capabilities.

关键词： visual neural process

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Highly transparent anti-reflection coating enhances the underwater efficiency and stability of perovskite solar modules

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Nano Research 2024年第9期17卷 8126-8133页

作者： Feng Qian Shihao Yuan Ting Zhang Lei Wang Xiaobo Li Hualin Zheng Qien Xu Zhi David Chen Shibin Li School of Optoelectronic Science and Engineering University of Electronic Science and Technology of ChinaChengdu 610054China Department of Electrical and Computer Engineering and Center for Nanoscale Science and Engineering University of KentuckyLexingtonKentucky 40506USA

Perovskite solar cells have shown great potential in the field of underwater solar cells due to their excellent optoelectronic properties;however,their underwater performance and stability still hinder their practical *** this research,a 1H,1H,2H,2H-heptadecafluorodecyl acrylate(HFDA)anti-reflection coating(ARC)was introduced as a high-transparent material for encapsulating perovskite solar modules(PSMs).Optical characterization results revealed that HFDA can effectively reduce reflection of light below 800 nm,aiding in the absorption of light within this wavelength range by underwater solar ***,a remarkable efficiency of 14.65%was achieved even at a water depth of 50 ***,the concentration of Pb^(2+)for HFDA-encapsulated film is significantly reduced from 186 to 16.5 ppb after being immersed in water for 347 ***,the encapsulated PSMs still remained above 80%of their initial efficiency after continuous underwater illumination for 400 ***,being exposed to air,the encapsulated PSMs maintained 94%of their original efficiency after 1000 h light *** highly transparent ARC shows great potentials in enhancing the stability of perovskite devices,applicable not only to underwater cells but also extendable to land-based photovoltaic devices.

关键词： underwater photovoltaics perovskite solar modules anti-reflection coating underwater stability

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SFI-Swin: symmetric face inpainting with swin transformer by distinctly learning face components distributions

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Multimedia Tools and Applications 2024年第17期84卷 1-15页

作者： Givkashi, MohammadHossein Naderi, MohammadReza Karimi, Nader Shirani, Shahram Samavi, Shadrokh Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan84156-83111 Iran Department of Electrical and Computer Engineering McMaster University HamiltonL8S 4L8 Canada Computer Science Department Seattle University Seattle98122 United States

Image inpainting consists of filling holes or missing parts of an image. Inpainting face images with symmetric characteristics is more challenging than inpainting a natural scene. None of the powerful existing models can fill out the missing parts of an image while considering the symmetry and homogeneity of the picture. Moreover, the metrics that assess a repaired face image quality cannot measure the preservation of symmetry between the rebuilt and existing parts of a face. In this paper, we intend to solve the symmetry problem in the face inpainting task by using multiple discriminators that check each face organ’s reality separately and a transformer-based network. We also propose "symmetry concentration score" as a new metric for measuring the symmetry of a repaired face image. The quantitative and qualitative results show the superiority of our proposed method compared to some of the recently proposed algorithms in terms of the reality, symmetry, and homogeneity of the inpainted parts. The code for the proposed method is available at https://***/mohammadrezanaderi4/SFI-Swin. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Deep learning

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Dynamics analysis and cryptographic implementation of a fractional-order memristive cellular neural network model

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Chinese Physics B 2024年第4期33卷 418-433页

作者：周新卫蒋东华 Jean De Dieu Nkapkop Musheer Ahmad Jules Tagne Fossi Nestor Tsafack 吴建华 Department of Information Engineering Gongqing CollegeNanchang UniversityJiujiang 332020China School of Computer Science and Engineering Sun Yat-Sen UniversityGuangzhou 511400China Department of Electrical Engineering and Industrial Computing University Institute of TechnologyDoualaCameroon Department of Computer Engineering Jamia Millia IslamiaNew Delhi 110025India Department of Physics Faculty of ScienceUniversity of YaoundeCameroon Electrical Engineering Department and Industrial Computing of ISTAMA University of DoualaDoualaCameroon

Due to the fact that a memristor with memory properties is an ideal electronic component for implementation of the artificial neural synaptic function,a brand-new tristable locally active memristor model is first proposed in this ***,a novel four-dimensional fractional-order memristive cellular neural network(FO-MCNN)model with hidden attractors is constructed to enhance the engineering feasibility of the original CNN model and its ***,its hardware circuit implementation and complicated dynamic properties are investigated on multi-simulation ***,it is used toward secure communication application *** it as the pseudo-random number generator(PRNG),a new privacy image security scheme is designed based on the adaptive sampling rate compressive sensing(ASR-CS)***,the simulation analysis and comparative experiments manifest that the proposed data encryption scheme possesses strong immunity against various security attack models and satisfactory compression performance.

关键词： cellular neural network memristor hardware circuit compressive sensing privacy data protection

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Anonymous TollPass: A Blockchain-Based Privacy-Preserving Electronic Toll Payment Model

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computers, Materials & Continua 2024年第6期79卷 3495-3518页

作者： Jane Kim Soojin Lee Chan Yeob Yeun Seung-Hyun Seo Department of Electronic&Electrical Engineering Graduate SchoolHanyang UniversitySeoul04763Korea Department of Electrical Engineering and Computer Science Khalifa University of Science and TechnologyAbu Dhabi127788United Arab Emirates School of Electrical Engineering Hanyang UniversityERICAAnsan15588Korea

As big data,Artificial Intelligence,and Vehicle-to-Everything(V2X)communication have advanced,Intelligent Transportation Systems(ITS)are being developed to enable efficient and safe transportation *** Toll Collection(ETC),which is one of the services included in ITS systems,is an automated system that allows vehicles to pass through toll plazas without stopping for manual *** ETC system is widely deployed on highways due to its contribution to stabilizing the overall traffic system *** ensure secure and efficient toll payments,designing a distributed model for sharing toll payment information among untrusted toll service providers is ***,the current ETC system operates under a centralized ***,both toll service providers and toll plazas know the toll usage history of *** raises concerns about revealing the entire driving routes and patterns of *** address these issues,blockchain technology,suitable for secure data management and data sharing in distributed systems,is being applied to the ETC *** enables efficient and transparent management of ETC ***,the public nature of blockchain poses a challenge where users’usage records are exposed to all *** tackle this,we propose a blockchain-based toll ticket model named AnonymousTollPass that considers the privacy of *** proposed model utilizes traceable ring signatures to provide unlinkability between tickets used by a vehicle and prevent the identity of the vehicle using the ticket from being identified among the ring members for the ***,malicious vehicles’identities can be traced when they attempt to reuse *** conducting simulations,we show the effectiveness of the proposed model and demonstrate that gas fees required for executing the proposed smart contracts are only 10%(when the ring size is 50)of the fees required in previous studies.

关键词： Blockchain electronic toll collection smart contract traceable ring signature

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Active Voltage Balancing of Series-Connected SiC MOSFETs During Body-Diode Turn-Off Using an Active Gate Driver

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IEEE Transactions on Power Electronics 2025年第8期40卷 10609-10622页

作者： Rai, Ajay Ganesan, P. Hatua, Kamalesh Bhattacharya, Subhashish Department of Electrical Engineering Indian Institute of Technology Madras Chennai India Centre for Development of Advanced Computing (C-DAC) Thiruvananthapuram India Department of Electrical and Computer Engineering NC State University Raleigh NC USA

The series connection of fast-switching SiC MOSFETs presents a promising approach to enhance the efficiency, compactness, and simplicity of Medium Voltage (MV) power converters. However, managing voltage imbalances during the turn-off of MOSFETs and their body diodes introduces significant challenges. While existing literature covers passive and active voltage balancing strategies for switch turn-off (e.g., MOSFETs/IGBTs), the issue of uneven voltage distribution during body diode turn-off remains largely unexplored. This gap limits the widespread adoption of series-connected devices in MV power converters, as achieving reliable performance with minimal additional components and low switching losses remains difficult. This article presents an Active Voltage Balancing technique for handling body diode turn-off events by regulating the gate charge of parallel MOSFETs during voltage rise transients in the closedloop using Active Gate Drivers (AGD). This approach ensures uniform voltage distribution among the body diodes of seriesconnected MOSFETs. A comprehensive analysis and modelling of gate charge control during voltage transients is presented. The proposed method is experimentally validated on two seriesconnected SiC MOSFETs operating in buck mode (DC-DC) and half-bridge inverter mode (DC-AC) at a 1.5 kV DC bus voltage, with switching frequencies up to 40 kHz. © 1986-2012 IEEE.

关键词： Diodes

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