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WLARS: Workload-Aware Recharge Scheduling Mechanism for Improving Surveillance Quality in Wireless Rechargeable Sensor Networks

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IEEE Sensors Journal 2023年第11期23卷 12237-12250页

作者： Dande, Bhargavi Chang, Chih-Yung Wu, Shih-Jung Roy, Diptendu Sinha National Taiwan University Department of Electrical Engineering Taipei10617 Taiwan Tamkang University Department of Computer Science and Information Engineering New Taipei25137 Taiwan National Institute of Technology Meghalaya Department of Computer Science and Engineering Shillong793003 India

With radio frequency (RF), the mobile charger (MC) can wirelessly transmit energy to the sensor nodes in the network. The wireless energy transfer enhances the lifetime of sensor nodes in wireless rechargeable sensor networks (WRSNs). Most of the studies improved the efficiency of MC or perpetuated the lifetime of WRSNs. At the same time, none of the studies focused on considering the spatial and temporal surveillance qualities (STSQs) of each sensor recharged. Therefore, this article proposed an efficient energy recharge scheduling for MC, aiming to maximize the STSQ of the given network. Initially, sensor routing load (RL) is considered to partition the network to distribute the charging load of the MCs evenly. Second, the busy level of the MC is considered to send the recharging requests to the MC. Based on the busy level of MC, the sensors adjust the sensing rate frequency to manage their energy. Finally, cooperation between the neighboring MCs is proposed to reduce the waiting time for recharging requested sensors. The simulation results present that the proposed work yields the literature in terms of STSQ, traveling distance, average waiting time (AWT), and energy usage efficiency. © 2001-2012 IEEE.

关键词： computer architecture

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A METHOD FOR MONITORING SLOW ELECTROMECHANICAL OSCILLATIONS IN MULTI-AREA electrical POWER SYSTEMS: THE CASE OF FOUR AREAS IEEE 39 BUS POWER SYSTEM 14

A METHOD FOR MONITORING SLOW ELECTROMECHANICAL OSCILLATIONS ...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Ilić, Marija D. Lawson, Riley E. Umbereen, Sayyeda Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical Engineering KTH Stockholm Sweden

ISBN: (纸本)9781837242689

This paper illustrates an earlier introduced method for systematic monitoring and control of slow electro-mechanical oscillations in electric power systems. The emphasis is on generalizing the two-area system concepts to a general multi-area power system. The method illustrates a transformed state space which explicitly models tie-line flow power dynamics between areas of interest (groups of interconnected equipment) and the rest of the system. Given parameters of an electric power grid, these tie-line power flow oscillations are expressed in terms of load and generation power deviations from given equilibrium, both controlled and uncontrolled. This new model sets the basis for identifying root causes of slow inter-area oscillations, needed to define the most important measurements and placement/enhancement of controllers for reducing these interactions. Notably, both conventional model and the transformed state space model have the same eigenvalues. The proposed approach does not require eigenmode calculations, and therefore lends itself to practical use of Phasor Measurmeent Units (PMUs). It is then shown how each area can monitor, compute and control inter-area oscillations either in an entirely decentralized way, much the same way as today's Automatic Generation Control (AGC) is carried out, or in a cooperative efficient way by jointly controlling inter-area fluctuations. © The Institution of engineering & Technology 2024.

关键词： Eigenvalues and eigenfunctions

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Dual-Buck Bipolar Buck-Boost AC-AC Converter With Reduced Semiconductor Devices

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IEEE Transactions on Industrial Electronics 2024年第9期71卷 10495-10511页

作者： Ahmed, Hafiz Furqan Chien, Howard Khan, Ashraf Ali Islam, Shirazul Akbar, Fazal Alzaabi, Omar National Sun Yat-sen University Department of Electrical Engineering Kaohsiung80424 Taiwan Memorial University of Newfoundland Faculty of Engineering And Applied Science Department of Electrical And Computer Engineering St. John'sNLA1B 3X9 Canada Qatar University Department of Electrical Engineering Doha2713 Qatar University of Edinburgh EdinburghEH9 3JL United Kingdom Khalifa University Department of Electrical Engineering And Computer Science Advanced Power And Energy Center Abu Dhabi127788 United Arab Emirates

Dual-buck (DB) structured ac-ac converters are becoming advanced due to their inherent protection from open- and short-circuit risks, and elimination of commutation issue. However, the existing DB ac-ac converters provide restricted bipolar voltage operations with a large semiconductor device count and underutilized inductors. This article proposed a new reduced switch DB ac-ac converter without commutation issue. The propose converter provides multiple buck-boost voltage operations with noninverting and inverting outputs, making it a flexible topology for various ac voltage applications. The propose converter exhibits the continuous input and output currents irrespective of operation mode, and performs well with nonunity power factor loads. The positive and negative voltage gains of the proposed converter can address the grid voltage sag and swell issues, respectively, making it right candidate for application as dynamic voltage restorer. A detailed comparative evaluation is carried out with existing DB converters, which validated the effectiveness of the proposed converter, including;reduced semiconductor device count and their power ratings, reduced inductor sizes with improved magnetic utilization, enhanced voltage compensation ranges, and better efficiency. A laboratory scale hardware prototype of the proposed converter is built and thoroughly tested to validate its operation. © 1982-2012 IEEE.

关键词： Semiconductor devices

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PharmaChain 3.0: Efficient Tracking and Tracing of Drugs in Pharmaceutical Supply Chain Using Blockchain Integrated Product Serialization Mechanism

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SN computer science 2024年第1期5卷 149页

作者： Bapatla, Anand Kumar Mohanty, Saraju P. Kougianos, Elias Department of Computer Science and Engineering University of North Texas Denton United States Department of Electrical Engineering University of North Texas Denton United States

Globalization has revolutionized how different entities are distributed across locations interconnect and collaborated to enhance the availability of different services even at remote areas. Supply chains have played an important role in expanding business operations globally and at the same time increasing operational efficiency and reducing costs. Pharmaceutical Supply Chain (PSC) is one of the important aspects of healthcare which is vital for resource acquisition, manufacturing, and distribution of prescription drugs from the manufacturer site to patients. "Five rights of medication” is the main motto of the PSC which ensures the delivery of the right medicine to the right patient, at the right time, in the right doses, and through the appropriate route. Following this principle achieves patient safety in the healthcare system. However, as the number of entities participating in the PSC is large, which are geographically distributed and interact in complex ways makes the PSC more abstract and causes adversaries to introduce counterfeit medicines into the system. Developing a transparent PSC with no information fragmentation is very much needed for efficient track and trace along with easy identification and avoidance of counterfeit drugs. The current paper proposes one such architecture that is integrated with Blockchain, Distributed File Storage System, and Barcode technologies to provide a secure Barcode mechanism for addressing such tracking and tracing issues in the pharmaceutical supply chain. The novel product serialization mechanism proposed in PharmaChain 3.0 also ensures accurate identification, capture, and sharing of information about the drugs manufactured between these participating entities without the use of centralized entities and removing blind parties. The current system is designed to efficiently capture both Pedigree and T3 information of drugs in order to comply with regulations like Drug Supply Chain Security Act (DSCSA) and Prescription D

关键词： Barcode mechanism Blockchain Distributed ledger technologies Drug labeling Ethereum Pharmaceutical supply chain Product serialization Smart contracts

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Exploring the Predictive Capabilities of AlphaFold Using Adversarial Protein Sequences

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第7期5卷 3384-3392页

作者： Alkhouri, Ismail R. Jha, Sumit Beckus, Andre Atia, George Jha, Susmit Ewetz, Rickard Velasquez, Alvaro OrlandoFL32816 United States Michigan State University Computational Mathematics Science and Engineering Department East LansingMI48824 United States University of Michigan Electrical Engineering and Computer Science Department Ann ArborMI48109 United States Florida International University Knights Foundation School of Computing and Information Sciences MiamiFL33199 United States Air Force Research Laboratory Rome Information Directorate NY13441 United States Department Computer Science Department OrlandoFL32816 United States SRI International Computer Science Laboratory Menlo ParkCA94025 United States Electrical and Computer Engineering Department OrlandoFL32816 United States University of Colorado Computer Science Department BoulderCO80309 United States

Protein folding neural networks (PFNNs) such as AlphaFold predict remarkably accurate structures of proteins compared to other approaches. However, the robustness of such networks has heretofore not been fully explored. This is particularly relevant given the broad social implications of such technologies and the fact that biologically small perturbations to noncritical residues of a protein sequence do not typically lead to drastic changes in the protein structure. Our study demonstrates that, similar to adversarial methods in machine learning, small changes to protein sequences can result in significant differences in the predicted protein structures using AlphaFold as determined by large distance measures. Despite this, our findings using multiple protein sequences suggest that AlphaFold is able to accurately predict the domain structure and folding regions of a protein. To gauge structural differences, we employ two alignment-based measures [root-mean-square deviation (RMSD) and the global distance test (GDT) similarity], and one alignment-free measure, which is an effective graph-based structure representation (GraSR) method. We prove that the problem of minimally perturbing protein sequences is NP-complete. Based on the well-established block substitution matrices (BLOSUM62) sequence alignment scoring matrix, we generate adversarial sequences. In our experimental evaluation, we consider 111 proteins (including 29 COVID-19 sequences) in the Universal Protein resource (UniProt), a central resource for protein data. Our findings suggest that, despite the high RMSD values returned by AlphaFold, it is capable of handling the BLOSUM adversarial sequences considered in our analysis, as evidenced by the preservation of the folded regions and the GraSR results. © 2020 IEEE.

关键词： Neural networks

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3D Kronecker Convolutional Feature Pyramid for Brain Tumor Semantic Segmentation in MR Imaging

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computers, Materials & Continua 2023年第9期76卷 2861-2877页

作者： Kainat Nazir Tahir Mustafa Madni Uzair Iqbal Janjua Umer Javed Muhammad Attique Khan Usman Tariq Jae-Hyuk Cha Medical Imaging and Diagnostics Lab NCAIDepartment of Computer ScienceCOMSATS University IslamabadIslamabad44000Pakistan Department of Electrical and Computer Engineering COMSATS University IslamabadWah CampusWahPakistan Department of Computer Science HITEC UniversityTaxilaPakistan Department of Management Information Systems College of Business AdministrationPrince Sattam Bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea

Brain tumor significantly impacts the quality of life and changes everything for a patient and their loved *** a brain tumor usually begins with magnetic resonance imaging(MRI).The manual brain tumor diagnosis from the MRO images always requires an expert ***,this process is time-consuming and ***,a computerized technique is required for brain tumor detection in MRI *** the MRI,a novel mechanism of the three-dimensional(3D)Kronecker convolution feature pyramid(KCFP)is used to segment brain tumors,resolving the pixel loss and weak processing of multi-scale lesions.A single dilation rate was replaced with the 3D Kronecker convolution,while local feature learning was performed using the 3D Feature Selection(3DFSC).A 3D KCFP was added at the end of 3DFSC to resolve weak processing of multi-scale lesions,yielding efficient segmentation of brain tumors of different sizes.A 3D connected component analysis with a global threshold was used as a post-processing *** standard Multimodal Brain Tumor Segmentation 2020 dataset was used for model *** 3D KCFP model performed exceptionally well compared to other benchmark schemes with a dice similarity coefficient of 0.90,0.80,and 0.84 for the whole tumor,enhancing tumor,and tumor core,***,the proposed model was efficient in brain tumor segmentation,which may facilitate medical practitioners for an appropriate diagnosis for future treatment planning.

关键词： Brain tumor segmentation connect component analysis deep learning kronecker convolution magnetic resonance imaging

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EVA2.0:Investigating Open-domain Chinese Dialogue Systems with Large-scale Pre-training

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Machine Intelligence Research 2023年第2期20卷 207-219页

作者： Yuxian Gu Jiaxin Wen Hao Sun Yi Song Pei Ke Chujie Zheng Zheng Zhang Jianzhu Yao Lei Liu Xiaoyan Zhu Minlie Huang The Conversational AI Group Tsinghua UniversityBeijing 100084China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China Department of Electrical Engineering and Computer Science York UniversityToronto M3J1P3Canada

Large-scale pre-training has shown remarkable performance in building open-domain dialogue ***,previous works mainly focus on showing and evaluating the conversational performance of the released dialogue model,ignoring the discussion of some key factors towards a powerful human-like chatbot,especially in Chinese *** this paper,we conduct extensive experiments to investigate these under-explored factors,including data quality control,model architecture designs,training approaches,and decoding *** propose EVA2.0,a large-scale pre-trained open-domain Chinese dialogue model with 2.8 billion parameters,and will make our models and codes publicly *** and human evaluations show that EVA2.0 significantly outperforms other open-source *** also discuss the limitations of this work by presenting some failure cases and pose some future research directions on large-scale Chinese open-domain dialogue systems.

关键词： Natural language processing deep learning(DL) large-scale pre-training dialogue systems Chinese open-domain conversational model

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Multicontrast Pocket Colposcopy Cervical Cancer Diagnostic Algorithm for Referral Populations

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Biomedical engineering Frontiers 2022年第1期3卷 381-393页

作者： Erica Skerrett Zichen Miao Mercy N.Asiedu Megan Richards Brian Crouch Guillermo Sapiro Qiang Qiu Nirmala Ramanujam Department of Biomedical Engineering Duke UniversityDurhamNCUSA Department of Electrical and Computer Engineering Purdue UniversityWest LafayetteINUSA Department of Computer Engineering Massachusetts Institute of TechnologyCambridgeMAUSA Department of Electrical and Computer Engineering Department of Biomedical EngineeringDepartment of Computer ScienceDepartment of MathematicsDuke UniversityDurhamNCUSA

Objective and Impact *** use deep learning models to classify cervix images—collected with a low-cost,portable Pocket colposcope—with biopsy-confirmed high-grade precancer and *** boost classification performance on a screened-positive population by using a class-balanced loss and incorporating green-light colposcopy image pairs,which come at no additional cost to the *** the majority of the 300,000 annual deaths due to cervical cancer occur in countries with low-or middle-Human Development Indices,an automated classification algorithm could overcome limitations caused by the low prevalence of trained professionals and diagnostic variability in provider visual *** dataset consists of cervical images(n=1,760)from 880 patient *** optimizing the network architecture and incorporating a weighted loss function,we explore two methods of incorporating green light image pairs into the network to boost the classification performance and sensitivity of our model on a test *** achieve an area under the receiver-operator characteristic curve,sensitivity,and specificity of 0.87,75%,and 88%,*** addition of the class-balanced loss and green light cervical contrast to a Resnet-18 backbone results in a 2.5 times improvement in *** methodology,which has already been tested on a prescreened population,can boost classification performance and,in the future,be coupled with Pap smear or HPV triaging,thereby broadening access to early detection of precursor lesions before they advance to cancer.

关键词： boost network backbone

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A FSS Inverse Design Method Based on Output Space Mapping Enhanced ECM

A FSS Inverse Design Method Based on Output Space Mapping En...

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2024 International Applied Computational Electromagnetics Society Symposium, ACES-China 2024

作者： Tian, Ziheng Zhang, Juntao Kuang, Yu Cheng, Qingsha S. Southern University of Science and Technology Department of Electrical and Electronic Engineering Shenzhen China National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore

ISBN: (纸本)9798350355581

This paper proposes an inverse design method for frequency selective surfaces (FSS) based on an equivalent circuit model (ECM) and output space mapping (OSM) technique. The method establishes an OSM enhanced ECM model (forward model) to replace expensive electromagnetic (EM) simulations for FSS shielding effectiveness (SE) evaluation. Furthermore, an inverse model is proposed to predict FSS unit cell structure parameter values using specification-driven feature point sampling method. Experiment results demonstrate that FSS designs with shielding frequency between 2-18GHz can be efficiently predicted and verified by EM simulation. © 2024 IEEE.

关键词： Frequency selective surfaces

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Beyond 5G Networks: Integration of Communication, Computing, Caching, and Control

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China Communications 2023年第7期20卷 137-174页

作者： Musbahu Mohammed Adam Liqiang Zhao Kezhi Wang Zhu Han State Key Laboratory of Integrated Service Networks Xidian UniversityXi’an 710071China Department of Computer and Information Sciences Northumbria UniversityNewcastle upon TyneUK Department of Electrical and Computer Engineering University of HoustonHoustonTX 77004 USAand also with the Department of Computer Science and EngineeringKyung Hee UniversitySeoul 02447 South Korea

In recent years,the exponential proliferation of smart devices with their intelligent applications poses severe challenges on conventional cellular *** challenges can be potentially overcome by integrating communication,computing,caching,and control(i4C)*** this survey,we first give a snapshot of different aspects of the i4C,comprising background,motivation,leading technological enablers,potential applications,and use ***,we describe different models of communication,computing,caching,and control(4C)to lay the foundation of the integration *** review current stateof-the-art research efforts related to the i4C,focusing on recent trends of both conventional and artificial intelligence(AI)-based integration *** also highlight the need for intelligence in resources ***,we discuss the integration of sensing and communication(ISAC)and classify the integration approaches into various ***,we propose open challenges and present future research directions for beyond 5G networks,such as 6G.

关键词： 4C 6G integration of communication,computing,caching,and control i4C multi-access edge computing(MEC)

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