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IEEE Texas Power and Energy Conference (TPEC)

作者： Mingze Li Weihang Ren Lei Fan Yongpei Guan Dept. of Electrical and Computer Engineering University of Houston TX USA Engineering Technology University of Houston TX USA Dept. of Industrial and Systems Engineering University of Florida FL USA

ISBN: (数字)9798331541125

ISBN: (纸本)9798331541132

This paper presents a preprocessing method to solve the security-constrained unit commitment with AC power flows (SCUC-ACPF), which is a large scale mixed-integer non-convex, nonlinear optimization problem. We introduce clustering algorithms and local search to reduce problem complexity, and obtain local optimal solutions within limited solving time and computational capacity. The clustering algorithms group buses into manageable clusters centered around core buses, creating smaller sub-grids for efficient optimization. The local search algorithms iteratively explore and improve solution quality. Our method ensures balanced clusters that respect physical and operational constraints, significantly enhancing optimization efficiency and contributing to more effective grid management and operation.

关键词： Heuristic algorithms Clustering methods Clustering algorithms Search problems Boundary conditions Power grids Complexity theory Optimization AC power transmission

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Accurate, provable, and fast nonlinear tomographic reconstruction: A variational inequality approach

arXiv

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arXiv 2025年

作者： Lou, Mengqi Verchand, Kabir Aladin Fridovich-Keil, Sara Pananjady, Ashwin Georgia Institute of Technology School of Industrial and Systems Engineering United States School of Electrical and Computer Engineering United States University of Cambridge Statistical Laboratory United Kingdom Stanford University Department of Electrical Engineering United States

We consider the problem of signal reconstruction for computed tomography (CT) under a nonlinear forward model that accounts for exponential signal attenuation, a polychromatic X-ray source, general measurement noise (e.g. Poisson shot noise), and observations acquired over multiple wavelength windows. We develop a simple iterative algorithm for single-material reconstruction, which we call EXACT (EXtragradient Algorithm for Computed Tomography), based on formulating our estimate as the fixed point of a monotone variational inequality. We prove guarantees on the statistical and computational performance of EXACT under practical assumptions on the measurement process. We also consider a recently introduced variant of this model with Gaussian measurements, and present sample and iteration complexity bounds for EXACT that improve upon those of existing algorithms. We apply our EXACT algorithm to a CT phantom image recovery task and show that it often requires fewer X-ray projection exposures, lower source intensity, and less computation time to achieve similar reconstruction quality to existing methods. © 2025, CC BY.

关键词： computerized tomography

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Decomposition Algorithm for Security-Constrained Unit Commitment with AC Optimal Power Flows

Decomposition Algorithm for Security-Constrained Unit Commit...

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IEEE Texas Power and Energy Conference (TPEC)

作者： Weihang Ren Mingze Li Lei Fan Yongpei Guan Dept. of Industrial and Systems Engineering University of Florida FL USA Dept. of Electrical and Computer Engineering University of Houston TX USA Engineering Technology University of Houston TX USA

ISBN: (数字)9798331541125

ISBN: (纸本)9798331541132

This paper presents a comprehensive approach to solving the security-constrained unit commitment with alternating current power flows (SCUC-ACPF) problem in contemporary power systems. We introduce algorithms that decompose the problem into subproblems suitable for specialized solvers, so that the large-scale mixed-integer nonlinear program-ming SCUC-ACPF problem can be solved. In case studies, we validate the efficiency and effectiveness of our algorithms on synthetic and industry-scale power system networks.

关键词： Runtime Scalability Power systems Planning Security Optimization AC power transmission Load flow

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Energy efficient indoor localisation for narrowband internet of things

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1150-1163页

作者： Ismail Keshta Mukesh Soni Mohammed Wasim Bhatt Azeem Irshad Ali Rizwan Shakir Khan Renato RMaaliw III Arsalan Muhammad Soomar Mohammad Shabaz Computer Science and Information Systems Department College of Applied SciencesAlMaarefa UniversityRiyadhSaudi Arabia Department of CSE University Centre for Research and Development Chandigarh UniversityMohaliPunjabIndia Department of Computer Science and Engineering National Institute of TechnologySrinagarIndia Asghar Mall College Rawalpindi Higher Education Department(HED)Govt.of the PunjabRawalpindiPakistan Department of Industrial Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddahSaudi Arabia College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University(IMSIU)RiyadhSaudi Arabia College of Engineering Southern Luzon State UniversityLucbanQuezonPhilippines Department of Automation Electronics and Electrical EngineeringGdansk University of TechnologyGdańskPoland Arba Minch University Arba MinchEthiopia

There are an increasing number of Narrow Band IoT devices being manufactured as the technology behind them develops *** high co‐channel interference and signal attenuation seen in edge Narrow Band IoT devices make it challenging to guarantee the service quality of these *** maximise the data rate fairness of Narrow Band IoT devices,a multi‐dimensional indoor localisation model is devised,consisting of transmission power,data scheduling,and time slot scheduling,based on a network model that employs non‐orthogonal multiple access via a *** on this network model,the optimisation goal of Narrow Band IoT device data rate ratio fairness is first established by the authors,while taking into account the Narrow Band IoT network:The multidimensional indoor localisation optimisation model of equipment tends to minimize data rate,energy constraints and EH relay energy and data buffer constraints,data scheduling and time slot *** a result,each Narrow Band IoT device's data rate needs are met while the network's overall performance is *** investigate the model's potential for convex optimisation and offer an algorithm for optimising the distribution of multiple resources using the KKT *** current work primarily considers the NOMA Narrow Band IoT network under a single EH ***,the growth of Narrow Band IoT devices also leads to a rise in co‐channel interference,which impacts NOMA's performance *** simulation,the proposed approach is successfully *** improvements have boosted the network's energy efficiency by 44.1%,data rate proportional fairness by 11.9%,and spectrum efficiency by 55.4%.

关键词： artificial inteligence detection of moving objects internet of things

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Autonomous Vehicle Security: A Deep Dive into Threat Modeling

arXiv

引用

arXiv 2024年

作者： Yousseef, Amal Satam, Shalaka Latibari, Banafsheh Saber Pacheco, Jesus Salehi, Soheil Hariri, Salim Satam, Partik Department of Electrical and Computer Engineering University of Arizona TucsonAZ United States Department of Systems and Industrial Engineering University of Arizona TucsonAZ United States Department of Industrial Engineering University of Sonora Hermosillo Mexico

Autonomous vehicles (AVs) are poised to revolutionize modern transportation, offering enhanced safety, efficiency, and convenience. However, the increasing complexity and connectivity of AV systems introduce significant cybersecurity challenges. This paper provides a comprehensive survey of AV security with a focus on threat modeling frameworks, including STRIDE, DREAD, and MITRE ATT&CK, to systematically identify and mitigate potential risks. The survey examines key components of AV architectures, such as sensors, communication modules, and electronic control units (ECUs), and explores common attack vectors like wireless communication exploits, sensor spoofing, and firmware vulnerabilities. Through case studies of real-world incidents, such as the Jeep Cherokee and Tesla Model S exploits, the paper highlights the critical need for robust security measures. Emerging technologies, including blockchain for secure Vehicle-to-Everything (V2X) communication, AI-driven threat detection, and secure Over-The-Air (OTA) updates, are discussed as potential solutions to mitigate evolving threats. The paper also addresses legal and ethical considerations, emphasizing data privacy, user safety, and regulatory compliance. By combining threat modeling frameworks, multi-layered security strategies, and proactive defenses, this survey offers insights and recommendations for enhancing the cybersecurity of autonomous vehicles. © 2024, CC BY.

关键词： Firmware

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A Novel Single-Phase Seven-Level Boost Inverter with Simplified Control

A Novel Single-Phase Seven-Level Boost Inverter with Simplif...

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2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

作者： Vo, Dai-Van Minh Thao, Nguyen Gia Nguyen, Minh-Khai Duong, Truong-Duy Bui, Van-Cuong Tran, Tan-Tai Lim, Young-Cheol Choi, Joon-Ho Chonnam National University Department of Electrical Engineering Gwangju Korea Republic of Shimane University Department of Mechanical Electrical and Electronic Engineering Matsue Japan General Motors Company Global Electrification and Battery Systems Warren United States Wayne State University Department of Electrical and Computer Engineering Detroit United States Industrial University of Ho Chi Minh City Ho Chi Minh City Viet Nam

ISBN: (纸本)9781665471640

This work proposes a new single-phase seven-level inverter (1P7LBI) for a single-phase system that uses only eight transistors to increase the output voltage three times. Out of these eight switches, two operate at low frequency to reduce loss with a simple control system. Besides, the capacitors used in the proposed structure are maintained at the input voltage and operate at high frequencies with low ripple. Furthermore, a comparison using the proposed 1P7LBI structure and other multi-level structures was performed to demonstrate the potential of the suggested structure. Finally, some simulation and experimental findings are given to confirm the feasibility and efficacy of this novel configuration. © 2023 IEEE.

关键词： Multilevel-inverter seven-level single-phase system switched capacitor voltage boosting

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Interactive Framework for Cybersecurity Education and Future Workforce Development

Interactive Framework for Cybersecurity Education and Future...

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Frontiers in Education (FIE) Conference

作者： Sujan Ghimire Muhtasim Alam Chowdhury Ryan Tsang Richard Yarnell Emma Heckert Jaeden Carpenter Yu-Zheng Lin Muntasir Mamun Ronald F. DeMara Setareh Rafatirad Pratik Satam Soheil Salehi Department of Systems and Industrial Engineering University of Arizona Tucson AZ Department of Electrical and Computer Engineering University of Arizona Tucson AZ Department of Electrical and Computer Engineering University of California Davis Davis CA Department of Electrical and Computer Engineering University of Central Florida Orlando FL Department of Computer Science University of California Davis Davis CA

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

This research-to-practice paper presents a novel pedagogical tool for hardware cybersecurity education and workforce development. The growing importance of hardware security has made it essential for individuals and organizations to understand hardware security principles and best practices. However, the current educational curriculum falls short of fulfilling these emerging demands due to the rapidly changing hardware security landscape and limited opportunities for hands-on training. To address these challenges, we propose and have developed the Interactive Hardware and Cybersecurity (I-HaC) Educational Framework, a pedagogical educational framework that supplements existing courses by leveraging generative AI for individualized instruction related to hardware and cybersecurity, data mining, and applied Machine Learning (ML), as well as data visualization to enhance cybersecurity education and workforce development. The framework is designed to be utilized by graduate and undergraduate electrical and computer engineering (ECE) and computer Science (CS) students for a comprehensive introduction to cybersecurity exploits and countermeasures in an interactive manner with hands-on components. Using I-HaC, we have developed tailored lab components for a diverse range of students and intend to release I-HaC as open-source for the benefit of the ECE and CS education community.

关键词： Training Generative AI Databases Hardware security Data visualization Organizations Machine learning Ontologies computer security Protection

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An Efficient Medical Image Deep Fusion Model Based on Convolutional Neural Networks

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computers, Materials & Continua 2023年第2期74卷 2905-2925页

作者： Walid El-Shafai Noha A.El-Hag Ahmed Sedik Ghada Elbanby Fathi E.Abd El-Samie Naglaa F.Soliman Hussah Nasser AlEisa Mohammed E.Abdel Samea Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelsheikh UniversityKafr El-SheikhEgypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Medical Imaging and Interventional Radiology National Liver InstituteMenoufia UniversityEgypt

Medical image fusion is considered the best method for obtaining one image with rich details for efficient medical diagnosis and *** learning provides a high performance for several medical image analysis *** paper proposes a deep learning model for the medical image fusion *** model depends on Convolutional Neural Network(CNN).The basic idea of the proposed model is to extract features from both CT and MR ***,an additional process is executed on the extracted *** that,the fused feature map is reconstructed to obtain the resulting fused ***,the quality of the resulting fused image is enhanced by various enhancement techniques such as Histogram Matching(HM),Histogram Equalization(HE),fuzzy technique,fuzzy type,and Contrast Limited Histogram Equalization(CLAHE).The performance of the proposed fusion-based CNN model is measured by various metrics of the fusion and enhancement *** realistic datasets of different modalities and diseases are tested and ***,real datasets are tested in the simulation analysis.

关键词： Image fusion CNN deep learning feature extraction evaluation metrics medical diagnosis

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Continuous Measurement of Respiratory Rate via Single-Wavelength Reflective Photoplethysmography 10

Continuous Measurement of Respiratory Rate via Single-Wavele...

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10th Mediterranean Conference on Embedded Computing, MECO 2021

作者： Protopsaltis, Grizoris Krizea, Maria Gialelis, John University of Patras Electrical and Computer Engineering Dept Greece University of Patras Industrial Systems Institute ATHENARC Electrical and Computer Engineering Dept Patras Greece

ISBN: (纸本)9780738133614

Respiratory rate (RR) is a key bio parameter used in a wide range of clinical settings. Albeit its diagnostic and prognostic value it is still mostly measured manually by counting breaths. Several algorithms have been proposed to estimate RR from the electrocardiogram (ECG) and photoplethysmogram (PPG). These RR algorithms pave the way for automated electronic and unobtrusive measurement of RR in both health care and fitness monitoring. The approach introduced in this work for estimating RR is based on single wavelength reflectance-type PPG through a custom low-power wrist wearable device. © 2021 IEEE.

关键词： Photoplethysmography

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Modeling the effect of bend radius on the performance of a conformal dual-band mmwave patch antenna array

Modeling the effect of bend radius on the performance of a c...

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作者： Umar, Ashraf Abdelatty, Mohamed Y. Obeidat, Abdullah Enakerakpo, Emuobosan Alhendi, Mohammed Poliks, Mark D. Dept. of Electrical and Computer Engineering State University of New York Binghamton United States Dept. of Systems Science and Industrial Engineering State University of New York Binghamton United States

There is growing interest in the use of additive manufacturing for the fabrication of RF devices due to fast prototyping capabilities and the use of less material as opposed to traditional fabrication techniques. In addition to the previously mentioned advantages, the aerosol jet printing method in particular allows for the conformal printing of RF components. This work models the effect of the bend radius on the return loss and radiation pattern of a dual-band (28 GHz and 39 GHz) mm wave patch antenna array design that will be aerosol jet printed. The antenna is modeled on a 5-mil thick flexible substrate (PET) and the simulation is run from 27 GHz to 40 GHz using HFSS. The return loss and radiation pattern results of the antenna are compared for various bend radii (0.25 in to 2 in) of the conformal surface the antenna is to be printed upon. Simulation results show a maximum frequency deviation of about 400 MHz on the return loss for the low (28 GHz) frequency band of the antenna when it is bent from a bend radius of 0 in to 2 in. © 2022 IMAPS-International Microelectronics and Packaging Society. All rights reserved.

关键词： Microstrip antennas

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