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An Optimized Offloaded Task Execution for Smart Cities Applications

computers, Materials & Continua 2023年第3期74卷 6321-6334页

作者： Ahmad Naseem Alvi Muhammad Awais Javed Mozaherul Hoque Abul Hasanat Muhammad Badruddin Khan Abdul Khader Jilani Saudagar Mohammed Alkhathami Department of Electrical and Computer Engineering COMSATS University Islamabad45550Pakistan Information Systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia

Wireless nodes are one of the main components in different applications that are offered in a smart *** wireless nodes are responsible to execute multiple tasks with different priority *** the wireless nodes have limited processing capacity,they offload their tasks to cloud servers if the number of tasks exceeds their task processing *** these tasks from remotely placed cloud servers causes a significant delay which is not required in sensitive task *** execution delay is reduced by placing fog computing nodes near these application nodes.A fog node has limited processing capacity and is sometimes unable to execute all the requested *** this work,an optimal task offloading scheme that comprises two algorithms is proposed for the fog nodes to optimally execute the time-sensitive offloaded *** first algorithm describes the task processing criteria for local computation of tasks at the fog nodes and remote computation at the cloud *** second algorithm allows fog nodes to optimally scrutinize the most sensitive tasks within their task *** results show that the proposed task execution scheme significantly reduces the execution time and most of the time-sensitive tasks are executed.

关键词： Smart cities fog computing task offloading knapsack

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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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Using Interim Recommitment to Reduce the Operational-cost Impacts of Wind Uncertainty

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Journal of Modern Power systems and Clean Energy 2022年第4期10卷 839-849页

作者： Mahan A.Mansouri Ramteen Sioshansi Department of Integrated Systems Engineering The Ohio State UniversityColumbusOH 43210USA Department of Integrated Systems Engineering Department of Electrical and Computer Engineeringand Center for Automotive ResearchThe Ohio State UniversityColumbusOH 43210USA

Using wind-availability forecasts in day-ahead unit commitment can require expensive real-time operational *** examine the benefit of conducting interim recommitment between day-ahead unit commitment and real-time *** a simple stylized example and a case study that is based on ISO New England,we compare system-operation costs with and without interim *** find an important tradeoff—later recommitment provides better wind-availability forecasts,but the system has less flexibility due to operating *** the time windows that we examine,hour-20 recommitment provides the greatest operational-cost reduction.

关键词： Power-system operation power-system economics unit commitment economic dispatch wind generation.

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A machine learning approach for skin lesion classification on iOS: implementing and optimizing a convolutional transfer learning model with Create ML

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International Journal of computers and Applications 2024年第8期46卷 666-685页

作者： Benedek Szabo, Aron Katona, Jozsef Department of Software Development and Application Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Department of Instrumentation and Automation Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary Department of Informatics GAMF Faculty of Engineering and Computer Science Kecskemét Hungary

The integration of machine learning (ML) into mobile applications presents unique challenges, particularly in resource-constrained environments such as iOS devices. Skin lesion classification is a critical task in dermatology, where accurate and efficient diagnostic tools can significantly aid in early detection of malignant lesions. This study aims to implement a machine learning-based iOS mobile application and develop a binary classification model for skin lesion images to determine whether a lesion is malignant. The research utilized Create ML to develop a convolutional neural network optimized for iOS, employing a transfer learning approach. A logistic regression model was cascaded with the convolutional neural network N to enhance classification accuracy. The model's performance was assessed through various validation metrics, ensuring its robustness and efficiency within the constraints of mobile hardware. A curated dataset from the International Skin Imaging Collaboration archive was used for training and testing. The model achieved an accuracy of 92%, a precision of 90%, a recall of 93%, and an F1-score of 91% in classifying skin lesions. These metrics validate the model's efficacy in identifying malignant lesions. Data curation involved collecting, labeling, and preparing a dataset from publicly available sources, ensuring the inclusion of diagnostically relevant features. The final model was integrated into an iOS application using Core ML and Vision frameworks. The developed application demonstrates reliable performance in classifying skin lesions with high accuracy on iOS devices. The inclusion of comprehensive performance metrics justifies the efficacy of the proposed approach. Future work will explore enhancements in model architecture and object detection capabilities to further improve diagnostic precision and application usability. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Image recognition

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Receding horizon optimization for distributed control of electric vehicle charging stations

Receding horizon optimization for distributed control of ele...

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2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Malkova, Anna Zepter, Jan Martin Marinelli, Mattia Amezquita, Herbert Morais, Hugo Technical University of Denmark Department of Wind and Energy Systems Roskilde Denmark Department of Electrical and Computer Engineering Lisbon Portugal

ISBN: (纸本)9789531842976

With the continuous increase of electric vehicle (EV) adoption, deploying smart charging techniques offer a practical solution to mitigate the impact of grid overloading caused by simultaneous EV charging. At the same time, smart charging can help to stabilize the fluctuations in the production from local renewable energy sources (RES). This article introduces a receding horizon optimization model for the distributed control of EV chargers at charging stations, focusing on maximizing the profit of the charging station, while enhancing the utilization of local PV generation. The proposed model operates in 5-minute intervals, determining the power reference for the EV cluster at the charging station. Results demonstrate that the proposed model effectively lowers electricity cost for charging stations, while ensuring more than 90% energy delivery for charging EVs. Future research will be focused on integrating wind energy and refining the model in controlled lab tests for practical implementation and validation. © 2024 IEEE.

关键词： Charging stations

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Integrated preparation and manipulation of high‑dimensional flying structured photons

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eLight 2024年第1期4卷 185-192页

作者： Haoqi Zhao Yichi Zhang Zihe Gao Jieun Yim Shuang Wu Natalia MLitchinitser Li Ge Liang Feng Department of Electrical and Systems Engineering University of PennsylvaniaPhiladelphiaPA 19104USA Department of Materials Science and Engineering University of PennsylvaniaPhiladelphiaPA 19104USA Department of Electrical and Computer Engineering and Department of Physics Duke UniversityDurhamNC 27708USA Department of Engineering Science and Physics College of Staten IslandCUNYStaten IslandNY 10314USA The Graduate Center CUNYNew YorkNY 10016USA

The hope for a futuristic global quantum internet that provides robust and high-capacity quantum information transfer lies largely on qudits,the fundamental quantum information carriers prepared in high-dimensional superposition ***,preparing and manipulating N-dimensional flying qudits as well as subsequently establishing their entanglement are still challenging tasks,which require precise and simultaneous maneuver of 2(N-1)parameters across multiple degrees of ***,using an integrated approach,we explore the synergy from two degrees of freedom of light,spatial mode and polarization,to generate,encode,and manipulate flying structured photons and their formed qudits in a four-dimensional Hilbert space with high quantum fidelity,intrinsically enabling enhanced noise resilience and higher quantum data *** four eigen spin–orbit modes of our qudits possess identical spatial–temporal characteristics in terms of intensity distribution and group velocity,thereby preserving long-haul coherence within the entirety of the quantum data transmission *** leveraging the bi-photon entanglement,which is well preserved in the integrated manipulation process,we present versatile spin–orbit cluster states in an extensive dimensional Hilbert *** cluster states hold the promise for quantum error correction which can further bolster the channel robustness in long-range quantum communication.

关键词： cluster thereby preparing

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A novel deep learning approach for automated grading of knee osteoarthritis severity

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Multimedia Tools and Applications 2024年 1-20页

作者： Kaur, PrabSimran Kohli, Guneet Singh Bedi, Jatin Wasly, Saud Department of Computer Science and Engineering Thapar Institute of Engineering and Technology Punjab Patiala India Electrical and Computer Engineering Department King Abdulaziz University Jeddah22254 Saudi Arabia Center of Excellence in Intelligent Engineering Systems King Abdulaziz University Jeddah22254 Saudi Arabia

Knee Osteoarthritis (OA) is a prevalent musculoskeletal disorder that affects the knee joint that causes pain, stiffness, and reduced mobility. It is also known as "Degenerative Joint Disease" and is caused by the degeneration of cartilage in the knee joint, leading to bone-on-bone contact and further damage. Knee OA is prevalent in the population, affecting around 22% to 39% of people in India, and there is currently no treatment available that can halt the progression of the disease. Therefore, early diagnosis and management of symptoms are essential to reduce its impact on an individual’s quality of life. To address this issue, have introduced a framework that leverages ConvNeXt architecture, a modernization of ResNets (ResNet-50) architecture towards Hierarchical Transformers (Swin Transformers), to provide accurate identification and classification of knee osteoarthritis. The classification of knee osteoarthritis was done using the Kellgren and Lawrence (KL) graded X-ray images. These images of the damaged knees are preprocessed and augmented, creating a scaled, enhanced, and varied version of the features, thus making the data fitter and more significant for classification. The performance estimation of the proposed strategy is conducted on the Osteoarthritis Initiative (OAI), a research project focused on knee osteoarthritis that works in partnership with NIH and other private industries to develop a public domain dataset that can facilitate research and evaluation. It involves training the prepared data using various hyper-tuned versions of ConvNeXt. The different fine-tuned results of the ConvNeXt models on each KL Grade are evaluated against the other state-of-the-art models and vision transformers. The comparative assessment of widely used performance measures shows that the proposed approach outperforms the conventional models by generating the highest score for all the KL grades. Lastly, an approach is employed to statistically confirm the validity of t

关键词： Joints (anatomy)

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Intelligent Dynamic Inversion Controller Design for Ball and Beam System

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computers, Materials & Continua 2022年第8期72卷 2341-2355页

作者： Ibrahim M.Mehedi Abdulah Jeza Aljohani Md Mottahir Alam Mohamed Mahmoud Mohammed J.Abdulaal Muhammad Bilal Waleed Alasmary Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia Electrical and Computer Engineering Electrical and Computer EngineeringTN38505United States Computer and Information Systems Umm Al-Qura UniversityMakkahSaudi Arabia

The Ball and beam system(BBS)is an attractive laboratory experimental tool because of its inherent nonlinear and open-loop unstable *** an effective ball and beam system controller is a real challenge for researchers and *** this paper,the control design technique is investigated by using Intelligent Dynamic Inversion(IDI)method for this nonlinear and unstable *** proposed control law is an enhanced version of conventional Dynamic Inversion control incorporating an intelligent control element in *** Moore-PenroseGeneralized Inverse(MPGI)is used to invert the prescribed constraint dynamics to realize the baseline control law.A sliding mode-based intelligent control element is further augmented with the baseline control to enhance the robustness against uncertainties,nonlinearities,and external *** semi-global asymptotic stability of IDI control is guaranteed in the sense of *** simulations and laboratory experiments are carried out on this ball and beam physical system to analyze the effectiveness of the *** addition to that,comparative analysis of RGDI control with classical Linear Quadratic Regulator and Fractional Order Controller are also presented on the experimental test bench.

关键词： Ball and beam system(BBS) unstable system internal model PD controllers IDI control robust control

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FPGA-based UWB Pulse Generator for IR-UWB Chipless RFID Reader 6

FPGA-based UWB Pulse Generator for IR-UWB Chipless RFID Read...

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6th Australian Microwave Symposium, AMS 2025

作者： Lasantha, Likitha Aliasgari, Javad Khan, Shahed I. Ray, Biplob Karmakar, Nemai C. Monash University Department of Electrical and Computer Systems Engineering Clayton Australia Central Queensland University School of Engineering and Technology Melbourne Australia

ISBN: (纸本)9798350379969

Ultra-wideband (UWB) technology has gained traction for applications demanding high bandwidth, precise target localisation, and low power consumption. This paper presents an FPGA-based UWB pulse generator tailored for an Impulse-radio (IR) UWB chipless RFID reader. Using a low-cost FPGA platform, the design generates a square wave signal with a pulse repetition frequency (PRF) of 1-50 MHz. This base signal undergoes pulse sharpening to produce picosecond-scale pulses, achieving the bandwidth exceeding 500 MHz necessary for UWB communication. Such a high-bandwidth signal ensures better range resolution, meeting the requirements of applications of UWB chipless RFID readers. By implementing pulse generation and PRF control on an FPGA, our system combines low cost, flexibility, and scalability, making it suitable for diverse UWB applications. © 2025 IEEE.

关键词： Ultra-wideband (UWB)

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Near-Optimal Scheduling for IC Packaging Operations Considering Processing-Time Variations and Factory Practices

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IEEE Robotics and Automation Letters 2024年第4期9卷 3878-3885页

作者： Tsai, Tsung-Han Yan, Bing Luh, Peter B. Yang, Haw-Ching Bragin, Mikhail A. Cheng, Fan-Tien National Cheng Kung University Institute of Manufacturing Information and Systems Tainan701401 Taiwan Rochester Institute of Technology Department of Electrical and Microelectronic Engineering RochesterNY14623 United States University of Connecticut Department of Electrical and Computer Engineering StorrsCT06269 United States National Taiwan University Department of Electrical Engineering Taipei106329 Taiwan National Kaohsiung University of Science and Technology Department of Electrical Engineering Kaohsiung824005 Taiwan University of California Department of Electrical and Computer Engineering RiversideCA92507 United States

Due to the short life cycles of electronic products, trial run lots of new products are crucial in IC packaging for production verification and engineering adjustments. The processing time of trial run lots may differ significantly from production lots due to engineering adjustments and is difficult to predict without sufficient historical data. The purpose of this letter is to develop a framework for near-optimal scheduling of IC packaging considering processing time variations and factory practices. Using an orthogonal greedy algorithm and recurrent neural network, this framework extracts key features and predicts the processing times of trial run lots and production lots for each operation using these algorithms. After formulating the scheduling problem in an integer linear programming form, an ordinal optimization method is embedded within the decomposition and coordination framework to obtain dynamic and near-optimal schedules in a computationally efficient manner. This approach can improve the efficiency of IC packaging and potentially other operations by optimizing lot scheduling, reducing production tardiness, and increasing productivity in the factory, paving the way for self-optimizing factories in the future. © 2016 IEEE.

关键词： Integer programming

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