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10th International Conference on Vehicle Technology and Intelligent Transport systems, VEHITS 2024

作者： Mu, Zeyu Tu, Guancheng Shi, Austin Yang, Kun Sun, Yixin Shen, Cong Park, B. Brian Department of Systems & Information Engineering University of Virginia CharlottesvilleVA United States Department of Computer Science University of Virginia CharlottesvilleVA United States Department of Electrical & Computer Engineering University of Virginia CharlottesvilleVA United States Departments of Computer Science and Electrical & Computer Engineering University of Virginia CharlottesvilleVA United States Departments of Civil & Environmental Engineering and Systems & Information Engineering University of Virginia CharlottesvilleVA United States

ISBN: (纸本)9789897587030

Preceding vehicle identification is crucial for establishing cooperative platooning. This paper presents the development of a prototype preceding vehicle identification system (PVIS) and its field evaluation for the assessment of commercial viability. We designed and assembled a prototype consisting of a processing unit (Jetson Nano board), a communication device (Wi-Fi dongle), a GPS unit, and a distance measurement sensor (Terabee sensor). The Jetson Nano integrates the SparkFun GPS-RTK-SMA unit, the Terabee time-of-flight sensor, and the Wi-Fi dongle. The PVIS prototype in the ego vehicle measures the distance to its preceding vehicle and receives the GPS data from potential preceding vehicles with the PVIS prototypes. With these, the PVIS in the ego vehicle determines the connectivity of the preceding vehicle. The field evaluation results showed that the prototype PVIS works as designed, and each successful identification takes about 5.3 seconds. However, it was found that the Terabee (time of flight) sensor, at times, did not properly measure distances, likely due to an angle issue caused by the roadway surface and vibration of the vehicle. We discussed how to overcome the challenges identified and enhance the prototype for successful commercialization. Copyright © 2024 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Vehicle to vehicle communications

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Latest Innovations in Intelligent Network-on-Chip Architectures: A Systematic Review 17

Latest Innovations in Intelligent Network-on-Chip Architectu...

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17th IEEE/ACM International Workshop on Network on Chip Architectures, NoCArc 2024

作者： Kakoulli, Elena Neapolis University Pafos Intelligent Systems Laboratory Department of Computer Science Pafos Cyprus Cyprus University of Technology Electrical Engineering and Computer Engineering and Informatics Limassol Cyprus

ISBN: (纸本)9798331506421

This review investigates the latest advancements in intelligent Network-on-Chip (NoC) architectures, focusing on innovations from 2022 to 2024. The integration of Artificial Intelligence (AI) and Machine Learning (ML) into NoC designs has driven significant improvements in performance, scalability, energy efficiency, and security. Key contributions include AI/ML-driven techniques to optimize routing, reduce latency, manage power consumption, and enhancing security against emerging threats. Despite these advancements, challenges such as computational overhead and integration complexities remain. This review consolidates these findings, addresses existing challenges, and proposes future research directions to further leverage AI and ML for developing robust and adaptable NoC architectures. © 2024 IEEE.

关键词： Federated learning

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Controller Placement in Software Defined Internet of Things Using Optimization Algorithm

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Computers, Materials & Continua 2022年第3期70卷 5073-5089页

作者： Sikander Hans Smarajit Ghosh Aman Kataria Vinod Karar Sarika Sharma Department of Electrical and Instrumentation Engineering Thapar Institute of Engineering&TechnologyPatialaIndia Optical Devices and Systems CSIR-Central Scientific Instruments OrganizationSector 30-CChandigarh160030India Department of Electrical Engineering Government PolytechnicAmbala CityAmbala134003India

The current and future status of the internet is represented by the upcoming Internet of Things(IoT).The internet can connect the huge amount of data,which contains lot of processing operations and efforts to transfer the pieces of *** emerging IoT technology in which the smart ecosystem is enabled by the physical object fixed with software electronics,sensors and network ***,there are two trending technologies that take the platform i.e.,Software Defined Network(SDN)and IoT(SD-IoT).The main aim of the IoT network is to connect and organize different objects with the internet,which is managed with the control panel and data panel in the SD *** main issue and the challenging factors in this network are the increase in the delay and latency problem between the *** is more significant for wide area networks,because of the large packet propagation latency and the controller placement problem is more important in every *** the proposed work,IoT is implementing with adaptive fuzzy controller placement using the enhanced sunflower optimization(ESFO)algorithm and Pareto Optimal Controller placement tool(POCO)for the placement problem of the *** order to prove the efficiency of the proposed system,it is compared with other existing methods like PASIN,hybrid SD and PSO in terms of load balance,reduced number of controllers and average latency and *** 2 controllers,the proposed method obtains 400 miles as average latency,which is 22.2%smaller than PSO,76.9%lesser than hybrid SD and 91.89%lesser than PASIN.

关键词： SD-IoT adaptive fuzzy controller enhanced sunflower optimization(ESFO) POCO placement tool controller placement problem and minimum latency

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Liver Ailment Prediction Using Random Forest Model

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Computers, Materials & Continua 2023年第1期74卷 1049-1067页

作者： Fazal Muhammad Bilal Khan Rashid Naseem Abdullah A Asiri Hassan A Alshamrani Khalaf A Alshamrani Samar M Alqhtani Muhammad Irfan Khlood M Mehdar Hanan Talal Halawani Department of Electrical Engineering University of Engineering and TechnologyMardan23200Pakistan City University of Science and Information Technology PeshawarPakistan Department of IT and Computer Science Pak-Austria Fachhochschule Institute of Applied Sciences and TechnologyHaripurPakistan Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajranSaudi Arabia Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajranSaudi Arabia Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia

Today,liver disease,or any deterioration in one’s ability to survive,is extremely common all around the *** research has indicated that liver disease is more frequent in younger people than in older *** the liver’s capability begins to deteriorate,life can be shortened to one or two days,and early prediction of such diseases is *** several machine learning(ML)approaches,researchers analyzed a variety of models for predicting liver disorders in their early *** a result,this research looks at using the Random Forest(RF)classifier to diagnose the liver disease early *** dataset was picked from the University of California,Irvine ***’s accomplishments are contrasted to those of Multi-Layer Perceptron(MLP),Average One Dependency Estimator(A1DE),Support Vector Machine(SVM),Credal Decision Tree(CDT),Composite Hypercube on Iterated Random Projection(CHIRP),K-nearest neighbor(KNN),Naïve Bayes(NB),J48-Decision Tree(J48),and Forest by Penalizing Attributes(Forest-PA).Some of the assessment measures used to evaluate each classifier include Root Relative Squared Error(RRSE),Root Mean Squared Error(RMSE),accuracy,recall,precision,specificity,Matthew’s Correlation Coefficient(MCC),F-measure,and *** has an RRSE performance of 87.6766 and an RMSE performance of 0.4328,however,its percentage accuracy is *** widely acknowledged result of this work can be used as a starting point for subsequent *** a result,every claim that a new model,framework,or method enhances forecastingmay be benchmarked and demonstrated.

关键词： Liver ailment random forest machine learning

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Green Energy Scavenging for Powering Mobile Phones

Green Energy Scavenging for Powering Mobile Phones

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2022 International Telecommunications Conference, ITC-Egypt 2022

作者： Shafiq, Raghda R.G. Elsherbini, M.M. Omara, A.N. Elhalawany, Basem M. Benha University Shoubra Faculty of Engineering Department of Electrical Engineering Egypt Shoubra Faculty of Engineering Department of Electrical Engineering Egypt Computer and Systems Department Egypt

ISBN: (数字)9781665488082

ISBN: (纸本)9781665488082

Egypt Mobile phones have become effective devices for a variety of everyday tasks, but while running large-scale multimedia tasks and the applications such as video games require regular charging of the battery, So significant important technological advances are being made in energy harvesting technology to extend battery life. Ambient energy sources are classified as energy tanks, energy distribution methods, or energy harvesting methods, which may enable portable or wireless systems to be completely battery-independent and self-sustaining. This study provides a comprehensive survey of environmentally friendly energy harvesting methods such as radio frequency (RF), solar energy, and provides a summary of electronic circuits utilized in this field alongside various power sources which are compared concerning voltage and harvested power. © 2022 IEEE.

关键词： Energy harvesting

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Design of a Tube Model Predictive Controller for Pneumatic Muscle Actuators Servomechanism under Uncertainty 10

Design of a Tube Model Predictive Controller for Pneumatic M...

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10th International Conference on Control, Instrumentation and Automation, ICCIA 2024

作者： Zibandehpoor, Mobina Rahmati, Fatemeh Delrobaei, Mehdi Nikoofard, Amirhossein K. N. Toosi University of Technology Faculty of Electrical Engineering Department of Mechatronics Tehran Iran K. N. Toosi University of Technology Faculty of Electrical Engineering Department of Systems and Control Tehran Iran

ISBN: (纸本)9798331509972

Pneumatic muscle actuators (PMAs) are efficient and versatile, mimicking natural muscle-Tendon systems. They are widely used in manufacturing, automotive, and aerospace industries due to their lightweight design, high force-To-weight ratio, and flexibility, making them suitable for delicate tasks and powerful exertions. Their application in industrial and biomechatronic systems highlights their potential to revolutionize automation and human-machine interaction. This research aimed to develop a PMA regulator using the Model Predictive Control (MPC) framework. Researchers identified key PMA characteristics and defined attributes for the regulator, ensuring accurate signal tracking, effective uncertainty handling, and real-Time operation. The initial stages involved implementing a proportional-integral-derived (PID) controller, and by integrating a PID block with a linear MPC block, a tube MPC controller was developed to enhance performance. The controllers' responses were tested in noisy environments using a low-pass filter for evaluation. The tube MPC controller demonstrated optimal control, robustness, and expertise in managing uncertainties, making it a reliable choice for system control. © 2024 IEEE.

关键词： Model predictive control

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Multi-Class Skin Cancer Detection Using Fusion of Textural Features Based CAD Tool

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Computers, Materials & Continua 2024年第12期81卷 4217-4263页

作者： Khushmeen Kaur Brar Bhawna Goyal Ayush Dogra Sampangi Rama Reddy Ahmed Alkhayyat Rajesh Singh Manob Jyoti Saikia Department of Electronics and Communication Engineering Chandigarh UniversityMohali140413India Chitkara University Institute of Engineering and Technology Chitkara UniversityChandigarh140401India Department of Physics&Electronics School of SciencesJAIN(Deemed to be University)Bangalore560001India College of Technical Engineering The Islamic UniversityNajaf54001Iraq Department of Electronics and Communication Engineering Uttaranchal Institute of TechnologyUttaranchal UniversityDehradun248007India Electrical and Computer Engineering Department University of MemphisMemphisTN 38152USA Biomedical Sensors&Systems Lab University of MemphisMemphisTN 38152USA

Skin cancer has been recognized as one of the most lethal and complex types of cancer for over a *** diagnosis of skin cancer is of paramount importance,yet the process is intricate and *** analysis and modeling of human skin pose significant difficulties due to its asymmetrical nature,the visibility of dense hair,and the presence of various substitute *** texture of the epidermis is notably different from that of normal skin,and these differences are often evident in cases of unhealthy *** a consequence,the development of an effective method for monitoring skin cancer has seen little ***,the task of diagnosing skin cancer from dermoscopic images is particularly *** is crucial to diagnose skin cancer at an early stage,despite the high cost associated with the procedure,as it is an expensive ***,the advancement of diagnostic techniques for skin cancer has been *** address this issue,there is a need for a more accurate and efficient method for identifying and categorizing skin cancer *** involves the evaluation of specific characteristics to distinguish between benign and malignant skin cancer *** present and evaluate several techniques for segmentation,categorized into three main types:thresholding,edge-based,and *** techniques are applied to a dataset of 200 benign and melanoma lesions from the Hospital Pedro Hispano(PH2)*** evaluation is based on twelve distinct metrics,which are designed to measure various types of errors with particular clinical ***,we assess the effectiveness of these techniques independently for three different types of lesions:melanocytic nevi,atypical nevi,and *** first technique is capable of classifying lesions into two categories:atypical nevi and melanoma,achieving the highest accuracy score of 90.00%with the Otsu(3-level)*** second technique also classifies lesions int

关键词： Melanoma computer-aided diagnosis segmentation PH2 ISIC(International Skin Imaging Collaboration) dermoscopy non-melanoma

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Adaptive Event-Triggered Fast Finite-Time Stabilization of High-Order Uncertain Nonlinear systems and its Application in Maglev systems

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IEEE Transactions on Cybernetics 2024年第3期54卷 1537-1546页

作者： Sun, Zong-Yao Zhou, Chao Wen, Changyun Chen, Chih-Chiang Institute of Automation Qufu Normal University Qufu273165 China Nanjing University of Aeronautics and Astronautics College of Automation Engineering Nanjing211106 China Nanyang Technological University School of Electrical and Electronic Engineering Jurong West639798 Singapore National Cheng Kung University Department of Systems and Naval Mechatronic Engineering Tainan70101 Taiwan

This article is concerned with the global fast finite-time adaptive stabilization for a class of high-order uncertain nonlinear systems in the presence of serious nonlinearities and constraint communications. By renovating the technique of continuous feedback domination to the construction of a serial of integral functions with nested sign functions, this article first proposes a new event-triggered strategy consisting of a sharp triggered rule and a time-varying threshold. The strategy guarantees the existence of the solutions of the closed-loop systems and the fast finite-time convergence of original system states while reaching a compromise between the magnitude of the control and the trigger interval. Quite different from traditional methods, a simple logic is presented to avoid searching all the possible lower bounds of trigger intervals. An example of the maglev system and a numerical example are provided to demonstrate the effectiveness and superiority of the proposed strategy. © 2013 IEEE.

关键词： Closed loop systems

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Internet of Energy for Energy Management of Interconnected Local Energy Communities: Case Study in BAM Campus - The Netherlands 24

Internet of Energy for Energy Management of Interconnected L...

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24th EEEIC International Conference on Environment and electrical engineering and 8th I and CPS Industrial and Commercial Power systems Europe, EEEIC/I and CPS Europe 2024

作者： Tran, Trung Thai Van Der Pijl, A.A. Huu Nguyen, An Thien Ngo, Minh-Duc Nguyen, P.H. Eindhoven Institute for Renewable Energy Systems Eindhoven University of Technology Eindhoven Netherlands Eindhoven University of Technology Department of Electrical Engineering Eindhoven Netherlands Thai Nguyen University of Technology Department of Electrical Engineering Thai Nguyen Viet Nam

ISBN: (纸本)9798350355185

The advent of renewable energy sources has progressively diminished reliance on fossil fuels. However, existing power grids were not designed to accommodate bi-directional power flows, leading to increasing concerns over technical challenges such as congestion, voltage violations, etc. Emerging technologies such as the Internet of Energy and Local Energy Communities (LECs) present viable solutions to these challenges. This paper proposes a IoE framework, focusing on power profile prediction for day-ahead optimization and real-time power control of LECs. The proposed framework explores how LECs can comply with technical constraints while maximizing self-sufficiency through objective functions. The developed model and subsequent simulations demonstrate the significant potential of LECs, from providing balancing services to elucidating the technical and economic impacts of integrating LECs into an interconnected network. Furthermore, the paper highlights the economic benefits of incorporating technologies like batteries and photovoltaic (PV) systems within LECs, offering substantial financial advantages to owners. The presented model serves as a foundational step in LEC research, outlining current possibilities and future avenues for exploration and development. © 2024 IEEE.

关键词： Congestion and Voltage Violation Day-ahead optimization Internet of Energy Local Energy Community

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Mitigating Sub-Synchronous Resonance with Adaptive Phase-Dependent Switching in Static Sub Synchronous Series Compensator

Mitigating Sub-Synchronous Resonance with Adaptive Phase-Dep...

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2024 IEEE Global Energy Conference, GEC 2024

作者： Shahzad, Sulman Alsenani, Theyab R. Kilic, Heybet Department of Electrical Engineering Islamia University of Bahawalpur Bahawalpur63100 Pakistan Department of Electrical Engineering College of Engineering in Al-Kharj Prince Sattam Bin Abdulaziz University Al-Kharj11942 Saudi Arabia Department of Electric Power and Energy Systems Dicle University Diyarbakır21280 Turkey

ISBN: (纸本)9798331532611

Sub-synchronous resonance (SSR) is a critical challenge in power systems, particularly in series-compensated transmission lines, where interactions between electrical and mechanical components can lead to damaging oscillations. The Static Synchronous Series Compensator (SSSC), a FACTS device, has proven effective in mitigating SSR by injecting controllable series voltage to modify line impedance dynamically. However, conventional SSSC control strategies, often based on proportional-integral (PI) controllers, can exhibit limited responsiveness during transient disturbances. This paper explores the enhancement of SSSC performance through Phase-Dependent Switching (PDS), an adaptive technique that modifies switching behavior based on real-time phase conditions. Using detailed time-domain simulations, we demonstrate that the PDS-enhanced SSSC achieves faster transient response, better damping of oscillations, and improved stability margins compared to traditional methods. The results also highlight challenges such as increased switching losses and computational demands, necessitating further research into optimized algorithms and hardware solutions. These findings underscore the potential of PDS in improving SSR damping, ensuring more reliable and efficient power system operation. ©2024 IEEE.

关键词： Damping

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