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2nd IEEE International Conference on Advances in Computing, Communication and Applied Informatics, ACCAI 2023

作者： Chitra Kiran, N. Parkash, Jai Cheerla, Sreevardhan Shanmugaraja, P. Manohara, M. Madan, Parul Alliance University Department of Electronics and Communication Engineering Karnataka Bangalore560068 India Gulzar Group of Institutes Department of Computer Science and Engineering Punjab Khanna141401 India Koneru Lakshmaiah Education Foundation Department of Electronics and Communications Engineering Andhra Pradesh Vaddeswaram522302 India Sona College of Technology Department of Information Technology Tamil Nadu Salem636005 India Mohan Babu University School of Engineering Andhra Pradesh Tirupati517102 India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttarakhand Dehradun248002 India

ISBN: (纸本)9798350315905

As the Web of Things (IoT) has created throughout recent years, unlicensed radio range has become more clogged with brilliant wireless gadgets that are utilized in an assortment of use spaces, prominently the 2.4 GHz ISM band. One of the easiest and most productive answers for energy-compelled networks is the wake-up receiver (WuRx). Rather than utilizing a conventional radio, this innovation empowers energy-independent on-request communication for persistent observing. One of the WSN methods that utilizes the most investment is directing. Consequently, planning an energy-effective steering procedure is fundamental. This exploration proposes Grouped WuRx based on Multicast wake-up (CWM), a progressive Wake-up Receiver-based directing convention that all the while streamlines energy use and time productivity for indoor conditions. In our proposed technique, bunches are made inside the organization. Estimation discoveries show that, in contrast with past directing conventions, our proposed arrangement has much better execution as far as conveyance delay and further developed energy effectiveness. © 2023 IEEE.

关键词： Wireless sensor networks

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A Photovoltaic Electric Vehicle Automatic Charging and Monitoring System 6

A Photovoltaic Electric Vehicle Automatic Charging and Monit...

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6th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2022

作者： Niu, Yitong Habeeb, Fadya A. Mansoor, Muneer Sameer Gheni Gheni, Hassan Muwafaq Ahmed, Saadaldeen Rashid Radhi, Ahmed Dheyaa School of Aeronautical Engineering AnYang University Anyang China College of Education for Women Tikrit University Department of Mathematics Iraq Department of Mobile Communications and Computing Engineering Baghdad Iraq Mustaqbal University College Computer Techniques Engineering Department Hillah Iraq Computer Science Computer Engineering Tikrit University Iraq Karabuk University Turkey College of Pharmacy University of Al-Ameed PO Box 198 Karbala Iraq

ISBN: (数字)9781665470131

ISBN: (纸本)9781665470131

This paper researches and designs an automatic charging control and monitoring system for PV electric vehicle batteries, which can automatically charge the low-voltage and high-voltage batteries by obtaining the operation mode of PV electric vehicles, avoiding battery maintenance to the maximum extent, preventing damage to the battery cell caused by over-discharge, and increasing the range of the whole vehicle. Suppose the PV EV is in parking mode. In that case, it will obtain the power of the low-voltage battery in real-Time and charge the low-voltage battery according to the request, and then it will obtain the power of the high-voltage battery and send a power-up request to charge the high-voltage battery according to the request;if the PV EV is in driving mode, it will obtain the power of the low-voltage battery in real-Time and generate a power-up request according to the power-up request. When the PV electric vehicle is in driving mode, it will obtain the low voltage battery power condition in real-Time and send a request to recharge the low voltage battery. © 2022 IEEE.

关键词： Electric vehicles

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Efficient Frameworks for EEG Epileptic Seizure Detection and Prediction

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Annals of Data Science 2022年第2期9卷 393-428页

作者： Emara, Heba M. Elwekeil, Mohamed Taha, Taha E. El-Fishawy, Adel S. El-Rabaie, El-Sayed M. El-Shafai, Walid El Banby, Ghada M. Alotaiby, Turky Alshebeili, Saleh A. Abd El-Samie, Fathi E. Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Security Engineering Laboratory Department of Computer Science Prince Sultan University Riyadh11586 Saudi Arabia Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt KACST Riyadh Saudi Arabia King Saud University Riyadh Saudi Arabia Department of Electrical Engineering King Saud University Riyadh11421 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh21974 Saudi Arabia

Seizure detection and prediction are a very hot topics in medical signal processing due to their importance in automatic medical diagnosis. This paper presents three efficient frameworks for applications related to electroencephalogram (EEG) signal processing. The first one is an automatic seizure detection framework based on the utilization of scale-invariant feature transform (SIFT) as an extraction tool. The second one depends on the utilization of the fast Fourier transform (FFT) and an artificial neural network for epileptic seizure prediction. Finally, an automated patient-specific framework for channel selection and seizure prediction is presented based on FFT. The simulation results show the success of the proposed frameworks for automated medical diagnosis. © 2021, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Fast Fourier transforms

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Effect of the Longitudinal Strain of PM Fiber on the Signal Group Velocity 3rd

Effect of the Longitudinal Strain of PM Fiber on the Signal ...

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3rd International Conference on Machine Learning, Internet of Things and Big Data, ICMIB 2023

作者： Slavicek, Karel Grenar, David Vavra, Jiri Kyselak, Martin Radil, Jan Frolka, Jakub Masaryk University Brno Czech Republic Department of Telecommunications Faculty of Electrical Engineering and Communications Brno University of Technology Brno Czech Republic University of Defence Czech Republic Department of Computer Science Faculty of Science University of South Bohemia in Ceske Budejovice Ceske Budejovice Czech Republic

ISBN: (纸本)9789819939312

The polarization of the light can be used as the core principle of fiber optic sensors. One of the physical quantities which can be detected or measured this way is the longitudinal tension of the fiber. A set of measurements leading to approval of the suitability of polarization for this purpose was performed. This paper analyzes the dependency of differential group delay of the signal in slow and fast axes of the birefringent optical fiber on the longitudinal tension. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Polarization

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Investigating Positive and Negative Qualities of Human-in-the-Loop Optimization for Designing Interaction Techniques 22

Investigating Positive and Negative Qualities of Human-in-th...

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2022 CHI Conference on Human Factors in Computing Systems, CHI 2022

作者： Chan, Liwei Liao, Yi-Chi Mo, George B Dudley, John J Cheng, Chun-Lien Kristensson, Per Ola Oulasvirta, Antti Department of Computer Science National Yang Ming Chiao Tung University Taiwan Department of Communications and Networking Aalto University Finland Department of Engineering University of Cambridge United Kingdom

ISBN: (纸本)9781450391573

Designers reportedly struggle with design optimization tasks where they are asked to find a combination of design parameters that maximizes a given set of objectives. In HCI, design optimization problems are often exceedingly complex, involving multiple objectives and expensive empirical evaluations. Model-based computational design algorithms assist designers by generating design examples during design, however they assume a model of the interaction domain. Black box methods for assistance, on the other hand, can work with any design problem. However, virtually all empirical studies of this human-in-the-loop approach have been carried out by either researchers or end-users. The question stands out if such methods can help designers in realistic tasks. In this paper, we study Bayesian optimization as an algorithmic method to guide the design optimization process. It operates by proposing to a designer which design candidate to try next, given previous observations. We report observations from a comparative study with 40 novice designers who were tasked to optimize a complex 3D touch interaction technique. The optimizer helped designers explore larger proportions of the design space and arrive at a better solution, however they reported lower agency and expressiveness. Designers guided by an optimizer reported lower mental effort but also felt less creative and less in charge of the progress. We conclude that human-in-the-loop optimization can support novice designers in cases where agency is not critical. © 2022 ACM.

关键词： Multiobjective optimization

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Human Activity Recognition Using Feedforward Backpropagation Neural Network

Human Activity Recognition Using Feedforward Backpropagation...

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International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)

作者： Fadi Al Debs Makram El Jurdy Elias Fares Gaby Abou Haidar Michel Owayjan Roger Achkar Department of Computer and Communications Engineering American University of Science and Technology Beirut Lebanon Department of Mechatronics Engineering American University of Science and Technology Beirut Lebanon

ISBN: (数字)9798331533137

ISBN: (纸本)9798331533144

This paper presents a feedforward backpropagation neural network designed to recognize human activities using loT sensor data. Human activity recognition based on mobile phones and wearable sensor data has garnered significant attention due to its wide range of applications in healthcare., smart environments., and beyond. Previous studies in this field have utilized various sensors., such as accelerometers., gyroscopes., and orientation sensors., among others., to categorize human activities using modern wearable technologies. The proposed system employs a Human Activity Recognition framework., which collects real-time sensor data and analyzes human movements using deep learning techniques. The model achieves an accuracy of approximately 96% in identifying human motions based on the sensor data.

关键词： Backpropagation Technological innovation Medical services Real-time systems Mobile handsets Feedforward neural networks Gyroscopes Human activity recognition Informatics Wearable sensors

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IoT-Based Smart Radiation Measuring System

IoT-Based Smart Radiation Measuring System

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Advances in Science and engineering Technology International Conferences (ASET)

作者： Tarig Faisal Moath Awawdeh Anees Bashir Abdel Ilah N. Alshbatat Department of Electrical Engineering Higher Colleges of Technology Abu Dhabi UAE Department of Communications Electronics and Computer Engineering Tafila Technical University Tafila Jordan

ISBN: (数字)9798350344134

ISBN: (纸本)9798350344141

In this paper we suggest an approach towards developing autonomous model for radiation measurement monitoring for remote area. The approach considers the involvement of Unmanned Aerial Vehicle (UAV) equipped with radiation detector sensors to detect gamma radiation along with geographical information system. A framework of data collection, monitoring and analysis is provided and with a guideline on implementation. A real-time measurement monitoring pipeline is considered along with radiation mapping and suggested data management system.

关键词： Radiation detectors Pipelines Autonomous aerial vehicles Sensor systems Real-time systems Data mining Monitoring Intelligent sensors Guidelines Geographic information systems

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Computational Intelligence Driven Secure Unmanned Aerial Vehicle Image Classification in Smart City Environment

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computer Systems Science & engineering 2023年第12期47卷 3127-3144页

作者： Firas Abedi Hayder M.A.Ghanimi Abeer D.Algarni Naglaa F.Soliman Walid El-Shafai Ali Hashim Abbas Zahraa H.Kareem Hussein Muhi Hariz Ahmed Alkhayyat Department of Mathematics College of EducationAl-Zahraa University forWomenKarbalaIraq Biomedical Engineering Department College of EngineeringUniversity ofWarith Al-AnbiyaaKarbalaIraq Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt College of Information Technology Imam Jaafar Al-Sadiq UniversityAl-Muthanna66002Iraq Department of Medical Instrumentation Techniques Engineering Al-Mustaqbal University CollegeHillah51001Iraq Computer Engineering Department Mazaya University CollegeDhi QarIraq College of Technical Engineering The Islamic UniversityNajafIraq

Computational intelligence(CI)is a group of nature-simulated computationalmodels and processes for addressing difficult real-life *** CI is useful in the UAV domain as it produces efficient,precise,and rapid ***,unmanned aerial vehicles(UAV)developed a hot research topic in the smart city *** the benefits of UAVs,security remains a major challenging *** addition,deep learning(DL)enabled image classification is useful for several applications such as land cover classification,smart buildings,*** paper proposes novel meta-heuristics with a deep learning-driven secure UAV image classification(MDLS-UAVIC)model in a smart city *** purpose of the MDLS-UAVIC algorithm is to securely encrypt the images and classify them into distinct class *** proposedMDLS-UAVIC model follows a two-stage process:encryption and image *** encryption technique for image encryption effectively encrypts the UAV ***,the image classification process involves anXception-based deep convolutional neural network for the feature extraction ***,shuffled shepherd optimization(SSO)with a recurrent neural network(RNN)model is applied for UAV image classification,showing the novelty of the *** experimental validation of the MDLS-UAVIC approach is tested utilizing a benchmark dataset,and the outcomes are examined in various *** achieved a high accuracy of 98%.

关键词： Computational intelligence unmanned aerial vehicles deep learning metaheuristics smart city image encryption image classification

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SAGIN-4C-6G: A Space-Air-Ground Integrated Network for Enhanced Communication, Computation, Caching and Control in 6G

SAGIN-4C-6G: A Space-Air-Ground Integrated Network for Enhan...

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IEEE Conference on Wireless communications and Networking

作者： Junyu Liu Min Sheng Di Zhou Zhu Han Mohamed-Slim Alouini Wei Wang The State Key Laboratory of ISN Xidian University Xi'an Shaanxi China Electrical and Computer Engineering Department The University of Houston USA Electrical and Computer Engineering Computer KAUST Kingdom of Saudi Arabia China Mobile Communications Group Shaanxi Co. Ltd.

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Space-air-ground integrated networks (SAGINs) hold great promise in delivering ubiquitous aerial access, effectively meeting the demands for large-coverage on-demand services. Moreover, in 6G networks, the integration of Communication, Computation, Caching, and Control (4C) enables seamless connectivity, efficient data processing, optimized content delivery, and intelligent decision-making for next-generation services. However, various components like unmanned aerial vehicles (UAVs), high-altitude platforms (HAPs), satellites, and terrestrial networks each face distinct limitations. In this demo, we first showcase a SAGIN-4C-6G platform capable of establishing a high-capacity backhaul link to the core network while ensuring stable and continuous coverage. Experiments demonstrate that the proposed platform can deliver high-speed, on-demand air-to-ground (A2G) coverage with wireless backhaul, extending over an area of up to 100 km 2 . Beyond communication enhancement and optimization control, we also illustrate the potential for computation and caching services by deploying the proposed SAGIN platform.

关键词： 6G mobile communication Wireless communication Satellites Decision making Space-air-ground integrated networks Air to ground communication Optimization Next generation networking Faces Backhaul networks

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Evaluating the Reliability of Integer Multipliers With Respect to Permanent Faults

Evaluating the Reliability of Integer Multipliers With Respe...

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IEEE Design and Diagnostics of Electronic Circuits and Systems (DDECS)

作者： Nikolaos I. Deligiannis Riccardo Cantoro Matteo Sonza Reorda S. E. D. Habib Department of Control and Computer Engineering (DAUIN) Politecnico di Torino Turin Italy Department of Electronics and Electrical Communications Engineering Cairo University Giza Egypt

Arithmetic circuits form the foundation of modern digital computation, enabling us to conduct precise mathematical operations and drive the digital age. They are integral components in nearly every digital circuit, such as processors' arithmetic and logic units. Especially in safety-critical domains like automotive and aviation, the flawless operation of these circuits is of paramount importance. This paper presents a case study involving two variants of Dadda multipliers and assesses their intrinsic reliability when affected by permanent hardware faults. We conducted extensive fault injection campaigns on the circuit models under various datasets, presenting the aggregated statistical errors in the form of the mean absolute error (MAE) for each case. Specifically, we performed fault injection campaigns in which the operands are sourced from trained quantized weights of a convolutional neural network, as well as randomly generated sets of integers. The results not only reveal differences between the two circuits but also show significant variations when different datasets are used in the fault injection campaigns.

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