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Optimized Deep Learning Approach for Efficient Diabetic Retinopathy Classification Combining VGG16-CNN

computers, Materials & Continua 2023年第11期77卷 1855-1872页

作者： Heba M.El-Hoseny Heba F.Elsepae Wael A.Mohamed Ayman S.Selmy Department of Computer Science the Higher Future Institute for Specialized Technological StudiesObour11828Egypt Department of Electrical Engineering Benha Faculty of EngineeringBenha UniversityBenha13511Egypt

Diabetic retinopathy is a critical eye condition that,if not treated,can lead to vision *** methods of diagnosing and treating the disease are time-consuming and ***,machine learning and deep transfer learning(DTL)techniques have shown promise in medical applications,including detecting,classifying,and segmenting diabetic *** advanced techniques offer higher accuracy and *** Diagnosis(CAD)is crucial in speeding up classification and providing accurate disease ***,these technological advancements hold great potential for improving the management of diabetic *** study’s objective was to differentiate between different classes of diabetes and verify the model’s capability to distinguish between these *** robustness of the model was evaluated using other metrics such as accuracy(ACC),precision(PRE),recall(REC),and area under the curve(AUC).In this particular study,the researchers utilized data cleansing techniques,transfer learning(TL),and convolutional neural network(CNN)methods to effectively identify and categorize the various diseases associated with diabetic retinopathy(DR).They employed the VGG-16CNN model,incorporating intelligent parameters that enhanced its *** outcomes surpassed the results obtained by the auto enhancement(AE)filter,which had an ACC of over 98%.The manuscript provides visual aids such as graphs,tables,and techniques and frameworks to enhance *** study highlights the significance of optimized deep TL in improving the metrics of the classification of the four separate classes of *** manuscript emphasizes the importance of using the VGG16CNN classification technique in this context.

关键词： No diabetic retinopathy(NDR) convolution layers(CNV layers) transfer learning data cleansing convolutional neural networks a visual geometry group(VGG16)

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Traction power substation balance and losses estimation in AC railways using a power transfer device through Monte Carlo analysis

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Railway engineering Science 2022年第1期30卷 71-95页

作者： Vitor A.Morais Antonio P.Martins Department of Electrical and Computer Engineering Faculty of EngineeringUniversity of PortoPorto 4200465Portugal

The high dynamic power requirements present in modern railway transportation systems raise research challenges for an optimal operation of railway electrification. This paper presents a Monte Carlo analysis on the application of a power transfer device installed in the neutral zone and exchanging active power between two sections. The main analyzed parameters are the active power balance in the two neighbor traction power substations and the system power losses. A simulation framework is presented to comprise the desired analysis and a universe of randomly distributed scenarios are tested to evaluate the effectiveness of the power transfer device system. The results show that the density of trains and the relative branch length of a traction power substation should be considered in the evaluation phase of the best place to install a power transfer device, towards the reduction of the operational power losses, while maintaining the two substations balanced in terms of active power.

关键词： Electric traction systems Monte Carlo analysis Power transfer device Power quality Railway power systems Smart railways

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Development of a Smart Shoe for Blind and Visual Impaired People

Development of a Smart Shoe for Blind and Visual Impaired Pe...

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2024 International Conference on engineering and Computing, ICECT 2024

作者： Ramzan, Aneeqa Mustafa, Rafay Kamran, Yashfa NUTECH Department of Electrical Engineering Islamabad Pakistan GIKI Faculty of Computer Science and Engg. Swabi Topi Pakistan IIUI Department of Electrical and Computer Engineering Pakistan

ISBN: (纸本)9798350349719

Providing adequate clinical and technical aid to blinds and visually impaired persons can be very challenging as it put financial strain on families due to the medical examination, treatment, surgical procedures and assistive devices expenses. The specialists to the mentioned individuals' ratio is low and exposure to ophthalmologists is limited. Either requirement of smartphone applications with need of internet connection or only direction oriented solutions but unable to avoid obstacles are the issues in existing market solutions. This paper proposes a novel technology of smart assistant aid for blind and visually impaired people (SSVIP) by developing a smart shoe prototype with sensors to detect obstacles, wet surfaces and ground vibrations, providing real-Time feedback to the user. If any of these are detected, the controller activates the buzzer and vibration motor, providing both audible alerts based on the detected sensor signal in order to alarm the wearer and tactile feedback respectively. SSVIP is then tested on 20 iterations after configuring and calibrating sensors and getting the optimized 20 units for ultrasonic sensor, 650 threshold for water sensor. Output accuracies of 87%, 80% and 83% for ultrasonic sensor, water sensor and vibration sensor resnectively and resulting overall 83% accuracy was acheived. © 2024 IEEE.

关键词： Ultrasonic sensors

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Hybrid lightweight encryption for IoT: integrating chaotic key generators with Feistel and substitution-permutation networks for secure 3DV transmission

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Multimedia Tools and Applications 2025年 1-47页

作者： El-Shafai, Walid Mesrega, Ahmed K. Ahmed, Hossam Eldin H. Elbahnasawy, Nirmeen A. El-Samie, Fathi E. Abd Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Deptartment of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Computer Science and Engineering Faculty of Electronic Engineering Menoufia University Menouf Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

The Internet of Things (IoT) stands as a revolutionary leap in digital connectivity, envisioning a future network connecting billions of devices, seamlessly. Amidst the myriad benefits, there arises an intricate web of challenges, prominently centered around potential threats and data security implications. Recent cryptography techniques, such as DNA-based cryptography, 3D chaos-based cryptography, and optical cryptography, face challenges including large encryption times, high energy consumption, and suboptimal rather than optimal performance. Particularly, the burden of long encryption cycles strains the energy resources of typical low-power and compact IoT devices. These challenges render the devices vulnerable to unauthorized breaches, despite large storage capacities. The hallmark of the IoT ecosystem, characterized by its low-power compact devices, is the burgeoning volume of data they generate. This escalating data influx, while necessitating expansive storage, remains vulnerable to unauthorized access and breaches. Historically, encryption algorithms, with their multifaceted architectures, have been the bulwark against such intrusions. However, their inherently-complex nature, entailing multiple encryption cycles, strains the limited energy reserves of typical IoT devices. In response to this intricate dilemma, we present a hybrid lightweight encryption strategy. Our algorithm innovatively leverages both one-dimensional (1D) and two-dimensional (2D) chaotic key generators. Furthermore, it amalgamates a classical encryption philosophy, harmonizing the strengths of Feistel and substitution-permutation networks. The centerpiece of our strategy is achieving effective encryption in merely three rounds, tailored expressly for compressed Three-Dimensional Video (3DV) frames, ensuring their unwavering integrity. Our workflow commences with the H.264/MVC compression algorithm, setting the stage for the subsequent encryption phase. Through rigorous MATLAB simulations,

关键词： Image coding

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A Self-adapting Pixel Antenna - Substrate Lens System for Infrared Frequencies

Periodica Polytechnica Electrical Engineering and Computer S...

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Periodica Polytechnica electrical engineering and computer Science 2025年第1期69卷 14-25页

作者： Shubbar, Mustafa Rakos, Balázs Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary

In this work, we propose a concentrator lens - antenna arrangement, potentially suitable for infrared sensing and energy harvesting rectenna systems. The structure consists of a pixel antenna, self-adapting for the direction of the incident infrared radiation, and a concentrator lens, both optimized for the mid-infrared spectrum. The silicon substrate lens is situated above the pixel antenna, enabling the concentration of the incident light on the antenna;silicon was chosen due to its transparency in the IR spectrum. We examine how various parameters of the lens, in conjunction with the different states of the pixel antenna, affects the performance of the system. The simulations show that the gain of the arrangement increases considerably in correlation with the radius of the lens. The results suggest that the energy conversion efficiency of infrared rectenna systems can be enhanced by several orders of magnitude with the utilization of the proposed arrangement. © 2025 Budapest University of Technology and Economics. All rights reserved.

关键词： Rectennas

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An Optimal DPM Based Energy-Aware Task Scheduling for Performance Enhancement in Embedded MPSoC

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computers, Materials & Continua 2023年第1期74卷 2097-2113页

作者： Hamayun Khan Irfan Ud Din Arshad Ali Mohammad Husain Department of Electrical Engineering Faculty of Engineering&Technology Superior University Lahore54000Pakistan Department of Computer Science Faculty of Computer Science&IT Superior University Lahore54000Pakistan Faculty of Computer and Information Systems Islamic University of MadinahAl Madinah Al Munawarah42351Saudi Arabia

Minimizing the energy consumption to increase the life span and performance of multiprocessor system on chip(MPSoC)has become an integral chip design issue for multiprocessor *** performance measurement of computational systems is changing with the advancement in *** to shrinking and smaller chip size power densities onchip are increasing rapidly that increasing chip temperature in multi-core embedded *** operating speed of the device decreases when power consumption reaches a threshold that causes a delay in complementary metal oxide semiconductor(CMOS)circuits because high on-chip temperature adversely affects the life span of the *** this paper an energy-aware dynamic power management technique based on energy aware earliest deadline first(EA-EDF)scheduling is proposed for improving the performance and reliability by reducing energy and power consumption in the system on chip(SOC).Dynamic power management(DPM)enables MPSOC to reduce power and energy consumption by adopting a suitable core configuration for task *** migration avoids peak temperature values in the multicore *** utilization factor(ui)on central processing unit(CPU)core consumes more energy and increases the temperature *** technique switches the core bymigrating such task to a core that has less temperature and is in a low power *** proposed EA-EDF scheduling technique migrates load on different cores to attain stability in temperature among multiple cores of the CPU and optimized the duration of the idle and sleep periods to enable the low-temperature *** effectiveness of the EA-EDF approach reduces the utilization and energy consumption compared to other existing methods and *** simulation results show the improvement in performance by optimizing 4.8%on u_(i) 9%,16%,23%and 25%at 520 MHz operating frequency as compared to other energy-aware techniques for MPSoCs when the least number of tasks is in running state and can

关键词： Dynamic power management dynamic voltage&frequency scaling dynamic thermal management multiprocessor system on chip complementary metal oxide semiconductor reliability

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FL-ProtectX: Combating Label flipping in complex multi-agent environments 11

FL-ProtectX: Combating Label flipping in complex multi-agent...

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11th International Symposium on Telecommunication, IST 2024

作者： Zamani, Mohammad Ali Amiri, Fatemeh Jamshidi, Pooya Hosseini, Seyed Mahdi Yazdani, Nasser University of Tehran Electrical and Computer Engineering Faculty Tehran Iran Hamedan University of Technology Department of Computer Engineering Hamedan Iran

ISBN: (纸本)9798350356250

Federated Learning (FL) has emerged as a key enabler for secure and decentralized model training while preserving user data privacy. Nonetheless, FL is vulnerable to poisoning attacks;in which a malicious participant tries to corrupt the global model by sending manipulated updates. One common attack is label-flipping, where attackers intentionally mess up labels for training data on their end. Current defenses against these threats treat scenarios where a single adversarial group is cooperating in coordination. This misses the modern real-world scenario in which different adversarial groups have differing, conflicting objectives and act independently. This paper introduces FL-ProtectX, a defense mechanism designed to combat label-flipping attacks targeting heterogeneous multi-adversary environments. Our model also detects the adversary (one that pursues a set of attack goals) behind and can differentiate from other adversaries using their unique target attacks. FL-ProtectX: by utilizing last-layer gradient analysis and cosine similarity computation along with PCA for compression, provides accurate separation and ensures that malicious participants are detected. To facilitate global model aggregation, our method adaptively adjusts trust factors according to the calculated angular similarities between updates. We evaluate the effectiveness of FL-ProtectX on defending against adversary groups by experimentally studying label-flipping attacks on the CIFAR10 dataset and show that for most situations, it effectively neutralizes these attacks, reducing attack success rate from 17.12 to 11.03 while maintaining high accuracy in non-attack-related classes in multi-agent configurations. © 2024 IEEE.

关键词： Federated learning

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Contactless monitoring of human behaviors in bed using RSSI signals

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Medical and Biological engineering and Computing 2023年第10期61卷 2561-2579页

作者： Thammachote, Peeradon Intongkum, Chawakorn Sengchuai, Kiattisak Jindapetch, Nattha Phukpattaranont, Pornchai Saito, Hiroshi Booranawong, Apidet Department of Electrical Engineering Faculty of Engineering Prince of Songkla University Songkhla90110 Thailand Division of Computer Engineering The University of Aizu Aizu-Wakamatsu965-8580 Japan

In this paper, contactless monitoring and classification of human activities and sleeping postures in bed using radio signals is presented. The major contribution of this work is the development of a contactless monitoring and classification system with a proposed framework that uses received signal strength indicator (RSSI) signals collected from only one wireless link, where different human activities and sleep postures, including (a) no one in the bed, (b) a man sitting on the bed, (c) sleeping on his back, (d) seizure sleeping, and (e) sleeping on his side, are tested. With our proposed system, there is no need to attach any sensors or medical devices to the human body or the bed. That is the limitation of the sensor-based technology. Additionally, our system does not raise a privacy concern, which is the major limitation of vision-based technology. Experiments using low-cost, low-power 2.4 GHz IEEE802.15.4 wireless networks have been conducted in laboratories. Results demonstrate that the proposed system can automatically monitor and classify human sleeping postures in real time. The average classification accuracy of activities and sleep postures obtained from different subjects, test environments, and hardware platforms is 99.92%, 98.87%, 98.01%, 87.57%, and 95.87% for cases (a) to (e), respectively. Here, the proposed system provides an average accuracy of 96.05%. Furthermore, the system can also monitor and separate the difference between the cases of the man falling from his bed and the man getting out of his bed. This autonomous system and sleep posture information can thus be used to support care people, physicians, and medical staffs in the evaluation and planning of treatment for the benefit of patients and related people. Graphical Abstract: The proposed system for non-invasive monitoring and classification of human activities and sleeping postures in bed using RSSI signals [Figure not available: see fulltext.] © 2023, International Federation for Med

关键词： Patient treatment

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Development of Dementia Care Training System Using AR and Large Language Model

Development of Dementia Care Training System Using AR and La...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Miyawaki, Tomoya Nishiura, Yuuki Fukuda, Ryouta Nakashima, Kazuto Kurazume, Ryo Graduate School of Information Science and Electrical Engineering Kyushu University Japan Kyushu University Faculty of Engineering Department of Electrical Engineering and Computer Science Japan Kyushu University Faculty of Information Science and Electrical Engineering Japan

ISBN: (纸本)9781665410205

We have developed HEARTS, a dementia care training system using augmented reality based on Humanitude. Humanitude is a multimodal comprehensive care technique for dementia, and has attracted attention as a method to reduce the burden on both caregivers and patients. However, the HEARTS developed so far could not evaluate 'speaking' skills based on the content of conversations among 'seeing,' 'touching,' and 'speaking,' all of which are fundamental skills in Humanitude. Therefore, we attempted a new quantitative evaluation of trainees' 'speaking' skills by estimating the emotional value of conversational content using GPT-4 named HEARTS 5. A survey of caregivers was conducted using the developed system and was well received by the participants. We also developed a HEARTS 5 conversational version based on HEARTS 5, with the addition of GPT-4 conversation generation and Azure Text-to-Speech. © 2024 IEEE.

关键词： Augmented reality

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Software design and FPGA implementation of optimized medical image fusion techniques

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Multimedia Tools and Applications 2025年 1-31页

作者： Elshazly, E.A. El-Shafai, Walid El-Hoseny, Heba El-Rabaie, El-Sayed M Zahran, O. Abdelwahab, Safey A. S. El-Halawany, M.M. Fikry, R.M. Elaraby, S.M. Faragallah, Osama S. Mohamed, Wael A. Mahmoud, Korany R. Abd El-Samie, Fathi E. Cairo Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Faculty of Computer Studies Arab Open University 11681 Riyadh Saudi Arabia Department of Information Technology College of Computers and Information Technology Taif University 11099 Taif21944 Saudi Arabia Department of Electrical Engineering Faculty of Engineering Benha University Benha Egypt Electronics and Communications Engineering Department Faculty of Engineering Helwan University Helwan Egypt Giza Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Nowadays, medical image fusion plays a crucial role in enhancing the diagnosis accuracy and the clinical decision-making process in various healthcare applications. This research work presents a comprehensive study of the design and implementation of optimized medical image fusion techniques using a combination of software and Field-Programmable Gate Array (FPGA) technologies. The proposed medical image fusion strategy is based on the utilization of Discrete Wavelet Transform (DWT) and Modified Central Force Optimization (MCFO). The implementation of the proposed technique as well as the traditional medical image fusion techniques is considered using an appropriate software design and FPGA. The presented techniques aim to overcome the limitations of traditional fusion techniques by integrating advanced image processing algorithms, optimization algorithms, and parallel computing capabilities offered by FPGA platforms. The first step in the proposed framework is to match the histogram of one of the images with that of the other, so that both images will have the same dynamic range. After that, the DWT is used to decompose the images that should be fused together. Based on some constraints, the MCFO optimization algorithm is used to evaluate the optimum level of decomposition and the optimum parameters for the best fusion quality. Finally, to improve the obtained visual quality and reinforce the information in the fusion result, an additional contrast enhancement step using adaptive histogram equalization is applied to the fusion result. Comparative study between the proposed optimized DWT-based fusion framework, the traditional Principal Component Analysis (PCA), Additive Wavelet Transform (AWT), and DWT-based fusion techniques is presented. Various metrics of fusion quality are considered, including average gradient, standard deviation, local contrast, entropy, edge strength, Peak Signal-to-Noise Ratio (PSNR), Qab/f, and processing time. The proposed optimized DWT-ba

关键词： MATLAB

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