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17th International Conference on Machine Vision, ICMV 2024

作者： Yadav, Rahul Shafiq, Muhammad Kumar, Mohit Wei, Li Elaziz, Mohamed Abd College of Computer Science and Technology Harbin Engineering University Harbin China Cyberspace Institute of Advance Technology Guangzhou University Guangzhou China Department of Information Technology National Institute of Technology Jalandhar India Department of Mathematics Faculty of Science Zagazig University Zagazig Egypt

ISBN: (纸本)9781510688278

Smart Healthcare is witnessing widespread implementation of Internet-of-Medical-Things (IoMT) devices. These devices play a crucial role in collecting vast amounts of data from various smart healthcare applications, which are then processed to facilitate informed decision-making. Edge computing has emerged as a valuable platform offering computational resources to handle this data collection efficiently. However, a critical challenge arises from the inappropriate and inefficient classical approaches to fair resource allocation in these energy-intensive, short battery life and delay-intolerant portable devices. To address this issue, this paper presents a Lightweight Adaptive Learning Offloading Algorithm designed to optimize energy and latency in an edge computing environment. The proposed algorithm formulates the problem as a combined minimization of latency and energy costs while satisfying constraints related to limited battery capacity and service latency deadlines. To achieve this, the algorithm employs the adaptation parameters (α, β, γ), and the tradeoff target (C′) is configured based on the specific task requirements. Experimental results demonstrate the advantages of the proposed scheme, including energy savings and minimized latency in an edge environment. To validate the effectiveness of the proposed scheme under a realistic scenario using the iFogSim2 simulator. © 2025 SPIE.

关键词： Electronic health record

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Automated COVID-19 Detection Based on Single-Image Super-Resolution and CNN Models

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computers, Materials & Continua 2022年第1期70卷 1141-1157页

作者： Walid El-Shafai Anas M.Ali El-Sayed M.El-Rabaie Naglaa F.Soliman Abeer D.Algarni Fathi E.Abd El-Samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Alexandria Higher Institute of Engineering&Technology(AIET) AlexandriaEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

In developing countries,medical diagnosis is expensive and time ***,automatic diagnosis can be a good cheap *** task can be performed with artificial intelligence tools such as deep Convolutional Neural Networks(CNNs).These tools can be used on medical images to speed up the diagnosis process and save the efforts of *** deep CNNs allow direct learning from the medical ***,the accessibility of classified data is still the largest challenge,particularly in the field of medical *** learning can deliver an effective and promising solution by transferring knowledge from universal object detection CNNs to medical image ***,because of the inhomogeneity and enormous overlap in intensity between medical images in terms of features in the diagnosis of Pneumonia and COVID-19,transfer learning is not usually a robust ***-Image Super-Resolution(SISR)can facilitate learning to enhance computer vision functions,apart from enhancing perceptual image ***,it helps in showing the main features of *** by the challenging dilemma of Pneumonia and COVID-19 diagnosis,this paper introduces a hybrid CNN model,namely SIGTra,to generate super-resolution versions of X-ray and CT *** depends on aGenerative Adversarial Network(GAN)for the super-resolution reconstruction ***,Transfer learning with CNN(TCNN)is adopted for the classification of *** different categories of chest X-ray and CT images can be classified with the proposed model.A comparison study is presented between the proposed SIGTra model and the other relatedCNNmodels for COVID-19 detection in terms of precision,sensitivity,and accuracy.

关键词： Medical images SIGTra GAN CT and X-ray images SISR TCNN

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Efficient Deep-Learning-Based Autoencoder Denoising Approach for Medical Image Diagnosis

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computers, Materials & Continua 2022年第3期70卷 6107-6125页

作者： Walid El-Shafai Samy Abd El-Nabi El-Sayed MEl-Rabaie Anas M.Ali Naglaa F.Soliman Abeer D.Algarni Fathi E.Abd El-Samie Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Alexandria Higher Institute of Engineering&Technology(AIET) AlexandriaEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Effective medical diagnosis is dramatically expensive,especially in third-world *** of the common diseases is pneumonia,and because of the remarkable similarity between its types and the limited number of medical images for recent diseases related to pneumonia,themedical diagnosis of these diseases is a significant ***,transfer learning represents a promising solution in transferring knowledge from generic tasks to specific ***,experimentation and utilization of different models of transfer learning do not achieve satisfactory *** this study,we suggest the implementation of an automatic detectionmodel,namelyCADTra,to efficiently diagnose pneumonia-related *** model is based on classification,denoising autoencoder,and transfer ***,pre-processing is employed to prepare the medical *** depends on an autoencoder denoising(AD)algorithm with a modified loss function depending on a Gaussian distribution for decoder output to maximize the chances for recovering inputs and clearly demonstrate their features,in order to improve the diagnosis ***,classification is performed using a transfer learning model and a four-layer convolution neural network(FCNN)to detect *** proposed model supports binary classification of chest computed tomography(CT)images and multi-class classification of chest X-ray ***,a comparative study is introduced for the classification performance with and without the denoising *** proposed model achieves precisions of 98%and 99%for binary classification and multi-class classification,respectively,with the different ratios for training and *** demonstrate the efficiency and superiority of the proposed CADTra model,it is compared with some recent state-of-the-art CNN *** achieved outcomes prove that the suggested model can help radiologists to detect pneumonia-related diseases and improve the diagnostic efficiency compared to the exis

关键词： Medical images CADTra AD CT and X-ray images autoencoder

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Malicious URL Classification Using Artificial Fish Swarm Optimization and Deep Learning

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computers, Materials & Continua 2023年第1期74卷 607-621页

作者： Anwer Mustafa Hilal Aisha Hassan Abdalla Hashim Heba G.Mohamed Mohamed K.Nour Mashael M.Asiri Ali M.Al-Sharafi Mahmoud Othman Abdelwahed Motwakel Department of Electrical and Computer Engineering International Islamic University Malaysia 53100 Kuala LumpurMalaysia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Electrical Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer Science College of Computers and Information TechnologyUniversity of BishaSaudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt

Cybersecurity-related solutions have become familiar since it ensures security and privacy against cyberattacks in this digital *** Uniform Resource Locators(URLs)can be embedded in email or Twitter and used to lure vulnerable internet users to implement malicious data in their *** may result in compromised security of the systems,scams,and other such *** attacks hijack huge quantities of the available data,incurring heavy financial *** the same time,Machine Learning(ML)and Deep Learning(DL)models paved the way for designing models that can detect malicious URLs accurately and classify *** this motivation,the current article develops an Artificial Fish Swarm Algorithm(AFSA)with Deep Learning Enabled Malicious URL Detection and Classification(AFSADL-MURLC)*** presented AFSADL-MURLC model intends to differentiate the malicious URLs from genuine *** attain this,AFSADL-MURLC model initially carries out data preprocessing and makes use of glove-based word embedding *** addition,the created vector model is then passed onto Gated Recurrent Unit(GRU)classification to recognize the malicious ***,AFSA is applied to the proposed model to enhance the efficiency of GRU *** proposed AFSADL-MURLC technique was experimentally validated using benchmark dataset sourced from Kaggle *** simulation results confirmed the supremacy of the proposed AFSADL-MURLC model over recent approaches under distinct measures.

关键词： Malicious URL cybersecurity deep learning machine learning metaheuristics gated recurrent unit

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Fiber-optic sensor based on Bragg grating and 3D printing technique for monitoring the heart rate of the human body

Fiber-optic sensor based on Bragg grating and 3D printing te...

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Optical Sensors 2023

作者： Krizan, Daniel Kostelansky, Michal Mohammed, Mazin Abed Martinek, Radek Nedoma, Jan Department of Telecommunications Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Czech Republic Department of Cybernetics and Biomedical Engineering Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Czech Republic College of Computer Science and Information Technology University of Anbar Anbar Iraq

ISBN: (数字)9781510662650

ISBN: (纸本)9781510662643

This paper discusses a proposed fiber-optic sensor that was based on the combination of the material called polyethylene terephthalate glycol (PETG) and a fiber Bragg grating (FBG). The practical experiments were conducted under laboratory conditions with a group of 6 volunteers. The data were compared with conventional electrocardiogram (ECG) and processed using a Bland-Altman method. The results described in this paper show that the 3D printing technique can be used for encapsulating the FBG and for the purpose of biomedical engineering. © 2023 SPIE.

关键词： Fiber Bragg gratings

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Exploring Auditory Hand Guidance for Eyes-free 3D Path Tracing

Exploring Auditory Hand Guidance for Eyes-free 3D Path Traci...

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2025 CHI Conference on Human Factors in Computing Systems, CHI EA 2025

作者： Abe, Yuki Hara, Kotaro Sakamoto, Daisuke Ono, Tetsuo Human-Computer Interaction Lab. Hokkaido University Hokkaido Sapporo Japan School of Computing and Information Systems Singapore Management University Singapore Singapore Division of Computer Science and Information Technology Hokkaido University Hokkaido Sapporo Japan Faculty of Engineering Kyoto Tachibana University Kyoto Japan

ISBN: (纸本)9798400713958

Guiding a user’s hand along a 3D path can help individuals avoid obstacles and manipulate everyday items with eyes-free. While prior work focused on haptic approaches using robots, auditory approaches for 3D path guidance remain underexplored. We prototyped and assessed two auditory hand guidance techniques for 3D path tracing: (1) VERBAL repeating spoken directional prompts;(2) Follow-Your-Finger (FYF) using the user’s index finger in moving hand as an embodied reference and sonifying whether the user should follow the index finger direction. In a controlled pilot study with 12 sighted participants under an eyes-free condition, VERBAL yielded about 1.5 times faster performance than FYF, while FYF achieved an error rate of less than half VERBAL’s. We thus recommend using VERBAL for wider paths with fewer obstacles and FYF for narrower paths with higher collision risks. We also discuss the research direction for applying these findings to real-world tasks. © 2025 Copyright held by the owner/author(s).

关键词： Three dimensional computer graphics

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Dynamic Scalable Energy-Aware Routing Protocol for Mobile Ad hoc Networks 34

Dynamic Scalable Energy-Aware Routing Protocol for Mobile Ad...

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34th International Conference on computer Theory and Applications, ICCTA 2024

作者： Qabajeh, Liana Amro, Yasmeen Qabajeh, Mohammad Palestine Polytechnic University Information Technology and Computer Engineering Faculty Hebron Palestine Palestine Polytechnic University Graduate Studies and Scientific Research Faculty Hebron Palestine Palestine Technical University Kadoorie Engineering and Technology Faculty Hebron Palestine

ISBN: (纸本)9798331529673

Mobile Ad hoc wireless Networks (MANETs) are becoming increasingly popular as a result of their flexibility and decrease in costs. However, MANETs have some challenging issues that are required to be taken into account. Routing is the most popular challenging issue. Energy is considered as a limiting factor for lifetime and connectivity in MANETs, so it is important to conserve energy using routing protocols. Scalability is also an important issue to be taken into account in developing routing protocols which presents the capability of the network to handle a growing amount of its characteristics like: nodes density, network area and speed of nodes, without affecting the performance of the network connection. Octopus is a position-based protocol in which the network region is divided into static eight sectors centered at the source. The source decides which sector contains the destination and broadcasts the packet into that sector. Networks properties are different from each other, so static sectors number is less efficient. Moreover, the nodes energy level is not taken into consideration. This paper proposes a new routing protocol (D-Octopus) based on restricted flooding approach position-Aware routing. D-Octopus is a dynamic, energy efficient and scalable protocol. D-Octopus has been proposed to improve the original Octopus routing protocol by dynamically dividing the area into different sectors number. Octopus routing protocol is implemented using Network Simulator with different parameters including mobility speed, network size and node initial energy. The results of this research conclude the best number of sectors for the network to be divided into for these cases. Our protocol has been compared to Octopus and LAR protocols. Results show that D-Octopus has better performance in all scenarios except in medium scenarios D-Octopus acts like Octopus. D-Octopus has achieved better performance regarding four metrics packet delivery fraction, packet routing load, ave

关键词： Dynamic Energy-Aware Routing Scalable

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Utilization of ECC in Smart Grids: A Review

Utilization of ECC in Smart Grids: A Review

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Gopala Krishna, K. Shekhawat, Jyoti Agarwal, Trapty Faculty of Engineering and Technology Department of Electronics and Communication Engineering Bangalore India Vivekananda Global University Department of Computer Science & Application Jaipur India Maharishi University of Information Technology Engineering Department Uttar Pradesh India

ISBN: (纸本)9798350357769

Within the realm of smart grids, a power service provider plays a crucial function in coordinating predicted power production with actual power demand in order to support power system stability. Insufficient protection means that, even with these advancements, data sent inside smart grids is still vulnerable to a variety of security risks and assaults. To enhance the security of electronic grid networks, a robust and effective authentication procedure must be put in place. The trouble of ensuring the security of communications among substations and electronic machines stays, even in shrewd lattice settings where SCADA (supervisory controls and data acquisition) frameworks assume a part in shielding associations between the administration place and substations. In this present circumstance, predominant security strategies frequently neglect to accomplish an unpretentious harmony among security and execution. With the expansion of an safe part on the smart machine side, this work incorporates security insurance into a moderation verification framework in view of elliptic bend cryptography. This clever convention handles the requirement for a finely tuned balance between the security and execution parts of shrewd lattices. Key arrangement, common verification, and character security are significant parts of the proposed convention. The convention's viability is upheld by a complete assessment utilizing the Gong-Needham-Yahalom rationale. This procedure is a critical improvement in reinforcing the security position of smart grids, particularly taking into account the continually changing climate of cyber threats and weaknesses. © 2023 IEEE.

关键词： Authentication Elliptic Curve Cryptography Privacy Protection SCADA Systems Security Smart Grids

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Maximum Power Point Tracking Controller with Neural Gas Network PID of Boost Converter 4

Maximum Power Point Tracking Controller with Neural Gas Netw...

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4th International Conference on Advanced Electrical and Energy Systems, AEES 2023

作者： Aly, Rabab Hamed M. Hussein, Aziza I. The Higher Institute for Management and Information Technology Minya Egypt Faculty of Computer Science Nahda University Computer Science Department Beni Suef Egypt College of Engineering Effat University Electrical and Computer Engineering Department Jeddah Saudi Arabia

ISBN: (纸本)9798350342659

Each photovoltaic (PV) system demonstrates a specific point on the current-voltage (IV) curve characteristics where the power generated reaches its maximum value which is referred to as the maximum power point (MPP). The maximum power point tracking (MPPT) system is designed to sample the output of solar cells and adjust the load in order to achieve maximum power output under various environmental conditions. In this paper, a design of a boost converter with MPPT based on a PID controller is proposed. The goal is to optimize the extraction of the highest attainable power from photovoltaic systems. The extracted power is subsequently directed to the load through a boost converter, which elevates the voltage to the necessary level. The PID controller is calibrated by Neural Gas Network (NGN) and utilized to achieve a consistent output voltage irrespective of fluctuations in the power source or the connected load. Moreover, an NGN technique is applied to generate the optimal PID parameters before using the PID. The comprehensive system design depicted has been simulated using MATLAB Simulink to verify the functionality of the system. © 2023 IEEE.

关键词： Controllers

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The Way to Check the Reliability Test in Smart Grids for the Smart Protection System

The Way to Check the Reliability Test in Smart Grids for the...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Hannah Jessie Rani, R. Goyal, Manish Kumar Mishra, Awakash Faculty of Engineering and Technology Department of Electrical and Elceltronics Engineering Bangalore India Vivekananda Global University Department of Computer Science & Application Jaipur India Maharishi University of Information Technology Engineering Department Uttar Pradesh India

ISBN: (纸本)9798350357769

The complex operation of contemporary power systems is closely linked to the widespread integration of computer networks, or cyber networks. These applications fall into two general categories: direct and indirect interdependencies, which are the result of how they communicate with power networks. Past studies explored the area of direct interdependencies in cyber-power networks and presented a state mapping-based model that was carefully designed to assess its impact on power system dependability. The investigation of indirect relationships between cyber and electricity networks is the new emphasis of this article. A wide range of applications involving indirect interdependencies in modern power systems are examined, laying the foundation for the release of a model that is based on state updating. This model is carefully crafted to provide a numerical evaluation of cyber-power networks' dependability in the face of indirect interdependencies. Two separate models are used to maximize data communication inside the cyber network and minimize load limitation in the power network, respectively, in order to maximize the functioning of these integrated networks. In order to demonstrate the efficacy of the suggested solution model, the research focuses on a high-voltage converter equipped with both protection and monitoring devices. By taking a comprehensive approach, the research makes a substantial contribution to a deeper understanding of the complex interactions between cyber and electricity networks, providing priceless insights for enhancing the dependability of these interconnected systems. © 2023 IEEE.

关键词： Cyber-Power Interdependencies Dependability Indices and Optimization Framework Indirect Relationships Monitoring Systems P- Table Protection Systems Reliability Assessment Smart Grid State Updating

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