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Game Theory-Based IoT Efficient Power Control in Cognitive UAV

Computers, Materials & Continua 2022年第7期72卷 1561-1578页

作者： Fadhil Mukhlif Norafida Ithnin Omar B.Abdulghafoor Faiz alotaibi Nourah saad alotaibi Information Assurance and Security Research Group(IASRG) School of ComputingFaculty of EngineeringUniversiti Teknologi MalaysiaJohorMalaysia Electronic and Telecommunication Department College of EngineeringThe American University of KurdistanIraq Faculty of Computer Science and Information Technology Universiti Putra MalaysiaSelangorMalaysia Computer Department Faculty of Applied CollegeImam Abdulrahman Bin Faisal UniversityDammamSaudi Arabia

With the help of network densification,network coverage as well as the throughput can be improved via ultra-dense networks(UDNs).In tandem,Unmanned Aerial Vehicle(UAV)communications have recently garnered much attention because of their high agility as well as widespread *** this paper,a cognitive UAV is proposed for wireless nodes power pertaining to the IoT ground ***,the UAV is included in the IoT system as the source of power for the wireless nodes as well as for resource *** quality of service(QoS)related to the cognitive node was considered as a utility function based on pricing scheme that was modelled as a non-cooperative game theory in order to maximise users’net utility ***,an energy efficiency non-cooperative game theory power allocation with pricing scheme(EE-NGPAP)is proposed to obtain an efficient power control within IoT wireless ***,uniqueness and existence of the Nash equilibrium have been demonstrated mathematically and through *** results show that the proposed energy harvest algorithm demonstrated considerable decrease in transmitted power consumption in terms of average power reduction,which is regarded to be apt with the 5Gnetworks’***,the proposed algorithm requires around 4 iterations only to converge to NE which makes the algorithm more suitable in practical heterogeneous scenarios.

关键词： UAV drones WSN IoT game theory energy efficiency 5G&B5G networks

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Analysis of Local Diagnostic Reference Levels for Pediatric Patients Undergoing 18F-FDG PET/CT Imaging for Oncology

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Journal of Applied Mathematics and Physics 2023年第7期11卷 2144-2155页

作者： saad Alqahtani Khaled Soliman saad alotaibi Khaled Alnofaie Abdullah Alahmari Fahad Alyahya Abdullah Albdullah Rashed Alharbi Radiodiagnostic and Medical Imaging Department Prince Sultan Military Medical City Riyadh Saudi Arabia Medical Physics Department Prince Sultan Military Medical City Riyadh Saudi Arabia

Background: The PET/CT imaging studies have two doses components the dose from the PET radiopharmaceutical and the other from the low dose CT used for PET images attenuation correction. We have one PET/CT scanner at our institution a Philips Time of Flight scanner. Our local patient’s radiation protection rules requires continuous assessment of radiation doses delivered to our patients. Purposes: The objectives of this study are to develop a weight- based facility DRLs for paediatric F-18-FDG PET-CT imaging for oncology in a large tertiary hospital and to determine whether the calculated DRLs compares with internationally published DRLs. Materials & Methods: Radiation dose data and patient demographics of two-hundreds and sixteen paediatric PET-CT oncology patients imaging procedures from one large tertiary hospital were selected and analysed in order to establish a facility paediatric DRLs. Statistical analysis was performed. Results: The PET dose reference levels ranged between [62 - 525] MBq of injected activity for a range of pediatric age groups. The CTDIvol values were between 3.5 and 16.5 mGy for all age groups. Comparison with current EANM and SNMMI recommendations of patient’s dose are discussed. Conclusion: Our pediatric PET/CT reference levels are higher than the ones reported internationally with notable variations. .

关键词： Diagnostic Reference Levels PET/CT 18-F-FDG Pediatric Radiation Dose CTDIvol Oncology

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Classified VPN Network Traffic Flow Using Time Related to Artificial Neural Network

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Computers, Materials & Continua 2024年第7期80卷 819-841页

作者： saad Abdalla Agaili Mohamed Sefer Kurnaz Department of Electrical and Computer Engineering Altinbas UniversityIstanbul34000Turkey

VPNs are vital for safeguarding communication routes in the continually changing cybersecurity ***,increasing network attack complexity and variety require increasingly advanced algorithms to recognize and categorizeVPNnetwork *** present a novelVPNnetwork traffic flowclassificationmethod utilizing Artificial Neural Networks(ANN).This paper aims to provide a reliable system that can identify a virtual private network(VPN)traffic fromintrusion attempts,data exfiltration,and denial-of-service *** compile a broad dataset of labeled VPN traffic flows from various apps and usage ***,we create an ANN architecture that can handle encrypted communication and distinguish benign from dangerous *** effectively process and categorize encrypted packets,the neural network model has input,hidden,and output *** use advanced feature extraction approaches to improve the ANN’s classification accuracy by leveraging network traffic’s statistical and behavioral *** also use cutting-edge optimizationmethods to optimize network characteristics and *** suggested ANN-based categorization method is extensively tested and *** show the model effectively classifies VPN traffic *** also show that our ANN-based technique outperforms other approaches in precision,recall,and F1-score with 98.79%*** study improves VPN security and protects against new *** VPNtraffic flows effectively helps enterprises protect sensitive data,maintain network integrity,and respond quickly to security *** study advances network security and lays the groundwork for ANN-based cybersecurity solutions.

关键词： VPN network traffic flow ANN classification intrusion detection data exfiltration encrypted traffic feature extraction network security

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Reinforcement Learning-Empowered Graph Convolutional Network Framework for Data Integrity Attack Detection in Cyber-Physical Systems

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 797-806页

作者： Edeh Vincent Mehdi Korki Mehdi Seyedmahmoudian Alex Stojcevski saad Mekhilef School of Science Computingand Engineering TechnologiesSwinburne University of TechnologyMelbourneAustralia

The massive integration of communication and information technology with the large-scale power grid has enhanced the efficiency, safety, and economical operation of cyber-physical systems. However, the open and diversified communication environment of the smart grid is exposed to cyber-attacks. Data integrity attacks that can bypass conventional security techniques have been considered critical threats to the operation of the grid. Current detection techniques cannot learn the dynamic and heterogeneous characteristics of the smart grid and are unable to deal with non-euclidean data types. To address the issue, we propose a novel Deep-Q-Network scheme empowered with a graph convolutional network (GCN) framework to detect data integrity attacks in cyber-physical systems. The simulation results show that the proposed framework is scalable and achieves higher detection accuracy, unlike other benchmark techniques.

关键词： Deep reinforcement learning graph convolutional network heterogeneous smart grid network

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RoGRUT: A Hybrid Deep Learning Model for Detecting Power Trapping in Smart Grids

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Computers, Materials & Continua 2024年第5期79卷 3175-3192页

作者： Farah Mohammad saad Al-Ahmadi Jalal Al-Muhtadi Center of Excellence in Information Assurance(CoEIA) King Saud UniversityRiyadh11543Saudi Arabia College of Computer&Information Sciences King Saud UniversityRiyadh11543Saudi Arabia

Electricity theft is a widespread non-technical issue that has a negative impact on both power grids and electricity *** hinders the economic growth of utility companies,poses electrical risks,and impacts the high energy costs borne by *** development of smart grids is crucial for the identification of power theft since these systems create enormous amounts of data,including information on client consumption,which may be used to identify electricity theft using machine learning and deep learning ***,there also exist different solutions such as hardware-based solutions to detect electricity theft that may require human resources and expensive ***-based solutions are presented in the literature to identify electricity theft but due to the dimensionality curse,class imbalance issue and improper hyper-parameter tuning of such models lead to poor *** this research,a hybrid deep learning model abbreviated as RoGRUT is proposed to detect electricity theft as amalicious and non-malicious *** key steps of the RoGRUT are data preprocessing that covers the problem of class imbalance,feature extraction and final theft *** advanced-level models like RoBERTa is used to address the curse of dimensionality issue,the near miss for class imbalance,and transfer learning for *** effectiveness of the RoGRUTis evaluated using the dataset fromactual smartmeters.A significant number of simulations demonstrate that,when compared to its competitors,the RoGRUT achieves the best classification *** performance evaluation of the proposed model revealed exemplary results across *** accuracy achieved was 88%,with precision at an impressive 86%and recall reaching 84%.The F1-Score,a measure of overall performance,stood at 85%.Furthermore,themodel exhibited a noteworthyMatthew correlation coefficient of 78%and excelled with an area under the curve of 91%.

关键词： Electricity theft smart grid RoBERTa GRU transfer learning

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Effect of Co on Solidification Characteristics and Microstructural Transformation of Non-equilibrium Solidified Cu-Ni Alloys

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Journal of Wuhan University of Technology(Materials Science) 2024年第2期39卷 444-453页

作者：安红恩 Bih-Lii Chua Ismail saad Willey Yun Hsien Liew Materials Engineering Research Group Faculty of EngineeringUniversity Malaysia Sabah88400 Kota KinabaluSabahMalaysia College of Mechanical and Electronic Engineering Huanghe Jiaotong UniversityJiaozuo 454950China Henan Engineering Technology Research Center on Intelligent Manufacturing Technology and Equipment Jiaozuo 454950China Centre of Research in Energy and Advanced Materials Faculty of EngineeringUniversiti Malaysia SabahJalan UMS88400 Kota KinabaluSabahMalaysia Nano Engineering and Materials Research group Faculty of EngineeringUniversity Malaysia Sabah88400 Kota KinabaluSabahMalaysia

Non-equilibrium solidification structures of Cu55Ni45 and Cu55Ni43Co2 alloys were prepared by the molten glass purification cycle superheating *** variation of the recalescence phenomenon with the degree of undercooling in the rapid solidification process was investigated using an infrared *** addition of the Co element affected the evolution of the recalescence phenomenon in Cu-Ni *** images of the solid-liquid interface migration during the rapid solidification of supercooled melts were captured by using a high-speed *** solidification rate of Cu-Ni alloys,with the addition of Co elements,was ***,the grain refinement structure with low supercooling was characterised using electron backscatter diffraction(EBSD).The effect of Co on the microstructural evolution during nonequilibrium solidification of Cu-Ni alloys under conditions of small supercooling is investigated by comparing the microstructures of Cu55Ni45 and Cu55Ni43Co2 *** experimental results show that the addition of a small amount of Co weakens the recalescence behaviour of the Cu55Ni45 alloy and significantly reduces the thermal strain in the rapid solidification *** the rapid solidification phase,the thermal strain is greatly reduced,and there is a significant increase in the characteristic undercooling ***,the addition of Co and the reduction of Cu not only result in a lower solidification rate of the alloy,but also contribute to the homogenisation of the grain size.

关键词： non-equilibrium solidification recalescence effect solidification character microstructure

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Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1339-1370页

作者： Ali S.Alghamdi Mohamed A.Zohdy saad Aldoihi Department of Electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia Electrical and Computer Engineering Department Oakland UniversityRochesterMI48309USA Institute of Earth and Space Science King Abdulaziz City for Science and Technology(KACST)Riyadh11442Saudi Arabia Computer Science and Systems Engineering Institute Polytechnique de ParisPalaiseau CedexFrance

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network *** study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic *** primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss ***,a carbon tax is included in the objective function to reduce carbon *** scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal *** results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution ***,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)*** research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local *** emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

关键词： Renewable energy integration optimal power flow stochastic renewable energy sources gaussian-bare-bones levy cheetah optimizer electrical network optimization carbon tax optimization

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An Adaptive Hate Speech Detection Approach Using Neutrosophic Neural Networks for Social Media Forensics

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Computers, Materials & Continua 2024年第4期79卷 243-262页

作者： Yasmine M.Ibrahim Reem Essameldin saad M.Darwish Department of Information Technology Institute of Graduate Studies and ResearchAlexandria UniversityAlexandria21526Egypt Faculty of Computers and Information Technology Egyptian E-Learning University(EELU)Giza12611Egypt Faculty of Computers and Data Science Alexandria UniversityAlexandria21554Egypt

Detecting hate speech automatically in social media forensics has emerged as a highly challenging task due tothe complex nature of language used in such platforms. Currently, several methods exist for classifying hatespeech, but they still suffer from ambiguity when differentiating between hateful and offensive content and theyalso lack accuracy. The work suggested in this paper uses a combination of the Whale Optimization Algorithm(WOA) and Particle Swarm Optimization (PSO) to adjust the weights of two Multi-Layer Perceptron (MLPs)for neutrosophic sets classification. During the training process of the MLP, the WOA is employed to exploreand determine the optimal set of weights. The PSO algorithm adjusts the weights to optimize the performanceof the MLP as fine-tuning. Additionally, in this approach, two separate MLP models are employed. One MLPis dedicated to predicting degrees of truth membership, while the other MLP focuses on predicting degrees offalse membership. The difference between these memberships quantifies uncertainty, indicating the degree ofindeterminacy in predictions. The experimental results indicate the superior performance of our model comparedto previous work when evaluated on the Davidson dataset.

关键词： Hate speech detection whale optimization neutrosophic sets social media forensics

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A Framework for Enhancing Privacy and Anonymity in Blockchain-Enabled IoT Devices

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Computers, Materials & Continua 2024年第3期78卷 4263-4282页

作者： Muhammad saad Muhammad Raheel Bhutta Jongik Kim Tae-Sun Chung Department of Artificial Intelligence Ajou UniversitySuwon443-749Korea Department of Electrical and Computer Engineering University of Utah Asia CampusIncheon21985Korea Department of Artificial Intelligence Chungnam National UniversityDaejeon34134Korea

With the increase in IoT(Internet of Things)devices comes an inherent challenge of *** the world today,privacy is the prime concern of every *** one’s privacy and keeping anonymity throughout the system is a desired functionality that does not come without inevitable trade-offs like scalability and increased complexity and is always exceedingly difficult to *** challenge is keeping confidentiality and continuing to make the person innominate throughout the *** address this,we present our proposed architecture where we manage IoT devices using blockchain *** proposed architecture works on and off blockchain integrated with the closed-circuit television(CCTV)security camera fixed at the rental *** this framework,the CCTV security camera feed is redirected towards the owner and renter based on the smart contract *** entity(owner or renter)can see the CCTV security camera feed at one *** is no third-party dependence except for the CCTV security camera deployment *** contributions include the proposition of framework architecture,a novel smart contract algorithm,and the modification to the ring signatures leveraging an existing cryptographic *** are made based on different systems’security and key management *** an empirical study,our proposed algorithm performed better in key generation,proof generation,and verification *** comparing similar existing schemes,we have shown the proposed architectures’*** now,we have developed this system for a specific area in the real ***,this system is scalable and applicable to other areas like healthcare monitoring systems,which is part of our future work.

关键词： Privacy anonymity blockchain IoT smart contracts

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Mechanical and magneto-electronic properties of europium lanthanide-based cubic perovskites EuYO_(3)(Y=Cr, Mn, Fe): An ab initio study

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Journal of Rare Earths 2024年第3期42卷 562-569,I0005页

作者： Hayat Ullah Azra Sarwar Sajad Ali Rabah Khenata Abdelmadjid Bouhemadou saad Bin-Omran Department of Physics Women University of Azad Jammu&Kashmir Bagh 10250Pakistan Department of Physics Abdul Wali Khan UniversityMardan23200KPPakistan LPQ3M Laboratory Institute of Science and TechnologyUniversity of Mascara29000MascaraAlgeria Laboratory for Developing New Materials and Their Characterization Farhat Abbas University Setif l19000SetifAlgeria Department of Physics and Astronomy College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

Computational calculations using density functional theory(DFT) were performed for the first time using the full potential linearized augmented plane wave plus local orbital method(FP-LAPW + LO) to determine the structural, elastic, electronic and magnetic properties of europium-based cubic perovskites EuYO_(3)(Y=Cr, Mn, Fe). The exchange correlation potentials of GGA along with some analytical methods were adopted for the computation of structural and elastic properties. Moreover, the GGA + U formalism was also added for obtaining more precise electronic and magnetic properties, particularly to address the Eu-4f and Y-3d orientations in the spin-polarized double cell symmetry. The observed lattice parameters of these compounds are consistent with experiment. The observed bulk moduli predict that EuCrO_(3) is harder and less compressible than EuMnO_(3) and EuFeO_(3). The calculated tolerance factors of these compounds are within the cubic symmetry range. Our computed critical radius of EuCrO_(3) shows that EuCrO_(3) has a larger migration energy. Based on their elastic properties, these compounds are ductile in nature. We also computed the thermal properties of these compounds. The band structures and density of states show that these compounds are metallic in character. The lowest ground state energy and magnetic moments of these compounds expose their ferromagnetic nature. The metallic nature and strong ferromagnetism of these compounds make them promising applicants for application in spintronic.

关键词： Perovskites GGA+U Elastic constants Band structure Magnetic moments Rare earths

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