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5G Resource Allocation Using Feature Selection and Greylag Goose Optimization Algorithm

computers, Materials & Continua 2024年第7期80卷 1179-1201页

作者： Amel Ali Alhussan S.K.Towfek Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Science and Intelligent Systems Research Center BlacksburgVA 24060USA

In the contemporary world of highly efficient technological development,fifth-generation technology(5G)is seen as a vital step forward with theoretical maximum download speeds of up to twenty gigabits per second(Gbps).As far as the current implementations are concerned,they are at the level of slightly below 1 Gbps,but this allowed a great leap forward from fourth generation technology(4G),as well as enabling significantly reduced latency,making 5G an absolute necessity for applications such as gaming,virtual conferencing,and other interactive electronic *** of this change are not limited to connectivity alone;it urges operators to refine their business strategies and offers users better and improved digital *** essential factor is optimization and the application of artificial intelligence throughout the general arrangement of intricate and detailed 5G *** Binary Greylag Goose Optimization(bGGO)to achieve a significant reduction in the feature set while maintaining or improving model performance,leading to more efficient and effective 5G network management,and Greylag Goose Optimization(GGO)increases the efficiency of the machine ***,the model performs and yields more accurate *** work proposes a new method to schedule the resources in the next generation,5G,based on a feature selection using GGO and a regression model that is an ensemble of K-Nearest Neighbors(KNN),Gradient Boosting,and Extra Trees *** ensemble model shows better prediction performance with the coefficient of determination R squared value equal *** proposed framework is supported by several Statistical analyses,such as theWilcoxon signed-rank *** of the benefits of this study are the introduction of new efficient optimization algorithms,the selection of features and more reliable ensemble models which improve the efficiency of 5G technology.

关键词： Optimization ensemble learning 5G technology artificial intelligence greylag goose optimization ANOVA test

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HYDRO:Optimizing interactive hybrid images for digital signage content

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Virtual Reality & Intelligent Hardware 2023年第6期5卷 565-577页

作者： Masanori NAKAYAMA Karin UCHINO Ken NAGAO Issei FUJISHIRO Department of Information&Computer Science Keio UniversityTokyoJapan Center for Information&Computer Science Keio UniversityTokyoJapan

Background In modern society,the digital signage installed in many large-scale facilities supports daily ***,owing to their limited screen size,it is difficult to simultaneously provide different types of information to many viewers at varying distances from the ***,in this study,we extend the existing research on the use of hybrid images for tiled *** To facilitate smoother information selection,a new interactive display method is proposed that incorporates touch-activated widgets as high-frequency parts of hybrid *** widgets are novel because they are more visible to viewers near the *** developed an authoring tool called the hybrid image display resolution optimizer(HYDRO),which features two types of control functions to optimize the visibility of touch-activated widgets in terms of placement and *** The effectiveness of the proposed method is demonstrated empirically through a quantitative user study and an eyetracking-based qualitative evaluation.

关键词： Digital signage Hybrid image Authoring tool information design

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quantum Computing for Optimization With Ising Machine

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IEEE Nanotechnology Magazine 2024年第3期18卷 15-22页

作者： Chang, Yen-Jui Nien, Chin-Fu Huang, Kuei-Po Zhang, Yun-Ting Cho, Chien-Hung Chang, Ching-Ray Chang Gung University Department of Computer Science and Information Engineering Taoyuan City33302 Taiwan National Taiwan University Department of Physics Taipei10617 Taiwan Chung Yuan Christian University Quantum Information Center Taoyuan City32023 Taiwan

Optimization problems, which involve finding the best solution from a set of possible solutions, are ubiquitous in various fields, from finance to engineering. Traditional algorithms sometimes struggle with these problems, especially when the solution space is vast, or the landscape is filled with numerous local minima. quantum-inspired computing, which emulates quantum mechanical principles on classical hardware, emerges as a promising paradigm to address these challenges. This paper delves into two notable approaches: coherent Ising machines (CIM) and graphics processing unit (GPU)-accelerated simulated annealing. In essence, both methods offer innovative strategies to navigate the solution landscape, potentially bypassing the pitfalls of local optima and ensuring more efficient convergence to solutions. By harnessing the strengths of these quantum-inspired techniques, we can pave the way for enhanced computational capabilities in tackling complex optimization problems, even without a fault-tolerant quantum computer. © 2007-2011 IEEE.

关键词： Program processors

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A Reputation-Based AODV Protocol for Blackhole and Malfunction Nodes Detection and Avoidance

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computers, Materials & Continua 2024年第8期80卷 1867-1888页

作者： Qussai M.Yaseen Monther Aldwairi Ahmad Manasrah Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjman346United Arab Emirates Department of Computer Information Systems Faculty of Computer and Information TechnologyJordan University of Science and TechnologyIrbid22110Jordan College of Technological Innovation Zayed UniversityAbu Dhabi144534United Arab Emirates Faculty of Information Technology and Computer Science Yarmouk UniversityIrbid21163Jordan Computer Information Systems Higher Colleges of TechnologySharjah341214United Arab Emirates

Enhancing the security of Wireless Sensor Networks(WSNs)improves the usability of their ***,finding solutions to various attacks,such as the blackhole attack,is crucial for the success of WSN *** paper proposes an enhanced version of the AODV(Ad Hoc On-Demand Distance Vector)protocol capable of detecting blackholes and malfunctioning benign nodes in WSNs,thereby avoiding them when delivering *** proposed version employs a network-based reputation system to select the best and most secure path to a *** achieve this goal,the proposed version utilizes the Watchdogs/Pathrater mechanisms in AODV to gather and broadcast reputations to all network nodes to build the network-based reputation *** minimize the network overhead of the proposed approach,the paper uses reputation aggregator nodes only for forwarding reputation ***,to reduce the overhead of updating reputation tables,the paper proposes three mechanisms,which are the prompt broadcast,the regular broadcast,and the light broadcast *** proposed enhanced version has been designed to perform effectively in dynamic environments such as mobile WSNs where nodes,including blackholes,move continuously,which is considered a challenge for other *** the proposed enhanced protocol,a node evaluates the security of different routes to a destination and can select the most secure routing *** paper provides an algorithm that explains the proposed protocol in detail and demonstrates a case study that shows the operations of calculating and updating reputation values when nodes move across different ***,the paper discusses the proposed approach’s overhead analysis to prove the proposed enhancement’s correctness and applicability.

关键词： AODV blackhole malfunction nodes pathrater reputation system wireless sensor networks(WSNs) watchdogs

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Enhanced Neutrosophic Set and Machine Learning Approach for Kidney Disease Prediction

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Neutrosophic Sets and Systems 2025年 80卷 465-477页

作者： Al-Doori, Humam M. Alkellezli, Tareef S. Abdelhafeez, Ahmed Eassaa, Mohamed Sawah, Mohamed S. El-Douh, Ahmed A. Cybersecurity Sciences Department College of Science Ashur University Baghdad Iraq Cybersecurity Engineering Department College of Engineering Ashur University Baghdad Iraq Computer Science Department Faculty of Information System and Computer Science October 6 University Giza12585 Egypt Applied Science Research Center Applied Science Private University Amman Jordan Department of Computer Science Faculty of Information Technology Ajloun National University P.O.43 Ajloun26810 Jordan Cybersecurity Technology Engineering Department College of Engineering Technology Ashur University Baghdad Iraq

Kidney disease (KD) is a gradually increasing global health concern. It is a chronic illness linked to higher rates of morbidity and mortality, a higher risk of cardiovascular disease and numerous other illnesses, and expensive medical expenses. The machine learning (ML) models are applied for KD prediction with higher accuracy and precision. The KD dataset has uncertainty and vague information, so, we used the neutrosophic set (NS) to deal with vague and uncertainty information in the KD dataset. The KD dataset is converted into the N-KD dataset with three membership functions: truth, indeterminacy, and falsity. Three ML models are used in this study such as logistic regression (LR), support vector machine (SVM), and k-nearest neighbor (KNN). These ML models are applied to the N-KD dataset. The results show the LR has higher accuracy and precision on the N-KD dataset than the original KD dataset. © 2025, University of New Mexico. All rights reserved.

关键词： Logistic regression

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SDN-Enabled Content Dissemination Scheme for the Internet of Vehicles

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computers, Materials & Continua 2023年第5期75卷 2383-2396页

作者： Abida Sharif Muhammad Imran Sharif Muhammad Attique Khan Nisar Ali Abdullah Alqahtani Majed Alhaisoni Ye Jin Kim Byoungchol Chang Department of Computer Science COMSATS University IslamabadPakistan Department of Computer Science HITEC University TaxilaPakistan College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-KharjSaudi Arabia Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea Center for Computational Social Science Hanyang UniversitySeoul04763Korea

The content-centric networking(CCN)architecture allows access to the content through name,instead of the physical location where the content is stored,which makes it a more robust and flexible content-based ***,in CCN,the broadcast nature of vehicles on the Internet of Vehicles(IoV)results in latency and network *** IoVbased content distribution is an emerging concept in which all the vehicles are connected via the *** to the high mobility of vehicles,however,IoV applications have different network requirements that differ from those of many other networks,posing new *** this,a novel strategy mediator framework is presented in this paper for managing the network resources ***-defined network(SDN)controller is deployed for improving the routing flexibility and facilitating in the interinteroperability of heterogeneous devices within the *** to the limited memory of edge devices,the delectable bloom filters are used for caching and ***,the proposed scheme is compared with the existing variants for validating its effectiveness.

关键词： Internet of vehicles(IOV) content dissemination multi mediator data traffic management

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Signifying quantum uncertainty relations by optimal observable sets and the tightest uncertainty constants

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science China(Physics,Mechanics & Astronomy) 2024年第9期67卷 43-50页

作者： Xiao-Bin Liang Bo Li Shao-Ming Fei School of Mathematics and Computer Science Shangrao Normal UniversityShangrao 334001China Quantum Information Research Center Shangrao Normal UniversityShangrao 334001China School of Mathematical Sciences Capital Normal UniversityBeijing 100048China

quantum uncertainty relations constrain the precision of measurements across multiple non-commuting quantum mechanical ***,we introduce the concept of optimal observable sets and define the tightest uncertainty constants to accurately describe these measurement *** any quantum state,we establish optimal sets of three observables for both product and summation forms of uncertainty relations,and analytically derive the corresponding tightest uncertainty *** demonstrate that the optimality of these sets remains consistent regardless of the uncertainty relation ***,the existence of the tightest constants excludes the validity of standard real quantum mechanics,underscoring the essential role of complex numbers in this ***,our findings resolve the conjecture posed in[***.118,180402(2017)],offering novel insights and potential applications in understanding preparation uncertainties.

关键词： uncertainty relation the tightest uncertainty constants optimal observable sets

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Coati Optimization-Based Energy Efficient Routing Protocol for Unmanned Aerial Vehicle Communication

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computers, Materials & Continua 2023年第6期75卷 4805-4820页

作者： Hanan Abdullah Mengash Hamed Alqahtani Mohammed Maray Mohamed K.Nour Radwa Marzouk Mohammed Abdullah Al-Hagery Heba Mohsen Mesfer Al Duhayyim Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computer ScienceCenter of Artificial Intelligence and Unit of CybersecurityKing Khalid UniversityAbha62529Saudi Arabia Department of Information Systems College of Computer ScienceKing Khalid UniversityAbha62529Saudi Arabia Department of Computer Sciences College of Computing and Information SystemsUmm Al-Qura UniversityMecca24382Saudi Arabia Department of Computer Science College of ComputerQassim UniversityBuraydah52571Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

With the flexible deployment and high mobility of Unmanned Aerial Vehicles(UAVs)in an open environment,they have generated con-siderable attention in military and civil applications intending to enable ubiquitous connectivity and foster agile *** difficulty stems from features other than mobile ad-hoc network(MANET),namely aerial mobility in three-dimensional space and often changing *** the UAV network,a single node serves as a forwarding,transmitting,and receiving node at the same ***,the communication path is multi-hop,and routing significantly affects the network’s performance.A lot of effort should be invested in performance analysis for selecting the optimum routing *** this motivation,this study modelled a new Coati Optimization Algorithm-based Energy-Efficient Routing Process for Unmanned Aerial Vehicle Communication(COAER-UAVC)*** presented COAER-UAVC technique establishes effective routes for communication between the *** is primarily based on the coati characteristics in nature:if attacking and hunting iguanas and escaping from ***,the presented COAER-UAVC technique concentrates on the design of fitness functions to minimize energy utilization and communication delay.A varied group of simulations was performed to depict the optimum performance of the COAER-UAVC *** experimental results verified that the COAER-UAVC technique had assured improved performance over other approaches.

关键词： Artificial intelligence unmanned aerial vehicle data communication routing protocol energy efficiency

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PSO-CHS Routing Protocol for Energy Consumption Enhancement in Wireless Sensor Networks 4

PSO-CHS Routing Protocol for Energy Consumption Enhancement ...

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4th IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Fakhri, Israa Sabri Marhoon, Haydar Abdulameer Hussein, Mohsin Hasan College of Computer Science and Information Technology University of Kerbala Department of Computer Science Karbala Iraq Scientific Research Center Al-Ayen University Department of Computer Science Information and Communication Technology Research Group Thi-Qar Iraq

ISBN: (纸本)9798350352931

A region's Wireless sensor networks consist of sensors distributed over a region that collect and send environmental data to a central station. It measures humidity and temperature. The formation is based on many key ideas, including the routing system that optimizes data flow to the base station. Routing introduces limits and obstacles to better results. One challenge is choosing the cluster head, who aggregates data from nearby sensors and sends it to the base station. Many methods are used to choose the cluster head. Instead of GSTEB, DCBRP, and ETSRP, which are laborious and time-consuming, modern cluster head identification methods use artificial intelligence. This study selects the cluster head quickly and accurately using PSO-CHS (particle swarm optimization-Cluster Head Selection Routing Protocol). It improves execution time by 84.1%, delay matrix by 44.3%, and energy matrix by 80.4% over previous protocols. PSO-CHS design promotes energy efficiency, network durability, and packet loss reduction. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Classifying extended,localized and critical states in quasiperiodic lattices via unsupervised learning

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Chinese Physics B 2025年第1期34卷 422-427页

作者： Bohan Zheng Siyu Zhu Xingping Zhou Tong Liu School of Computer Science and Technology School of SoftwareNanjing University of Posts and TelecommunicationsNanjing 210023China Institute of Quantum Information and Technology Nanjing University of Posts and TelecommunicationsNanjing 210003China Department of Applied Physics School of ScienceNanjing University of Posts and TelecommunicationsNanjing 210003China

Classification of quantum phases is one of the most important areas of research in condensed matter *** this work,we obtain the phase diagram of one-dimensional quasiperiodic models via unsupervised ***,we choose two advanced unsupervised learning algorithms,namely,density-based spatial clustering of applications with noise(DBSCAN)and ordering points to identify the clustering structure(OPTICS),to explore the distinct phases of the Aubry–André–Harper model and the quasiperiodic p-wave *** unsupervised learning results match well with those obtained through traditional numerical ***,we assess similarity across different algorithms and find that the highest degree of similarity between the results of unsupervised learning algorithms and those of traditional algorithms exceeds 98%.Our work sheds light on applications of unsupervised learning for phase classification.

关键词： quantum phase quasiperiodic machine learning

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