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Falcon Optimization Algorithm-Based Energy Efficient communication Protocol for Cluster-Based Vehicular networks

Computers, Materials & Continua 2024年第3期78卷 4243-4262页

作者： Youseef Alotaibi B.Rajasekar R.Jayalakshmi Surendran Rajendran department of Software Engineering College of ComputingUmm Al-Qura UniversityMakkah21955Saudi Arabia department of Electronics and communication Engineering Sathyabama Institute of Science and TechnologyChennai600119India department of Computer Science and Engineering Panimalar Engineering CollegeChennai600123India department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical ScienceChennai602105India

Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)*** networks give a safe and more effective driving experience by presenting time-sensitive and location-aware *** communication occurs directly between V2V and Base Station(BS)units such as the Road Side Unit(RSU),named as a Vehicle to Infrastructure(V2I).However,the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with ***,the scheme of an effectual routing protocol for reliable and stable communications is *** research demonstrates that clustering is an intelligent method for effectual routing in a mobile ***,this article presents a Falcon Optimization Algorithm-based Energy Efficient communication Protocol for Cluster-based Routing(FOA-EECPCR)technique in *** FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the *** accomplish this,the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy,distance,and trust *** the routing process,the Sparrow Search Algorithm(SSA)is derived with a fitness function that encompasses two variables,namely,energy and distance.A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR *** experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods.

关键词： Vehicular networks communication protocol clustering falcon optimization algorithm routing

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Low-cost,large-coverage,and high-flexibility coherent PON for next-generation access networks:advances,challenges,and prospects[Invited]

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Chinese Optics Letters 2024年第4期22卷 26-35页

作者：邢思哲张俊文申王伟颜安李国强孙奥龙周骥郭栋施剑阳李子薇沈超迟楠 Key Laboratory of EMW Information(MoE) Fudan UniversityShanghai 200433China department of communication Science and Engineering Shanghai ERC of LEO Satellite Communication and ApplicationsShanghai CIC of LEO Satellite Communication TechnologyFudan UniversityShanghai 200433China department of Electronic Engineering Jinan UniversityGuangzhou 510632China School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China

Increasing bandwidth requirements have posed significant challenges for traditional access *** is difficult for intensity modulation/direct detection to meet the power budget and flexibility requirements of the next-generation passive optical network(PON)at 100G and beyond considering the new *** is driving researchers to develop novel optical access ***-cost,wide-coverage,and high-flexibility coherent PON is emerging as a strong contender in the *** this article,we will review technologies that reduce the complexity of coherent PON(CPON),enabling it to meet the commercial ***,advanced algorithms and architectures that can enhance system coverage and flexibility are also discussed.

关键词： access network coherent optics flexible data rate low complexity wide dynamic range

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Pure-high-even-order dispersion bound solitons complexes in ultra-fast fiber lasers

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Light(Science & Applications) 2024年第5期13卷 957-972页

作者： Ying Han Bo Gao Honglin Wen Chunyang Ma Jiayu Huo Yingying Li Luyao Zhou Qi Li Ge Wu Lie Liu College of communication Engineering Jilin UniversityChangchun 130012China. Research Center of Circuits and systems Peng Cheng LaboratoryShenzhen 518055China. International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology of Ministry of Education Institute of Microscale OptoelectronicsShenzhen UniversityShenzhen 518060China. College of Electronic Science and Engineering Jilin UniversityChangchun 130012China

Temporal solitons have been the focus of much research due to their fascinating physical *** solitons can form bound states,which are fundamentally crucial modes in fiber laser and present striking analogies with their matter molecules counterparts,which means they have potential applications in large-capacity transmission and alloptical information *** traditionally,second-order dispersion has been the dominant dispersion for conventional solitons,recent experimental and theoretical research has shown that pure-high-even-order dispersion(PHEOD)solitons with energy-width scaling can arise from the interaction of arbitrary negative-even-order dispersion and Kerr *** these advancements,research on the bound states of PHEOD solitons is currently *** this study,we obtained PHEOD bound solitons in a fiber laser using an intra-cavity spectral pulse shaper for high-order dispersion ***,we experimentally demonstrate the existence of PHEOD solitons and PHEOD bound solitons with pure-quartic,-sextic,-octic,and-decic *** simulations corroborate these experimental ***,vibrating phase PHEOD bound soliton pairs,sliding phase PHEOD bound soliton pairs,and hybrid phase PHEOD bound tri-soliton are discovered and *** results broaden the fundamental understanding of solitons and show the universality of multi-soliton patterns.

关键词： dispersion solitons soliton

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Multi-layer network embedding on scc-based network with motif

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Digital communications and networks 2024年第3期10卷 546-556页

作者： Lu Sun Xiaona Li Mingyue Zhang Liangtian Wan Yun Lin Xianpeng Wang Gang Xu department of communication Engineering Institute of Information Science TechnologyDalian Maritime UniversityDalian116026China Key Laboratory of Big Data Intelligent Computing Chongqing University of Posts and TelecommunicationsChongqing400065China Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province DUT School of Software Technology&DUT-RU International School of Information Science and EngineeringDalian University of TechnologyDalian 116620China College of Information and communication Engineering Harbin Engineering UniversityHarbin 150001China School of Information and communication Engineering Hainan UniversityHaikou 570228China State Key Laboratory of Millimeter Waves School of Information Science and EngineeringSoutheast UniversityNanjing 210096China

Interconnection of all things challenges the traditional communication methods,and Semantic communication and Computing(SCC)will become new *** is a challenging task to accurately detect,extract,and represent semantic information in the research of SCC-based *** previous research,researchers usually use convolution to extract the feature information of a graph and perform the corresponding task of node ***,the content of semantic information is quite *** graph convolutional neural networks provide an effective solution for node classification tasks,due to their limitations in representing multiple relational patterns and not recognizing and analyzing higher-order local structures,the extracted feature information is subject to varying degrees of ***,this paper extends from a single-layer topology network to a multi-layer heterogeneous topology *** Bidirectional Encoder Representations from Transformers(BERT)training word vector is introduced to extract the semantic features in the network,and the existing graph neural network is improved by combining the higher-order local feature module of the network model representation network.A multi-layer network embedding algorithm on SCC-based networks with motifs is proposed to complete the task of end-to-end node *** verify the effectiveness of the algorithm on a real multi-layer heterogeneous network.

关键词： Semantic communication and computing Multi-layer network Graph neural network Motif

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Enhancing Human Action Recognition with Adaptive Hybrid Deep Attentive networks and Archerfish Optimization

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Computers, Materials & Continua 2024年第9期80卷 4791-4812页

作者： Ahmad Yahiya Ahmad Bani Ahmad Jafar Alzubi Sophers James Vincent Omollo Nyangaresi Chanthirasekaran Kutralakani Anguraju Krishnan department of Accounting and Finance Faculty of BusinessMiddle East UniversityAmman11831Jordan Faculty of Engineering Al-Balqa Applied UniversitySalt19117Jordan department of Mathematics Kongunadu College of Engineering and Technology(Autonomous)TholurpattiTrichy621215India department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and TechnologyBondo210-40601Kenya department of Electronics and communication Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai602105India department of Electronics and communication Engineering Saveetha Engineering College(Autonomous)Chennai602105India department of Computer Science and Engineering Kongunadu College of Engineering and Technology(Autonomous)TholurpattiTrichy621215India

In recent years,wearable devices-based Human Activity Recognition(HAR)models have received significant *** developed HAR models use hand-crafted features to recognize human activities,leading to the extraction of basic *** images captured by wearable sensors contain advanced features,allowing them to be analyzed by deep learning algorithms to enhance the detection and recognition of human *** lighting and limited sensor capabilities can impact data quality,making the recognition of human actions a challenging *** unimodal-based HAR approaches are not suitable in a real-time ***,an updated HAR model is developed using multiple types of data and an advanced deep-learning ***,the required signals and sensor data are accumulated from the standard *** these signals,the wave features are *** the extracted wave features and sensor data are given as the input to recognize the human *** Adaptive Hybrid Deep Attentive Network(AHDAN)is developed by incorporating a“1D Convolutional Neural Network(1DCNN)”with a“Gated Recurrent Unit(GRU)”for the human activity recognition ***,the Enhanced Archerfish Hunting Optimizer(EAHO)is suggested to fine-tune the network parameters for enhancing the recognition *** experimental evaluation is performed on various deep learning networks and heuristic algorithms to confirm the effectiveness of the proposed HAR *** EAHO-based HAR model outperforms traditional deep learning networks with an accuracy of 95.36,95.25 for recall,95.48 for specificity,and 95.47 for precision,*** result proved that the developed model is effective in recognizing human action by taking less ***,it reduces the computation complexity and overfitting issue through using an optimization approach.

关键词： Human action recognition multi-modal sensor data and signals adaptive hybrid deep attentive network enhanced archerfish hunting optimizer 1D convolutional neural network gated recurrent units

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Nonlinear Filtering With Sample-Based Approximation Under Constrained communication:Progress, Insights and Trends

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IEEE/CAA Journal of Automatica Sinica 2024年第07期11卷 1539-1556页

作者： Weihao Song Zidong Wang Zhongkui Li Jianan Wang Qing-Long Han IEEE the State Key Laboratory for Turbulence and Complex systems Department of Mechanics and Engineering ScienceCollege of Engineering Peking University the department of Computer Science Brunel University London the School of Aerospace Engineering Beijing Institute of Technology the School of Science Computing and Engineering Technologies Swinburne University of Technology

The nonlinear filtering problem has enduringly been an active research topic in both academia and industry due to its ever-growing theoretical importance and practical *** main objective of nonlinear filtering is to infer the states of a nonlinear dynamical system of interest based on the available noisy measurements. In recent years, the advance of network communication technology has not only popularized the networked systems with apparent advantages in terms of installation,cost and maintenance, but also brought about a series of challenges to the design of nonlinear filtering algorithms, among which the communication constraint has been recognized as a dominating concern. In this context, a great number of investigations have been launched towards the networked nonlinear filtering problem with communication constraints, and many samplebased nonlinear filters have been developed to deal with the highly nonlinear and/or non-Gaussian scenarios. The aim of this paper is to provide a timely survey about the recent advances on the sample-based networked nonlinear filtering problem from the perspective of communication constraints. More specifically, we first review three important families of sample-based filtering methods known as the unscented Kalman filter, particle filter,and maximum correntropy filter. Then, the latest developments are surveyed with stress on the topics regarding incomplete/imperfect information, limited resources and cyber ***, several challenges and open problems are highlighted to shed some lights on the possible trends of future research in this realm.

关键词： communication constraints maximum correntropy filter networked nonlinear filtering particle filter sample-based approximation unscented Kalman filter

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Layered Coded Cache Placement and Cooperative Delivery with Sharing Links in Satellite-Terrestrial Integrated networks

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China communications 2024年第3期21卷 217-229页

作者： Gu Shushi Chen Zihan Wu Yaonan Zhang Qinyu Wang Ye School of Electronic and Information Engineering Harbin Institute of Technology(Shenzhen)Shenzhen 518055China Guangdong Provincial Key Laboratory of Aerospace communication and Networking Technology Shenzhen 518055China Broadband communications Research department Pengcheng LaboratoryShenzhen 518052China

Cooperative utilization of multidimensional resources including cache, power and spectrum in satellite-terrestrial integrated networks(STINs) can provide a feasible approach for massive streaming media content delivery over the seamless global coverage area. However, the on-board supportable resources of a single satellite are extremely limited and lack of interaction with others. In this paper, we design a network model with two-layered cache deployment, i.e., satellite layer and ground base station layer, and two types of sharing links, i.e., terrestrial-satellite sharing(TSS) links and inter-satellite sharing(ISS) links, to enhance the capability of cooperative delivery over STINs. Thus, we use rateless codes for the content divided-packet transmission, and derive the total energy efficiency(EE) in the whole transmission procedure, which is defined as the ratio of traffic offloading and energy consumption. We formulate two optimization problems about maximizing EE in different sharing scenarios(only TSS and TSS-ISS),and propose two optimized algorithms to obtain the optimal content placement matrixes, *** results demonstrate that, enabling sharing links with optimized cache placement have more than 2 times improvement of EE performance than other traditional placement schemes. Particularly, TSS-ISS schemes have the higher EE performance than only TSS schemes under the conditions of enough number of satellites and smaller inter-satellite distances.

关键词： coded content placement cooperative delivery energy efficiency sharing links STINs

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All-optical amplitude-shift keying and differential phase-shift keying to differential phase amplitude-shift keying format combination in highly nonlinear fiber

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Chinese Optics Letters 2009年第7期7卷 564-567页

作者：吴琳张德朝张帆陈章渊徐安士 State Key Laboratory of Advanced Optical communication systems and networks Electronics Department Peking University

We propose an all-optical modulation formats combination scheme that merges an amplitude-shift keying （ASK） signal and a differential phase-shift keying （DPSK） signal into a single differential phase amplitude- shift keying （DPASK） signal based on parametric amplification in a highly nonlinear fiber. By optimizing the power of the ASK channel, formats combination of ASK and DPSK to DPASK signal is successfully demonstrated by computational simulation. The demodulation process of the generated DPASK pulses is investigated and the relationship between optical signal-to-noise ratio （OSNR） penalty and the input ASK power is presented. The proposed scheme may be used for increasing spectral efficiency and all-optical logic device.

关键词： Amplification Light modulation Logic devices Optical devices Phase shift Phase shift keying Signal to noise ratio Spectrum analyzers

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Optimal coordination of zero carbon building energy systems

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National Science Open 2024年第3期3卷 13-28页

作者： Wangyi Guo Zhanbo Xu Jinhui Liu Yaping Liu Jiang Wu Kun Liu Xiaohong Guan School of Future Technology Xi'an Jiaotong University Ministry of Education Key Lab for Intelligent networks and Network Security School of Automation Science and EngineeringXi'an Jiaotong University Center for Intelligent and Networked systems Department of AutomationTNLISTTsinghua University

Optimal scheduling of renewable energy sources and building energy systems serves as a pivotal strategy for achieving zero carbon ***,the coordination of zero carbon building energy systems(ZCBS) is still challenging due to the complicated interactions among multi-energy hybrid storage and the complex coordination between seasonal and daily ***,this study develops a coordination scheduling approach for *** operation model and a seasonal-daily scheduling approach are developed to optimize the operation of hydrogen,geothermal,and water storage *** performance of the developed method is demonstrated using numerical case *** results show that the ZCBS can be achieved by using renewable energy sources with the system flexibility provided by hydrogen,geothermal,and water storage *** is also found that the developed scheduling approach reduces operation costs by more than 43.4%under the same device capacity,compared with existing scheduling approaches.

关键词： zero carbon building energy systems seasonal-daily scheduling multi-energy storage two-stage robust optimization

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Improving Prediction of Chronic Kidney Disease Using KNN Imputed SMOTE Features and TrioNet Model

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 3513-3534页

作者： Nazik Alturki Abdulaziz Altamimi Muhammad Umer Oumaima Saidani Amal Alshardan Shtwai Alsubai Marwan Omar Imran Ashraf department of Information systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia department College of Computer Science and Engineering University of Hafr Al-BatinHafarAl-Batin39524Saudi Arabia department of Computer Science&Information Technology The Islamia University of BahawalpurP.O.Box 63100BahawalpurPakistan department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia Information Technology and Management Illinois Institute of TechnologyChicagoIL 60616-3793USA Information and communication Engineering Yeungnam UniversityGyeongsan38541Korea

Chronic kidney disease(CKD)is a major health concern today,requiring early and accurate *** learning has emerged as a powerful tool for disease detection,and medical professionals are increasingly using ML classifier algorithms to identify CKD *** study explores the application of advanced machine learning techniques on a CKD dataset obtained from the University of California,UC Irvine Machine Learning *** research introduces TrioNet,an ensemble model combining extreme gradient boosting,random forest,and extra tree classifier,which excels in providing highly accurate predictions for ***,K nearest neighbor(KNN)imputer is utilized to deal withmissing values while synthetic minority oversampling(SMOTE)is used for class-imbalance *** ascertain the efficacy of the proposed model,a comprehensive comparative analysis is conducted with various machine learning *** proposed TrioNet using KNN imputer and SMOTE outperformed other models with 98.97%accuracy for *** in-depth analysis demonstrates the model’s capabilities and underscores its potential as a valuable tool in the diagnosis of CKD.

关键词： Precisionmedicine chronic kidney disease detection SMOTE missing values healthcare KNNimputer ensemble learning

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