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Prediction and Regulation of Delamination at Flexible Film/Finite-Thickness-Substrate Structure Interfaces

Acta Mechanica Solida Sinica 2024年第2期37卷 238-251页

作者： Yutang Zhou Yunlong Xu Haoran Gong Chenyu Wang department of engineering Mechanics Northwestern Polytechnical UniversityXi’an710072China School of instrumentation Science and Opto-electronics engineering Beihang UniversityBeijing100191China

Regulating the surface instability of thin film/substrate structures has been successfully applied to prepare new ductile electronic ***,such electronic devices need to be subjected to external loads during operation,which can easily induce delamination of the thin-film electronic device from the *** study aims to investigate the instability characteristics of hard films on flexible substrate surfaces from theoretical analysis and numerical simulation *** finite-thickness substrates,this paper establishes theoretical models for pure bending,bent wrinkle,partial delamination,and total delamination buckling of film/substrate structures based on the nonlinear Euler–Bernoulli beam theory and the principle of minimum energy;then the effects of material and geometric parameters of the structure,interfacial adhesion strength,and pre-strain on the evolutionary path of the four patterns are *** study results show that:the greater Young’s modulus of the substrate is,the larger the parameter region where partial delamination of the film/substrate structure occurs,and the smaller the parameter region where bent wrinkle *** varying Young’s modulus,thickness of the film and substrate,interfacial adhesion coefficient,and pre-strain,the buckling pattern of the structure can be predicted and *** parametric design intervals for each pattern are summarized in the phase *** results of this paper provide theoretical support for the design and reliability evaluation of flexible electronic devices.

关键词： Thin film/finite-thickness-substrate structure Delamination Surface instability Pattern evolution

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An efficient permutation approach for SbPN-based symmetric block ciphers

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Cybersecurity 2024年第2期7卷 113-130页

作者： Mir Nazish M.Tariq Banday Insha Syed Sheena Banday department of electronics and instrumentation Technology University ofKashmirSrinagar 190006India

It is challenging to devise lightweight cryptographic primitives efficient in both hardware and software that can provide an optimum level of security to diverse Internet of Things applications running on low-end constrained ***,an effcient hardware design approach that requires some specific hardware resource may not be effcient if implemented in *** bit Permutation Network based ciphers such as PRESENT and GIFT are effcient,lightweight cryptographic hardware design *** ciphers introduce confusion and diffu-sion by employing a 4×4 static substitution box and bit *** bit-wise permutation is realised by sim-ple rerouting,which is most cost-effective to implement in hardware,resulting in negligible power ***,this method is highly resource-consuming in software,particularly for large block-sized ciphers,with each single-bit permutation requiring multiple *** paper proposes a novel software-based design approach for permutation operation in Substitution bit Permutation Network based ciphers using a bit-banding *** conventional permutation using bit rotation and the proposed approach have been implemented,analysed and compared for GIFT and PRESENT ciphers on ARM Cortex-M3-based LPC1768 development platform with KEIL MDK used as an Integrated Development *** real-time performance comparison between conven-tional and the proposed approaches in terms of memory(RAM/ROM)footprint,power,energy and execution time has been carried out using ULINKpro and ULINKplus debug adapters for various code and speed optimisation *** proposed approach substantially reduces execution time,energy and power consumption for both PRE-SENT and GIFT ciphers,thus demonstrating the effciency of the proposed method for Substitution bit Permutation Network based symmetric block ciphers.

关键词： Lightweight cryptography PRESENT GIFT SbPN Cortex-M LPC1768 Bit-band memory

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Stochastic Ranking Improved Teaching-Learning and Adaptive Grasshopper Optimization Algorithm-Based Clustering Scheme for Augmenting Network Lifetime in WSNs

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China Communications 2024年第9期21卷 159-178页

作者： N Tamilarasan SB Lenin P Mukunthan NC Sendhilkumar department of electronics and Communications engineering Sri Indu College of Engineering and TechnologyHyderabadTelanganaIndia department of electronics and Communications engineering Sri Manakula Vinayagar Engineering CollegePondicherryIndia

In Wireless Sensor Networks(WSNs),Clustering process is widely utilized for increasing the lifespan with sustained energy stability during data *** clustering protocols were devised for extending network lifetime,but most of them failed in handling the problem of fixed clustering,static rounds,and inadequate Cluster Head(CH)selection criteria which consumes more *** this paper,Stochastic Ranking Improved Teaching-Learning and Adaptive Grasshopper Optimization Algorithm(SRITL-AGOA)-based Clustering Scheme for energy stabilization and extending network *** SRITL-AGOA selected CH depending on the weightage of factors such as node mobility degree,neighbour's density distance to sink,single-hop or multihop communication and Residual Energy(RE)that directly influences the energy consumption of sensor *** specific,Grasshopper Optimization Algorithm(GOA)is improved through tangent-based nonlinear strategy for enhancing the ability of global *** the other hand,stochastic ranking and violation constraint handling strategies are embedded into Teaching-Learning-based Optimization Algorithm(TLOA)for improving its exploitation ***,SR and VCH improved TLOA is embedded into the exploitation phase of AGOA for selecting better CH by maintaining better balance amid exploration and *** results confirmed that the proposed SRITL-AGOA improved throughput by 21.86%,network stability by 18.94%,load balancing by 16.14%with minimized energy depletion by19.21%,compared to the competitive CH selection approaches.

关键词： Adaptive Grasshopper Optimization Algorithm(AGOA) Cluster Head(CH) network lifetime Teaching-Learning-based Optimization Algorithm(TLOA) Wireless Sensor Networks(WSNs)

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A muon high-resolution pseudorange measurement method: Application to muon navigation in confined spaces

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Chinese Journal of Aeronautics 2024年第4期37卷 391-404页

作者： Haoyang LI Chunxi ZHANG Xingming FAN Longjie TIAN Tianqi LI Yang PANG Yanqiang YANG Institute of Optics and electronics School of Instrumentation Science and Optoelectronics EngineeringBeihang UniversityBeijing 100191China Institute of High Energy Physics Chinese Academy of SciencesBeijing 100049China

Confined spaces such as polar regions, deep earth and deep ocean are crucial navigation scenarios where traditional navigation techniques have difficulty in obtaining external signals for positioning. The cosmic ray muons, which carry the spatial and energetic information, are easy to penetrate these confined spaces. Therefore, the unique muon characteristic provides a new perspective to estimate detector position, which can be considered using in confined spaces *** this paper, a well-developed theory of muon navigation is established by combining a muon pseudorange measurement method. Moreover, an Equivalent Velocity Calculation Model(EVCM)and a Muon Sequence Matching Technology(MSMT) are proposed. The first model corrects flight pseudorange error caused by the relativistic energy loss and the second technology compensates the random error in pseudorange measurement. Further, a series of simulations are performed to analyze the muon events number which can be received by detector in different scenarios with the variations of zenith angle, detector area, varied detector plates gap, and muon flight ***, the simulation results demonstrate that the muon navigation update rate every 10 minutes can reach 5.989 in confined spaces at 100 m, and further pseudorange error analysis indicates that the meter-level positioning accuracy can be acquired. Finally, we construct a muon coincidence measurement scheme and verify that the laws of the muon positioning system for high-energy muons are consistent with the simulation results.

关键词： Muon navigation Cosmic ray muons Muon detection technology Muon transmission technology Pseudorange measurement

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Tailoring MXene Thickness and Functionalization for Enhanced Room‑Temperature Trace NO_(2) Sensing

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Nano-Micro Letters 2024年第5期16卷 71-86页

作者： Muhammad Hilal Woochul Yang Yongha Hwang Wanfeng Xie department of Physics Dongguk UniversitySeoul 04620Republic of Korea department of Control and instrumentation engineering Korea UniversitySejong 30019Republic of Korea School of electronics&Information University‑Industry Joint Center for Ocean Observation and Broadband CommunicationQingdao UniversityQingdao 266071China

In this study,precise control over the thickness and termination of Ti3C2TX MXene flakes is achieved to enhance their electrical properties,environmental stability,and gas-sensing *** a hybrid method involving high-pressure processing,stirring,and immiscible solutions,sub-100 nm MXene flake thickness is achieved within the MXene film on the *** control is achieved by defunctionalizing MXene at 650℃ under vacuum and H2 gas in a CVD furnace,followed by refunctionalization with iodine and bromine vaporization from a bubbler attached to the ***,the introduction of iodine,which has a larger atomic size,lower electronegativity,reduce shielding effect,and lower hydrophilicity(contact angle:99°),profoundly affecting *** improves the surface area(36.2 cm^(2) g^(-1)),oxidation stability in aqueous/ambient environments(21 days/80 days),and film conductivity(749 S m^(-1)).Additionally,it significantly enhances the gas-sensing performance,including the sensitivity(0.1119Ωppm^(-1)),response(0.2% and 23%to 50 ppb and 200 ppm NO_(2)),and response/recovery times(90/100 s).The reduced shielding effect of the–I-terminals and the metallic characteristics of MXene enhance the selectivity of I-MXene toward *** approach paves the way for the development of stable and high-performance gas-sensing two-dimensional materials with promising prospects for future studies.

关键词： Controlled MXene thickness Gaseous functionalization approach Lower electronegativity functional groups Enhanced MXene stability Trace NO_(2)sensing

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Cooperative THz communication for UAVs in 6G and beyond

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Green Energy and Intelligent Transportation 2024年第1期3卷 25-31页

作者： Nazifa Mustari Muhammet Ali Karabulut A.F.M.Shahen Shah Ufuk Tureli department of electronics and Communication engineering Yildiz Technical UniversityTurkey department of Electrical electronics engineering Faculty of Engineering and ArchitectureKafkas UniversityKarsTurkey

One of the key components of any smart city is considered to be its intelligent transportation systems(ITSs).Unmanned aerial vehicles(UAVs)are envisioned in several ITS application fields because of their autonomous operation,mobility,communication/processing capabilities,and other *** this paper,cooperative terahertz(THz)communication is proposed for flying ad hoc networks(FANETs),which is a particular kind of network made up of a collection of small UAVs linked in an ad hoc fashion and working together to accomplish high-level *** frequency spectrum for wireless communication has been expanding continuously in order to meet the demand for *** the forthcoming 6G and beyond,communications in the THz range will be vital,similar to how mmWave-band communications are currently influencing the 5G of wireless mobile *** finite state machine(FSM)of the proposed cooperative communication system for THz band is presented.A Markov chain model-based analytical study is carried out,which derives relationships among ***,numerical results are provided to support the analytical study.

关键词： Cooperative MAC THz UAVs 6G

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Fast Two-dimensional Positioning Method of Crab Pulsar Based on Multiple Optimization Algorithms

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Research in Astronomy and Astrophysics 2024年第10期24卷 92-103页

作者： Jianfeng Chen Jin Liu Xin Ma Xiaolin Ning College of Information Science and engineering Wuhan University of Science and TechnologyWuhan 430081China School of instrumentation Science and Opto-electronics engineering Beihang UniversityBeijing 100191China Hefei National Laboratory Hefei 230088China

In the two-dimensional positioning method of pulsars, the grid method is used to provide non-sensitive direction and positional estimates. However, the grid method has a high computational load and low accuracy due to the interval of the grid. To improve estimation accuracy and reduce the computational load, we propose a fast twodimensional positioning method for the crab pulsar based on multiple optimization algorithms(FTPCO). The FTPCO uses the Levenberg–Marquardt(LM) algorithm, three-point orientation(TPO) method, particle swarm optimization(PSO) and Newton–Raphson-based optimizer(NRBO) to substitute the grid method. First, to avoid the influence of the non-sensitive direction on positioning, we take an orbital error and the distortion of the pulsar profile as optimization objectives and combine the grid method with the LM algorithm or PSO to search for the non-sensitive direction. Then, on the sensitive plane perpendicular to the non-sensitive direction, the TPO method is proposed to fast search the sensitive direction and sub-sensitive direction. Finally, the NRBO is employed on the sensitive and sub-sensitive directions to achieve two-dimensional positioning of the Crab pulsar. The simulation results show that the computational load of the FTPCO is reduced by 89.4% and the positioning accuracy of the FTPCO is improved by approximately 38% compared with the grid method. The FTPCO has the advantage of high real-time accuracy and does not fall into the local optimum.

关键词： (stars:)pulsars:individual(Crab pulsar) space vehicles methods:data analysis astrometry

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Design of Digital Filters for Medical Images Using Optimized Learning Based Multi-Level Discrete Wavelet Cascaded Convolutional Neural Network

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Journal of Harbin Institute of Technology(New series) 2024年

作者： Vaibhav Jain Ashutosh Datar Yogendra Kumar Jain department of electronics and instrumentation engineering， Rajiv Gandhi Proudyogiki Vishwavidyalaya department of electronics engineering， Samrat Ashok Technological Institute

In digital signal processing， image enhancement or image denoising are challenging task to preserve pixel quality. There are several approaches from conventional to deep learning that are used to resolve such issues. But they still face challenges in terms of computational requirements， overfitting and generalization issues， etc. To resolve such issues， optimization algorithms provide greater control and transparency in designing digital filters for image enhancement and denoising. Therefore， the paper presented a novel denoising approach for medical applications using an Optimized Learning-based Multi-level Discrete Wavelet Cascaded Convolutional Neural Network (OLMWCNN). In this approach， the optimal filter parameters are identified to preserve the image quality after denoising. The performance and efficiency of the OLMWCNN filter are evaluated， demonstrating significant progress in denoising medical images while overcoming the limitations of conventional methods.

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Dielectric size optimization for high power density in large-scale triboelectric nanogenerators

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Nano Research 2024年第9期17卷 8455-8464页

作者： Abdulkerim Karabiber Ömer Dirik Feyyaz Koc Faruk Ozel department of Electrical and electronics engineering Bingol UniversityBingol 12000Turkey department of Metallurgical and Materials engineering Karamanoglu Mehmetbey UniversityKaraman 70200Turkey

Triboelectric nanogenerators(TENGs)have emerged as a promising technology to harvest electrical energy from natural motions such as human movement,wind,and water *** TENGs show significant potential in small-scale applications,developing large-scale TENGs capable of generating high power remains a significant *** factors that can affect the performance of large-scale TENGs are being investigated to overcome this challenge,including the size and configuration of dielectric *** study optimizes dielectrics regarding surface area,thickness,and multicell configuration to improve harvested electrical power density in large-scale *** the studies,glass fiber was used as the positive dielectric,and multipurpose white silicone was used as the negative dielectric because of their high tribo-potential,durability,and easy *** the size optimization phase,dielectric thicknesses and surface areas that provide the maximum power density were ***,horizontal and vertical multicell configurations were examined to efficiently integrate size-optimized *** results reveal that large-scale TENGs with vertical multicell configurations can achieve high and usable energy density for *** findings provide valuable insight into the development of large-scale TENGs with advanced power generation capabilities.

关键词： triboelectric nanogenerator dielectric layer size optimization multi-cell structure high power density

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An Intelligent Big Data Security Framework Based on AEFS-KENN Algorithms for the Detection of Cyber-Attacks from Smart Grid Systems

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Big Data Mining and Analytics 2024年第2期7卷 399-418页

作者： Sankaramoorthy Muthubalaji Naresh Kumar Muniyaraj Sarvade Pedda Venkata Subba Rao Kavitha Thandapani Pasupuleti Rama Mohan Thangam Somasundaram Yousef Farhaoui department of Electrical and electronics engineering CMR College of Engineering&TechnologyHyderabad 501401India department of electronics and Communication engineering Vardhaman College of Engineering KacharamShamshabad 501218India department of electronics and Communication engineering Sreenidhi Institute of Science and TechnologyHyderabad 501301India department of electronics and Communication engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai 600062India department of Electrical and electronics engineering Bharat Institute of Engineering and TechnologyHyderabad 501510India department of Computer Science and engineering Amrita School of ComputingAmrita Vishwa VidhyapeethamBengaluru 560035India T-IDMS Department of Computer ScienceFaculty of Sciences and TechniquesMoulay Ismail UniversityErrachidia 52000Morocco

Big data has the ability to open up innovative and ground-breaking prospects for the electrical grid,which also supports to obtain a variety of technological,social,and financial *** is an unprecedented amount of heterogeneous big data as a consequence of the growth of power grid technologies,along with data processing and advanced *** main obstacles in turning the heterogeneous large dataset into useful results are computational burden and information *** original contribution of this paper is to develop a new big data framework for detecting various intrusions from the smart grid systems with the use of AI ***,an AdaBelief Exponential Feature Selection(AEFS)technique is used to efficiently handle the input huge datasets from the smart grid for boosting ***,a Kernel based Extreme Neural Network(KENN)technique is used to anticipate security vulnerabilities more *** Polar Bear Optimization(PBO)algorithm is used to efficiently determine the parameters for the estimate of radial basis ***,several types of smart grid network datasets are employed during analysis in order to examine the outcomes and efficiency of the proposed AdaBelief Exponential Feature Selection-Kernel based Extreme Neural Network(AEFS-KENN)big data security *** results reveal that the accuracy of proposed AEFS-KENN is increased up to 99.5%with precision and AUC of 99%for all smart grid big datasets used in this study.

关键词： smart grid Machine Learning(ML) big data analytics AdaBelief Exponential Feature Selection(AEFS) Polar Bear Optimization(PBO) Kernel Extreme Neural Network(KENN)

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