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Systematic Cloud-Based Optimization: Twin-Fold Moth Flame Algorithm for VM Deployment and Load-Balancing

Intelligent automation & Soft Computing 2024年第3期39卷 477-510页

作者： Umer Nauman Yuhong zhang zhihui Li Tong Zhen Information Science and engineering College Henan University of TechnologyZhengzhou450001China School of Artificial Intelligence and Big Data Henan University of TechnologyZhengzhou450001China Key Laboratory of Grain Information Processing and Control Ministry of EducationHenan University of TechnologyZhengzhou450001China

Cloud computing has gained significant recognition due to its ability to provide a broad range of online services and ***,existing commercial cloud computing models demonstrate an appropriate design by concentrating computational assets,such as preservation and server infrastructure,in a limited number of large-scale worldwide data *** the deployment of virtual machines(VMs)is crucial in this scenario to ensure system dependability,performance,and minimal latency.A significant barrier in the present scenario is the load distribution,particularly when striving for improved energy consumption in a hypothetical grid computing *** design employs load-balancing techniques to allocate different user workloads across several virtual *** address this challenge,we propose using the twin-fold moth flame technique,which serves as a very effective optimization *** intentionally designed the twin-fold moth flame method to consider various restrictions,including energy efficiency,lifespan analysis,and resource *** provides a thorough approach to evaluating total costs in the cloud computing *** assessing the efficacy of our suggested strategy,the study will analyze significant metrics such as energy efficiency,lifespan analysis,and resource *** investigation aims to enhance cloud computing techniques by developing a new optimization algorithm that considers multiple factors for effective virtual machine placement and load *** proposed work demonstrates notable improvements of 12.15%,10.68%,8.70%,13.29%,18.46%,and 33.39%for 40 count data of nodes using the artificial bee colony-bat algorithm,ant colony optimization,crow search algorithm,krill herd,whale optimization genetic algorithm,and improved Lévy-based whale optimization algorithm,respectively.

关键词： Optimizing cloud computing deployment of virtual machines load-balancing twin-fold moth flame algorithm grid computing computational resource distribution data virtualization

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Memristive feature and mechanism induced by laser-doping in defect-free 2D semiconductor materials

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Journal of Semiconductors 2024年第7期45卷 85-91页

作者： Xiaoshan Du Shu Wang Qiaoxuan zhang Shengyao Chen Fengyou Yang Zhenzhou Liu Zhengwei Fan Lijun Ma Lei Wang Lena Du Zhongchang Wang Cong Wang Bing Chen Qian Liu College of Electronic and Information engineering Shandong University of Science and TechnologyQingdao 266590China National Center for Nanoscience and Technology&university of Chinese Academy of Sciences Beijing 100190China Hebei university of Water Resources and Electric engineering Electrical automation department Cangzhou 061001China The MOE Key Laboratory of Weak-Light Nonlinear Photonics and International Sino-Slovenian Join Re-search Center on Liquid Crystal Pho-tonics TEDA Institute of Applied Physics and School of PhysicsNankai UniversityTianjin 300457China College of Mathematics and Physics Shandong Advanced Optoelectronic Materials and Technologies Engineering LaboratoryQingdao Uni-versity of Science and TechnologyQingdao 266061China department of Physics Capital Normal UniversityBeijing 100048China department of Advanced Materials and Computing International Iberian Nanotechnology Laboratory(INL)4715-330 BragaPortugal College of Mathematics and Physics Beijing University of Chemical TechnologyBeijing 100029China

Memristors as non-volatile memory devices have gained numerous attentions owing to their advantages in storage,in-memory computing, synaptic applications, etc. In recent years, two-dimensional(2D) materials with moderate defects have been discovered to exist memristive feature. However, it is very difficult to obtain moderate defect degree in 2D materials, and studied on modulation means and mechanism becomes urgent and essential. In this work, we realized memristive feature with a bipolar switching and a configurable on/off ratio in a two-terminal MoS_(2) device(on/off ratio ~100), for the first time, from absent to present using laser-modulation to few-layer defect-free MoS_(2)(about 10 layers), and its retention time in both high resistance state and low resistance state can reach 2×10^(4) s. The mechanism of the laser-induced memristive feature has been cleared by dynamic Monte Carlo simulations and first-principles calculations. Furthermore, we verified the universality of the laser-modulation by investigating other 2D materials of TMDs. Our work will open a route to modulate and optimize the performance of 2D semiconductor memristive devices.

关键词： 2D-material memristor laser doping laser direct writing memristive mechanism

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时延Hopfield神经网络稳定性分析

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系统工程与电子技术 2003年第3期25卷 323-325页

作者：张帆慕春棣曹喜滨邹经湘清华大学计算机科学与技术系北京100084 清华大学自动化系北京100084 哈尔滨工业大学航天工程与力学系黑龙江哈尔滨150001

根据李亚普诺夫稳定函数建立了时延神经网络渐近稳定性判据的充分条件。给出了其详细的证明及其3个推论。该判据实用性很强,不仅适用于对称和不对称的关联矩阵,而且适用于零增益的激励函数。通过两个例子表明这个判据比已有的一些判据... 详细信息

根据李亚普诺夫稳定函数建立了时延神经网络渐近稳定性判据的充分条件。给出了其详细的证明及其3个推论。该判据实用性很强,不仅适用于对称和不对称的关联矩阵,而且适用于零增益的激励函数。通过两个例子表明这个判据比已有的一些判据更积极,更具有实用性。

关键词： Hopfield神经网络渐近稳定时延神经网络稳定性李亚普诺夫函数

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Adaptive Control of MIMO Nonlinear Systems with Disturbances and Time Delays

Adaptive Control of MIMO Nonlinear Systems with Disturbances...

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2010 Chinese Control and Decision Conference

作者： Qiuqin zhu~1,Tianping zhang~1,Baicheng zhu~1 1.department of automation,College of Information engineering,Yangzhou university,Yangzhou 225009,china

＜正＞Based on the principle of sliding mode control,an adaptive control scheme is proposed for a class of multiinput multi-output（MIMO） nonlinear time-varying delay systems with unknown dis *** networks are used to approximate the unknown nonlinear *** choosing appropriate Lyapunov-Krasovskii functionals,unknown time-varying delay uncertainties are compensated *** utilizing the integral-type Lyapunov function and Young’s inequality,the restrictions of the control gain and the assumptions of time-varying delay uncertainties are *** theoretical analysis,it is shown that all the signals in the closed-loop system are uniformly ultimately ***, simulation results are provided to illustrate the effectiveness of the proposed app oach.

关键词： Adaptive control Neural control Time-varying delay Sliding mode control

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Spatial and Contextual Path Network for Image Inpainting

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Intelligent automation & Soft Computing 2024年第2期39卷 115-133页

作者： Dengyong zhang Yuting Zhao Feng Li Arun Kumar Sangaiah Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and TechnologyChangsha410114China School of Computer and Communication engineering Changsha University of Science and TechnologyChangsha410114China International Graduate Institute of AI National Yunlin University of Science and TechnologyYunlinTaiwan department of Electrical and Computer engineering Lebanese American UniversityByblosLebanon

Image inpainting is a kind of use known area of information technology to repair the loss or damage to the *** feature extraction is the core of image *** enough space for information and a larger receptive field is very important to realize high-precision image ***,in the process of feature extraction,it is difficult to meet the two requirements of obtaining sufficient spatial information and large receptive fields at the same *** order to obtain more spatial information and a larger receptive field at the same time,we put forward a kind of image restoration based on space path and context path *** the space path,we stack three convolution layers for 1/8 of the figure,the figure retained the rich spatial *** the context path,we use the global average pooling layer,where the accept field is the maximum of the backbone network,and the pooling module can provide global context information for the maximum accept *** order to better integrate the features extracted from the spatial and contextual paths,we study the fusion module of the two *** fusionmodule first path output of the space and context path,and then through themass normalization to balance the scale of the characteristics,finally the characteristics of the pool will be connected into a feature vector and calculate the weight *** of images in order to extract context information,we add attention to the context path refinement *** modules respectively from channel dimension and space dimension to weighted images,in order to obtain more effective *** show that our method is better than the existing technology in the quality and quantity of themethod,and further to expand our network to other inpainting networks,in order to achieve consistent performance improvements.

关键词： Image inpainting attention deep learning convolutional network

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Wearable Observation Supporting System for Face Identification based on Wearable Camera

Wearable Observation Supporting System for Face Identificati...

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2010 3rd IEEE International Conference on Computer Science and Information Technology—ICCSIT 2010

作者： Lu Han and Zushu Li department of automation Chongqing university Chongqing 400044 china Heng zhang and Dongyi Chen School of automation engineering university of Electronic Science and Technology of china Chengdu 610054 china

Introduces a prototype of wearable observation supporting system for helping human complete the observation and recognition tasks based on wearable camera. The research presented here addresses special challenge problems encountered in wearable computing environment. The implementation of new architecture and system process flow with functions will help the wearers real-time face detection, recognition and identification. The algorithm begins with capturing sufficient quality video frames from wearable camera followed by interested object detection and recognition. We demonstrate effectiveness and the feasibility of this system by experimental results.

关键词： wearable computing wearable camera face identification wearable assistant observation supporting system.

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Adaptive Neural Tracking Control of Pure-feedback Nonlinear Systems

Adaptive Neural Tracking Control of Pure-feedback Nonlinear ...

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第24届中国控制与决策会议

作者： Tianping zhang, Baicheng zhu and Xiaocheng Shi the department of automation, College of Information engineering, Yangzhou university, Yangzhou 225127, P. R. china

In this paper, an novel adaptive tracking con- trol is developed for a class of completely non-affine pure- feedback nonlinear systems using radial basis function neural networks (RBFNNs). Combining the dynamic surface control (DSC) technique and backstepping method, the explosion of complexity in the traditional backstepping design is avoided. Using mean value theorem and Young’s inequality, only one learning parameter need to be tuned online in the whole controller design, and the computational burden is effectively alleviated. It is proved that the proposed design method is able to guarantee semi-global uniform ultimate boundedness (SGUUB) of all signals in the closed-loop system. Simulation results verify the effectiveness of the proposed approach.

关键词： Adaptive Control Neural Networks Dynamic Surface Control Pure-Feedback Nonlinear Systems

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用于电容层析成像技术的共轭梯度算法

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天津大学学报（自然科学与工程技术版） 2005年第1期38卷 1-4页

作者：王化祥朱学明张立峰天津大学电气与自动化工程学院天津300072 华北电力大学自动化系保定071003

针对电容层析成像技术中的“软场”效应和病定问题,基于灵敏度矩阵的奇异值分解理论,提出共轭梯度图像重建算法及其改进算法———正则化共轭梯度法.仿真实验得知:经过 200次迭代后,Landweber算法残差为0. 139 5,未加正则化的共轭梯度... 详细信息

针对电容层析成像技术中的“软场”效应和病定问题,基于灵敏度矩阵的奇异值分解理论,提出共轭梯度图像重建算法及其改进算法———正则化共轭梯度法.仿真实验得知:经过 200次迭代后,Landweber算法残差为0. 139 5,未加正则化的共轭梯度算法残差为 1. 357 7×10-4;完成同样操作,Landweber算法迭代耗时 9. 3s,共轭梯度法只需 6. 8s.可见,共轭梯度法是一种比其他的迭代算法收敛更快、成像效果更好的图像重建算法.

关键词：电容层析成像灵敏度矩阵共轭梯度法正则化奇异值分解

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Multi-Channel Based on Attention Network for Infrared Small Target Detection

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Journal of Shanghai Jiaotong university(Science) 2024年第3期29卷 414-427页

作者：张彦军王碧云蔡云泽 department of automation Shanghai Jiao Tong UniversityShanghai 200240China Shanghai Institute of Aerospace Control Technology Shanghai 201109China Infrared Detection Technology R&D Center of china Aerospace Science and Technology Corporation Shanghai 201109China Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai 200240China Shanghai engineering Research Center of Intelligent Control and Management Shanghai 200240China Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong UniversityShanghai 200240China Institute of Marine Equipment Shanghai Jiao Tong UniversityShanghai 200240China

Infrared detection technology has the advantages of all-weather detection and good concealment,which is widely used in long-distance target detection and tracking ***,the complex background,the strong noise,and the characteristics of small scale and weak intensity of targets bring great difficulties to the detection of infrared small targets.A multi-channel based on attention network is proposed in this paper,aimed at the problem of high missed detection rate and false alarm rate of traditional algorithms and the problem of large model,high complexity and poor detection performance of deep learning ***,given the difficulty in extracting the features of infrared multiscale and small dim targets,the multiple channels are designed based on dilated convolution to capture multiscale target ***,the coordinate attention block is incorporated in each channel to suppress background clutters adaptively and enhance target *** addition,the fusion of shallow detail features and deep abstract semantic features is realized by synthesizing the contextual attention fusion ***,it is verified that,compared with other state-of-the-art methods based on the datasets SIRST and MDFA,the proposed algorithm further improves the detection effect,and the model size and computational complexity are smaller.

关键词： infrared image small target detection deep learning attention mechanism feature fusion

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New development thoughts on the bio-inspired intelligence based control for unmanned combat aerial vehicle

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Science china(Technological Sciences) 2010年第8期53卷 2025-2031页

作者： DUAN HaiBin 1 ,SHAO Shan 2 ,SU BingWei 3 &zhang Lei 41 State Key Laboratory of Science and Technology on Holistic Flight Control,School of automation Science and Electrical engineering, Beijing university of Aeronautics and Astronautics,Beijing 100191,china 2 Flight Control department,Shenyang Aircraft Design and Research Institute,Shenyang 110035,china 3 Beijing Institute of Near Space Vehicle’s System engineering,Beijing 100076,china 4Integration and Project Section,Air Force Equipment Academy,Beijing 100085,china 1. State Key Laboratory of Science and Technology on Holistic Flight Control School of Automation Science and Electrical Engineering Beijing University of Aeronautics and Astronautics Beijing 100191 China2. Flight Control Department Shenyang Aircraft Design and Research Institute Shenyang 110035 China3. Beijing Institute of Near Space Vehicle’s System Engineering Beijing 100076 China4. Integration and Project Section Air Force Equipment Academy Beijing 100085 China

Bio-inspired intelligence is in the spotlight in the field of international artificial intelligence,and unmanned combat aerial vehicle(UCAV),owing to its potential to perform dangerous,repetitive tasks in remote and hazardous,is very promising for the technological leadership of the nation and essential for improving the security of *** the basis of introduction of bioinspired intelligence and UCAV,a series of new development thoughts on UCAV control are proposed,including artificial brain based high-level autonomous control for UCAV,swarm intelligence based cooperative control for multiple UCAVs,hy-brid swarm intelligence and Bayesian network based situation assessment under complicated combating environments, bio-inspired hardware based high-level autonomous control for UCAV,and meta-heuristic intelligence based heterogeneous cooperative control for multiple UCAVs and unmanned combat ground vehicles(UCGVs).The exact realization of the proposed new development thoughts can enhance the effectiveness of combat,while provide a series of novel breakthroughs for the intelligence,integration and advancement of future UCAV systems.

关键词： bio-inspired intelligence unmanned combat aerial vehicle(UCAV) artificial brain autonomous control bayesian network bio-inspired hardware heterogeneous cooperative control

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