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IEEE International Symposium on Industrial Electronics 2005, ISIE 2005

作者： Šijak, Tomislav Kuljača, Ognjen Antonić, Radovan Kuljača, Ljubomir Brodarski Institute Control Engineering Dept. Zagreb Croatia Alcorn State University Dept. of Advanced Technologies Alcorn State United States University of Split Maritime Faculty Split Croatia University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (纸本)0780387384

The paper presents the procedure for analytical determination of describing function of nonlinear element with fuzzy logic nonlinearity. The procedure is based on the method of analytical determination of describing function of generalized static characteristic of nonlinear element. The procedure is also illustrated with examples. © 2005 IEEE.

关键词： Nonlinear control systems

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Optimized Ensemble Algorithm for Predicting Metamaterial Antenna Parameters

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Computers, Materials & Continua 2022年第6期71卷 4989-5003页

作者： El-Sayed M.El-kenawy Abdelhameed Ibrahim Seyedali Mirjalili Yu-Dong Zhang Shaima Elnazer Rokaia M.Zaki Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Centre for Artificial Intelligence Research and Optimization Torrens University AustraliaFortitude ValleyQLD 4006Australia Yonsei Frontier Lab Yonsei UniversitySeoul03722Korea School of Computing and Mathematical Sciences University of LeicesterLeicesterLE17RHUK Nile Higher Institute for Engineering and Technology MansouraEgypt Computer and Information Technology College Taif UniversityTaifSaudi Arabia Higher Institute of Engineering and Technology Kafrelsheikh Department of Electrical Engineering Shoubra Faculty of EngineeringBenha UniversityEgypt

Metamaterial Antenna is a subclass of antennas that makes use of metamaterial to improve *** antennas can overcome the bandwidth constraint associated with tiny *** learning is receiving a lot of interest in optimizing solutions in a variety of *** learning methods are already a significant component of ongoing research and are anticipated to play a critical role in today’s *** accuracy of the forecast is mostly determined by the model *** purpose of this article is to provide an optimal ensemble model for predicting the bandwidth and gain of the Metamaterial *** Vector Machines(SVM),Random Forest,K-Neighbors Regressor,and Decision Tree Regressor were utilized as the basic *** Adaptive Dynamic Polar Rose Guided Whale Optimization method,named AD-PRS-Guided WOA,was used to pick the optimal features from the *** suggested model is compared to models based on five variables and to the average ensemble *** findings indicate that the presented model using Random Forest results in a Root Mean Squared Error(RMSE)of(0.0102)for bandwidth and RMSE of(0.0891)for *** is superior to other models and can accurately predict antenna bandwidth and gain.

关键词： Metamaterial antenna machine learning ensemble model feature selection guided whale optimization support vector machines

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An energy-efficient bandwidth allocation method for single-chip heterogeneous processor 7

An energy-efficient bandwidth allocation method for single-c...

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7th International Green and Sustainable computing Conference, IGSC 2016

作者： Zhu, Yatao Zhang, Shuai Ye, Xiaochun Wang, Da Tan, Xu Fan, Dongrui Zhang, Zhimin Li, Hongliang State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi Jiangsu China

ISBN: (纸本)9781509051175

In recent years, many studies on optimization of energy consumption have focused on heterogeneous processor architectures. Heterogeneous computing model composed of CPU and GPU has developed from co-processing between the chips to CPU and GPU integration on the same die. On the one hand, because GPU can work under low voltage and ultra-low frequency, heterogeneous multi-core processors exhibit better energy efficiency compared to traditional CPU;On the other hand, because GPU usually has little or no shared cache, its memory bandwidth demand will be several times more than that of CPU for the same performance. Considering the constraints of power consumption and memory bandwidth, the contention problems of power and bandwidth among CPU and GPU in heterogeneous processor will inevitably occur. In this paper, energy-efficient bandwidth allocation method for heterogeneous processors allocates bandwidth to CPU and GPU and increases the overall throughput of CPU and GPU. Meanwhile the efficiency of energy consumption of heterogeneous processors is improved. The queuing delay is introduced to build a performance-energy model for heterogeneous processors. According to experience parameters, we analyze how the memory bandwidth allocation of off-chip affects the total throughput and energy efficiency. This paper also explores the change of performance-energy gains with the cache miss ratio of processors and the degree of scarce of available peak bandwidth. Based on the above research, the analytical solution of energy-efficient bandwidth allocation for optimal performance is obtained, and the solution can get more performance-energy gains compared with natural bandwidth allocation. © 2016 IEEE.

关键词： Bandwidth

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Dynamic Formation Tracking of Multi-agent Systems with Bounded Unknown Leader Input 5th

Dynamic Formation Tracking of Multi-agent Systems with Bou...

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5th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2021

作者： Su, Piaoyi Dong, Xiwang Zhao, Qin Li, Qingdong Ren, Zhang School of Automation Science and Electronic Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China Beijing Institute of Control and Electronics Technology Beijing100038 China

ISBN: (纸本)9789811939976

This literature investigate the dynamic formation tracking problem of multiple Lagrange systems with linear nonautonomous leader over directed topology. In order to estimate the leader system, a distributed control scheme is proposed firstly by constructing adaptive distributed observer. Secondly, this paper design a nonlinear function to decrease the influence from the leader’s bounded unknown input. Then, the dynamic formation tracking problem of multiple Euler-Lagrange systems with nonlinear uncertainties and disturbances is solved by distributed tracking algorithm. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

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Exploring the GLIDE model for Human Action-effect Prediction 2

Exploring the GLIDE model for Human Action-effect Prediction

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2nd Workshop on People in Vision, Language, and the Mind, P-VLAM 2022

作者： Li, Fangjun Hogg, David C. Cohn, Anthony G. School of Computing University of Leeds United Kingdom Luzhong Institute of Safety Qingdao University of Science and Technology China College of Electronic and Information Engineering Tongji University China School of Mechanical and Electrical Engineering Qingdao University of Science and Technology China School of Control Science and Engineering Shandong University China

ISBN: (纸本)9791095546795

We address the following action-effect prediction task. Given an image depicting an initial state of the world and an action expressed in text, predict an image depicting the state of the world following the action. The prediction should have the same scene context as the input image. We explore the use of the recently proposed GLIDE model for performing this task. GLIDE is a generative neural network that can synthesize (inpaint) masked areas of an image, conditioned on a short piece of text. Our idea is to mask-out a region of the input image where the effect of the action is expected to occur. GLIDE is then used to inpaint the masked region conditioned on the required action. In this way, the resulting image has the same background context as the input image, updated to show the effect of the action. We give qualitative results from experiments using the EPIC dataset of ego-centric videos labelled with actions. © European Language Resources Association (ELRA)

关键词： Forecasting

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Learning Label-Specific Features and Class-Dependent Labels for Multi-Label Classification

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IEEE Transactions on Knowledge and Data engineering 2016年第99期PP卷 3309-3323页

作者： Huang, Jun Li, Guorong Huang, Qingming Wu, Xindong School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing101480 China Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China School of Computer Science and Information Engineering Hefei University of Technology Hefei230009 China Department of Computer Science University of Vermont 33 Colchester Avenue BurlingtonVT05405 United States

Binary Relevance is a well-known framework for multi-label classification, which considers each class label as a binary classification problem. Many existing multi-label algorithms are constructed within this framework and utilize identical data representation in the discrimination of all the class labels. In multi-label classification, however, each class label might be determined by some specific characteristics of its own. In this paper, we seek to learn label-specific data representation for each class label, which is composed of label-specific features. Our proposed method LLSF can not only be utilized for multi-label classification directly, but also be applied as a feature selection method for multi-label learning and a general strategy to improve multi-label classification algorithms comprising a number of binary classifiers. Inspired by the research works on modeling high-order label correlations, we further extend LLSF to learn class-Dependent Labels in a sparse stacking way, denoted as LLSFDL. It incorporates both second-order and high-order label correlations. A comparative study with the state-of-the-art approaches manifests the effectiveness and efficiency of our proposed methods. © 2016 IEEE.

关键词： Classification (of information)

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Few-shot Object Detection Algorithm Based on YOLOv8-Mamba-Like Linear Attention 16

Few-shot Object Detection Algorithm Based on YOLOv8-Mamba-Li...

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16th International Conference on Communication Software and Networks, ICCSN 2024

作者： Wang, Hongliang Wang, Kaizhu Ji, Binglong Deng, Changyi Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Liaoning Province Human- Computer Interaction System Engineering Research Center Based on DigitTwin Shenyang China Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Shenyang China Institute of Software China Industrial Control Systems Cyber Emergency Response Team Beijing China

ISBN: (纸本)9798331506322

In the production and assembly process, the accuracy of detection is usually low due to limited resources and small quantities. In this paper, we propose a few-shot learning method for object detection based on the combination of YOLOv8 and Mamba-Like Linear Attention (MLLA) module. This method utilizes a high-pixel camera to capture the shape and size of the workpiece. By consistency-based mutual augmentation structure for few-shot samples data augmentation. By introducing the efficient and lightweight MLLA module, the model's speed and accuracy in object detection and segmentation tasks on mobile devices are significantly improved. Specifically, MLLA mainly integrates the two key elements of 'forget gate' and 'block design' in Mamba, and MLLA replaces forget gate by using position coding (RoPE) to provide necessary location information while maintaining parallel computation and fast inference speed. This makes MLLA improves the accuracy of detection and segmentation recognition. Experimental results show that compared to the original YOLOv8 model, the model with the MLLA module exhibits improvements in segmentation precision and recognition accuracy. This method demonstrates high accuracy and robustness in workpiece recognition, making it suitable for real-time industrial applications. © 2024 IEEE.

关键词： Object detection

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CLSIFT: An optimization study of the scale invariance feature transform on GPUs

CLSIFT: An optimization study of the scale invariance featur...

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15th IEEE International Conference on High Performance computing and Communications, HPCC 2013 and 11th IEEE/IFIP International Conference on Embedded and Ubiquitous computing, EUC 2013

作者： Wang, Weiyan Zhang, Yunquan Guoping, Long Yan, Shengen Jia, Haipeng Lab. of Parallel Software and Computational Science Institute of Software Chinese Academy of Sciences China State Key Laboratory of Computing Science Institute of Software Chinese Academy of Sciences China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9780769550886

Scale Invariance Feature Transform (SIFT) is quite suitable for image matching because of its invariance to image scaling, rotation and slight changes in illumination or viewpoint. However, due to high computation complexity it's technically challenging to deploy SIFT in real time application situations. To address this problem, we propose CLSIFT, an OpenCL based highly speeded up and performance portable SIFT solution. Important optimization techniques employed in CLSIFT such as: (1) For less global memory traffic, independent logical functions are merged into the same kernel to reuse data.(2) loop buffers are introduced in for data and intermediate results reusing.(3)Task queue used to schedule threads in the same branch to remove branch divergences. (4) Data partition is based on the statics patterns for workload balance among workgroups. (5) Overlap of CPU time and better parallel strategies are used too. With all mentioned efforts, CLSIFT processes lena. jpg at 74.2 FPS and 43.4FPS respectively on NVidia and AMD GPUS, much higher than CPU's nearly 10 FPS and the known fastest SIFTGPU's 39.8 FPS and 13FPS. Moreover in a quantitative comparison approach we analyze those successful strategies beating SIFTGPU, a famous existing GPU implementation. Additionally, we observe and conclude that NVidia GPU achieves better occupancy and performance due to some factors. Finally, we summarize some techniques and empirical guiding principles that may be shared by other applications on GPU. © 2013 IEEE.

关键词： Graphics processing unit

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A structured mathematical model of PHA biopolymer production process

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Archives of control Sciences 2013年第3期23卷 351-360页

作者： Finkeová, Jana Hrnčiřík, Pavel Mareš, Jan Vovsík, Jaroslav Hudeček, Ondřej Náhlík, Jan Department of Computing and Control Engineering Institute of Chemical Technology Prague Technická 5 166 28 Prague 6 Czech Republic

The paper describes a mathematical model of PHA biopolymer production process by Pseudomonas putida KT2442 where the octanoic acid is used as a substrate. The process is modeled using mass balances for fed-batch cultivation. Proper fitting to experimental data is obtained by identification of the model parameters. The model exhibits good agreement with experiments and its possible application for control is considered in the paper.

关键词： Bacteria

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Wavelet de-noising and gradient enhancement in biomedical image processing

Wavelet de-noising and gradient enhancement in biomedical im...

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8th IASTED International Conference on Visualization, Imaging, and Image Processing, VIIP 2008

作者： Procházka, Aleš Hošťálková, Eva Vyšata, Oldřich Department of Computing and Control Engineering Institute of Chemical Technology in Prague Technická 6 166 28 Prague 6 Czech Republic Neurocenter Caregroup Jiráskova 1389 516 01 Rychnov nad Kněžnou Czech Republic

ISBN: (纸本)9780889867598

Detection of specific image components, their visualization and classification belong to main topics of biomedical image processing. The paper is devoted to problems related to the use of discrete wavelet transform (DWT) and the dual-tree complex wavelet transform (DTCWT) for image denoising and to selected methods of its enhancement. The study presents the analysis of results achieved for different wavelet functions and the following application of gradient methods for specific image components detection. The information content of final images is followed both from the medical point of view using the previous experience and numerically through the analysis of image spectral components. The proposed methods indicate the efficiency of the dual-tree complex wavelet transform use in this area.

关键词： Image denoising

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