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arXiv 2020年

作者： Alanwar, Amr Gaßmann, Victor He, Xingkang Said, Hazem Sandberg, Henrik Johansson, Karl Henrik Althoff, Matthias School of Computer Science and Engineering Constructor University Germany Department of Computer Engineering Technical University of Munich Germany Division of Decision and Control Systems Kth Royal Institute of Technology Sweden Department of Computer Engineering Ain Shams University Egypt

The set-based estimation has gained a lot of attention due to its ability to guarantee state enclosures for safety-critical systems. However, collecting measurements from distributed sensors often requires outsourcing the set-based operations to an aggregator node, raising many privacy concerns. To address this problem, we present set-based estimation protocols using partially homomorphic encryption that preserve the privacy of the measurements and sets bounding the estimates. We consider a linear discrete-time dynamical system with bounded modeling and measurement uncertainties. Sets are represented by zonotopes and constrained zonotopes as they can compactly represent high-dimensional sets and are closed under linear maps and Minkowski addition. By selectively encrypting parameters of the set representations, we establish the notion of encrypted sets and intersect sets in the encrypted domain, which enables guaranteed state estimation while ensuring privacy. In particular, we show that our protocols achieve computational privacy using the cryptographic notion of computational indistinguishability. We demonstrate the efficiency of our approach by localizing a real mobile quadcopter using ultra-wideband wireless devices. Copyright © 2020, The Authors. All rights reserved.

关键词： Uncertainty analysis

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Mathematical Modeling and Analysis of Multirobot Cooperative Hunting Behaviors

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Journal of Robotics 2015年第1期2015卷

作者： Song, Yong Li, Yibin Li, Caihong Ma, Xin School of Control Science and Engineering Shandong University Jinan250061 China School of Mechanical Electrical and Information Engineering Shandong University at Weihai Weihai264209 China School of Computer Science and Technology Shandong University of Technology Zibo255012 China

This paper presents a mathematical model of multirobot cooperative hunting behavior. Multiple robots try to search for and surround a prey. When a robot detects a prey it forms a following team. When another "searching" robot detects the same prey, the robots form a new following team. Until four robots have detected the same prey, the prey disappears from the simulation and the robots return to searching for other prey. If a following team fails to be joined by another robot within a certain time limit the team is disbanded and the robots return to searching state. The mathematical model is formulated by a set of rate equations. The evolution of robot collective hunting behaviors represents the transition between different states of robots. The complex collective hunting behavior emerges through local interaction. The paper presents numerical solutions to normalized versions of the model equations and provides both a steady state and a collaboration ratio analysis. The value of the delay time is shown through mathematical modeling to be a strong factor in the performance of the system as well as the relative numbers of the searching robots and the prey. © 2015 Yong Song et al.

关键词： Behavioral research

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Tightly-Coupled Integrated LR-WPAN/WiMAX Network: Architecture and Performance Modelling

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IERI Procedia 2013年 4卷 59-67页

作者： Ayyoub Akbari-Moghanjoughi Aduwati Sali José Roberto Amazonas Burhanuddin Mohd Ali Shamala Subramaniam Sabira Khatun Department. of Computer & Communications Systems Engineerin Faculty of Engineering Universiti Putra Malaysia Department of Telecommunications and Control Engineering of Escola Politécnica of the University of São Paulo Brazil Department of Communication Technology & Networks Faculty of Computer Science and IT Universiti Putra Malaysia School of Computer and Communication Engineering Universiti Malaysia Perlis Malaysia

In this paper a general architecture of tightly-coupled integrated LR-WPAN/WiMAX network has been introduced by proposing and utilising a novel access router named Wireless Integrated Access Router (WIAR). The suggested access router effectively combines both WiMAX and LR-WPAN technologies in a same device. The main motivation to propose this integration is to deploy Internet of Things (IoT) applications and services in wide area networks. Using WiMAX as backhaul service, the Internet connection can be provided for dispersed mobile LR-WPAN users over a wide area. Moreover, it enables to access all collected data in the local LR-WPAN coverage area – which is named as Senspot in this paper – by third-party clients through the Internet. Furthermore, an analytic model has been developed for the integrated network to evaluate the system's performance. Theoretical results on blocking probability of new and handover calls from WiMAX subscribers, as well as new connections from LR-WPAN Senspots in a cell of WiMAX have been investigated in terms of call/connection rates and number of allocated channels.

关键词： Backhaul Support Heterogeneous Wireless Network IoT Networks Integration WiMAX LR-WPAN.

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Empirical assessment for end-to-end link quality of scalable mobile sensor networks

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2011年第4期5卷 217-279页

作者： Zhuang, Wei Chen, Xi Tan, Jindong School of Information and Control Nanjing University of Information Science and Technology China Department of Electrical and Computer Engineering Michigan Technological University Houghton United States

This paper presents a comprehensive metric to evaluate the link quality of scalable mobile sensor networks to maintain end-to-end communication links. The mobile nodes dynamically reconfigure themselves to maintain reliable end-to-end communication links. We present the empirical analysis and results of a link variability study for an indoor environment. All experiments are implemented on a mobile platform called PioMote team. Inspired by the Shannon-Hartley theorem, the analysis of three metrics is proposed, including received signal strength indicator (RSSI), active throughput, and packet loss rate (PLR). RSSI is adopted to reflect the basic performance of link quality in mobile sensor networks. Active throughput acting as a decaying threshold generator is used to estimate the critical point for smooth and stable communication. The metric PLR is adopted to reflect the cut-off point in end-to-end communication. The evaluation of link quality acts as feedback for the cooperative control of mobile nodes. The experimental results show the effectiveness of evaluation for link quality of scalable mobile sensor networks.

关键词： Throughput

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Computational fluid dynamic and machine learning modeling of nanofluid flow for determination of temperature distribution and models comparison

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Scientific reports 2025年第1期15卷 19073页

作者： Farag M A Altalbawy Ahmad Alkhayyat Ramdevsinh Jhala Anupam Yadav T Ramachandran Aman Shankhyan A Karthikeyan Dhirendra Nath Thatoi Vladimir Vladimirovich Sinitsin Department of Chemistry University College of Duba University of Tabuk Tabuk Saudi Arabia. f_altalbawy@***. Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq. Department of Computers Techniques Engineering College of Technical Engineering The Islamic University of Al Diwaniyah Al Diwaniyah Iraq. Department of Computers Techniques Engineering College of Technical Engineering The Islamic University of Babylon Babylon Iraq. Marwadi University Research Center Department of Mechanical Engineering Faculty of Engineering & Technology Marwadi University Rajkot Gujarat 360003 India. Department of Computer Engineering and Application GLA University Mathura 281406 India. Department of Mechanical Engineering School of Engineering and Technology JAIN (Deemed to be University) Bangalore Karnataka India. Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Rajpura Punjab 140401 India. Department of Mechanical Engineering Sathyabama Institute of Science and Technology Chennai Tamil Nadu India. Department of Mechanical Engineering Siksha 'O' Anusandhan (Deemed to be University) Bhubaneswar Odisha 751030 India. Research Laboratory of Technical Self-Diagnostics and Self-Control of Devices and Systems Department of Scientific and Innovative Activities Research Institute of Mechanical Engineering South Ural State University Lenin prospect 76 Chelyabinsk 454080 Russian Federation.

This paper introduces an approach to temperature prediction by employing three distinct machine learning models: K-Nearest Neighbors (KNN), Gaussian Process Regression (GPR), and Multi-layer Perceptron (MLP) which are integrated into Computational Fluid Dynamics (CFD). The dataset consists of inputs, represented by the features x and y, and the corresponding output, which is the temperature. The case study is fluid flow of nanofluid through a pipe and the nanofluid contains CuO particles. To enhance model efficacy, the Political Optimizer (PO) algorithm was utilized for fine-tuning purposes. The findings substantiate the capability of the optimized frameworks in delivering precise temperature estimations. GPR yielded a notable R value of 0.998, reflecting a strong concordance between the estimated and actual measurements. In a comparable manner, the KNN approach exhibited outstanding predictive performance, also attaining an R value of 0.998. MLP, although slightly lower in performance compared to the other models, still proves to be a reliable predictor of temperature values, with an R-squared score of 0.984. Overall, the combination of the PO algorithm and the machine learning models showcases promising results in temperature prediction. The study's findings offer valuable insights for decision-making processes in a variety of domains that rely on accurate temperature forecasting.

关键词： Gaussian process regression Heat transfer K-Nearest neighbors Multi-layer perceptron Nanofluid

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Semi-Markov Telecommunication Networks Model

Semi-Markov Telecommunication Networks Model

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2024 International Conference on Actual Problems of Electron Devices engineering, APEDE 2024

作者： Svetlov, Mikhail S. L’vov, Alexey A. Martirosyan, Arman M. Martirosyan, David M. Bagaev, Igor S. Khasanov, Semen T. Laboratory of Control and Automation Problems in Mechanical Engineering Institute of Precision Mechanics and Control of RAS Saratov Russia Institute of Institute of Electronic Engineering and Instrumentation Yuri Gagarin State Technical University of Saratov Saratov Russia Institute of Applied Information Technologies and Communications Yuri Gagarin State Technical University of Saratov Saratov Russia Phystech-School of Applied Mathematics and Computer Science Moscow Institute of Physics and Technology Moscow Russia

ISBN: (纸本)9798350393316

This paper proposes a semi-Markov model of telecommunication network (TCN). The variant of dynamic traffic adaptive control of queuing system as a special case of TCN is considered. The main purpose of control is to minimize the average cost per unit of time to service the incoming flow of information (packets). This takes into account the different bandwidth of the channels, the processing speed of information in the channel and the information capacity of the buffers. The approach to the organization of dynamic control taking into account noise immunity (information reliability) and information security is discussed. © 2024 IEEE.

关键词： Bandwidth

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Undo the codebook bias by linear transformation for visual applications 13

Undo the codebook bias by linear transformation for visual a...

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21st ACM International Conference on Multimedia, MM 2013

作者： Zhang, Chunjie Zhang, Yifan Wang, Shuhui Pang, Junbiao Liang, Chao Huang, Qingming Tian, Qi School of Computer and Control Engineering University of Chinese Academy of Sciences 100049 Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China Key Lab of Intell. Info. Process Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China College of Computer Science and Technology Beijing University of Technology 100124 Beijing China School of Computer National Engineering Research Center for Multimedia Software Wuhan University 430072 Wuhan China Department of Computer Sciences University of Texas at San Antonio San Antonio TX 78249 United States

ISBN: (纸本)9781450324045

The bag of visual words model (BoW) and its variants have demonstrate their effectiveness for visual applications and have been widely used by researchers. The BoW model first extracts local features and generates the corresponding codebook, the elements of a codebook are viewed as visual words. The local features within each image are then encoded to get the final histogram representation. However, the codebook is dataset dependent and has to be generated for each image dataset. This costs a lot of computational time and weakens the generalization power of the BoW model. To solve these problems, in this paper, we propose to undo the dataset bias by codebook linear transformation. To represent every points within the local feature space using Euclidean distance, the number of bases should be no less than the space dimensions. Hence, each codebook can be viewed as a linear transformation of these bases. In this way, we can transform the pre-learned codebooks for a new dataset. However, not all of the visual words are equally important for the new dataset, it would be more effective if we can make some selection using sparsity constraints and choose the most discriminative visual words for transformation. We propose an alternative optimization algorithm to jointly search for the optimal linear transformation matrixes and the encoding parameters. Image classification experimental results on several image datasets show the effectiveness of the proposed method. Copyright © 2013 ACM.

关键词： Linear transformations

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Hierarchical Retrieval of High-Resolution Fingerprints Based on Pore Feature

Hierarchical Retrieval of High-Resolution Fingerprints Based...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jing Ma Yuanrong Xu Suyu Dong Wei Wang School of Computer Science and Technology Harbin Institute of Technology Shenzhen China School of Computer Science and Technology Harbin Institute of Technology Weihai China College of Computer and Control Engineering Northeast Forestry University Harbin China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Faced with an escalating number of fingerprint images, most existing retrieval approachs suffer from a common problem: diminishing computational efficiency. This paper presents a hierarchical retrieval system tailored for high-resolution fingerprint images that utilizes abundant pore features and robust recognizability to improve retrieval performance. The framework comprises two core components. Firstly, a CNN-based feature extraction network is established, incorporating an attention mechanism to capture pore features in fingerprint images comprehensively. Subsequently, a hierarchical fingerprint retrieval approach is introduced, involving connection graph construction and a hierarchy of jump table structures for efficient retrieval of query pores. Empirical experiments conducted on high-resolution fingerprint image datasets underscore the system’s effectiveness. Compared with other advanced pore-based fingerprint retrieval methods, the proposed method exhibits a notable rise in the hit rate with reduced penetration rates, significantly reducing the retrieval time.

关键词： Accuracy Image recognition Attention mechanisms Image matching Fingerprint recognition Feature extraction Robustness Computational efficiency Bioinformatics

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Fuzzy synthetic condition assessment of wind turbine based on combination weighting and cloud model

Fuzzy synthetic condition assessment of wind turbine based o...

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作者： Zheng, Kai Han, Lina Guo, Shuli Wang, Zhenyu Zhang, Xinmiao Dong, Xinghui College of Energy Power and Mechanical Engineering North China Electric Power University ChangPing District Beijing China Department of Cardiovascular Internal Medicine Nanlou Branch of Chinese PLA General Hosptal Beijing China School of Automation Beijing Institute of Technology Beijing100081 China School of Control and Computer Engineering North China Electric Power University ChangPing District Beijing China

This paper presented an improved fuzzy synthetic model based on combination weighting and a cloud model to optimize wind turbine maintenance strategy and improve operational reliability. First, a condition assessment framework was proposed by analyzing the monitored physical quantities of a working wind turbine. Based on the establishment of a state health evaluation index and health status classification of wind turbines, the weight of each index was determined with a combination weighting method while the membership degree of each state grade was determined with a membership cloud model. A comprehensive evaluation of the health status of the wind turbine was carried out using the method of stratified evaluation. The results showed that the proposed method was effective and feasible. The results also showed that the condition assessment that utilized the improved method predicted the change of operating conditions and more closely matched real operating conditions than the traditional fuzzy assessment method. © 2017-IOS Press and the authors. All rights reserved.

关键词： Wind turbines

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Protein-Folding Inspired Programmable control System for Robot Swarms

Protein-Folding Inspired Programmable Control System for Rob...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Zhang, Feng Gu, Yuping Wang, Zebin Yuan, Shuai Yang, Yongliang School of Electrical and Control Engineering Shenyang Jianzhu University Liaoning Shenyang110168 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Liaoning Shenyang110106 China School of Computer Science and Engineering Shenyang Jianzhu University Liaoning Shenyang110168 China

ISBN: (纸本)9781665481090

In swarm robotics, most of the control algorithms are inspired by the behaviors of animal swarms. The capability gap between robots and animals, however, hinders the reliability of these algorithms. Toward developing reliable algorithms of robot swarms, a promising solution is learning from the collective behaviors of low-intelligent natural swarms, such as cell collectives and molecular assemblies. Here, we proposed a programmable control system inspired by protein folding. Using our homemade RoboFold platform, we demonstrated a protein-folding inspired programmable control method for robot swarms. By programming and designing the sequence of a thread of protein-like robots, the developed system can mimic the formation of hierarchical structures in robot swarms as the three-level of protein structures. We quantitatively characterized the specific features of self-organized morphologies. The experimental results together demonstrated the feasibility of this method. To summarize, this work successfully translated the principles of protein-folding into programming methods to control the morphology of robot swarms. Considering that the protein folding problem is essentially a physicochemical problem, this system is not only beneficial for the control of swarm robots but also has the potential to develop into a tool for studying the protein folding problem. © 2024 IEEE.

关键词： Robot programming

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