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29th International computing and Combinatorics Conference, COCOON 2023

作者： Guo, Hongjie Li, Jianzhong Shen, Fangyao Gao, Hong Faculty of Computing Harbin Institute of Technology Heilongjiang Harbin China School of Computer Science and Technology Zhejiang Normal University Zhejiang Jinhua China Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9783031491924

Multi-criteria decision-making often involves selecting a small representative set from a database. A recently proposed method is the regret minimization set (RMS) queries. It aims to rectify the shortcomings of needing a utility function in top-k queries and the overly large result size of skyline queries. However, the existing definition of RMS only ensures one result under any utility function, and do not consider the diversity and freshness of the returned results. In this paper, we define a strong regret set, which guarantees the utility value error of k data points under any utility function. Given this new definition, we propose two problems, namely the Minimum Size problem and the Max-sum Diversity and Freshness problem. Both proposed problems have been proven to be NP-hard. Correspondingly, we devise approximation algorithms for them, and analyze algorithms’ time complexities and the approximation ratios of the solutions obtained. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Approximation algorithms

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Developing Educational Programs Using Russian IT Job Market Analysis

Developing Educational Programs Using Russian IT Job Market ...

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2021 Ural Symposium on Biomedical engineering, Radioelectronics and Information Technology, USBEREIT 2021

作者： Sozykin, Andrey Koshelev, Anton Bersenev, Alexander Shadrin, Denis Aksenov, Alexander Kuklin, Evgeniy N.N. Krasovskii Institute of Mathematics and Mechanics Department of Computing Systems Ekaterinburg Russia Engineering School of IT Telecom. and Control Systems Ural Federal University Ekaterinburg Russia Institute of Natural Sciences and Mathematics Ural Federal University Ekaterinburg Russia

ISBN: (纸本)9781728176918

The paper presents an approach to developing new educational programs for information technologies (IT) specialists using job market analysis. We developed a set of innovative software tools for collecting data from job sites and analyzing the data using machine learning algorithms. The tools were used to create a dataset of job advertisements from popular Russian job site HeadHunter for a period from 2006 until 2020. Both tools and dataset are freely available on the Internet. In order to develop the educational programs, we analyzed the demand for IT professions and programming languages, as well as joint occurrence of skills in job descriptions. To demonstrate the possibilities of our approach, two educational programs were created: A JavaScript-based program for Web Development and a Python-based program for Data Science. Developing the educational programs based on the requirements of the job market allows graduates to increase their employability. During the programs, students not only study the foundation of the profession such as programming languages, but also acquire a complete set of skills required to work in demanded positions. © 2021 IEEE.

关键词： Employment

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Enforcing stability through ellipsoidal inner approximations in the indirect approach for continuous-time system identification

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IFAC-PapersOnLine 2020年第2期53卷 566-571页

作者： Rodrigo A. González James S. Welsh Cristian R. Rojas Decision and Control Systems KTH Royal Institute of Technology 10044 Stockholm Sweden School of Electrical Engineering and Computing University of Newcastle Australia

Recently, a new indirect approach method for continuous-time system identification has been proposed that provides complete freedom on the number of poles and zeros of the linear and time-invariant continuous-time model structure. However, this procedure has reliability issues, as it may deliver unstable estimates even if the initialisation model and true system are stable. In this paper, we propose a method to overcome this problem. By generating ellipsoids that contain parameter vectors whose coefficients yield stable polynomials, we introduce a convex constraint in the indirect prediction error method formulation, and show that the proposed method enjoys optimal asymptotic properties while being robust in small and noisy data set scenarios. The effectiveness of the novel method is tested through extensive simulations.

关键词： System identification Continuous-time systems Stability Sampled data

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Prediction of multi-parameters in the inverse heat conduction problems

Prediction of multi-parameters in the inverse heat conductio...

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2020 International Conference on Physics, Mechanics and Mathematical Science, PMMS 2020

作者： Abdelhamid, Talaat Chen, Rongliang Alam, Mahbub Shenzhen Institutes of Advanced Technology Chinese Academy of Science Shenzhen China Institute for Turbulence-Noise-Vibration Interaction and Control Shenzhen Graduate School Harbin Institute of Technology Shenzhen China Physics and Mathematical Engineering Department Faculty of Electronic Engineering Menoufiya University Menouf Egypt Shenzhen Key Laboratory for Exascale Engineering and Scientific Computing Shenzhen China

This paper studies the prediction of the spatial-dependent-heat transfer coefficient γ(x) and- heat flux q(x), using the modified conjugate gradient method (MCGM). The mathematical formulation of the problem well defined and the existence of the minimizer is investigated. We establish the sensitivity and adjoint equations for computing the gradient with respect to γ(x) and q(x). The proposed algorithm 4.1 is derived for reconstructing γ(x) and q(x) using the MCGM. The numerical experiments are examined to show the efficiency and accuracy of the proposed method. Finally, some conclusions and remarks are given. © Published under licence by IOP Publishing Ltd.

关键词： Conjugate gradient method

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Relation Model of Burden Operation and State Variables of Blast Furnace Based on Low Frequency Feature Extraction*

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IFAC-PapersOnLine 2017年第1期50卷 13796-13801页

作者： Zhang, Kexin Wu, Min An, Jianqi Cao, Weihua Liu, Zhentao Ning, Fulong School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Faculty of Engineering China University of Geosciences wuhan430074 China Department of Computer Science School of Computing Tokyo Institute of Technology Yokohama226-8502 Japan

In the blast furnace ironmaking process, the running state of the blast furnace can be directly adjusted by the burden operation. Therefore, the explicit relation between the burden operation and the running state variables is vital for the blast furnace operators. However, the state variables of the blast furnace are affected by many factors and the burden matrix is complicated. In this paper, a support vector regression(SVR) predicting model based on low frequency feature extraction is proposed to solve these problems. First, the low frequency components of state variables time series which are mostly affected by the burden operation are extracted. Then, the dimensions of the burden matrix are reduced by a devised simple expression method. Finally, the relation model based on SVR is proposed to predict the values of the expected state variables according to the simplified burden matrix and the value of initial state variables. The simulation on real factory data indicates that the model reflects the accurate quantitative relation between the burden operation and the state variables. © 2017

关键词： Blast furnaces Blast furnace practice Extraction Feature extraction Support vector regression Blast furnace iron making Blast furnace operators burden operation Initial state variables Low frequency components Relation models State variables Support vector regression (SVR)

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Multi agent based kinematics solution method for multi link robot

Multi agent based kinematics solution method for multi link ...

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Joint 5th International Conference on Soft computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2010

作者： Haramaki, Shinya Hayashi, Akihiro Satake, Toshifumi Komori, Mochimitsu Department of Mechanical Engineering Ariake National College of Technology Ohmuta Fukuoka Japan Department of Mechanical Information Science and Technology Kyushu Institute of Technology Iizuka Fukuoka Japan Department of Control and Computing Engineering Asahikawa National College of Technology Asahikawa Hokkaido Japan Department of Integrated System Engineering Kyushu Institute of Technology Tobata Fukuoka Japan

This paper proposes a framework of a distributed kinematics resolution model which can be applied to various types of multi link robot structures. In the framework, hardware modules which consists of joints and links are defined as joint components of robotic systems, then kinematics resolution models are composed of a set of the local kinematics modules (LKMs) which are software module to compute the localized direct and inverse kinematics corresponding to each joint component. Kinematics computation throughout the robotic systems is resolved by the localized kinematics calculation of LKMs for an end effecter to a target position and an information exchange among LKMs. The proposed framework has been applied to case studies of the inverse kinematics problems of 7 degree of freedom multi link robot manipulator. Case studies have confirmed the proposed model to be able to provide a dexterous framework of kinematics resolution systems for modular type robotic systems and various types of robotic systems.

关键词： Inverse problems

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Stability of Markovian jump systems over networks via delta operator approach

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Circuits, Systems, and Signal Processing 2012年第1期31卷 107-125页

作者： Yang, Hongjiu Xia, Yuanqing Shi, Peng Fu, Mengyin Department of Automatic Control Beijing Institute of Technology Beijing 100081 China Department of Computing and Mathematical Sciences University of Glamorgan Pontypridd CF37 1DL United Kingdom School of Engineering and Science Victoria University Melbourne 8001 VIC Australia Faculty of Automation Harbin University of Science and Technology Harbin China

This paper investigates the problem of stability for a class of linear uncertain Markovian jump systems over networks via the delta operator approach. The sensor-to-controller random network-induced delay and arbitrary packet losses are considered for mode-dependent time delays. That is, a Markov process is used to model the time-varying delays which are dependent on the system mode. Based on the Lyapunov-Krasovskii functional in the delta domain, a new sufficient condition for the solvability of the stability problem is presented in terms of linear matrix inequalities. A numerical example is given to illustrate the effectiveness of the techniques developed. © Springer Science+Business Media, LLC 2011.

关键词： Networked control systems

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Rotation Estimation for Mobile Robot Based on Single-axis Gyroscope and Monocular Camera

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International Journal of Automation and computing 2012年第3期9卷 292-298页

作者： Yang, Ke-Hu Yu, Wen-Sheng Ji, Xiao-Qiang School of Mechanical Electronic and Information Engineering China University of Mining and Technology Beijing 100083 China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai 200062 China State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

The rotation matrix estimation problem is a keypoint for mobile robot localization, navigation, and control. Based on the quaternion theory and the epipolar geometry, an extended Kalman filter (EKF) algorithm is proposed to estimate the rotation matrix by using a single-axis gyroscope and the image points correspondence from a monocular camera. The experimental results show that the precision of mobile robot s yaw angle estimated by the proposed EKF algorithm is much better than the results given by the image-only and gyroscope-only method, which demonstrates that our method is a preferable way to estimate the rotation for the autonomous mobile robot applications.

关键词： Rotation matrix estimation quaternion extended Kalman filter (EKF) monocular camera gyroscope.

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Hierarchical Multiview Top-k Pooling with Deep-Q-Networks

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第6期5卷 2985-2996页

作者： Li, Zhi-Peng Su, Hai-Long Wu, Yong- Zhang, Qin-Hu Yuan, Chang-An Gribova, Valeriya Filaretov, Vladimir Fedorovich Huang, De-Shuang Eastern Institute of Technology Zhejiang Ningbo315201 China University of Science and Technology of China School of Life Sciences Anhui Hefei230026 China Tongji University Institute of Machine Learning and Systems Biology School of Electronics and Information Engineering Shanghai201804 China Guangxi Academy of Sciences Institute of Big Data and Intelligent Computing Research Center Nanning530007 China Far Eastern Branch of the Russian Academy of Sciences Institute of Automation and Control Processes Vladivostok690041 Russia

Graph neural networks (GNNs) are extensions of deep neural networks to graph-structured data. It has already attracted widespread attention for various tasks such as node classification and link prediction. Existing research focuses more on graph convolutional neural networks (GCNs). However, it is usually overlooked that graph pooling can obtain graph representations by summarizing and down-sampling node information. Meanwhile, existing graph pooling methods mainly use top-k for node selection, but most of them consider only single view information when scoring nodes, and the k values in top-k are usually selected empirically. This work proposes the hierarchical multiview top-k pooling (HMTPool) with deep-Q-networks, which scores nodes taking into account multiview information (considering graph structure and features) and does not rely on the empirical adaptive selection of the best k value. HMTPool is a two-stage process. It first uses a variant GCN and multilayer perceptron to score the nodes from structural and feature perspectives, respectively and then performs fusion operations on the multiview information scores of the nodes. In addition, to select the optimal pooling ratio of top-k, we propose a deep-Q-network-based top-k (DTop-k) node selection method, which can adaptively select the best pooling ratio without prior knowledge. Experimental results on six TUDatasets and two Benchmarking GNNs datasets demonstrate the effectiveness of our proposed approach. © 2020 IEEE.

关键词： Convolution

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Estimating infinitesimal generators of stochastic systems with formal error bounds: A data-driven approach 24

Estimating infinitesimal generators of stochastic systems wi...

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24th ACM International Conference on Hybrid Systems Computation and control, HSCC 2021, held as part of the 14th Cyber Physical Systems and Internet-of-Things Week, CPS-IoT Week 2021

作者： Lavaei, Abolfazl Nejati, Ameneh Soudjani, Sadegh Zamani, Majid Institute for Dynamic Systems and Control Eth Zurich Switzerland Department of Electrical Engineering Technical University of Munich Germany School of Computing Newcastle University United Kingdom Department of Computer Science University of Colorado Boulder United States

ISBN: (纸本)9781450383394

In this work, we propose a data-driven technique for a formal estimation of infinitesimal generators of continuous-time stochastic systems with unknown dynamics. In the proposed framework, we first approximate the infinitesimal generator of the solution process via a set of data collected from solution processes of unknown systems. We then put some proper assumptions on dynamics of systems and quantify the closeness between the infinitesimal generator and its approximation while providing a priori guaranteed confidence bound. We show that both the time discretization and the number of data play significant roles in providing a reasonable closeness precision. Motivations and Related Works. Infinitesimal generator of a stochastic process (i.e., a partial differential operator that encodes a great deal of information about the process) plays a principal role in many analysis frameworks including: (i) stability analysis of continuous-time stochastic systems via Lyapunov functions [1], (ii) establishing similarity relations between two continuous-time stochastic systems via stochastic simulation functions [2], (iii) constructing finite abstractions of continuous-time stochastic control systems [3], and (iv) safety analysis of continuous-time stochastic systems via barrier certificates [4], to name a few. In the relevant literature, only [5] studies the estimation of infinitesimal generators, whose approach is based on the assumption of knowing the precise model and discretizing both time and state. To the best of our knowledge, our work is the first to propose a method for estimating the infinitesimal generator of stochastic systems with unknown dynamics while providing formal guarantees. The complete version of this work can be found in [6]. © 2021 Owner/Author.

关键词： Stochastic systems

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