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An Improved Page Rank Algorithm Based on Fuzzy C-Means Clustering and Information Entropy 3

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An Improved Page Rank Algorithm Based on Fuzzy C-Means Clust...

2017 3rd IEEE International Conference on control Science and Systems Engineering (ICCSSE)

作者： Wenbo Zheng Shaocong Mo Pengfei Duan Xiaotian Jin School of Software Engineering Xi’an Jiaotong University The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Computer Science and Technology Wuhan University of Technology Hubei Key Laboratory of Transportation Internet of Things Wuhan University of Technology

ISBN: (纸本)9781538604854

This paper proposes an improvement to the Page Rank algorithm. Most existing Page Rank algorithms expect a strong correlation among consecutively accessed webpages, which in reality should be a fuzzy relationship when a user accesses pages on an arbitrarily basis. We mine data from search-behavior logs by analyzing chronological sequential patterns, and cluster all webpages using fuzzy C clustering. The weight of each cluster is identified with information entropy, which is then used to adjust the average weight. A sample of 1 million pages is used for testing. Compared with traditional Page Rank, the new algorithm decreases search time by 34.83% and increases search accuracy by 41.88%;when compared with HITS, the improvements are 31.82% and 64.04% respectively.

关键词： fuzzy c-means information entropy PageRank

Machine discovery of partial differential equations from spatiotemporal data

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arXiv 2019年

作者： Yuan, Ye Li, Junlin Li, Liang Jiang, Frank Tang, Xiuchuan Zhang, Fumin Liu, Sheng Goncalves, Jorge Voss, Henning U. Li, Xiuting Kurths, Jürgen Ding, Han School of Artificial Intelligence and Automation State Key Laboratory of Digital Manufacturing Equipments and Technology Huazhong University of Science and Technology Wuhan430074 China School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan430074 China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm11428 Sweden School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan430074 China School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta30332 United States School of Power and Mechanical Engineering Wuhan University Wuhan430074 China Department of Engineering University of Cambridge CambridgeCB2 1PZ United Kingdom Luxembourg Centre for Systems Biomedicine University of Luxembourg BelvauxL-4367 Luxembourg Citigroup Biomedical Imaging Center Weill Cornell Medical College New York10021 United States Research Domain IV - Transdisciplinary Concepts & Methods Potsdam Institute for Climate Impact Research Potsdam14473 Germany School of Mechanical Science and Engineering State Key Laboratory of Digital Manufacturing Equipments and Technology Huazhong University of Science and Technology Wuhan430074 China

The study presents a general framework for discovering underlying Partial Differential Equations (PDEs) using measured spatiotemporal data. The method, called Sparse Spatiotemporal System Discovery (S3d), decides which physical terms are necessary and which can be removed (because they are physically negligible in the sense that they do not affect the dynamics too much) from a pool of candidate functions. The method is built on the recent development of Sparse Bayesian Learning;which enforces the sparsity in the to-be-identified PDEs, and therefore can balance the model complexity and fitting error with theoretical guarantees. Without leveraging prior knowledge or assumptions in the discovery process, we use an automated approach to discover ten types of PDEs, including the famous Navier-Stokes and sine-Gordon equations, from simulation data alone. Moreover, we demonstrate our data-driven discovery process with the Complex Ginzburg-Landau Equation (CGLE) using data measured from a traveling-wave convection experiment. Our machine discovery approach presents solutions that has the potential to inspire, support and assist physicists for the establishment of physical laws from measured spatiotemporal data, especially in notorious fields that are often too complex to allow a straightforward establishment of physical law, such as biophysics, fluid dynamics, neuroscience or nonlinear optics. Copyright © 2019, The Authors. All rights reserved.

关键词： Nonlinear optics

Parallel medical imaging for intelligent medical image analysis: Concepts, methods, and applications

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arXiv 2019年

作者： Gou, Chao Shen, Tianyu Zheng, Wenbo Xue, Huadan Yu, Hui Ji, Qiang Jin, Zhengyu Wang, Fei-Yue School of Intelligent Systems Engineering Sun Yat-sen University Guangzhou510275 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China School of Software Engineering Xi’an Jiaotong University Xi’an710049 China Department of Radiology Peking Union Medical College Hospital Chinese Academy of Medical Sciences Peking Union Medical College Beijing100730 China School of Creative Technologies University of Portsmouth PortsmouthPO1 2DJ United Kingdom Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Qingdao Academy of Intelligent Industries Qingdao266000 China

Data-driven artificial intelligence technologies have made much progress in medical image analysis in the last decades. However, it still remains challenging due to its distinctive complexity of acquiring and annotating image data, extracting medical domain knowledge, and explaining the diagnostic decision for medical image analysis. In this paper, we propose a data-knowledge-driven framework termed as Parallel Medical Imaging (PMI) for intelligent medical image analysis based on the methodology of interactive ACP-based parallel intelligence. In the PMI framework, computational experiments with predictive learning in a data-driven way are conducted to extract medical knowledge for diagnostic decision support. Artificial imaging systems are introduced to select and prescriptively generate medical image data in a knowledge-driven way to utilize medical domain knowledge. Through the closed-loop optimization based on parallel execution, our proposed PMI framework can boost the generalization ability and alleviate the limitation of medical interpretation for diagnostic decisions. Furthermore, we illustrate the preliminary implementation of PMI method through the case studies of mammogram analysis and skin lesion image analysis. Experimental results on several public medical image datasets demonstrate the effectiveness of proposed PMI. © 2019, CC BY.

关键词： Medical imaging

Functional voxel method for the computer calculations

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Scientific Visualization

Scientific Visualization 2017年第2期9卷 1-12页

作者： Tolok, A.V. Tolok, N.B. V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Moscow Russia Laboratory of the Computer Graphics Laboratory of GasHydrodynamic Tools for Automation Russia

In this paper, one of the approaches to the voxel visualization tools' application in the computer representation of algebraic function defined over some field is being considered. Here we offer the thumbnail summary of the functional voxel method intended for the computer solution of a wide class of mathematical problems with geometrical definition. The design principle of the computer model of algebraic function using a set of voxel images is shown. Each image reflects one of the coefficients of the local approximating function, determined for the point environment in the considered field of algebraic function. The final composition of such basic voxel images organizes voxel computer representation for the geometrical model of algebraic function which can be applied in different mathematical computer calculations. As an example, we consider the main computational constructions based on addition/subtraction of algebraic functions, their multiplication/division and taking the modulus. Given examples show the solutions of functional equations with voxel representation of a function as a result. The original geometrical approach to solve the system of algebraic equations using the functional voxel model is considered. Also, the computer calculation of integral characteristics Rfunctional for the described superposition of algebraic functions is proposed as a tool of square and volume definition for the surfaces and objects of irregular shape. Each example is provided with generalization of the solution for multidimensional space.

关键词： Functions

Scalable full flow with learned binary descriptors

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arXiv 2017年

作者： Munda, Gottfried Shekhovtsov, Alexander Knöbelreiter, Patrick Pock, Thomas Institute of Computer Graphics and Vision Graz University of Technology Austria Czech Technical University in Prague Center for Vision Automation and Control Austrian Institute of Technology

We propose a method for large displacement optical flow in which local matching costs are learned by a convolutional neural network (CNN) and a smoothness prior is imposed by a conditional random field (CRF). We tackle the computation- and memory-intensive operations on the 4D cost volume by a min-projection which reduces memory complexity from quadratic to linear and binary descriptors for efficient matching. This enables evaluation of the cost on the y and allows to perform learning and CRF inference on high resolution images without ever storing the 4D cost volume. To address the problem of learning binary descriptors we propose a new hybrid learning scheme. In contrast to current state of the art approaches for learning binary CNNs we can compute the exact non-zero gradient within our model. We compare several methods for training binary descriptors and show results on public available benchmarks. Copyright © 2017, The Authors. All rights reserved.

关键词： Random processes

On limit cycle chattering in sliding mode control systems under the influence of sampling intervals based on describing function approach

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The Journal of China Universities of Posts and Telecommunications 2016年第1期23卷 55-59页

作者： Kang Hongbo Shen Yu Institute of Electrical and Control Engineering Chang'an University College of Automation Xi'an University of Posts Communications School of Computer and Information Science Southwest University

In this paper, the influence of sampling intervals on the chattering in sliding mode （SM） control systems is considered. The describing function （DF） approach is employed to analyze the chattering characteristics in the sampling SM control. By the DF calculations and limit cycle existence conditions, an unstable limit cycle and two stable limit cycles are found in the SM control system. The frequencies and amplitudes of the two limit cycles can also be estimated by graphical calculations. The estimation accuracy of chattering parameters is evaluated by the simulations. The results of simulations show that the system could converge to a large and a small limit cycle from different initial conditions.

关键词： sampling interval chattering parameters describing function approach multiple limit cycle analysis

Immersion and Invariance Adaptive control with σ-modification for Air-breathing Hypersonic Vehicles

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Immersion and Invariance Adaptive Control with σ-modificati...

IEEE International Conference on Mechatronics and automation

作者： Chao Han Zhen Liu Jianqiang Yi School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781509067602

A novel immersion and invariance (I&I) adaptive control with σ-modification is proposed for flexible air-breathing hypersonic vehicles in the paper. Based on the framework of backstepping, the controller is a combination of I&I adaptive control and σ-modification. The control system can not only deal with the significant aerodynamic parameter uncertainties in AHVs model, but also guarantee the stability of the adaptive law in the presence of unavoidable nonparametric uncertainties. With the introduction of σ-modification, the adaptive law is designed away from the problem of parameter drift. Moreover, the structured design process and taking amplitude/rate constraints of states and actuators into account make the control system feasible to engineering practice. The stability of the closed-loop system is demonstrated by Lyapunov theory and the effectiveness of the method is illustrated by numerical simulations.

关键词： Immersion and invariance Adaptive control Hypersonic vehicles σ-modificatoin

ConnNet: A long-range relation-aware pixel-connectivity network for salient segmentation

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arXiv 2018年

作者： Kampffmeyer, Michael Dong, Nanqing Liang, Xiaodan Zhang, Yujia Xing, Eric P. Machine Learning Group UiT The Arctic University of Norway Tromsø9019 Norway Cornell University IthacaNY14850 United States Machine Learning Department Carnegie Mellon University PittsburghPA15213 United States Institute of Automation Chinese Academy of Sciences School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing100190 China

Salient segmentation aims to segment out attention grabbing regions, a critical yet challenging task and the foundation of many high-level computer vision applications. It requires semantic-aware grouping of pixels into salient regions and benefits from the utilization of global multi-scale contexts to achieve good local reasoning. Previous works often address it as two-class segmentation problems utilizing complicated multi-step procedures including refinement networks and complex graphical models. We argue that semantic salient segmentation can instead be effectively resolved by reformulating it as a simple yet intuitive pixel-pair based connectivity prediction task. Following the intuition that salient objects can be naturally grouped via semanticaware connectivity between neighboring pixels, we propose a pure Connectivity Net (ConnNet). ConnNet predicts connectivity probabilities of each pixel with its neighboring pixels by leveraging multi-level cascade contexts embedded in the image and long-range pixel relations. We investigate our approach on two tasks, namely salient object segmentation and salient instancelevel segmentation, and illustrate that consistent improvements can be obtained by modeling these tasks as connectivity instead of binary segmentation tasks for a variety of network architectures. We achieve state-of-the-art performance, outperforming or being comparable to existing approaches while reducing inference time due to our less complex approach. Copyright © 2018, The Authors. All rights reserved.

关键词： Pixels

Hierarchical P systems with randomized right-hand sides of rules 18th

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Hierarchical P systems with randomized right-hand sides of r...

18th International Conference on Membrane Computing, CMC 1018

作者： Alhazov, Artiom Freund, Rudolf Ivanov, Sergiu Institute of Mathematics and Computer Science Academy of Sciences of Moldova Academiei 5 Chişinău2028 Moldova Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Automation Huazhong University of Science and Technology Wuhan430074 China Faculty of Informatics TU Wien Favoritenstraße 9–11 Vienna1040 Austria LACL Université Paris Est – Créteil Val de Marne 61 av. Général de Gaulle Créteil94010 France TIMC-IMAG/DyCTiM Faculty of Medicine of Grenoble 5 avenue du Grand Sablon La Tronche38700 France

ISBN: (纸本)9783319733586

P systems are a model of hierarchically compartmentalized multiset rewriting. We introduce a novel kind of P systems in which rules are dynamically constructed in each step by non-deterministic pairing of left-hand and right-hand sides. We define three variants of right-hand side randomization and compare each of them with the power of conventional P systems. It turns out that all three variants enable non-cooperative P systems to generate exponential (and thus non-semi-linear) number languages. We also give a binary normal form for one of the variants of P systems with randomized rule right-hand sides. © 2018, Springer International Publishing AG.

关键词： Hierarchical systems