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Exploring Auto-Generation of Network Models With Performance Evaluation Process Algebra

IEEE ACCESS 2018年 6卷 42971-42983页

作者： Ding, Jie Wang, Rui Chen, Xiao Ge, Ying-En Shanghai Maritime Univ China Inst FTZ Supply Chain Shanghai 201306 Peoples R China Yangzhou Univ Sch Informat Engn Yangzhou 225127 Jiangsu Peoples R China Jiangsu Univ Sch Comp Sci & Commun Engn Zhenjiang 212013 Peoples R China Beihang Univ State Key Lab Software Dev Environm Beijing 100083 Peoples R China Shanghai Maritime Univ Coll Transport & Commun Shanghai 201306 Peoples R China

Formal method plays an important role in modeling large scale concurrent networks through its efficient model construction and analysis. Taking urban road networks and public transportation systems as examples, such models can be defined in a formal method in order to investigate the performance of current bus-line deployment based on a given road network. This paper considers how to efficiently build a formal model based on such an original prototype of the specified road network and transportation system. As the model prototype can be represented by a directed graph that is then transformed into a numerical incidence matrix, we proposed an algorithm, in this paper, to assist the construction of formal models by sorting all potential compositional structures and components based on the previously obtained numerical incidence matrix. Thereafter, a performance evaluation process algebra-based formal model can be automatically generated on the basis of sorted compositional structures, which extends the use of formal method for large-scale and comprehensive network, and system modeling. The findings reveal that the proposed algorithm can efficiently find all potential compositional structures that include all potential components and related activity flows in models.

关键词： Formal method PEPA incidence matrix compositional structures sorting algorithm

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A gas source declaration scheme based on a tetrahedral sensor structure in three-dimensional airflow environments

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REVIEW OF SCIENTIFIC INSTRUMENTS 2019年第2期90卷 024104-1-024104-11页

作者： Hou, Hui-Rang Tong, Yuan Ren, Chao Meng, Qing-Hao Tianjin Univ Tianjin Key Lab Proc Measurement & Control Sch Elect & Informat Engn Inst Robot & Autonomous Syst Tianjin 300072 Peoples R China

A gas source declaration scheme based on a tetrahedral sensor structure in three-dimensional airflow environments is proposed. First, a tetrahedral sensor structure was established. Based on the tetrahedral structure, the gas source declaration problem was converted into a two-class classification issue. Then a classification algorithm combining an extreme learning machine (ELM, a fast neural network classifier) with a gas mass flux criterion is proposed. A novel calculation method for the mass flux through a closed tetrahedral surface is presented, and a mass flux criterion was developed which acts as a training sample filter for the ELM. The source declaration scheme was validated by using both regular and irregular tetrahedron experiments. Published under license by AIP Publishing.

关键词： Mass flux sorting algorithm computational methods Environments valve diameter Sensors Phyla

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Simulation-based SONET ADM optimization approach for dynamic traffic grooming in WDM optical networks

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PHOTONIC NETWORK COMMUNICATIONS 2008年第1期16卷 11-21页

作者： Roy, Kuntal Naskar, Mrinal Kanti Jadavpur Univ Dept Elect & Telecommun Engn Kolkata 700032 India

The article addresses a simulation-based optimization approach for allocation of ADMs in WDM optical networks with stochastic dynamic traffic. Since ADMs are expensive, it is desirable that if each node in WDM optical networks can use a minimum number of ADMs to achieve a near-ideal performance. In this article, first, the utilization statistics of ADMs are gathered by simulation. Then, ADMs are allocated based on the utilization statistics. In this respect, a simple sorting mechanism is used. The distinguished feature of the proposed approach is that it shows the way to allocate ADMs at the nodes of WDM optical networks with stochastic dynamic traffic. The experimental results ensure that the proposed approach can solve the problem of allocating ADMs in practical WDM optical networks considering stochastic dynamic traffic.

关键词： WDM optical networks SONET add-drop multiplexer dynamic traffic grooming sorting algorithm

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ON THE CHARACTERIZATION OF ULTRASONIC TRANSDUCERS USING PATTERN-RECOGNITION

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IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS 1993年第5期23卷 1443-1450页

作者： OBAIDAT, MS Department of Electrical Engineering City College City University of New York New York NY USA

This correspondence is concerned with presenting a methodology for characterizing ultrasonic transducers using pattern recognition techniques. An apparatus was developed to collect focus, frequency spectrum, impulse response, and diameter parameters. Six different pattern recognition techniques were applied to classify 83 different transducers. These include: K-means, minimum distance, perceptron, potential function, cosine measure, and Bayes' classifier. Moreover, two dimensionality reduction techniques, the K-L transform and the Fisher Multiple discriminant, were applied to reduce the feature space. It was found that the K-means was the most successful classification algorithm. Very close behind in performance was the combination of K-L transform with minimum distance classifier. The latter reduced the feature space by 44 percent with only 6 percent misclassification error more than K-means. The potential function scheme did not converge to a solution in a time equal to 60 times that was required for the other algorithms. Results of the classification, dimensionality reduction, comparison and validation are presented to highlight the advantages and limitations of the investigated techniques.

关键词： ultrasonic transducers potential function Percent Eigenvector minimum distance dimensionality reduction Pattern recognition pictorial pattern recognition algorithm sorting algorithm

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IMAGE VECTOR QUANTIZER BASED ON A CLASSIFICATION IN THE DCT DOMAIN

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IEEE TRANSACTIONS ON COMMUNICATIONS 1991年第4期39卷 549-556页

作者： KIM, DS LEE, SU Department of Control and Instrumentation Engineering Seoul National University Seoul South Korea

In vector quantization (VQ) of image signal at low bit rate, edge degradations are sometimes observed because of the use of the conventional mean square error (MSE) distortion measure. A classified VQ (CVQ) technique, based on the edge-oriented classifier, can reduce the edge degradation as well as the encoding complexity. In this paper, we propose a classification algorithm in the discrete cosine transform (DCT) domain for the CVQ. The classifier employs four DCT coefficients of 4 x 4 subblock as edge-oriented features. Then the classifier is designed using a cluster-seeking algorithm to ensure that the centroid of a set of vector in a class always belong to that class. Since the classification is performed in the DCT-domain, this approach can be easily extended to the well-established DCT transform coding technique. Simulation results show that a good visual quality of the coded image at fixed rates in the 0.625-0.813 b/pixel (bpp) is obtained with comparable complexity. In addition, the weighted MSE (WMSE) analysis in conjunction with the proposed classifier is also discussed in this paper.

关键词： sorting algorithm Domain discrete cosine transforms Set of vectors quantizer Centroid Classifiers

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A review of associative classification mining

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KNOWLEDGE ENGINEERING REVIEW 2007年第1期22卷 37-65页

作者： Thabtah, Fadi Univ Huddersfield Dept Comp & Engn Huddersfield HD1 3DH W Yorkshire England

Associative classification mining is a promising approach in data mining that utilizes the association rule discovery techniques to construct classification systems, also known as associative classifiers. In the last few years, a number of associative classification algorithms have been proposed, i.e. CPAR, CMAR, MCAR, MMAC and others. These algorithms employ several different rule discovery, rule ranking, rule pruning, rule prediction and rule evaluation methods. This paper focuses on surveying and comparing the state-of-the-art associative classification techniques with regards to the above criteria. Finally, future directions in associative classification, such as incremental learning and mining low-quality data sets, are also highlighted in this paper.

关键词： mining Taxonomy Associative learning (artificial intelligence) Surveying Rule Dataset sorting algorithm

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Fully automatic detection of deep white matter T1 hypointense lesions in multiple sclerosis

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PHYSICS IN MEDICINE AND BIOLOGY 2013年第23期58卷 8323-8337页

作者： Spies, Lothar Tewes, Anja Suppa, Per Opfer, Roland Buchert, Ralph Winkler, Gerhard Raji, Alaleh Jung Diagnost GmbH Hamburg Germany Charite Dept Nucl Med Berlin Germany Neurozentrum Hamburg Hamburg Germany

A novel method is presented for fully automatic detection of candidate white matter (WM) T1 hypointense lesions in three-dimensional high-resolution T1-weighted magnetic resonance (MR) images. By definition, T1 hypointense lesions have similar intensity as gray matter (GM) and thus appear darker than surrounding normal WM in T1-weighted images. The novel method uses a standard classification algorithm to partition T1-weighted images into GM, WM and cerebrospinal fluid (CSF). As a consequence, T1 hypointense lesions are assigned an increased GM probability by the standard classification algorithm. The GM component image of a patient is then tested voxel-by-voxel against GM component images of a normative database of healthy individuals. Clusters (>= 0.1 ml) of significantly increased GM density within a predefined mask of deep WM are defined as lesions. The performance of the algorithm was assessed on voxel level by a simulation study. A maximum dice similarity coefficient of 60% was found for a typical T1 lesion pattern with contrasts ranging from WM to cortical GM, indicating substantial agreement between ground truth and automatic detection. Retrospective application to 10 patients with multiple sclerosis demonstrated that 93 out of 96 T1 hypointense lesions were detected. On average 3.6 false positive T1 hypointense lesions per patient were found. The novel method is promising to support the detection of hypointense lesions in T1-weighted images which warrants further evaluation in larger patient samples.

关键词： ground truth Lesions Patients automatic detection pixel sorting algorithm White Matter

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A patch connectivity index and its change in relation to new wetland at the Yellow River Delta

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INTERNATIONAL JOURNAL OF REMOTE SENSING 2004年第21期25卷 4617-4628页

作者： Yue, TX Xu, B Liu, JY Chinese Acad Sci Inst Geog Sci & Nat Resources Res State Key Lab Resources & Environm Informat Syst Beijing 100101 Peoples R China Univ Calif Berkeley CAMFER Berkeley CA 94720 USA

In this paper, we introduce a patch connectivity index and analyse its changes in relation to ecotope diversity and human impact intensity. Land-use maps of the newly born wetland at the Yellow River Delta of 1984, 1991 and 1996 were produced by applying an unsupervised and a supervised classification algorithm to the corresponding three scenes of Landsat Thematic Mapper (TM) images. A model for calculating the patch connectivity index was proposed and applied to the classified images. Our results show that patch connectivity has a negative relationship with ecotope diversity and human impact intensity. This indicates that an important measure for conserving the benign succession of the newly born wetland is to prevent it from disturbance of industrial activities in order to maintain ecotope diversity and natural patch connectivity.

关键词： Indexes human impacts connectivity RIVER DELTAS Wetlands Yellow River Delta sorting algorithm

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Revisiting the effect of spatial resolution on information content based on classification results

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INTERNATIONAL JOURNAL OF REMOTE SENSING 2019年第12期40卷 4489-4505页

作者： Palacio, M. G. Ferrero, S. B. Frery, A. C. Univ Nacl Rio Cuarto Fac Ciencias Exactas Fis Quim & Nat Dept Matemat Cordoba Argentina Univ Fed Alagoas Lab Comp Cient & Anal Numer Maceio Brazil

Polarimetric Synthetic Aperture Radar (PolSAR) images are an important source of information. Speckle noise gives SAR images a granular appearance that makes interpretation and analysis hard tasks. A major issue is the assessment of information content in these kinds of images, and how it is affected by usual processing techniques. Previous works have resulted in various approaches for quantifying image information content. In this paper, we study this problem from the classification accuracy viewpoint, focusing on the filtering and the classification stages. Thus, through classified images, we verify how changing the properties of the input data affects their quality. The input is an actual PolSAR image, the control parameters are (i) the filter (Local Mean, LM, or Model-Based PolSAR, MBPolSAR) and the size of their support, and (ii) the classification method (Maximum Likelihood, ML, or Support Vector Machine, SVM), and the output is the precision of the classification algorithm applied to the filtered data. To expand the conclusions, this study deals not only with Classification Accuracy but also with Kappa and Overall Accuracy as measures of map precision. Experiments were conducted on two airborne PolSAR images. Differently from what was observed in previous works, almost all quality measures are good and increase with degradation, i.e. the filtering algorithms that we used always improve the classification results at least up to supports of size 7 x 7.

关键词： incoming data image information sorting algorithm Support Vector Network Taxonomy Precision images Filtering algorithms Polarimetric synthetic aperture radar Filtration control parameter

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Surface reconstruction for thin aero engine blade from disorganized contact measured points

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE 2018年第5期232卷 746-758页

作者： Lyu, Xuegeng Yu, Hongying Wu, Jialu Harbin Inst Technol Sch Mechatron Engn Xidazhi St 92 Harbin 150001 Heilongjiang Peoples R China

Blade surface reconstruction is one of the necessary steps in blade adaptive machining system. The majority of the current reconstruction methods are based on point-cloud, which is obtained using noncontact measurements. Correspondingly, these methods are invalid when the points are obtained using contact measurements. In this paper, we studied the method of surface reconstruction for thin features based on measured contact points. Owing to the random order of the measured points, and the fact that when the distance between two measured points is larger than the wall thickness of the blade will lead to interpolation errors, a quad tree-based region division method, and a points sorting algorithm, are proposed for correctly ordering the points. On this basis, inverse interpolation of cross-sectional curves using a cubic NURBS curve is used to fit them and reconstruct surfaces. Surface reconstruction examples are presented herein, and a comparison between the reconstructed and designed surfaces is used to verify the validity of our method.

关键词： Surface reconstruction thin aero engine blade disorganized measured contact points sorting algorithm cross-sectional curve fitting

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