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An Automatic Elaborate Requirement Specification By Using Hierarchical Text Classification

An Automatic Elaborate Requirement Specification By Using Hi...

引用

International Conference on computer Science and Software engineering

作者： Jantima Polpinij Aditya Ghose Department of Computer Science Faculty of Informatics Mahasarakham University Kantarawichai Mahasarakham Thailand Decision Systems Lab School of Computer Science and Software Engineering Faculty of Informatics University of Wollongong Wollongong Australia

ISBN: (纸本)9781424439027

Ambiguity is a major problem of software errors because much of the requirements specification is written in a natural language format. Therefore, it is hard to identify consistencies because this format is too ambiguous for specification purposes. This paper aims to propose a method for handling requirement specification documents which have a similar content to each other through a hierarchical text classification. The method consists of two main processes of classification: heavy classification and light classification. The heavy classification is to classify the requirement specification documents having similar content together. Meanwhile, light classification is to elaborate specification requirement documents by using the Euclidean distance. Finally, slimming down the number of requirements specification through hierarchical text classification classifying may yield a specification which is easier to understand. That means the proposed method is more effective for reducing and handling in the requirements specification.

关键词： Text categorization computer science Software engineering Euclidean distance Quality assessment informatics computer errors Natural languages Document handling Australia

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Random black hole particle swarm optimization and its application

Random black hole particle swarm optimization and its applic...

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International Conference on Neural Networks and Signal Processing

作者： Junqi Zhang Kun Liu Ying Tan Xingui He Languages Informatics Systems and Software Engineering Department Faculty of Computer Science Peking University Beijing China

ISBN: (纸本)9781424423101

This paper introduces a novel particle swarm optimization algorithm based on the concept of black holes in physics, called random black hole particle swarm optimization (RBH-PSO) for the first time. In each dimension of a particle, we randomly generate a black hole located nearest to the best particle of the swarm in current generation and then randomly pull particles of the swarm into the black hole with a probability p. By this mechanism of random black hole, we can give all the particles another interesting direction to converge as well as another chance to fly out of local minima when a premature convergence happens. Several experiments on fifteen benchmark test functions are conducted to demonstrate that the proposed RBH-PSO algorithm is able to speedup the evolution process distinctly and improve the performance of global optimizer greatly. Finally, an actual application of the proposed algorithm to spam detection is conducted then compared to other three current methods.

关键词： Benchmark testing Algorithm design and analysis Particle swarm optimization Optimization Electronic mail Convergence Support vector machines

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Improved robust 𝒟𝒰-stability measures via S-procedure

Improved robust 𝒟𝒰-stability measures via S-procedure

引用

American Control Conference (ACC)

作者： Bilal Sari Olivier Bachelier Driss Mehdi Toufic Al Chaer Languages Informatics Systems and Software Engineering Department Faculty of Computer Science University of Poitiers Poitiers France

In this paper we focus on the notion of robust matrix root-clustering analysis in a union of regions that are possibly disjoint and non symmetric. Indeed this work aims at computing a bound on the size of the uncertainty domain preserving matrix D u -stability. A Linear Fractional Transform (LFT) uncertainty is considered. To reduce conservatism, a new approach, based on some generalized S-procedure, is addressed. In the case where the studied matrices depend afflnely on the uncertain parameters or when the studied matrices are subject to polytopic uncertainty, it is known that recently developed L.M.J conditions are effective to assess the robust performance in a less conservative fashion. This paper further extends the preceding results and propose a unified way to obtain new L.M.J conditions even in the case of rational parameter dependence. Some conservatism induced by some techniques encountered in the literature is here reduced .

关键词： Robustness Uncertainty Lyapunov method Robust control Symmetric matrices Robust stability Control system synthesis Control system analysis Control systems Uncertain systems

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Numerical and symbolic state space realizations of linear systems with algebraic loops

Numerical and symbolic state space realizations of linear sy...

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IEEE International Symposium on computer Aided Control System Design (CACSD)

作者： Masanobu Koga Satoru Anan Kentaro Yano Department of Systems Design and Informatics Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka Japan

ISBN: (纸本)9781424422210

This paper proposes a method which gives a state space realization of the linear systems with algebraic loops not only in numerical format but also in symbolic format and guarantees that the order of the system is preserved. The method uses an adjacency matrix in graph theory for the modeling of the control systems and uses the matrix inversion lemma to calculate the inverse of matrix symbolically and to obtain the symbolic state space realizations. We have developed a new software platform for modeling and simulation of control systems using the proposed method.

关键词： Control systems USA Councils

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March Test BDN: A new March Test for dynamic faults

March Test BDN: A new March Test for dynamic faults

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IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR

作者： Alberto Bosio Giorgio Di Natale Languages Informatics Systems and Software Engineering Department Faculty of Computer Science Université Montpelher II Montpellier France

High-density components and process scaling lead more and more to the occurrence of new class of dynamic faults, especially in Static Random Access Memories (SRAMs), thus requiring more and more sophisticated test algorithms. Among the different types of algorithms proposed for testing SRAMs, March Tests have proven to be the most performing due to their low complexity, their simplicity and regular structure. Several March Tests for dynamic faults have been published, with different fault coverage. In this paper we propose March BDN, an extended version of the March AB. We will prove that it is able to increase the fault coverage in order to target latest dynamic faults. We show that the proposed March BDN has the highest known fault coverage compared to March Tests with the same complexity.

关键词： Circuit faults Heuristic algorithms Random access memory Decoding Complexity theory Arrays Taxonomy

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A Novel Semantic Video Classification Model

A Novel Semantic Video Classification Model

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Workshops on Image Processing Theory, Tools and Applications, IPTA

作者： Wei Ren Maneesha Singh Sameer Singh Faculty of Computer and Information Engineering Peking University Shenzhen China Research School of Informatics Loughborough University UK

In this paper, we propose a novel spatio-temporal video retrieval model to extract spatio-temporal attributes for semantic video category classification using high-level reasoning of video objects and scenes. We also explore the semantic logical inference learning of video attributes based on interpreting camera movements and object spatial constraints, as well the views on temporal continuity of video. We have used Minerva international video benchmark for the analysis of our algorithm.

关键词： Video compression Videoconference Information retrieval Layout Video sequences Image retrieval Indexing Image processing Application software Data mining

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Information-based dichotomization: A method for multiclass Support Vector Machines

Information-based dichotomization: A method for multiclass S...

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International Joint Conference on Neural Networks (IJCNN)

作者： Patoomsiri Songsiri Boonserm Kijsirikul Thimaporn Phetkaew Department of Computer and Technology Mahidol Wittayanusorn School National Science High School of Thailand Department of Computer Engineering Faculty of Engineering Chulalongkom University Bangkok Thailand Department of Computer Engineering Faculty of Engineering Chulalongkom University Bangkok Thailand School of Informatics Walailak University Thailand

Approaches for solving a multiclass classification problem by support vector machines (SVMs) are typically to consider the problem as combination of two-class classification problems. Previous approaches have some limitations in classification accuracy and evaluation time. This paper proposes a novel method that employs information-based dichotomization for constructing a binary classification tree. Each node of the tree is a binary SVM with the minimum entropy. Our method can reduce the number of binary SVMs used in the classification to the logarithm of the number of classes which is lower than previous methods. The experimental results show that the proposed method takes lower evaluation time while it maintains accuracy compared to other methods.

关键词： Artificial neural networks Joints

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The synthesis level in Bloom’s Taxonomy — a nightmare for an LMS

The synthesis level in Bloom’s Taxonomy — a nightmare for ...

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EAEEIE Annual Conference,

作者： Heinz-Dietrich Wuttke Raimund Ubar Karsten Henke Artur Jutman Faculty Informatics and Automation Ilmenau University of Technology Ilmenau Germany Department of Computer Engineering Tallinn University of Technology Estonia

A lot of learning management systems (LMS) were developed in the last ten years since e-learning opens new possibilities in learning scenarios. They offer the possibility to watch any of the students action on the computer, but possibilities to verify the level of knowledge, a student has reached (accordingly to Bloompsilas taxonomy), are very poor. Multiple choice questions and the like can only verify lower levels in this taxonomy. In this paper we discuss a new approach in verifying higher levels of knowledge in connection with interactive teaching software and online laboratories, which are coupled to an LMS. This work is a result of eight years cooperation between the Tallinn University of Technology and the Ilmenau University of Technology.

关键词： Least squares approximation Education Taxonomy Digital circuits Cognition Software Laboratories

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An Ontology-Based Sentiment Classification Methodology for Online Consumer Reviews

An Ontology-Based Sentiment Classification Methodology for O...

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Jantima Polpinij Aditya K. Ghose Decision Systems Laboratory School of Computer Science and Software Engineering Faculty of Informatics University of Wollongong Wollongong NSW Australia

This paper presents a method of ontology-based sentiment classification to classify and analyse online product reviews of consumers. We implement and experiment with a support vector machines text classification approach based on a lexical variable ontology. After testing, it could be demonstrated that the proposed method can provide more effectiveness for sentiment classification based on text content.

关键词： Ontologies Motion pictures Support vector machines Text categorization Intelligent agent Support vector machine classification Electronic commerce Internet Web search Automotive engineering

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Teaching digital test with BIST analyzer

Teaching digital test with BIST analyzer

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EAEEIE Annual Conference,

作者： A. Jutman A. Tsertov A. Tsepurov I. Aleksejev R. Ubar H.-D. Wuttke Department of Computer Engineering Tallinn University of Technology Tallinn Estonia Faculty of Informatics and Automation Ilmenau University of Technology Ilmenau Germany

This paper describes a new software tool for high quality training/learning in the field of digital microelectronics. Its main purpose is to give insight into reliability and quality assurance technologies based on linear feedback shift registers (LFSR) and other pseudo-random pattern generators (PRPG). Various PRPG types are becoming the mainstream test generation solution used in built-in self-test (BIST) structures. Taking into account complex theoretical concepts behind the microelectronics self-testing (including data coding and compression, cryptography, field theory, linear programming) it is important to effectively educate engineers in this field. The software tool we present in this paper is aimed at facilitating this goal. Unlike other similar systems, this tool facilitates study of various test optimization problems, allows fault coverage analysis for different circuits and with different LFSR parameters. The main didactic aim of the tool is presenting complicated concepts in a comprehensive graphical and analytical way. The multi-platform JAVA runtime environment allows for easy usage of the tool both in the classroom and at home. The BIST Analyzer represents an integrated simulation, training, and research environment that supports both analytic and synthetic way of learning. Due to the above mentioned facts the tool provides a unique training platform to use in courses on electronic testing and design for testability.

关键词： Built-in self-test Circuit faults Optimization Polynomials Training Testing Microelectronics

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