Some expanded fuzzy rough sets models have been investigated to handle fuzzy databases with uncertain, imprecise and incomplete real-valued information. In this paper, we make further research on fuzzy rough sets mode...
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Some expanded fuzzy rough sets models have been investigated to handle fuzzy databases with uncertain, imprecise and incomplete real-valued information. In this paper, we make further research on fuzzy rough sets models in fuzzy environment, and we generalize rough fuzzy sets model based on a covering to fuzzy rough sets model based on a fuzzy covering. The lower and upper approximations of fuzzy subsets are defined based on a fuzzy covering, and basic properties are investigated. Then, the axiom definition of the lower approximation operator is given. It is shown that the rough fuzzy sets model based on a covering is a special instance of the fuzzy rough sets model based on a fuzzy covering.
The upper domination Ramsey number u(3, 3, 3) is the smallest integer n such that every 3-coloring of the edges of complete graph Kn contains a monochromatic graph G with T(G) ≥ 3, where T(G) is the maximum order ove...
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The upper domination Ramsey number u(3, 3, 3) is the smallest integer n such that every 3-coloring of the edges of complete graph Kn contains a monochromatic graph G with T(G) ≥ 3, where T(G) is the maximum order over all the minimal dominating sets of the complement of G. In this note, with the help of computers, we determine that U(3, 3, 3) = 13, which improves the results that 13 ≤ U(3, 3, 3) ≤ 14 provided by Michael A. Henning and Ortrud R. Oellermann.
Software testing is the key validation technique used by industry up to today, but remain error prone and expensive cost. Automatically generating test cases from formal models of the system under test is a promising ...
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Software testing is the key validation technique used by industry up to today, but remain error prone and expensive cost. Automatically generating test cases from formal models of the system under test is a promising improvement approach to cut down the testing cost. This paper introduces a technique that automatically generate real-time conformance test cases from timed automata specifications. First, both reactive system and its environment is modeled by restricted automata with the notion of deterministic, input enabled and output urgent. Then demonstration is given to show how to efficiently generate real-time test cases with optimal execution time from diagnostic trace. Finally, we formally specify user's single purpose or coverage criteria to convert the test case generation problem into a reachability problem. This approach is implemented using model checkers as test case generation tools and experiment results on three different coverage criteria specifications show feasibility and effectiveness of our technique.
The Web Services Business Process Execution Language (BPEL) is a language used to specify compositions of web services. In the last few years, a considerable amount of work has been done on modeling (parts of) BPE...
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The Web Services Business Process Execution Language (BPEL) is a language used to specify compositions of web services. In the last few years, a considerable amount of work has been done on modeling (parts of) BPEL and developing verification techniques and tools for BPEL. Petri nets and formal languages have been widely used to model Web services composition, but temporal value passing calculus of communicating systems (TVPCCS) language seems to be more adequate for several reasons. Generally BPEL programs are mapped to other languages and then the verification is performed, A more promising way is to directly build TVPCCS model, to check it and then map it to a BPEL process model. This paper describes a mapping from TVPCCS onto BPEL process model.
The Web Services Business Process Execution Language (BPEL) is a language used to specify compositions of web *** the last few years,a considerable amount of work has been done on modeling (parts of) BPEL and developi...
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The Web Services Business Process Execution Language (BPEL) is a language used to specify compositions of web *** the last few years,a considerable amount of work has been done on modeling (parts of) BPEL and developing verification techniques and tools for *** nets and formal languages have been widely used to model Web services composition,but temporal value passing calculus of communicating systems (TVPCCS) language seems to be more adequate for several *** BPEL programs are mapped to other languages and then the verification is performed,A more promising way is to directly build TVPCCS model,to check it and then map it to a BPEL process *** paper describes a mapping from TVPCCS onto BPEL process model.
Most of quantum codes have been constructed by using classical linear codes over finite field. However, little is known about the construction of quantum codes from symmetric designs. In this work, we present the cons...
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The motivation for this work was that little is known about the construction of asymmetric quantum error-correcting codes from linear codes over finite rings. In this work, attempts are made to construct asymmetric qu...
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The motivation for this work was that little is known about the construction of asymmetric quantum error-correcting codes from linear codes over finite rings. In this work, attempts are made to construct asymmetric quantum error-correcting codes from linear codes over finite rings Zp2, where p is any prime. Furthermore, we present explicit parameters for infinite families of asymmetric quantum error correcting codes which derived from linear over finite rings.
TWSVM(Twin Support Vector Machines) is based on the idea of GEPSVM (Proximal SVM based on Generalized Eigenvalues), which determines two nonparallel planes by solving two related SVM-type problems, so that its computi...
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TWSVM(Twin Support Vector Machines) is based on the idea of GEPSVM (Proximal SVM based on Generalized Eigenvalues), which determines two nonparallel planes by solving two related SVM-type problems, so that its computing cost in the training phase is 1/4 of standard SVM. In addition to keeping the superior characteristics of GEPSVM, the classification performance of TWSVM significantly outperforms that of GEPSVM. In order to further improve the speed and accuracy of TWSVM, this paper proposes the twin support vector machines based on rough sets. Firstly, using the rough sets theory to reduce the attributes, and then using TWSVM to train and predict the new datasets. The final experimental results and data analysis show that the proposed algorithm has higher accuracy and better efficiency compared with the traditional twin support vector machines.
At present, most of the attribute reduction algorithms based on granularity are simply computing the granularity of knowledge. Repeated calculation will increase the time complexity. Binary discernibility matrix is us...
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At present, most of the attribute reduction algorithms based on granularity are simply computing the granularity of knowledge. Repeated calculation will increase the time complexity. Binary discernibility matrix is used to express binary form, which has a clear ascension whether in space or in time than the traditional discernibility matrix efficiency. On the basis of granularity-based attribute reduction, a method is proposed to preprocess the dataset by using binary discernibility matrix. Firstly, find the core attribute and a minimal reduction. Then use the granularity thought to calculate each particle of the importance of attributes. Most important is joined to the reduction set, thereby achieving the attributes reduction. The example analysis shows that the method can improve the performance of the traditional attribute reduction algorithms effectively. It is a feasible approach to reduce attributes.
Traditional support vector machine has disadvantages of slow training speed and great time consumption when dealing with large-scale datasets. This paper proposes a support vector extraction method based on clustering...
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Traditional support vector machine has disadvantages of slow training speed and great time consumption when dealing with large-scale datasets. This paper proposes a support vector extraction method based on clustering membership, which preprocesses the training datasets and extracts all possible support vectors for SVM training according to the memberships. Considering the training datasets may be linear or nonlinear, this paper severally uses FCM and KFCM to extract support vectors. Experiment results show that the method proposed in this paper can improve the training speed greatly in the condition of maintaining the classification accuracy.
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