Sparse matrices are pervasive in many Computational Science and Engineering (CS&E) applications. There is a significant number of storage formats used to represent sparse matrices. This paper presents a performanc...
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Sparse matrices are pervasive in many Computational Science and Engineering (CS&E) applications. There is a significant number of storage formats used to represent sparse matrices. This paper presents a performance evaluation of storage formats for the main kernel of iterative methods for numerical linear algebra, namely matrix-vector multiplication. The experiments consider a set of almost 200 sparse matrices from the Matrix Market collection covering both systems of linear equations and eigenvalue problems. For each matrix, the experiments perform the matrix-vector multiplication with most commonly used sparse storage formats and also the recently proposed Java Sparse Array storage fonmat. To the best of the authors' knowledge, there is no other performance evaluation of storage formats for sparse matrices which consider such a variety of matrices and storage formats.
Images are being produced and made available in ever increasing numbers;but how can we find images "like this one" that are of interest to us? Many different systems have been developed which offer content-b...
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A dynamic multi-secrets sharing threshold scheme is presented to apply to a large scale electronic voting system with many talliers (tallying authorities). Even if there exists adaptive adversaries, this scheme can gu...
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A dynamic multi-secrets sharing threshold scheme is presented to apply to a large scale electronic voting system with many talliers (tallying authorities). Even if there exists adaptive adversaries, this scheme can guard the ballot's producing, encrypting, transmitting, decrypting and final tallying in spite of the adversaries's attack, so the scheme guarantees robustness. In this paper, the verifiability of the voters' qualification and talliers' identification will be solved by a dynamic multi-secret sharing scheme without invoking more zero knowledge proof to maintain privacy, universal verifiability, and anonymity of ballots. It holds more communication efficiency and more security than the proposed schemes in early time.
Efficient methods for generating pseudorandomly distributed unitary operators are needed for the practical application of Haar-distributed random operators in quantum communication and noise estimation protocols. We d...
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Efficient methods for generating pseudorandomly distributed unitary operators are needed for the practical application of Haar-distributed random operators in quantum communication and noise estimation protocols. We develop a theoretical framework for analyzing pseudorandom ensembles generated through a random circuit composition. We prove that the measure over random circuits converges exponentially (with increasing circuit length) to the uniform (Haar) measure on the unitary group, though the rate for uniform convergence must decrease exponentially with the number of qubits. We describe how the rate of convergence for test functions associated with specific randomization tasks leads to weaker convergence conditions that may allow efficient random circuit constructions.
In this paper, we propose a novel approach to DNA computing- inspired semantic model. The model is theoretically proposed and constructed with DNA molecules. The preliminary experiment on construction of the small tes...
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Attribute reduction is often used in simplifying decision table in rough set, but as far as a specific rule is concerned attribute value reduction. In this paper, through analyzing the nature of reduction, we have obt...
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Attribute reduction is often used in simplifying decision table in rough set, but as far as a specific rule is concerned attribute value reduction. In this paper, through analyzing the nature of reduction, we have obtained a simplified algorithm. Moreover, we can verify the validity by some tests.
Analysis of how to extract medical diagnosis rules from medical cases. Based on the rough set theory, a way of acquiring knowledge is introduced. Using this theory, we analyze the data, propose some possible rules and...
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Analysis of how to extract medical diagnosis rules from medical cases. Based on the rough set theory, a way of acquiring knowledge is introduced. Using this theory, we analyze the data, propose some possible rules and reveal an optimized probability formula. The steps of implementation, which includes the continual information discretization system, information reduction system, decision acquirement rules, decision model generation, etc., are explained through case study. In the end, the whole process of knowledge acquirement is discussed, which can effectively solve the choke point problem of acquiring knowledge in the expert system. At the same time, it also provides a new way to solve the application of artificial intelligence technology in the field of medicinal diagnosis.
Mobile agent and web service are promising new technologies with bright future, and have wide application in aspect of scientific study as well as in engineering industry. Meanwhile they both have deficiencies. The pa...
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Mobile agent and web service are promising new technologies with bright future, and have wide application in aspect of scientific study as well as in engineering industry. Meanwhile they both have deficiencies. The paper first analyzes the similarities and differences between these two technologies by example, then engages in attempting to integrate these two technologies into a totally new technology, called agenice (agent and service), a kind of intelligence service. These are aspects’ discussion: 1) VM and IL, translate the agent classes which are programmed by other languages such as Java to interface language for running on multi-OS and multi-platform; 2) AML, the agenice description language based on semantics; 3) mobility, the way to transfer agenices code and state.
The failure probability of a system can be expressed as an integral of the joint probability density function within the failure domain defined by the limit state functions of the system. Generally, it is very difficu...
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The failure probability of a system can be expressed as an integral of the joint probability density function within the failure domain defined by the limit state functions of the system. Generally, it is very difficult to solve this integral directly. The evaluation of system reliability has been the active research area. Some methods were developed to solve system reliability analysis, such as Monte Carlo method, importance sampling method, bounding techniques and probability network evaluation technique (PNET). This paper presents the implementation of several optimization algorithms, modified method of feasible direction (MFD), sequential linear programming (SLP) and sequential quadratic programming (SQP), in order to demonstrate the convergence abilities and robust nature of the optimization technique when applied to series system reliability analysis. Examples taken from the published references were calculated and the results were compared with the answers of various other methods and the exact solution. Results indicate the optimization technique has a wide range of application with good convergence ability and robustness, and handle problems under generalized conditions or cases.
The efficiency of transferring a pack of small-sized flies or a large-sized file is very low in FTP based file transfer system. To solve this problem, we have studied the optimized method of different types of file tr...
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The efficiency of transferring a pack of small-sized flies or a large-sized file is very low in FTP based file transfer system. To solve this problem, we have studied the optimized method of different types of file transfer and present an adaptive transfer algorithm. Based on this algorithm. We design and implement the file transfer subsystem of global distributed storage system.
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