Knowledge reduction is one of the most important issues in rough sets theory. Many works are related to connection-degree-based rough sets model to treat incomplete information systems. However, the model is not used ...
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Knowledge reduction is one of the most important issues in rough sets theory. Many works are related to connection-degree-based rough sets model to treat incomplete information systems. However, the model is not used to knowledge reduction. In this paper, a connection-degree-based rough sets model is proposed and used to knowledge reduction. Two ways for knowledge reduction are proposed and the relationships between them are shown. A knowledge reduction algorithm is also shown for incomplete information systems. The algorithm is based on elementary discernibility matrix and the significance degree of an attribute. Examples are used to show that the validity of the algorithm.
Vehicular Ad-hoc networks (VANETS) provide distributed real time communication of traffic hazards and road conditions among vehicles in a radio line of sight. We propose using VANETS to securely communicate with Posit...
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Vehicular Ad-hoc networks (VANETS) provide distributed real time communication of traffic hazards and road conditions among vehicles in a radio line of sight. We propose using VANETS to securely communicate with Positive Train Control (PTC) Systems in order to reduce Highway Rail Intersection (HRI) incidents. This paper illustrates the similarities and differences between the two systems, discusses previous research into the work already done to integrate the two systems, and outlines the additional work necessary to successfully integrate the two systems.
Ant colony optimization (ACO) algorithm is a metaheuristic and stochastic search technology, which has been one of the effective tools for solving discrete optimization problems. However, there are two bottlenecks for...
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ISBN:
(纸本)9780769530277
Ant colony optimization (ACO) algorithm is a metaheuristic and stochastic search technology, which has been one of the effective tools for solving discrete optimization problems. However, there are two bottlenecks for large-scaled optimization problems: the ACO algorithm needs too much time to convergent and the solutions may not be really optimal. This paper proposes a novel ACO algorithm for the multidimensional knapsack problems (MKP), which employs a new pheromone diffusion model and a mutation scheme. First, in light of the preference to better solutions, the association distances among objects are mined in each iteration with top-k strategy. Then, a pheromone diffusion model based on info fountain of an object is established, which strengthens the collaborations among ants. Finally, an unique mutation scheme is applied to optimizing the evolution results of each step. The experimental results for the benchmark testing set of MKPs show that the proposed algorithm can not only get much more optimal solutions but also greatly enhance convergence speed.
Image based reconstruction from multiple views is an interesting challenge. Recently methods of optimisation based voxel colouring have appeared which make use of incremental visibility updates. We present an alternat...
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Image based reconstruction from multiple views is an interesting challenge. Recently methods of optimisation based voxel colouring have appeared which make use of incremental visibility updates. We present an alternative incremental voxel colouring algorithm in the mould of GVC-LDI, which directly associates each visible voxel with the set of rays in it's visible projection, using ray-voxel traversal as a mechanism for updates. We make some time comparisons using calibrated photographs and synthetic images, as well looking at optimisation based voxel colouring and level of detail. Results show that our method compares favourably to GVC-LDI
Multicomputers are distributed memory systems in which independent computers are connected with each other by a network. Multicomputers are widely used in business and scientific applications. Due to their flexibility...
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Multicomputers are distributed memory systems in which independent computers are connected with each other by a network. Multicomputers are widely used in business and scientific applications. Due to their flexibility, scalability, and cost performance, multicomputer systems are considered preferable to multiprocessor systems. They are also gaining attraction in the area of Internetbased computing, in which delays or interruptions in client-server interactions may be equally costly to service providers and customers. Multicomputer systems attributed with high available (HA) solutions may be used to withstand service unavailability due to the web servers' failures. In this paper we investigate a Markov model-based approach to estimate the availability of multicomputer systems with and without HA. The availability is computed as a function of server failure rate and the number of surviving servers. This model can estimate the number of nodes needed for a required availability measure.
This talk provides a personal perspective on the evolution of empirical softwareengineering. The evolution has included the focus of the studies, e.g., from attempting to demonstrate the effectiveness of various proc...
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ISBN:
(纸本)1595932186
This talk provides a personal perspective on the evolution of empirical softwareengineering. The evolution has included the focus of the studies, e.g., from attempting to demonstrate the effectiveness of various processes to the building of knowledge around a domain or a set of processes. The study designs have changed from strictly quantitative studies to all forms of controlled experiments, quasi-experiments, preexperimental designs, case studies, field studies, and focus group activities. There has been recognition of the importance and influence of context variables and the domain in interpreting the results of studies. The issue of meta-analysis has become more important and is still an elusive goal. A community of empiricists has evolved that allows for the replication of studies leading to the identification of context variables. But there still does not exist a community consensus on the right ways to build bodies of knowledge or a "blessed" set of approaches. We argue over what is appropriate evidence when we review papers. We struggle with the concept of experimental replication. We do not know how to break an empirical study into significant small enough chunks for publication in the various standard forums. We have not convinced the softwareengineering community that empirical study is a necessary or even valuable research paradigm for the field. What other problems that remain? How can they be solved? What will the future hold for empirical study? This talk will address these issues and propose a possible path towards a mature empirical softwareengineering discipline.
During reverse engineering, developers often need to understand the undocumented design of a software. In particular, recognizing design patterns in the software can provide reverse engineers with considerable insight...
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ISBN:
(纸本)1595934006
During reverse engineering, developers often need to understand the undocumented design of a software. In particular, recognizing design patterns in the software can provide reverse engineers with considerable insight on the software structure and its internal characteristics. Researchers have therefore proposed techniques based on static analysis to automatically recover design patterns in a program. Unfortunately, most design patterns comprise not only structural, but also significant behavioral aspects. Although static analysis is well suited for the recognition of structural aspects, it is typically limited and imprecise in analyzing behavior. To address this limitation, we present a new technique that complements our existing static analysis with a dynamic analysis, so as to perform a more accurate design-pattern recognition. The dynamic analysis is based on (1) transforming behavioral aspects of design patterns into finite automata, (2) identifying and instrumenting relevant method calls, and (3) monitoring relevant calls at runtime and matching them against the automata. The results of the dynamic analysis are then used to compute the likelihood of a pattern to be in the code. This paper describes our technique and presents a preliminary empirical study performed to assess the technique. Copyright 2006 ACM.
In a competitive market, quality is essential to the software. software test plays an important role during the software-developing period. Any saving on software test, will greatly reduce the total cost of software. ...
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ISBN:
(纸本)1424400384
In a competitive market, quality is essential to the software. software test plays an important role during the software-developing period. Any saving on software test, will greatly reduce the total cost of software. The key point of this paper is to build a software test process with the cost control management and to make tradeoff between the quality and the cost. Typical software testing model are analyzed and compared. A novel QC 3-D test model is introduced. The model combined with software test process, software quality cost and testing type. The computational formula is defined to calculate software quality cost. A software quality balance law is introduced to balance control cost and failure cost. By adjusting software test method and strategy, organization can reach the objective of the best balance between software quality and cost. An enterprise case is studied and the result is analyzed to prove the basic law. The result shows an optimistic point that will prove the accurate of the model and the law.
Unstructured Peer-to-Peer network uses flooding algorithm to route searching messages which not only brings unnecessary expenditure of network bandwidth, but also limits the rate of resource searching and expandabilit...
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Unstructured Peer-to-Peer network uses flooding algorithm to route searching messages which not only brings unnecessary expenditure of network bandwidth, but also limits the rate of resource searching and expandability of P2P system. In order to decrease the influence of this problem, this paper presented a new auto-clustering Peer-to-Peer system (ACP2P) based on classification search, and implemented the archetype of this system. The experiments using network simulator based on data packets show that the system can increase the rate of resource searching and expandability effectively.
One of the most difficult challenges in requirements engineering is understanding the information provided by the stakeholders so as to establish the requirements. Moreover, there is considerable frustration whenever ...
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