28523270
Goal based agent-oriented software modeling
This paper presents a goal based modeling method for an agent-oriented software system. In modeling research for agent-oriented software, problems often emerged in that the properties of an agent system were not efficiently reflected in the development phase (analysis, design, etc.), because the techniques based on the other software paradigm are adopted to develop agent-oriented software. The result of analysis differs depending on which paradigm is used. An agent is goal-oriented, which necessitates a shift in paradigm. Therefore, the modeling method for an agent system should start from the concept of goal.
8536996
Goal and scenario based domain requirements analysis environment
Identifying and representing domain requirements among products in a product family are crucial activities for a successful software reuse. The domain requirements should be not only identified based on the business goal, which drives marketing plan, product plan, and differences among products, but also represented as familiar notations in order to support developing a particular product in the product family. Thus, our proposal is to identify the domain requirements through goals and scenarios, and represent them as variable use cases for a product family. Especially, for identification of the domain requirements, we propose four abstraction levels of requirements in a product family, and goal and scenario modeling. For representation of them, variable use case model is suggested, and also the use case transfer rules are proposed so as to bridge the gap between the identification and representation activity. The paper illustrates the application of the approach within a supporting tool using the HIS (Home Integration System) example.
35666646
A Linguistics-Based Approach for Use Case Driven Analysis Using Goal and Scenario Authoring
Although Use Case driven analysis has been widely used in requirements analysis, it does not facilitate effective requirements elicitation or provide rationale for the various artifacts that get generated. On the other hand, goal and scenario based approach is considered to be effective for elicitation but it does not lead to use cases. This paper discusses how to combine goal and scenario based requirements elicitation technique with use case driven analysis using natural language concepts. In our proposed approach, four levels of goals, scenario authoring rules, and linguistic techniques have been developed to identify use cases from text based goal and scenario descriptions. The artifacts resulting from our approach could be used as input to a use case diagramming tool to automate the process of use case diagram generation.
16878992
Improving use case driven analysis using goal and scenario authoring: A linguistics-based approach
Use case driven analysis does not facilitate effective requirements elicitation or provide rationale for the various artifacts that get generated during the requirements analysis phase. On the other hand, goal and scenario based approach is considered to be effective for elicitation but it does not lead to use cases. This paper discusses how to combine goal and scenario based requirements elicitation technique with use case driven analysis using natural language concepts. In our proposed approach, four levels of goals, scenario authoring rules, and linguistic techniques have been developed to identify use cases from text based goal and scenario descriptions. The artifacts resulting from our approach could be used as input to a use case diagramming tool to automate the process of use case diagram generation.
2562587
Creating a Robust Desktop Grid using Peer-to-Peer Services
The goal of the work described in this paper is to design and build a scalable infrastructure for executing grid applications on a widely distributed set of resources. Such grid infrastructure must be decentralized, robust, highly available, and scalable, while efficiently mapping application instances to available resources in the system. However, current desktop grid computing platforms are typically based on a client-server architecture, which has inherent shortcomings with respect to robustness, reliability and scalability. Fortunately, these problems can be addressed through the capabilities promised by new techniques and approaches in peer-to-peer (P2P) systems. By employing P2P services, our system allows users to submit jobs to be run in the system and to run jobs submitted by other users on any resources available in the system, essentially allowing a group of users to form an ad-hoc set of shared resources. The initial target application areas for the desktop grid system are in astronomy and space science simulation and data analysis.
18486242
Perfect matchings in random uniform hypergraphs
Let ℋk(n, p) be the random k-uniform hypergraph on V = [n] with edge probability p. Motivated by a theorem of Erdős and Renyi 7 regarding when a random graph G(n, p) = ℋ2(n, p) has a perfect matching, the following conjecture may be raised. (See J. Schmidt and E. Shamir 16 for a weaker version.) Conjecture. Let k|n for fixed k ≥ 3, and the expected degree d(n, p) = p(). Then 
 
 
 
 
 
 
(Erdős and Renyi 7 proved this for G(n, p).) Assuming d(n, p)/n1/2 ∞, Schmidt and Shamir 16 were able to prove that ℋk(n, p) contains a perfect matching with probability 1 − o(1). Frieze and Janson 8 showed that a weaker condition d(n, p)/n1/3 ∞ was enough. In this paper, we further weaken the condition to 
 
 
 
 
 
 
A condition for a similar problem about a perfect triangle packing of G(n, p) is also obtained. A perfect triangle packing of a graph is a collection of vertex disjoint triangles whose union is the entire vertex set. Improving a condition p ≥ cn−2/3+1/15 of Krivelevich 12, it is shown that if 3|n and p ≫ n−2/3+1/18, then 
 
 
 
 
 
 
© 2003 Wiley Periodicals, Inc. Random Struct. Alg., 23: 111–132, 2003
5105796
Two-stage normalization using background intensities in cDNA microarray data
BackgroundIn the microarray experiment, many undesirable systematic variations are commonly observed. Normalization is the process of removing such variation that affects the measured gene expression levels. Normalization plays an important role in the earlier stage of microarray data analysis. The subsequent analysis results are highly dependent on normalization. One major source of variation is the background intensities. Recently, some methods have been employed for correcting the background intensities. However, all these methods focus on defining signal intensities appropriately from foreground and background intensities in the image analysis. Although a number of normalization methods have been proposed, no systematic methods have been proposed using the background intensities in the normalization process.ResultsIn this paper, we propose a two-stage method adjusting for the effect of background intensities in the normalization process. The first stage fits a regression model to adjust for the effect of background intensities and the second stage applies the usual normalization method such as a nonlinear LOWESS method to the background-adjusted intensities. In order to carry out the two-stage normalization method, we consider nine different background measures and investigate their performances in normalization. The performance of two-stage normalization is compared to those of global median normalization as well as intensity dependent nonlinear LOWESS normalization. We use the variability among the replicated slides to compare performance of normalization methods.ConclusionsFor the selected background measures, the proposed two-stage normalization method performs better than global or intensity dependent nonlinear LOWESS normalization method. Especially, when there is a strong relationship between the background intensity and the signal intensity, the proposed method performs much better. Regardless of background correction methods used in the image analysis, the proposed two-stage normalization method can be applicable as long as both signal intensity and background intensity are available.
15504838
Utilization-based heuristics for statically mapping real-time applications onto the HiPer-D heterogeneous computing system
Real-time applications continue to increase in importance as they are employed in various critical areas, such as command and control systems. These applications have traditionally required custom-made systems to execute them. Recently, with the widespread use of increasingly powerful commercial off-the-shelf (COTS) products, some real-time system designers have started a shift from custom development to COTS-based systems to achieve lower costs and more flexible systems. This research investigates the problem of allocating real-time applications to a set of COTS heterogeneous machines connected together by a COTS high-speed network. The heuristics were implemented on the High Performance Distributed Computing Program's (HiPer-D) Naval Surface Warfare Center (NSWC) testbed. At the specification of NSWC, the goal of this study is to design static resource allocation heuristics that balance the utilization of the computation and network resources in the HiPer-D system based on the system information provided. The broader goal is to maximize the time before dynamic reallocation is required for managing an increased workload at runtime.
16116503
Evolutionary programming techniques for constrained optimization problems
Two evolutionary programming (EP) methods are proposed for handling nonlinear constrained optimization problems. The first, a hybrid EP, is useful when addressing heavily constrained optimization problems both in terms of computational efficiency and solution accuracy. But this method offers an exact solution only if both the mathematical form of the objective function to be minimized/maximized and its gradient are known. The second method, a two-phase EP (TPEP) removes these restrictions. The first phase uses the standard EP, while an EP formulation of the augmented Lagrangian method is employed in the second phase. Through the use of Lagrange multipliers and by gradually placing emphasis on violated constraints in the objective function whenever the best solution does not fulfill the constraints, the trial solutions are driven to the optimal point where all constraints are satisfied. Simulations indicate that the TPEP achieves an exact global solution without gradient information, with less computation time than the other optimization methods studied here, for general constrained optimization problems.