4495280
Mapping Nominal Values to Numbers for Effective Visualization
Data sets with a large numbers of nominal variables, including some with large number of distinct values, are becoming increasingly common and need to be explored. Unfortunately, most existing visual exploration tools are designed to handle numeric variables only. When importing data sets with nominal values into such visualization tools, most solutions to date are rather simplistic. Often, techniques that map nominal values to numbers do not assign order or spacing among the values in a manner that conveys semantic relationships. Moreover, displays designed for nominal variables usually cannot handle high cardinality variables well. This paper addresses the problem of how to display nominal variables in general-purpose visual exploration tools designed for numeric variables. Specifically, we investigate (1) how to assign order and spacing among the nominal values, and (2) how to reduce the number of distinct values to display. We propose a new technique, called the Distance-Quantification-Classing (DQC) approach, to preprocess nominal variables before being imported into a visual exploration tool. In the Distance Step, we identify a set of independent dimensions that can be used to calculate the distance between nominal values. In the Quantification Step, we use the independent dimensions and the distance information to assign order and spacing among the nominal values. In the Classing Step, we use results from the previous steps to determine which values within the domain of a variable are similar to each other and thus can be grouped together. Each step in the DQC approach can be accomplished by a variety of techniques. We extended the XmdvTool package to incorporate this approach. We evaluated our approach on several data sets using a variety of measures.
14384022
Designing semantics-preserving cluster representatives for scientific input conditions
In scientific domains, knowledge is often discovered from experiments by grouping or clustering them based on the similarity of their output. The causes of similarity are analyzed based on the input conditions characterizing a given type of output, i.e., a given cluster. This analysis helps in applications such as decision support in industry. Cluster representatives form at-a-glance depictions for such applications. Randomly selecting a set of conditions in a cluster as its representative is not sufficient since distinct combinations of inputs could lead to the same cluster. In this paper, an approach called DesCond is proposed to design semantics-preserving cluster representatives for scientific input conditions. We define a notion of distance for conditions to capture semantics based on the types of their attributes and their relative importance. Using this distance, methods of building candidate cluster representatives with different levels of detail are proposed. Candidates are compared using the DesCond Encoding proposed in this paper that assesses their complexity and information loss, given user interests. The candidate with the lowest encoding for each cluster is returned as its designed representative. DesCond is evaluated with real data from Materials Science. Evaluation with domain expert interviews and formal user surveys shows that designed representatives consistently outperform randomly selected ones and different candidates suit different users.
13541175
Evaluating Network Serviceability
Abstract The capability to manage network operations on a day-to-day basis has become an important area of concern given the rapid expansion of computer networks. A related, but much less studied area, is the impact that the design of a network has on the ease with which it can be serviced. Evaluating the ease of servicing the network and its components does not concentrate on day-to-day operations of the network, but rather examines the network design over a longer term to identify problematic components, configurations and dependencies between components based on expert knowledge and historical data. This paper reports on our experience with a system to evaluate the ease of servicing a network—its serviceability—given a description of its design. The motivation for the work is that computer networks are more often “grown” than “designed” without concern for serviceability issues. The work also examines the impact of dependencies between components on the role of service and the potential disruption costs caused by these dependencies. This work is important because it is pro-active in explicitly considering the role of servicing a network when changing the components or configuration of a network. This approach is in contrast to network management, which is reactive in dealing with problems. The paper reports on a successful implementation of such as system and our experiences with it.
195710721
Special Issue: Machine Learning in Design
This issue of AIEDAM is based on a workshop on Machine Learning in Design held at the 1996 Conference on Artificial Intelligence in Design, AID'96 (Gero & Sudweeks, 1996), the third of such workshops, with the previous two being held at AID'92 (Gero, 1992) and at AID'94 (Gero & Sudweeks, 1994). The first two workshops also resulted in special issues of AIEDAM (Maher et al., 1994; Duffy et al., 1996).
7484630
A Graduate Level Expert Systems Course
This article presents an approach to a graduate-level course in expert, knowledge-based, problem-solving systems. The core of the course, and this article, is a set of questions called a profile, that can be used to characterize and compare each system studied.
6315058
Knowledge and Control for a Mechanical Design Expert System
A new variety of Oriental hybrid lily plant bearing large upright-facing flowers particularly characterized by their clear pink coloration with deeper midribs, their large size and substance, and their upright to semi-upright orientation, the flowers being of excellent form and long persistence both on the plant and as cut flowers. This combination is completely new in the Oriental hybrid divisions of lilies suited to forcing and to mass commercial cultivation. The plant is an excellent garden plant, highly resistant to disease and shows tolerance of virus; the bulbs may be precooled and forced for cut flower production and the clone is vigorous, a good grower and a good propagator.
317687
A Cost Model for Determining the Optimal Number of Software Test Cases
A probabilistic model is presented that demonstrates the optimal number of software test cases required in situations where the following can be estimated as independent parameters: (1) the cost per test; (2) the cost per error if undetected until field implementation; (3) the number of software executions over its lifetime; (4) the number of possible different executions; and (5) the number of faults embedded in the software. A formula is derived by the use of calculus and is solved by approximation techniques. Tables of the optimal number of tests over a range of parameter values are presented to illustrate the results. The model serves as a basis for further research efforts to improve the accuracy of input variable estimation. >
1207779
Experience in Teaching a Management-Oriented Capstone Software Engineering Course
Many computer science departments teach a capstone software engineering course involving the design and implementation of a large-scale project. Such a course is normally taught with students working together in teams; consequently, students must face a number of problems related to project management and team dynamics. Our experience has been that students frequently fail to adequately cope with these organizational problems, and consequently fail to complete their projects at an acceptable level of quality. To prepare students to better face these problems, we have modified our capstone software engineering course to provide equal emphasis in both management and technical areas. Our approach to management topics is formal rather than anecdotal, stressing general principles applied to organizational problems arising specifically from situations that occur frequently in technical organizations. This paper reports on the structure of this course, and provides insight into our initial experience in teaching it.
3217487
A Rule-Based Software Test Data Generator
Rule-based software test data generation is proposed as an alternative to either path/predicate analysis or random data generation. A prototype rule-based test data generator for Ada programs is constructed and compared to a random test data generator. Four Ada procedures are used in the comparison. Approximately 2000 rule-based test cases and 100000 randomly generated test cases are automatically generated and executed. The success of the two methods is compared using standard coverage metrics. Simple statistical tests showing that even the primitive rule-based test data generation prototype is significantly better than random data generation are performed. This result demonstrates that rule-based test data generation is feasible and shows great promise in assisting test engineers, especially when the rule base is developed further. >
14059768
Spatial process and data models: Toward integration of agent-based models and GIS
Abstract.The use of object-orientation for both spatial data and spatial process models facilitates their integration, which can allow exploration and explanation of spatial-temporal phenomena. In order to better understand how tight coupling might proceed and to evaluate the possible functional and efficiency gains from such a tight coupling, we identify four key relationships affecting how geographic data (fields and objects) and agent-based process models can interact: identity, causal, temporal and topological. We discuss approaches to implementing tight integration, focusing on a middleware approach that links existing GIS and ABM development platforms, and illustrate the need and approaches with example agent-based models.
12974717
A System for Learning Routes and Schedules with Genetic Algorithms