Fitness assessment of document model

Document classification is a supervised machine learning process, where predefined category labels are assigned to documents based on the hypothesis derived from training set of labelled documents. Documents cannot be directly interpreted by a computer system unless they have been modelled as a collection of computable features. Rogati and Yang [M. Rogati and Y. Yang, Resource selection for domain-specific cross-lingual IR, in SIGIR 2004: Proceedings of the 27th annual international conference on Research and Development in Information Retrieval, ACM Press, Sheffied: United Kingdom, pp. 154-161.] pointed out that the effectiveness of document classification system may vary in different domains. This implies that the quality of document model contributes to the effectiveness of document classification. Conventionally, model evaluation is accomplished by comparing the effectiveness scores of classifiers on model candidates. However, this kind of evaluation methods may encounter either under-fitting or over-fitting problems, because the effectiveness scores are restricted by the learning capacities of classifiers. We propose a model fitness evaluation method to determine whether a model is sufficient to distinguish positive and negative instances while still competent to provide satisfactory effectiveness with a small feature subset. Our experiments demonstrated how the fitness of models are assessed. The results of our work contribute to the researches of feature selection, dimensionality reduction and document classification.

Web services based state of the environment reporting

The Environmental Sciences Division within Queensland Environmental Protection Agency works to monitor, assess and model the condition of the environment. The Division has as a legislative responsibility to produce a whole-of-government report every four years dealing environmental conditions and trends in a ”State of the Environment report” (SoE)[1][2][3]. State of Environment Web Service Reporting System is a supplementary web service based SoE reporting tool, which aims to deliver accurate, timely and accessible information on the condition of the environment through web services via Internet [4][5]. This prototype provides a scientific assessment of environmental conditions for a set of environmental indicators. It contains text descriptions and tables, charts and maps with spatiotemporal dimensions to show the impact of certain environmental indicators on our environment. This prototype is a template based indicator system, to which the administrator may add new sql queries for new indicator services without changing the architecture and codes of this template. The benefits are brought through a service-oriented architecture which provides an online query service with seamless integration. In addition, since it uses web service architecture, each individual component within the application can be implemented by using different programming languages and in different operating systems. Although the services showed in this demo are built upon two datasets of regional ecosystem and protection area of Queensland, it will be possible to report on the condition of water, air, land, coastal zones, energy resources, biodiversity, human settlements and natural culture heritage on the fly as well. Figure 1 shows the architecture of the prototype. In the next section, I will discuss the research tasks in the prototype.

Internet-based indicated prevention for panic disorder: An effectiveness trial in primary care

Previous studies have shown that an internet delivered indicated prevention program for panic disorder can be effective. However, those studies were done with select populations. Most individuals who are at risk for panic disorder present to hospital emergency rooms and primary care settings. This paper reports on a study currently being undertaken in Scotland where the program is being trialed in primary care. The intervention and experimental design will be described. However the key research question is whether General Practitioners will make use of the internet-based intervention system. Preliminary results will be reported. The results of the study will have implications for the way that primary care is recruited into the prevention of mental health problems.

UML approach to the generation of test sequences for Java-based concurrent systems

Starting with a UML specification that captures the underlying functionality of some given Java-based concurrent system, we describe a systematic way to construct, from this specification, test sequences for validating an implementation of the system. The approach is to first extend the specification to create UML state machines that directly address those aspects of the system we wish to test. To be specific, the extended UML state machines can capture state information about the number of waiting threads or the number of threads blocked on a given object. Using the SAL model checker we can generate from the extended UML state machines sequences that cover all the various possibilities of events and states. These sequences can then be directly transformed into test sequences suitable for input into a testing tool such as ConAn. As an illustration, the methodology is applied to generate sequences for testing a Java implementation of the producer-consumer system. © 2005 IEEE

Patterns in complex systems modeling

The design, development, and use of complex systems models raises a unique class of challenges and potential pitfalls, many of which are commonly recurring problems. Over time, researchers gain experience in this form of modeling, choosing algorithms, techniques, and frameworks that improve the quality, confidence level, and speed of development of their models. This increasing collective experience of complex systems modellers is a resource that should be captured. Fields such as software engineering and architecture have benefited from the development of generic solutions to recurring problems, called patterns. Using pattern development techniques from these fields, insights from communities such as learning and information processing, data mining, bioinformatics, and agent-based modeling can be identified and captured. Collections of such 'pattern languages' would allow knowledge gained through experience to be readily accessible to less-experienced practitioners and to other domains. This paper proposes a methodology for capturing the wisdom of computational modelers by introducing example visualization patterns, and a pattern classification system for analyzing the relationship between micro and macro behaviour in complex systems models. We anticipate that a new field of complex systems patterns will provide an invaluable resource for both practicing and future generations of modelers.

Differential evolution based total transfer capability assessment with optimal dispatch

In this paper, a new differential evolution (DE) based power system optimal available transfer capability (ATC) assessment is presented. Power system total transfer capability (TTC) is traditionally solved by the repeated power flow (RPF) method and the continuation power flow (CPF) method. These methods are based on the assumption that the productions of the source area generators are increased in identical proportion to balance the load increment in the sink area. A new approach based on DE algorithm to generate optimal dispatch both in source area generators and sink area loads is proposed in this paper. This new method can compute ATC between two areas with significant improvement in accuracy compared with the traditional RPF and CPF based methods. A case study using a 30 bus system is given to verify the efficiency and effectiveness of this new DE based ATC optimization approach.