MORTALITY SALIENCE AND REACTIONS TOWARD CRITICAL INGROUP AND OUTGROUP MEMBERS

Ph.DDOCTOR OF PHILOSOPH

Influenza pattern analysis system through mining weblogs

Weblogs are resource of social structure to discover and track the various type of information written by bloggers. In this paper we proposed to use mining weblogs technique for identifying the trends of influenza where blogger had disseminated their opinion for the anomaly disease. In order to identify the trends, web crawler is applied to perform a search and generated a list of visited links based on a set of influenza keywords. This information is used to implement the analytics report system for monitoring and analyzing the pattern and trends of influenza (H1N1. Statistical and graphical analysis reports are generated. Both types of the report have shown satisfactory reports that reflect the awareness of Malaysian on the issue of influenza outbreak through blogs

Strategies for Preventing Drug Recidivism Cycle in Taiwan

Drug abuse is currently a worldwide problem and Taiwan is no exception. Drug abuse is a disease that must be treated on the basis of evidence (United Nations Office on Drugs and Crime 2007; World Health Organisation 2004). In order to reduce the damage caused by drug abuse to the nation, society and people, the government not only developed two anti-drug strategies - that of supply eradication and demand reduction - but since May 1994, has mobilised relevant government departments to take assertive action. Some of the actions include law enforcement enhancement, anti-drug enforcement and drug rehabilitation utilisation. In 2005, new anti-drug programs, such as the sterile needle exchange program and substitution therapy program, were also introduced. The cities implementing the Harm Reduction Program (HR Program) showed lower HIV infection rates in comparison to others without the HR Program. The income and employment conditions of drug addicted patients receiving Methadone Maintenance Treatment have been improved. The future drug policies in Taiwan will focus on drug rehabilitation (treatment), anti-drug actions (prevention) and law enforcement (punishment). The educational system, community recovery and aftercare for drug addicts will also be indispensable (WHO/UNODC/UNAIDS 2004)

Side-Effect Localization for Lazy, Purely Functional Languages via Aspects

Many side-effecting programming activities, such as profiling and tracing, can be formulated as crosscutting concerns and be framed as side-effecting aspects in the aspect-oriented programming paradigm. The benefit gained from this separation of concerns is particularly evident in purely functional programming, as adding such aspects using techniques such as monadification will generally lead to crosscutting changes. This paper presents an approach to provide side-effecting aspects for lazy purely functional languages in a user transparent fashion. We propose a simple yet direct state manipulation construct for developing side-effecting aspects and devise a systematic monadification scheme to translate the woven code to monadic style purely functional code. Furthermore, we present a static and dynamic semantics of the aspect programs and reason about the correctness of our monadification scheme with respect to them

Driving behavior-guided battery health monitoring for electric vehicles using machine learning

An accurate estimation of the state of health (SOH) of batteries is critical to ensuring the safe and reliable operation of electric vehicles (EVs). Feature-based machine learning methods have exhibited enormous potential for rapidly and precisely monitoring battery health status. However, simultaneously using various health indicators (HIs) may weaken estimation performance due to feature redundancy. Furthermore, ignoring real-world driving behaviors can lead to inaccurate estimation results as some features are rarely accessible in practical scenarios. To address these issues, we proposed a feature-based machine learning pipeline for reliable battery health monitoring, enabled by evaluating the acquisition probability of features under real-world driving conditions. We first summarized and analyzed various individual HIs with mechanism-related interpretations, which provide insightful guidance on how these features relate to battery degradation modes. Moreover, all features were carefully evaluated and screened based on estimation accuracy and correlation analysis on three public battery degradation datasets. Finally, the scenario-based feature fusion and acquisition probability-based practicality evaluation method construct a useful tool for feature extraction with consideration of driving behaviors. This work highlights the importance of balancing the performance and practicality of HIs during the development of feature-based battery health monitoring algorithms

Augmenting Dublin Core digital library metadata with Dewey Decimal Classification

Purpose – The purpose of this paper is to describe a new approach to a well-known problem for digital libraries, how to search across multiple unrelated libraries with a single query. Design/methodology/approach – The approach involves creating new Dewey Decimal Classification terms and numbers from existing Dublin Core records. In total, 263,550 records were harvested from three digital libraries. Weighted key terms were extracted from the title, description and subject fields of each record. Ranked DDC classes were automatically generated from these key terms by considering DDC hierarchies via a series of filtering and aggregation stages. A mean reciprocal ranking evaluation compared a sample of 49 generated classes against DDC classes created by a trained librarian for the same records. Findings – The best results combined weighted key terms from the title, description and subject fields. Performance declines with increased specificity of DDC level. The results compare favorably with similar studies. Research limitations/implications – The metadata harvest required manual intervention and the evaluation was resource intensive. Future research will look at evaluation methodologies that take account of issues of consistency and ecological validity. Practical implications – The method does not require training data and is easily scalable. The pipeline can be customized for individual use cases, for example, recall or precision enhancing. Social implications – The approach can provide centralized access to information from multiple domains currently provided by individual digital libraries. Originality/value – The approach addresses metadata normalization in the context of web resources. The automatic classification approach accounts for matches within hierarchies, aggregating lower level matches to broader parents and thus approximates the practices of a human cataloger. </jats:sec