The application of adaptive partitioned random search in feature selection problem

Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.

Systems for assessing the effectiveness of management in protected areas

Since the mid-1990s, numerous methodologies have been developed to assess the management effectiveness of protected areas, many tailored to particular regions or habitats. Recognizing the need for a generic approach, the World Commission on Protected Areas (WCPA) developed an evaluation framework allowing specific evaluation methodologies to be designed within a consistent overall approach. Twenty-seven assessment methodologies were analyzed in relation to this framework. Two types of data were identified: quantitative data derived from monitoring and qualitative data derived from scoring by managers and stakeholders. The distinction between methodologies based on data types reflects different approaches to assessing management. Few methodologies assess all the WCPA framework elements. More useful information for adaptive management will come from addressing all six elements. The framework can be used to adapt existing methodologies or to design new, more comprehensive methodologies for evaluation, using quantitative monitoring data, qualitative scoring data, or a combination of both.

Ex ante evaluations of alternate data structures for end user queries: Theory and experimental test

The data structure of an information system can significantly impact the ability of end users to efficiently and effectively retrieve the information they need. This research develops a methodology for evaluating, ex ante, the relative desirability of alternative data structures for end user queries. This research theorizes that the data structure that yields the lowest weighted average complexity for a representative sample of information requests is the most desirable data structure for end user queries. The theory was tested in an experiment that compared queries from two different relational database schemas. As theorized, end users querying the data structure associated with the less complex queries performed better Complexity was measured using three different Halstead metrics. Each of the three metrics provided excellent predictions of end user performance. This research supplies strong evidence that organizations can use complexity metrics to evaluate, ex ante, the desirability of alternate data structures. Organizations can use these evaluations to enhance the efficient and effective retrieval of information by creating data structures that minimize end user query complexity.

A companison of socially responsible and conventional investors

Socially responsible investment is a rapidly emerging phenomenon within the field of personal investment. However, the factors that lead investors to choose socially responsible investment products are not well understood, especially in an Australian context. This study provides a comparative examination of conventional and socially responsible investors, with the aim of identifying such factors. A total of 55 conventional investors and 54 ethical investors participated in the study by completing mailed questionnaires about their investment and general behaviour and their attitudes and beliefs. Results indicated some important differences between socially responsible and conventional investors in their beliefs of the importance of ethical issues, their investment decision-making style, and their perceptions of moral intensity. These results support the notion that socially responsible investors differ in critical ways to conventional investors, and are discussed in terms of theoretical and practical implications.

Factors affecting student attitudes toward flexible online learning in management education

In response to recent technological advances and the trend toward flexible learning in education, the authors examined the factors affecting student satisfaction with flexible online learning. The authors identified 2 key student attributes of student satisfaction: (a) positive perceptions of technology in terms of ease of access and use of online flexible learning material and (b) autonomous and innovative learning styles. The authors derived measures of perceptions of technology from research on the Technology Acceptance Model and used locus of control and innovative attitude as indicators of an autonomous and innovative learning mode. First-year students undertaking an introductory management course completed surveys at the beginning (n = 248) and at the end (n = 256) of course work. The authors analyzed the data by using structural equation modeling. Results suggest that student satisfaction is influenced by positive perceptions toward technology and an autonomous learning mode.

Towards a profitable and sustainable future for grain growers: A professional development model for farm partners

Many Australian grain growers need to change their management approach to ensure their continued viability, but do not have the required knowledge and skills. Uptake of relevant education and training is poor, despite the positive correlation between learning, change and farm viability. As men are generally occupied with the operational aspects of the farm, much of the management role has been taken on by their partners, despite their lack of relevant formal qualifications. Professional development of farm partners therefore has the potential to improve the viability of grain growers. A model combining learning circles and action learning projects is proposed.