The status and relevance of Vietnamese journalism education: An empirical analysis

Based primarily on data from indepth interviews with senior journalists and journalism educators as well as a content analysis of journalism curricula, this paper sets out to provide an overview of the demand, overall provision structure, teaching materials and methods of Vietnamese journalism education. It first shows that with a fast expansion in both size and substance, the Vietnamese media system is beginning to feel the urgent need for formal journalism education. However, the country's major journalism programs have been criticised for producing hundreds of unqualified journalism graduates a year. In general, the most deplorable aspects of Vietnamese journalism education include its body of outdated and awkward teaching material, its undue focus on theories and politics at the expense of practical training, its lack of qualified teaching staff and its inadequate teaching resources.

From bush to bouquet: The relevance of market research

‘Adopt a consumer focus’ is the mantra that pervades the commercialisation strategies of horticultural products world-wide, but does this translate into practice in small and medium enterprises or is the process still production driven? Typically, new products in floriculture are modifications of existing products, which are introduced to existing markets, where consumers’ needs are well understood. Under these circumstances, the traditional role of market research is marginalised. In contrast, the commercialisation of ‘true’ new products into new markets involves a greater effort. Here, market research can identify market segments that are more receptive to innovation and experimentation. In this paper, the authors draw upon preliminary research and their initial experiences in the commercialisation of an Australian native flower to examine the inter-play of information flows and new product development.

Customer information system data pre-processing with feature selection techniques for non-technical losses prediction in an electricity market

Non-technical losses (NTL) identification and prediction are important tasks for many utilities. Data from customer information system (CIS) can be used for NTL analysis. However, in order to accurately and efficiently perform NTL analysis, the original data from CIS need to be pre-processed before any detailed NTL analysis can be carried out. In this paper, we propose a feature selection based method for CIS data pre-processing in order to extract the most relevant information for further analysis such as clustering and classifications. By removing irrelevant and redundant features, feature selection is an essential step in data mining process in finding optimal subset of features to improve the quality of result by giving faster time processing, higher accuracy and simpler results with fewer features. Detailed feature selection analysis is presented in the paper. Both time-domain and load shape data are compared based on the accuracy, consistency and statistical dependencies between features.