• Korean Journal of Food Science and Technology
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• v.49 no.6
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• pp.599-604
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• 2017

The purpose of this study was to explore methods for efficient management of the quality and safety of simple processed agricultural products in Busan. We tested 258 samples of simple processed agricultural products for distribution of aerobic bacteria and coliforms, and identified food-borne pathogens. The average aerobic bacterial and coliforms counts were 7.1 and 4.1 log CFU/g in simple processed vegetables, 6.8 and 3.5 log CFU/g in dried vegetables, and 6.2 and 2.9 log CFU/g in simple processed fruits. Additionally Staphylococcus aureus, Salmonella spp., Campylobacter jejuni/coli and Listeria monocytogenes were not detected in any samples. However, Bacillus cereus, Clostridium perfringens and E. coli were detected in 41 samples (16.3%), 2 samples (0.8%), and 4 samples (1.6%), respectively. This analysis revealed that none of C. perfringens and E. coli isolates harbored pathogenic toxic genes. However, all of B. cereus isolates carried at least 1 toxin gene.

• Korean Business Review
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• v.13
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• pp.179-193
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• 2000

It is not simple to manage software quality, because software development process and product itself are very complex. Recently ISO/IEC 15504- international standard for software process improvement, capability determination and development - was completed and applied to many local trials, and their results are being reported as registered local trials. The first step of software process assessment is established by examining whether its base practices are performed and which level they are achieved. And as far as assessment responsibility and credibility are concerned, assessment is generally performed by team-based assessors. Therefore assessment team construction and its preference of practice importances have a great effect on the credibility and the objectivity of assessment. In this paper, we analyse a SPICE-based software process assessment trial by comparing base practice importances of assessed processes, which are expressed through a real assessment, with its final rating results. Survey data are collected from assessors and interviewees who were engaged in the SPICE trial that was performed by ISO/IEC 15504, and final data analysis are derived from the factor analysis method. It is convinced that the result of this paper is able to enhance the credibility of software process assessment by provisions of objective and rational criteria and preference information for assessment team construction and base practice importances in future.

• Journal of Korean Home Economics Education Association
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• v.21 no.4
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• pp.105-125
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• 2009

This study attempts to extract the necessary criteria as a secondary school home economics teacher through the factor analysis, and to analysis the teacher's and student's perceptions for the requirement criteria of home economics teacher(RCHET) thereof to confirm the necessary criteria as a secondary school home economics teachers. This research was based on the requirement criteria of home economics teacher developed by Korea Institute for Curriculum and Evaluation(KICE) Korean Home Economics Education Association(2008)(KHEEA) collected from secondary, upper secondary school home economics teachers and students in Jeollabuk-do. RCHET encompasses the six areas : (l)'Expert of lesson related to evaluation' (2)'Efficient manager of diverse materials for study', (3)'Student advisor equipped with a teaching sense of duty and sound humanity', (4)'Curriculum expert equipped with a expertise knowledge', (5)'A fair and democratic schoolroom environment promoter'. (6)'Career path counselling expert understanding student's characteristics and environments'. Through the factor analysis, six RCHET factors are more important to teachers than students. According to importance perception for RCHET, home economics teachers' qualification for minor second subject and participation of training program showed similar differences statistically in all RCHET factors. Thus, effort for expertise improvement of teacher had important influence on expertise improvement of teacher. As a result of examining the differences from importance evaluation for RCHET, similar differences from frequence of home project, preference of home economics teacher, manual training and home economics score, interest of home economics showed statistically.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.