• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.10
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• pp.1594-1606
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• 2014

The purpose of this study was to examine safety accidents related to school foodservice, working and operating environments of school foodservice, status and awareness of safety education, educational needs, and information on qualitative improvement of school foodservice. The subjects in this study were 234 cooks in charge of cooking at elementary and secondary schools in Chungbuk. A survey was conducted from July 30 to August 8, 2012, and among 202 questionnaires gathered, 194 completed questionnaires were analyzed. Statistical analyses were performed on data utilizing the SPSS version 19.0. The main results of this study were as follows: 44.3% of workers experienced safety accidents. The most frequent safety accident was 'once' (60.5%), and most safety accidents took place between June and August (31.4%). The time at which most safety accidents happened was between 8 and 11 am. Most safety accidents happened during cooking (52.3%) and while using a soup pot or frying pot (52.4%). The most common accidents were 'burns', 'wrist and arm pain', and 'slips and falls'. Respondents who experienced safety accidents replied that 57.6% of employees dealt with injuries at their own expense, and only 35.3% utilized industrial accident insurance. In terms of the operating environment, the score for 'offering information and application' was highest (3.76 points), whereas that for 'security of budget' was lowest (1.77 points). As for accident education, employees received safety education approximately 3.45 times and 5.10 hours per year. Improving the working environment of school foodservice cooks requires administrative and financial support. Furthermore, educational materials and guidelines based on the working environment and safety accident status of school foodservice cooks are required in order to minimize potential risk factors and control safety accidents in school foodservice.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.109-122
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• 2016

Recently, big data analysis has developed into a field of interest to individuals and non-experts as well as companies and professionals. Accordingly, it is utilized for marketing and social problem solving by analyzing the data currently opened or collected directly. In Korea, various companies and individuals are challenging big data analysis, but it is difficult from the initial stage of analysis due to limitation of big data disclosure and collection difficulties. Nowadays, the system improvement for big data activation and big data disclosure services are variously carried out in Korea and abroad, and services for opening public data such as domestic government 3.0 (data.go.kr) are mainly implemented. In addition to the efforts made by the government, services that share data held by corporations or individuals are running, but it is difficult to find useful data because of the lack of shared data. In addition, big data traffic problems can occur because it is necessary to download and examine the entire data in order to grasp the attributes and simple information about the shared data. Therefore, We need for a new system for big data processing and utilization. First, big data pre-analysis technology is needed as a way to solve big data sharing problem. Pre-analysis is a concept proposed in this paper in order to solve the problem of sharing big data, and it means to provide users with the results generated by pre-analyzing the data in advance. Through preliminary analysis, it is possible to improve the usability of big data by providing information that can grasp the properties and characteristics of big data when the data user searches for big data. In addition, by sharing the summary data or sample data generated through the pre-analysis, it is possible to solve the security problem that may occur when the original data is disclosed, thereby enabling the big data sharing between the data provider and the data user. Second, it is necessary to quickly generate appropriate preprocessing results according to the level of disclosure or network status of raw data and to provide the results to users through big data distribution processing using spark. Third, in order to solve the problem of big traffic, the system monitors the traffic of the network in real time. When preprocessing the data requested by the user, preprocessing to a size available in the current network and transmitting it to the user is required so that no big traffic occurs. In this paper, we present various data sizes according to the level of disclosure through pre - analysis. This method is expected to show a low traffic volume when compared with the conventional method of sharing only raw data in a large number of systems. In this paper, we describe how to solve problems that occur when big data is released and used, and to help facilitate sharing and analysis. The client-server model uses SPARK for fast analysis and processing of user requests. Server Agent and a Client Agent, each of which is deployed on the Server and Client side. The Server Agent is a necessary agent for the data provider and performs preliminary analysis of big data to generate Data Descriptor with information of Sample Data, Summary Data, and Raw Data. In addition, it performs fast and efficient big data preprocessing through big data distribution processing and continuously monitors network traffic. The Client Agent is an agent placed on the data user side. It can search the big data through the Data Descriptor which is the result of the pre-analysis and can quickly search the data. The desired data can be requested from the server to download the big data according to the level of disclosure. It separates the Server Agent and the client agent when the data provider publishes the data for data to be used by the user. In particular, we focus on the Big Data Sharing, Distributed Big Data Processing, Big Traffic problem, and construct the detailed module of the client - server model and present the design method of each module. The system designed on the basis of the proposed model, the user who acquires the data analyzes the data in the desired direction or preprocesses the new data. By analyzing the newly processed data through the server agent, the data user changes its role as the data provider. The data provider can also obtain useful statistical information from the Data Descriptor of the data it discloses and become a data user to perform new analysis using the sample data. In this way, raw data is processed and processed big data is utilized by the user, thereby forming a natural shared environment. The role of data provider and data user is not distinguished, and provides an ideal shared service that enables everyone to be a provider and a user. The client-server model solves the problem of sharing big data and provides a free sharing environment to securely big data disclosure and provides an ideal shared service to easily find big data.

• The Journal of Natural Sciences
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• v.14 no.1
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• pp.83-121
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• 2004

This study was carried out to examine how solid the production foundation of rice in Chung-Nam Province is, and, if not, to probe alternative measures through the size of farms specializing in rice, of which direction would be a pivot of rice industry-oriented policy. The results obtained can be summarized as follows : 1. The amount of rice production in Chung-Nam Province is highest in Korea and the size of paddy field area is the second largest : This implying that the probability that rice production in Chung-Nam Province would be severely influenced by a global trend of market conditions. The number of farms specializing in rice becoming the core group of rice farming account for 7.7 percent of the total number of farm household in Korea. Average field area financial support which had been input to farm household by Government had a noticeable effect on the improvement of the policy of farm-size program. 2. Farm-size program in Chung-Nam Province established from 1980 to 2002 in creased the cultivation size of paddy field to 19,484 hectares, and this program enhanced the buying and selling of farmland and the number of farmland bargain reached 6,431 household and 16,517 hectares, respectively, in 1995-2002. Meanwhile, long-term letting and hiring of farmland appeared so active that the bargain acreage reached 6,970 hectares, and farm involved was 7,059 households, however, the farm-exchange-and-unity program did not satisfy our expectation, because the retirement farm operators reluctantly participated to sell their farms. Another reason that had delayed the bargain of farms rested on the general category of social complication attendant upon the exchange and unity operation for scattered farm. Such difficulties would work negative effects out to carry on the target of farm-size work in general. 3. The following measures were presented to propel the farm-size promotion program : a. Occupation shift project, followed by the social security program for retirement and elderly farm operators, should be promptly established and also a number of types of incentives for promoting the letting and hiring work and farm-exchange-and-unity program would also be set up. b. To establish the effective key system of rice production, all the farm operators should increase the unit area yield of rice and lower the production cost. To do so, a great deal of production teams of rice equipped with managerial techniques and capabilities need to be organized. And, also, there should be appropriate arrays of facilities including information system. This plan is desirable to be in line with a diversity of the structural implement of regional integration based on farm system building. c. To extend the size of farm and to improve farm management, we have to devise the enlargement of individual size of farm for maximized management and the utilization of farm-size grouping method. In conclusion, it can be said that the farm-size project in Chung-Nam Province which has continued since the 1980s was satisfactorily achieved. However, we still have a lot of problems to be solved to break down the barrier for attainment of the desirable farm-size operation work.. Farm-size project has fairly close relation with farm specialization in rice and, thus, the positive support for farm household including the integrated program for both retirement farmers and off-farm operators should be considered to pursue the progressive development of the farm-size program, which is key means to successful achievement of rice farming enforcement in Chung-Nam Province.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.123-139
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• 2019

The job classification system of major job sites differs from site to site and is different from the job classification system of the 'SQF(Sectoral Qualifications Framework)' proposed by the SW field. Therefore, a new job classification system is needed for SW companies, SW job seekers, and job sites to understand. The purpose of this study is to establish a standard job classification system that reflects market demand by analyzing SQF based on job offer information of major job sites and the NCS(National Competency Standards). For this purpose, the association analysis between occupations of major job sites is conducted and the association rule between SQF and occupation is conducted to derive the association rule between occupations. Using this association rule, we proposed an intelligent job classification system based on data mapping the job classification system of major job sites and SQF and job classification system. First, major job sites are selected to obtain information on the job classification system of the SW market. Then We identify ways to collect job information from each site and collect data through open API. Focusing on the relationship between the data, filtering only the job information posted on each job site at the same time, other job information is deleted. Next, we will map the job classification system between job sites using the association rules derived from the association analysis. We will complete the mapping between these market segments, discuss with the experts, further map the SQF, and finally propose a new job classification system. As a result, more than 30,000 job listings were collected in XML format using open API in 'WORKNET,' 'JOBKOREA,' and 'saramin', which are the main job sites in Korea. After filtering out about 900 job postings simultaneously posted on multiple job sites, 800 association rules were derived by applying the Apriori algorithm, which is a frequent pattern mining. Based on 800 related rules, the job classification system of WORKNET, JOBKOREA, and saramin and the SQF job classification system were mapped and classified into 1st and 4th stages. In the new job taxonomy, the first primary class, IT consulting, computer system, network, and security related job system, consisted of three secondary classifications, five tertiary classifications, and five fourth classifications. The second primary classification, the database and the job system related to system operation, consisted of three secondary classifications, three tertiary classifications, and four fourth classifications. The third primary category, Web Planning, Web Programming, Web Design, and Game, was composed of four secondary classifications, nine tertiary classifications, and two fourth classifications. The last primary classification, job systems related to ICT management, computer and communication engineering technology, consisted of three secondary classifications and six tertiary classifications. In particular, the new job classification system has a relatively flexible stage of classification, unlike other existing classification systems. WORKNET divides jobs into third categories, JOBKOREA divides jobs into second categories, and the subdivided jobs into keywords. saramin divided the job into the second classification, and the subdivided the job into keyword form. The newly proposed standard job classification system accepts some keyword-based jobs, and treats some product names as jobs. In the classification system, not only are jobs suspended in the second classification, but there are also jobs that are subdivided into the fourth classification. This reflected the idea that not all jobs could be broken down into the same steps. We also proposed a combination of rules and experts' opinions from market data collected and conducted associative analysis. Therefore, the newly proposed job classification system can be regarded as a data-based intelligent job classification system that reflects the market demand, unlike the existing job classification system. This study is meaningful in that it suggests a new job classification system that reflects market demand by attempting mapping between occupations based on data through the association analysis between occupations rather than intuition of some experts. However, this study has a limitation in that it cannot fully reflect the market demand that changes over time because the data collection point is temporary. As market demands change over time, including seasonal factors and major corporate public recruitment timings, continuous data monitoring and repeated experiments are needed to achieve more accurate matching. The results of this study can be used to suggest the direction of improvement of SQF in the SW industry in the future, and it is expected to be transferred to other industries with the experience of success in the SW industry.