• Korean Journal of Soil Science and Fertilizer
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• v.47 no.6
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• pp.510-517
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• 2014

The purpose of this study was to analyze microbial hazards for cultivation environments and personal hygiene of strawberry and tomato farms at the growth and harvesting stage. Samples were collected from thirty strawberry farms and forty tomato farms located in Korea and tested for Staphylococcus aureus and Bacillus cereus. To investigate the change in the distribution of the S. aureus and B. cereus, a total of 4,284 samples including air born, soil or medium, mulching film, harvest basket, groves and irrigation water etc. were collected from eight strawberry farms and nine tomato farms for one year. As a result, total S. aureus and B. cereus in all samples were detected. Among the total bacteria of strawberry farms, S. aureus (glove: $0{\sim}2.1Log\;CFU/100cm^2$, harvest basket: $0{\sim}3.0Log\;CFU/100cm^2$, soil or culture media: 0~4.1 Log CFU/g, mulching film: $0{\sim}3.8Log\;CFU/100cm^2$), B. cereus (glove: $0{\sim}2.8Log\;CFU/100cm^2$, harvest basket: $0{\sim}4.8Log\;CFU/100cm^2$, soil or culture media: 0~5.3 Log CFU/g, mulching film: $0{\sim}4.5Log\;CFU/100cm^2$) were detected in all samples. The total bacteria of tomato farms, S. aureus (glove: $0{\sim}4.0Log\;CFU/100cm^2$, harvest basket: $0{\sim}5.0Log\;CFU/100cm^2$, soil or culture media: 0~6.1 Log CFU/g, mulching film: $0{\sim}4.0Log\;CFU/100cm^2$), B. cereus (glove: $0{\sim}4.0Log\;CFU/100cm^2$, harvest basket: $0{\sim}4.3Log\;CFU/100cm^2$, soil or culture media: 0~5.9 Log CFU/g, mulching film: $0{\sim}4.7Log\;CFU/100cm^2$) were detected in all samples. The contamination of S. aureus and B. cereus were detected in soil, mulching film and harvest basket from planting until harvest to processing, with the highest count recorded from the soil. But S. aureus and B. cereus were not detected in irrigation water samples. The incidence of S. aureus and B. cereus in hydroponics culture farm were less than those in soil culture. The amount of S. aureus and B. cereus detected in strawberry and tomato farms were less than the minimum amount required to produce a toxin that induces food poisoning. In this way, the degree of contamination of food poisoning bacteria was lower in the production environment of the Korea strawberry and tomato, but problems can be caused by post-harvest management method. These results will be used as fundamental data to create a manual for sanitary agricultural environment management, and post-harvest management should be performed to reduce the contamination of hazardous microorganisms.

• The Journal of Society for e-Business Studies
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• v.18 no.2
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• pp.191-203
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• 2013

Today, information technologies have been applied to operations in container terminals, and it is possible to collect operational log data due to development of equipment and operations technology. Terminal operators are collecting event log data and try to figure out the way of resolving operations problems. Operators want to analyze event logs to determine the causes of the operation problems, but it can hardly be done manually. In this paper, we suggest a formal framework to evaluate performance measures using the collected log data of operations in container terminals. The proposed formal framework supports different container terminal layout, operational processes, and equipment. Our formal framework is composed of specification of terminal layout, log data, workflow, statistics, and report, based on the concept of container handling objects. For validation of our framework, we have implemented a terminal performance analysis system based on the proposed framework.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.89-97
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• 2023

In this paper, we propose factors that make log analysis difficult and design technique for detecting various objects embedded in the logs which helps in the subsequent analysis. In today's IT systems, logs have become a critical source data for many advanced AI analysis techniques. Although logs contain wealth of useful information, it is difficult to directly apply techniques since logs are semi-structured by nature. The factors that interfere with log analysis are various objects such as file path, identifiers, JSON documents, etc. We have designed a BERT-based object pattern recognition algorithm for these objects and performed object identification. Object pattern recognition algorithms are based on object definition, GROK pattern, and regular expression. We find that simple pattern matchings based on known patterns and regular expressions are ineffective. The results show significantly better accuracy than using only the patterns and regular expressions. In addition, in the case of the BERT model, the accuracy of classifying objects reached as high as 99%.

• Korea journal of population studies
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• v.26 no.1
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• pp.143-170
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• 2003

During the last few decades dramatic expansion of education occurred for women as well as men in Korea. Taking into account such a rapid expansion of education, this study examines trends in the effects of education on first occupational attainment among Korean women. Using the data from "the 4th Survey on Women's Employment," conducted by Korean Women's Development Institute in 2001, this study investigates the trends across three cohorts classified on the basis of the year of labor force entry after schooling: before 1980, 19801989, and 1990 or later. First, log-linear models are applied to the data to detect the temporal change in the overall association between education and first occupational attainment controlling for marginal distribution. The log-linear analysis shows that the strength of association between education and first occupation has declined over time. An additional analysis of OLS regression is conducted to see how the effects of each level of educational attainment on occupational prestige have changed across the three cohorts. The results of OLS regression suggest that the differences in prestige scores between the lowest and each of other educational levels are narrower in recent cohorts.t cohorts.

• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.203-209
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• 2009

Frailty models are useful for the analysis of correlated and/or heterogeneous survival data. However, the inferences of fixed parameters, rather than random effects, have been mainly studied. The prediction (or estimation) of random effects is also practically useful to investigate the heterogeneity of the hospital or patient effects. In this paper we propose how to extend the prediction method for random effects in HGLMs (hierarchical generalized linear models) to log-normal semiparametric frailty models with nonparametric baseline hazard. The proposed method is demonstrated by a simulation study.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.190-192
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• 2002

데이터 마이닝(Data Mining)이란 저장된 많은 양의 자료로부터 통계적 수학적 분석방법을 이용하여 다양한 가치 있는 정보를 찾아내는 일련의 과정이다. 데이터 클러스터링은 이러한 데이터 마이닝을 위한 하나의 중요한 기법이다. 본 논문에서는 Fuzzy C-Means 알고리즘을 이용하여 웹 사용자들의 행위가 기록되어 있는 웹 로그 데이터를 데이터 클러스터링 하는 방법에 관하여 연구하고자 한다. Fuzzv C-Means 클러스터링 알고리즘은 각 데이터와 각 클러스터 중심과의 거리를 고려한 유사도 측정에 기초한 목적 함수의 최적화 방식을 사용한다. 웹 로그 데이터의 여러 필드 중에서 사용자 IP, 시간, 웹 페이지 필드를 WLDF(Web Log Data for FCM)으로 가공한 후, 다차원 Fuzzy C-Means 클러스터링을 한다. 그리고 이를 이용하여 샘플 데이터와 임의의 데이터간의 유사 패턴 분석을 하고자 한다.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1561-1566
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• 2017

Due to the advances in machine learning and artificial intelligence technologies, many new services have become available. Among such services, recommendation systems have already been successfully applied to commercial services and made profits as in online shopping malls. Most recommendation algorithms in commercial services are based on content analysis or explicit feedback rates as in movie recommendations. However, many online shopping malls have difficulties in content analysis or are lacking explicit feedbacks on their items, which results in no recommendation system for their items. Even for such service systems, user log data is easily available, and if recommendations are possible with such log data, the quality of their service can be improved. In this paper, we extract implicit feedback like click information for items from log data and provide a recommendation system based on the implicit feedback. The proposed system is applied to a real in-service online shopping mall.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.43-52
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• 1999

The local influence method is adapted to quadratic discriminant analysis for the identification of influential observations affecting the estimation of probability density function probabilities and log odds. The method allows a simultaneous perturbation on all observations so that it can identify multiple influential observations. The proposed method is applied to a real data set and satisfactory result is obtained.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.5
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• pp.236-244
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• 2006

Many attempts have been made to track the web usage patterns and provide suggestions that might help web operators get the information they need. These tracking mechanisms rely on mining web log files for usage patterns. The purpose of this study is to verify a web agent prototype that was built for mining web log files. The web agent for this paper was made by Java and ASP and the agent came into being as part of a cookie for a short-term data storage. For long-term data storage, the agent used a My-SQL as a Data Base. This agent system could inform that if the data comes from the web data mining agent, it could be a rapid information providing method rather than the case of data coming into a data mining tool. Therefore, the developed tool in this study will be helpful as a new kind of decision making system and expert system.

• Journal of Korea Multimedia Society
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• v.6 no.4
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• pp.707-713
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• 2003

Convenience and promptness of the internet have been not only making the electronic commerce grow rapidly in case of website, analyzing a navigation pattern of the users has been also making personalization and customization techniques develop rapidly for providing service accordant to individual interestingness. Web personalization and customization skill has been utilizing various methods, such as web log mining to use web log data and web mining to use the transaction of users etc, especially e-CRM analyzing a navigation pattern of the users. In this paper, We measure exact duration time of the users in web page and web site, compute weight about duration time each page, and propose a way to comprehend e-loyalty through the computed weight.