• 한국조리학회지
• /
• 제13권1호
• /
• pp.75-86
• /
• 2007

This study was carried out to find out the effect of food hygiene awareness on kitchen employees' performance in the banquet cuisine of five-star hotels in Seoul. 279 kitchen employees were asked to fill out the questionnaire, and the collected data were analyzed by SPSS package(version 11.0). First, results of analysis on food hygiene showed that there were four factors, each respectively named as, food security regulations, food storage, period of circulation of food, and food safekeeping. Second, after analyzing each item in whole according to each of the factors, the average degree of priority on food hygiene in general was 4.52. Results according to each of the elements showed that food security regulations(4.56) and period of circulation of food(4.55) were considered as a priority. After analyzing the difference between the degree of priority and degree of performance according to each of the factors, it was found out that the latter was significantly lower than the former in all factors. Third, after analyzing the difference of food hygiene priority in accordance with general characteristics, statistically significant difference was only shown in education(F=3.308, p<0.05) and class(F=4.418, p<0.01). Fourth, after analyzing the difference of food hygiene performance in accordance with general characteristics, the only significant difference was found in food security regulation of education(F=4.418, p<0.01) and food security regulation of class(F=3.859, p<0.01). Fifth, after analyzing the effect of cook's awareness of priority on food hygiene on the degree of performance, it was found out that the awareness of priority on food hygiene had a positive effect(+) on the degree of performance. Therefore, we can conclude that as kitchen employees recognize the priority on the food hygiene better, their degree of performance was higher.

• 대한산업공학회지
• /
• 제42권2호
• /
• pp.112-121
• /
• 2016

This paper focuses on competencies of data scientists and behavioral intention that affect big data analysis performance. This experiment examined nine core factors required by data scientists. In order to investigate this, we conducted a survey to gather data from 103 data scientists who participated in big data competition at Kaggle platform and used factor analysis and PLS-SEM for the analysis methods. The results show that some key competency factors have influential effect on the big data analysis performance. This study is to provide a new theoretical basis needed for relevant research by analyzing the structural relationship between the individual competencies and performance, and practically to identify the priorities of the core competencies that data scientists must have.

• Journal of information and communication convergence engineering
• /
• 제21권3호
• /
• pp.244-251
• /
• 2023

Engineering or humanities data are stored in databases and are often used for search services. While the latest deep-learning technologies, such like BART and BERT, are utilized for data analysis, humanities data still rely on traditional databases. Representative analysis methods include n-gram and lexical statistical extraction. However, when using a database, performance limitation is often imposed on the result calculations. This study presents an experimental process using MariaDB on a PC, which is easily accessible in a laboratory, to analyze the impact of the database on data analysis performance. The findings highlight the fact that the database becomes a bottleneck when analyzing large-scale text data, particularly over hundreds of thousands of records. To address this issue, a method was proposed to provide real-time humanities data analysis web services by leveraging the open source database, with a focus on the Seungjeongwon-Ilgy, one of the largest datasets in the humanities fields.

• 태양에너지
• /
• 제9권3호
• /
• pp.81-91
• /
• 1989

This study represents the method to predict the flow duration curve and primary design specifications of small hydropower plant at hydropower site through analyzing the monthly rainfall data. Weibull distribution was selected to characterize the rainfall data and Thiessen method was used to calculate monthly average flowrate at site. Application of these results, primary design specifications such as design flowrate, annual average load factor and utility factor, annual average hydropower density and annual electric energy production were estimated and discussed for surveyed site located in Daigi-ri, Kangwon province. And performance characteristic model of small hydro-power plant was applied to estimate these specifications.

• 한국경영과학회:학술대회논문집
• /
• 한국경영과학회 1996년도 추계학술대회발표논문집; 고려대학교, 서울; 26 Oct. 1996
• /
• pp.147-150
• /
• 1996

A homing torpedo's performance can be expressed a function of many variables, i.e. technical and tactical variables. When designing a homing torpedo, these variables have to be decided upon. The system effectiveness of a homing torpedo can be determined by analyzing of these variables. This paper describes a procedure of simulation metamodelling using a Factor Analysis methodology. A simulation model was used in order to obtain the data base for analyzing detection probability of torpedo. By analyzing the main and interaction effects these variables on the analysis of detection probability, we will show the importance of certain variables, of a homing torpedo.

• 국제학술발표논문집
• /
• The 3th International Conference on Construction Engineering and Project Management
• /
• pp.738-746
• /
• 2009

The purpose of this study is to develop the web-based system for work performance analysis(WPAS). The need of work performance analysis system has already been suggested in many previous researches on the computerization of the performance measurement in the construction site by using the indicators such as time, cost and quality. However, they had focused on measuring or analyzing the result when the project would be over. The WPAS suggests three indicators - work reliability, work effectiveness and work efficiency - to manage the performance of the construction site. It can help the manager more easily recognize the status of on-going work in the construction site by measuring and analyzing the work reliability rate, the work effectiveness and work efficiency every day. This research includes the procedures for WPAS measurement process, database structure of WPAS which was analyzed by the IDEF0 and the data flow diagram. Finally, this research introduces the result of WAPS's case studies and validation in the Korean construction site.

• 정보보호학회논문지
• /
• 제23권4호
• /
• pp.667-677
• /
• 2013

방화벽은 대표적인 네트워크 보안 장비로서 대부분의 네트워크 내/외부에 설치되어 패킷의 입/출입을 통제하는 시스템이다. 때문에 이에 저장된 로그 데이터를 분석하는 것은 네트워크 보안연구에 중요한 기초 자료를 제공해 줄 수 있다. 그런데 최근 기술의 발달로 인터넷망의 속도가 향상되고, 네트워크가 대형화 되면서 방화벽에서 저장하는 로그데이터들의 양도 대용량화 또는 빅데이터화 되어 가고 있다. 이러한 추세 속에서, 기존의 전통적인 RDBMS방식으로 로그데이터를 분석하는 데는 한계가 있다. 본 논문은 NoSQL 기반의 MapReduce 설계를 이용한 방화벽 로그 분석기법을 통해 NoSQL방식을 도입하는 것이 대용량 로그 데이터를 더욱 효율적으로 분석할 수 있다는 점을 발견했다. 우리는 기존의 RDBMS방식과의 데이터 처리 성능을 비교하여 NoSQL방식 데이터베이스의 우수한 성능을 입증하였고, 이를 바탕으로 제안하는 설계 기법을 평가하기 위해 3가지 공격 패턴을 선정하고 이를 집계 하여 분석을 수행하는 실험을 통해 제안하는 분석 기법의 성능 및 정확성을 입증하였다.

• 대한조선학회논문집
• /
• 제56권2호
• /
• pp.143-151
• /
• 2019

This study describes a method for analyzing log data generated in a process using process mining techniques. A system for collecting and analyzing a large amount of log data generated in the process of manufacturing an offshore plant piping material was constructed. The analyzed data was visualized through various methods. Through the analysis of the process model, it was evaluated whether the process performance was correctly input. Through the pattern analysis of the log data, it is possible to check beforehand whether the problem process occurred. In addition, we analyzed the process performance data of partner companies and identified the load of their processes. These data can be used as reference data for pipe production allocation. Real-time decision-making is required to cope with the various variances that arise in offshore plant production. To do this, we have built a system that can analyze the log data of real - time system and make decisions.

• 지식경영연구
• /
• 제12권4호
• /
• pp.55-75
• /
• 2011

Scant attention has been given to analyzing how knowledge sourcing strategies affect firm performance in SMEs and what are the differences between SMEs and large firms in the patterns of knowledge sourcing strategies adoption. This study attempts to advance the current literature by examining the impact of knowledge sourcing strategies on SMEs performance. The empirical segment of our work is based on data on knowledge sourcing strategies of SMEs and organizational performance from a sample of 166 Korean firms. Our results indicate knowledge sourcing adoption patterns of SMEs are different from large firms. In addition, the results confirm that substitutability between internal- and external-oriented, person- and external-oriented sourcing strategies. This study sheds new light on knowledge management (KM) research by identifying the relationship between knowledge sourcing strategies and SMEs performance.

• 지능정보연구
• /
• 제21권3호
• /
• pp.101-116
• /
• 2015

많은 기관들이 데이터에 기반을 둔 의사결정을 수행해 왔으며, 특히 수치자료를 비롯한 정형 데이터가 이러한 목적으로 널리 활용되어 왔다. 하지만 최근에는 스마트기기와 소셜미디어의 발달로 인해 다양한 형태를 가진 방대한 양의 정보가 생성, 공유, 저장되면서, 전통적인 정형 데이터 기반 의사결정으로부터 비정형 빅데이터 기반 의사결정으로 관심의 전환이 이루어지고 있다. 데이터 기반 의사결정의 대표적 분야인 추천시스템 분야에서도 성능 향상을 위해 비정형 데이터를 활용해야 한다는 필요성이 최근 꾸준히 제기되고 있다. 특히 사용자의 성향이나 선호도는 고객의 니즈와 직결되기 때문에, 비정형 데이터 분석을 통해 사용자의 성향을 파악하고 이를 통해 상품 추천 및 구매 예측의 정확도를 향상시키기 위한 노력이 매우 시급하게 이루어질 필요가 있다. 따라서 본 연구에서는 사용자의 성향을 측정하여 재구매 예측 정확도, 특히 카테고리별 재구매 예측 정확도를 높임으로써, 궁극적으로 추천시스템의 성능을 향상시킬 수 있는 방안을 제시한다. 구체적으로는 사용자의 일상적인 인터넷 사용 기록을 분석하여 고객이 조회하는 뉴스 기사의 이슈를 식별하고 다양한 이슈에 대한 고객의 관심을 계량화한 후, 이를 활용하여 고객의 카테고리별 재구매 여부를 예측하는 모델을 제안하고자 한다. 실제 웹 트랜잭션으로부터 도출된 인터넷 뉴스 조회 기록 및 쇼핑몰 구매 기록을 대상으로 실험을 수행한 결과, 고객의 과거 구매이력만을 활용한 카테고리 재구매 예측 모형에 비해 본 연구에서 제안한 모형, 즉 고객의 과거 구매이력과 관심 이슈를 모두 활용한 예측 모형의 정확도가 다소 우수한 것으로 나타났다.