• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2007년도 학술대회 1부
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• pp.949-956
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• 2007

This paper describes the design and implementation of the database which is used in Personal Life Log Media system. The database contains information about media that capture personal experiences and enables the user to retrieve the media in a user friendly ways. The implementation of the database design is done by managing video data, which captures user's personal experiences, with its spatial and temporal information. The database enables the user to retrieve the video by mentioning where and/or when the video has been taken.

• 동아시아식생활학회지
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• 제24권4호
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• pp.481-487
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• 2014

본 연구는 대도시지역(서울, 대전, 부산, 광주)에서 판매되는 길거리 식품(김밥, 어묵, 순대)에 대한 미생물 모니터링 검사를 실시하여, 이들 제품에 대한 위생 안전성 확보를 위한 기초 자료를 제공하기 위해 진행되었다. 김밥의 총호기성균은 5.1~9.9 log CFU/g으로 검출되었으며, 여름철에 가장 높게 검출되었다. 호냉성균은 총호기성균과 유사한 패턴으로 검출되었으며, 여름철에 수거된 순대 7건에서 6.0~7.9 log CFU/g 수준으로 검출되었다. Total coliform은 53.6%의 검출률을 나타내었으며, 김밥의 70.8%에서 4.0 log CFU/g 이상 검출되었다. E. coli는 김밥과 순대에서 15건이 검출되었으며, 어묵에서는 검출되지 않았다. 식중독균중 S. aureus가 28건(7.8%)이 검출되었으며, C. perfringens는 12건(3.3%)이 검출되었다. 특히 김밥에서 S. aureus, C. perfringens가 각각 24건, 10건에서 검출되어 식중독 발생 가능성이 높은 것으로 판단되었다. 그리고 계절별로 보면 겨울에 비해 봄, 여름의 검출률이 높았으며, 지역별로 보면 부산지역에서 가장 높은 검출률을 보였다.

• 디지털산업정보학회논문지
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• 제9권2호
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• pp.1-10
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• 2013

In this paper, make a study decision problem called an optimal release policies after testing a software system in development phase and transfer it to the user. In the course of correcting or modifying the software, finite failure non-homogeneous Poisson process model, presented and was proposed release policies of the life distribution, half-logistic and log-logistic distributions model which used to an area of reliability because of various shape and scale parameter. In this paper, discuss optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement. In a numerical example, the parameter estimation using maximum likelihood estimation of failure time data make out, and software optimal release time was estimated.

• 대한산업공학회지
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• 제34권4호
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• pp.460-469
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• 2008

Process mining aims at mining valuable information from process execution results (called "event logs"). Even though process mining techniques have proven to be a valuable tool, the mining results from real process logs are usually too complex to interpret. The main cause that leads to complex models is the diversity of process logs. To address this issue, this paper proposes a trace clustering approach that splits a process log into homogeneous subsets and applies existing process mining techniques to each subset. Based on log profiles from a process log, the approach uses existing clustering techniques to derive clusters. Our approach are implemented in ProM framework. To illustrate this, a real-life case study is also presented.

• Journal of the Korean Data and Information Science Society
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• 제26권1호
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• pp.271-280
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• 2015

In this paper, the maximum likelihood estimators for parameters are derived under three step-stress accelerated life tests for Type-I hybrid censored data. The exponential distribution and the cumulative exposure model are considered based on the assumption that a log quadratic relationship exits between stress and the mean lifetime ${\theta}$. The test plan to search optimal stress change times minimizing the asymptotic variance of maximum likelihood estimators are presented. A numerical example to illustrate the proposed inferential procedures and some simulation results to investigate the sensitivity of the optimal stress change times by the guessed parameters are given.

• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1375-1386
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• 2006

In life testing, the lifetimes of test units under the usual conditions are so long that life testing at usual conditions is impractical. Testing units are subjected to conditions of high stress to yield informations quickly. In this paper, the inferences of parameters on the three step-stress accelerated life testing are studied. The two-parameter exponential distribution with a failure rate function that a log-quadratic function of stress and the tempered failure rate model are considered. We obtain the maximum likelihood estimators of the model parameters and their confidence regions. A numerical example will be given to illustrate the proposed inferential procedures.

• 한국정보처리학회논문지
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• 제6권5호
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• pp.1189-1202
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• 1999

As compared with VOD data, NOD article data has the following characteristics: it is created at any time, has a short life cycle, is selected as not one article but several articles by a user, and has high access locality in time. Because of these intrinsic features, user access patterns of NOD article data are different from those of VOD. Thus, building NOD system using the existing techniques of VOD system leads to poor performance. In this paper, we analysis the log file of a currently running electronic newspaper, show that the popularity distribution of NOD articles is different from Zipf distribution of VOD data, and suggest a new popularity model of NOD article data MS-Zipf(Multi-Selection Zipf) distribution and its approximate solution. Also we present a life cycle model of NOD article data, which shows changes of popularity over time. Using this life cycle model, we develop LLBF (Largest Life-cycle Based Frequency) prefetching algorithm and analysis he performance by simulation. The developed LLBF algorithm supports the similar level in hit-ratio to the other prefetching algorithms such as LRU(Least Recently Used) etc, while decreasing the number of data replacement in article prefetching and reducing the overhead of the prefetching in system performance. Using the accurate user access patterns of NOD article data, we could analysis correctly the performance of NOD server system and develop the efficient policies in the implementation of NOD server system.

• 한국산업정보학회논문지
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• 제25권6호
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• pp.33-45
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• 2020

본 논문은 최근 다양한 종류의 웨어러블 디바이스가 헬스케어 도메인에 급증하여 사용되고 있는 상황에서 최신 첨단 기술이 실제 메디컬 환경에서 개인의 질병예측이라는 관점을 바라본다. 사용자 참여형 웨어러블 디바이스를 통하여 임상 데이터와 유전자 데이터, 라이프 로그 데이터를 병합하여 데이터를 수집, 처리, 전송하는 과정을 걸쳐 딥뉴럴 네트워크의 환경에서 학습모델의 제시와 피드백 모델을 연결하는 과정을 제시한다. 이러한 첨단 의료 현장에서 일어나는 메디컬 IT의 임상시험 절차를 걸친 실제 현장의 경우 대사 증후군에 의한 특정 유전자가 질병에 미치는 영향을 측정과 더불어 임상 정보와 라이프 로그 데이터를 병합하여 서로 각기 다른 이종 데이터를 처리하면서 질병의 특이점을 확인하게 된다. 즉, 이종 데이터의 딥뉴럴 네트워크의 객관적 적합성과 확실성을 증빙하게 되고 이를 통한 실제 딥러닝 환경에서의 노이즈에 따른 성능 평가를 실시한다. 이를 통해 자동 인코더의 경우의 1,000 EPOCH당 변화하는 정확도와 예측치가 변수의 증가 값에 수차례 선형적으로 변화하는 현상을 증명하였다.

• 보험의학회지
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• 제3권1호
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• pp.103-141
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• 1986

The present study was undertaken to establish the decision standard of builds for the insured by using the ratio of weight-for-height as build index. Materials being examined were the ratio of weight-for-height being calculated from the actually measured heights and weights of a total of 15,838 insured persons who were examined medically at Honam Medical Department of Dong Bang Life Insurance Company, Ltd. from June, 1979 to September, 1985. The ratio of weight-for-height is calculated by the following formula. The ratio of weight-for-height(%)=$\frac{weight(kg){\times}100}{\{height(cm)-100\}{\times}0.9(kg)$ The results were as follows: 1. The distribution of the ratio of weight. for-height of the 15,838 insureds follows Log normal distribution being skewed to the left(the direction of underweight). 2. The ratio of weight-for-height were Log transformed to lead to a sym metrical pattern of distribution in which statistical rules are known to be applied more exactly. Thereafter, the establishment of dicision standard of builds was undertaken by using the log of the ratio of weight-for-height as build index. Through all ages in male, the ratio of weight-for-height indicating the range of standard lives including slight overweighted and underweighted lives besides normal lives is 80-130%, and corresponds to $"M-2{\delta}"-"M+1.5{\delta}"$ and to $M{\pm}20%$ ; in female, 85-135%, and corresponds to $"M-2{\delta}"-"M+1.5{\delta}"$ and to $M{\pm}20%$. Through all ages in male, the ratio of weight-for-height indicating the initial level of super-overweighted and super-underweighted lives is 130-150% and 75-80%,and corresponds to $M+3{\delta}\;and\;M-3{\delta}$ and to M+40% and M-25% respectively;in female, 140-160% and 75-80%, and corresponds to $M+3{\delta}\;and\;M-3{\delta}$ and to M+40%-+50% and M-25% respectively. 3. Author's rating table model for builds(a table of weight per height) is proposed. On the table, the ratings for builds, i. e. standard, super-weighted and super-underweighted lives, are listed.

• 한국인터넷방송통신학회논문지
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• 제18권6호
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• pp.21-31
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• 2018

초연결사회에서 IoT 기반의 라이프로그 데이터는 사물인터넷 기술 전반에 활용되며 사용자의 요구사항을 반영한 맞춤형 서비스의 중요 요소로 자리 잡고 있다. 또한 사용자들은 소셜네트워크서비스를 활용하여 관심사 및 감정들을 쉽게 표현하면서 다양한 라이프로그 데이터가 축척되고 있다. 본 논문에서는 IoT 기반의 라이프로그 데이터를 활용한 지능형 캐릭터를 개발하여 사용자들의 감성을 체계적으로 파악하기 위해 정성적/정량적 데이터를 수집 및 분석한다. 이를 위해 사용자가 이용하는 소셜네트워크서비스를 통한 정성적 데이터와 웨어러블 디바이스를 통한 정량적 데이터를 수집한다. 수집한 데이터는 에스노그라피를 통한 페르소나와 비교하여 신뢰성을 검증한다. 추후에는 더 많은 사용자 라이프로그 데이터를 수집하여 데이터의 신뢰성을 확보하고 분석 과정에서 오차를 줄여 개인맞춤형 서비스를 제공할 수 있도록 지능형 캐릭터를 개발할 예정이다.