• 한국산학기술학회:학술대회논문집
• /
• 한국산학기술학회 2003년도 Proceeding
• /
• pp.197-206
• /
• 2003

With the growing usage of the networks, the world-wide Internet has become the main means to exchange data and carry out transactions. It has also become the main means to attack hosts. To solve the security problems which occur in the network such as Internet, we import software products of network security elements like an IDS (Intrusion Detection System) and a firewall. In this paper, we have designed and constructed the General Simulation Environment of Network Security model composed of multiple IDSes and a firewall which coordinate by CNP (Contract Net Protocol) for the effective detection of the intrusion. The CNP, the methodology for efficient integration of computer systems on heterogeneous environment such as distributed systems, is essentially a collection of agents, which cooperate to resolve a problem. Command console in the CNP is a manager who controls tie execution of agents or a contractee, who performs intrusion detection. In the Network Security model, each model of simulation environment is hierarchically designed by DEVS (Discrete EVent system Specification) formalism. The purpose of this simulation is to evaluate the characteristics and performance of CNP architecture with rete pattern matching algorithm and the application of rete pattern matching algorithm for the speeding up the inference cycle phases of the intrusion detection expert system.

• 한국의류학회지
• /
• 제24권6호
• /
• pp.907-917
• /
• 2000

Although interest in the potential and actual usage of the Internet as a transaction medium is increasing, the market for fashion merchandise on the Internet in Korea has yet to take off. As the Internet environment is expected to bring about a transformation of conventional consumer buying behavior, the purpose of this exploratory research is to investigate the buying behavior of fashion products on the Internet to identify relevant concepts and generate hypotheses for further empirical research. The research methods selected for the study were observation and in-depth interview. Twelve subjects who had purchased fashion products on the Internet were selected and interviewed. Those who could not participate in face-to-face in-depth interviews because of the geographic locations were interviewed on-line. The results are as follows: First, subjects went through the stages of shopping motivation stage, site choice behavior stage, in-site behavior stage, and postpurchase behavior stage. Second, a model was extracted for each shopping stage, and a final model was completed based on comparisons with the participants processes. The information content of each phase was discussed. Finally, each participant was classified using their purchasing process, revealing six possible mixed usage patterns of the Internet marketing system and the traditional marketing system.

• 한국식품영양학회지
• /
• 제33권3호
• /
• pp.356-361
• /
• 2020

This study was performed to provide fundamental data on the convenience foods purchase according to the food-related lifestyle. This study was conducted on 398 Chinese international students residing in Gyeonggi area between October and December 2019. Among the total 373 survey subjects, gender was 183 male students (49.1%) and 190 female students (50.9%). This study was conducted by questionnaire method with reference to previous studies. There are significant differences in economic pursuit and taste pursuit for delivery food use, economic pursuit and taste pursuit for delivery food information, health pursuit and taste pursuit in delivery food ordering method, and economic pursuit and convenience pursuit for delivery food use (p<0.05). Delivery food usage time was significantly different in convenience pursuit, health pursuit, eating out pursuit, and taste pursuit (p<0.05), and the delivery food preference menu was significantly different in economic pursuit, health pursuit, eating out pursuit, and taste pursuit (p<0.05). The menu positive factors among satisfaction factors showed statistically significant differences in economic pursuit (β=0.188, t=3.531) and health pursuit (β=0.160, t=3.099) among food related lifestyle factors. In conclusion, this study presented the desirable direction of delivery food usage in Chinese students.

• 전기전자학회논문지
• /
• 제12권1호
• /
• pp.65-74
• /
• 2008

패턴 분류에 많이 사용되는 기법 중의 하나인 메모리 기반 추론 알고리즘은 단순히 메모리에 저장하고 분류 시에 저장된 패턴과 테스트 패턴간의 거리를 계산하여 가장 가까운 학습패턴의 클래스로 분류하는 기법이기 때문에 패턴의 개수가 늘어나면 메모리가 증가하고 또한 추가로 패턴이 발생할 경우 처음부터 다시 수행해야하는 문제점을 가지고 있다. 이러한 문제점을 해결하기 위하여 이미 학습한 대표패턴을 기억하고 새로 들어오는 패턴에 대해서만 학습하는 점진적 학습 방법을 제안한다. 즉 추가로 학습패턴이 발생할 경우 매번 전체 학습 패턴을 다시 학습하는 것이 아니라, 새로 추가된 데이터만을 학습하여 대표패턴을 추출하여 메모리사용을 줄이는 iMPA(incremental Multi Partition Averaging)기법을 제안하였다. 본 논문에서 제안한 기법은 대표적인 메모리기반 추론 기법인 k-NN 기법과 비교하여 현저하게 줄어든 대표패턴으로 유사한 분류 성능을 보여주며, 점진적 특성을 지닌 NGE 이론을 구현한 EACH 시스템과 점진적인 실험에서도 탁월한 분류 성능을 보여준다.

• 한국콘텐츠학회논문지
• /
• 제14권11호
• /
• pp.143-153
• /
• 2014

기존 미디어 서비스의 속성을 복합적으로 보유하면서도 서로 다른 단말기의 상호작용을 통해 새로운 가치를 제공하는 N스크린은 미디어와 콘텐츠, 그리고 소비자 간의 관계를 재구성하고 있다. 본 연구는 정보통신정책연구원의 2012년 한국미디어패널조사 통계조사에서 수집된 8,524명의 미디어 행태 자료 중 N스크린 이용을 중심으로 하여 서비스의 수용과 관련된 소비자 변수들과의 관계를 검증해 보고자 한다. 우선 N스크린 서비스 이용자와 비이용자 간에 인구통계변수, 미디어 이용 행태 중의 하나로서 온라인활동 참여, 라이프스타일 관련 활동 정도 및 제품구매성향, 기존 미디어 레퍼토리, 유료 콘텐츠 소비지출 등의 측면에서 차이가 나는지 각각 살펴보고 서비스 수용에 대한 다양한 변수들의 영향력을 종합적으로 고찰하였다. 본 연구는 소비자의 디지털 라이프스타일의 일부가 되고 있으며 미디어와 콘텐츠 소비 패턴의 변화를 주도할 것으로 예상되는 N스크린 서비스의 중요성에 주목하고, 서비스 수용과 관련이 있는 소비자들의 인구 통계학적, 사회심리학적 변수들과 미디어 행동 변수들을 살펴보았다는 점에서 의의가 있다.

• 한국식품영양학회지
• /
• 제25권2호
• /
• pp.299-307
• /
• 2012

In this study, Kimchi usage was examined by nationwide consumers. 1,000 consumers between 20~60 years olds from 15 cities/province based on an administrative district participated in this questionnaire, which were one-on one interviews from September 23th to October 14th, 2009. 76.1% of the customers prepared Kimchi by them self, 26.9% customers received Kimchi from relatives and, 13.1% purchase Kimchi from the market. In addition, the rate of preparing Kimchi by themselves increased with age(p<0.05). 4~6 cabbage heads(34.5%) was the most preferred quantity for preparing Kimchi at a time, which was followed by more than 10 heads(25.2%) and 2~3 heads(22.9%). Chinese cabbage Kimchi was the most preferred type for purchase. 49.1% of customers purchased Kimchi at the supermarket and warehouse market and the origin of the ingredients, taste and-, price of Kimchi were considered important factors. The satisfactory scores of selling Kimchi were variety 3.60, taste 3.11, freshness of main ingredient 3.10, hygiene 2.86, -appropriate salt usage 2.99 and-, the origin of ingredients 2.94. There were significant difference between gender in taste and hygiene of selling Kimchi (p<0.05). In conclusion, to provide more appropriate Kimchi based on changes in Kimchi usage and consumption patterns at home and in the community, new types of Kimchi should be developed.

• 정보처리학회논문지A
• /
• 제12A권3호
• /
• pp.223-228
• /
• 2005

임베디드 시스템에서 일반적으로 메모리가 가장 많은 에너지를 소비하는 것으로 알려지고 있다. 임베디드 자바가상기계의 경우도 마찬가지이며, 따라서 보다 에너지 효율이 높은 자바가상기계의 개발을 위해서는 자바 메모리의 에너지 사용을 최적화 하는 것이 무엇보다 중요하다. 본 논문에서는 자바 프로그램 실행 시 수많은 바이트코드들이 어떻게 논리적 메모리를 접근하는지 분석하였다. 이런 접근 형태 분석은 자바 메모리의 설계 및 구현 기술을 선택하는데 큰 통찰력을 제공해 준다 힙, 오퍼랜드 스택, 지역변수배열 등 세 가지 논리적 데이터 공간에 대해 각각 메모리 접근을 분석하였으며, 분석 결과 오퍼랜드 스택이 가장 빈번하게, 또한 균일하게 사용되었으며 힙이 가장 드물게, 그리고 불균일하게 사용되었음을 알 수 있었다. 힙과 지역변수배열은 읽기 위주로 사용되었으며, 오퍼랜드 스택은 읽기와 쓰기 비율이 크게 다르지 않았다.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
• /
• 제8권4호
• /
• pp.87-92
• /
• 2019

본 연구에서는 머신 러닝 기법을 활용하여 공장에서 발생하는 에너지 사용량에 대한 데이터 분석 및 패턴 추출에 대해 다룬다. 통계학이나 기존의 방법들은 몇 가지 물리적 특성을 반영하는 수학적 모델을 구축하는 반면, 머신 러닝을 통한 접근방법은 데이터 학습을 통하여 모델의 계수들을 결정하게 된다. 기존의 방법들은 특정한 구조를 갖는 수학적 모델을 구축해야 한다는 어려움이 있으며 과연 데이터의 특징들을 잘 반영하는지에 대한 의문이 존재했다. 그러나 머신 러닝을 통한 방법은 사람이 구축하기 어려운 작업들을 용이하게 구축한다는 장점을 가지고 있기 때문에 데이터 간의 관계를 파악하기에 더 효율적이라는 장점을 가지고 있다. 공장의 에너지 소비에 직접적으로 영향을 끼치는 요소들이 존재하며 이러한 전력 소비는 시간에 따른 데이터로 나타나게 된다. 각 요소들로부터 발생하는 소비 전력을 계측하고 데이터 베이스를 구축하기 위해 각 요소에 센서를 장착하였다. 취득된 데이터에 대해 전처리 과정 및 통계적인 분석을 거친 뒤, 머신 러닝을 통해 패턴을 분석하는 과정을 거쳤다. 이를 통해 공장에서 발생하는 소비 전력 데이터에 대한 패턴 분석을 진행하였다.

• 한국주거학회:학술대회논문집
• /
• 한국주거학회 2005년도 추계학술대회 논문집
• /
• pp.89-92
• /
• 2005

The purpose of this study was to clarify the space use pattern and the daily living activities of the elderly with dementia in the common space (living room) of nursing home. The subjects were 2 units(living room) of the nursing home. For this, researcher visited from June 20 to July 2 and collected data by observations of behavior of the elderly with dementia in common space(living room) and interviews with staff for the information about basic characteristics of the elderly with dementia and administration and operation of the facilities. The data were analyzed using the frequency and percentage. The results revealed as follows: first, the daily living activities of the elderly with dementia in common space tended to focus on self-concentration type and physical environment-interest type. Second, physical environmental -interest type. Second, physical environmental characteristics of common space affected space usage pattern of the elderly with dementia. And it was perceived like as living oriented space, social interaction space, facility space, staff oriented space. Conclusively it was suggested to plan dining space as semi-private space, day corner as semi-public space.

• 아태비즈니스연구
• /
• 제13권3호
• /
• pp.293-309
• /
• 2022

Purpose - The purpose of this study is to explore the possibility of predicting the degree of smartphone overdependence based on mobile phone usage patterns. Design/methodology/approach - In this study, a survey conducted by Korea Internet and Security Agency(KISA) called "problematic smartphone use survey" was analyzed. The survey consists of 180 questions, and data were collected from 29,712 participants. Based on the data on the smartphone usage pattern obtained through the questionnaire, the smartphone addiction level was predicted using machine learning techniques. k-NN, gradient boosting, XGBoost, CatBoost, AdaBoost and random forest algorithms were employed. Findings - First, while various factors together influence the smartphone overdependence level, the results show that all machine learning techniques perform well to predict the smartphone overdependence level. Especially, we focus on the features which can be obtained from the smartphone log data (without psychological factors). It means that our results can be a basis for diagnostic programs to detect problematic smartphone use. Second, the results show that information on users' age, marriage and smartphone usage patterns can be used as predictors to determine whether users are addicted to smartphones. Other demographic characteristics such as sex or region did not appear to significantly affect smartphone overdependence levels. Research implications or Originality - While there are some studies that predict smartphone overdependence level using machine learning techniques, but the studies only present algorithm performance based on survey data. In this study, based on the information gain measure, questions that have more influence on the smartphone overdependence level are presented, and the performance of algorithms according to the questions is compared. Through the results of this study, it is shown that smartphone overdependence level can be predicted with less information if questions about smartphone use are given appropriately.