• 품질경영학회지
• /
• 제46권4호
• /
• pp.797-820
• /
• 2018

Purpose: It is to seek for an appropriate cost rate analysis methodology of credit card value propositions in Korea. For this issue, it is claimed that methodologies based on probability distribution is more suitable than methodologies based on data-mining. The analysis model constructed for the cost rate estimation is called VCPM model. Methods: The model includes two major variables denoted as S and P. S is monthly credit card usage amount. P stands for the proportion of usage amount at special merchants over the whole monthly usage amount. The distributions assumed for P are positively skewed distributions such as exponential, gamma and lognormal. The major inputs to the model are also derived from S and P, which are E(S) and the aggregate proportion of usage amount at special merchants over the total monthly usage amount. Results: When the credit card's value proposition is general discount, the VCPM model fits well and generates reasonable cost rate(denoted as R). However, it seems that the model does not work well for other types of credit cards. Conclusion: The VCPM model is reliable for calculating cost rate for credit cards with positively skewed distribution of P, which are general discount card. However, another model should be built for cards with other types of distributions of P.

• International Journal of Computer Science & Network Security
• /
• 제22권7호
• /
• pp.131-146
• /
• 2022

The Internet is becoming a basic need for many individuals globally in this digital age. The youths became more active online than before, with the majority relying on different platforms to communicate and interact with peers. Saudi Arabia is one of the nations where internet usage is high, with an increasing number of active internet users. The youth in Saudi Arabia are engaged in various online platforms. However, they lack adequate knowledge about cybersecurity and the dangers of internet usage, which exposes them to the risk of falling victims to cybercriminals. The most common dangers of internet usage include viruses, malware, phishing, and hacking, compromising users' sensitive information. Increased awareness of these potential threats helps protect Internet users and secure their data. The understanding of the dangers of Internet usage among youths varies across countries. In this regard, our study explores the risks of internet usage among youth in Saudi Arabia compared to the United States, South Africa, and New Zealand.

• Asia pacific journal of information systems
• /
• 제32권2호
• /
• pp.249-274
• /
• 2022

This study is to focuses on users' attitudes toward augmented reality games. Based on the Technology Acceptance Model (TAM) and Flow theory, continuous usage intention was set as a dependent variable, and immersion was set as a mediating variable. As independent variables, spatial presence, perceived interactivity, perceived pleasure, and sickness were set. Besides, this study strived to compare and analyze Korean and Chinese Data. The results of this study were as follows. First of all, Korean users significantly affected spatial presence, perceived pleasure, and immersion. Spatial presence and perceived pleasure had also mediated effects on continuous usage intention through immersion. However, perceived interactivity and sickness did not affect immersion and even no mediating effect to continuous usage intention. In the case of Chinese users, spatial presence, perceived interactivity, and perceived pleasure were grouped into one variable. This variable influenced immersion and also had mediated effect on continuous usage intention. However, sickness, like Korean users, did not affect the set path. This study had implications for analyzing user perspective using immersion, a significant variable in previous research. In addition, this study found similarities and characteristics through a comparative analysis between Korean and Chinese users indirectly.

• 한국환경과학회지
• /
• 제20권10호
• /
• pp.1297-1308
• /
• 2011

This study is to analyze the characteristics of golf course water usage using groundwater and rainwater data obtained from 17 golf courses in Jeju Island during 2007~2009. The groundwater usages were 246,275 $m^3/year$, 213,062 $m^3/year$, 155,235 $m^3/year$, and 126,666 $m^3/year$ in the west, south, east, and north regions, respectively. Monthly rate of the amount of groundwater usage to the amount of permission was 29.5%. The rainfall usages were 386,591 $m^3/year$, 326,464 $m^3/year$, 251,248 $m^3/year$, and 232,061 $m^3/year$ in the south, west, east, and north regions, respectively. Monthly rate of rainwater usage to the amount of water retention of golf courses was 19.6%. The average annual water usage in the 17 golf courses was 499,377 $m^3/year$. From the average usage, it was found that the rainwater usage (305,126 $m^3/year$ ) was 1.6 times higher than that of groundwater (194,251 $m^3/year$ ). That means the annual average rainwater usage to the entire water usage was 61.1%, which was above the criteria of 40%.

• 한국비블리아학회지
• /
• 제27권2호
• /
• pp.193-212
• /
• 2016

이 연구의 목적은 도서관이용과 도서관예산 사이에 영향관계가 있는지를 알아보고, 이를 통해 잠재적 이용자들을 도서관으로 유인하기 위해서는 적정예산의 확보가 필요하다는 것을 설명하는데 있다. 다시 말해, 도서관예산은 도서관이용을 증진시킬 수 있는 중요한 요인임을 설명하기 위해 시도되었다. 이를 위해 부산광역시 공공도서관 31개관을 대상으로 국가도서관통계시스템으로부터 확보된 2013년 통계데이터를 사용하여 분석을 실시하였다. 분석을 위해 독립변수는 도서관예산을 설명하는 '총비용지수(TFI: Total Funding Indicator) = $\sqrt{인건비{\times}자료구입비}$'와 도서관이용을 나타내는 'LU(Library Usage) = (연간 방문자수) + (연간 대출자료수) / 봉사대상인구'의 개념을 통해 산출된 값을 종속변수로 사용하였다. 연구결과는 도서관총비용지수(TFI)와 도서관이용(LU) 사이에는 영향관계가 존재하는 것으로 나타났으며, 도서관의 예산이 증가할수록 도서관이용은 증가하는 것으로 설명되었다. 본 연구의 결과가 비록 도서관예산과 도서관이용의 긍정적인 관계를 설명하고 있지만, 분석대상 및 분석기간의 제한성 및 한정성으로 인해 정책결정을 위한 도구로서 활용되기 위해서는 대상의 확대 및 분석기간의 다년화를 통한 타당성이 확보되어야 한다.

• 한국식생활문화학회지
• /
• 제22권1호
• /
• pp.43-57
• /
• 2007

This study was designed to identify the actual state of ready-to-eat street-foods usage in a college-town in northern part of seoul. For the empirical study, data was collected from customers who had eaten street-foods and a survey was conducted from 16 to 30, May 2006. The results showed that many respondents had irregular eating habits. More than 60% of them responded they usually skipped breakfast and the reason was no time. It was shown that they have had Frequent snacks and unbalanced diet. The results of survey are as follows ; 1. The major time for street-foods usage: p.m 3-5 (28.77%). 2. The frequency of street-foods usage: 1-2 times/week (43.85%). 3. The street-foods usage days of the week: weekday (52.79%). 4. The mean cost for the onetime purchase of street-foods usage: 1000-3000won (71.79%). 5. The monthly cost for the purchase of street-foods usage: below 50000won (81.84%). 6. The reason for street-foods usage: mainly convenience (60.61%). 7. The reason for minding street-foods : mainly insanitary (40.50)%. 8. Factors considered when choosing street-foods: tastes of the foods (65.08%). Also, it was shown that over 50% of respondents have considered the street-foods as the worth of meal replacement, and taken effective factor on eating habits for influx of new culture. It was indicated that problems of street-foods usage was the unbalanced nutrition for 81.8% of respondents and suggestions for improving the street-foods were sanitary controls for products for 63.4% of respondents.

• 한국정보과학회논문지:소프트웨어및응용
• /
• 제30권9호
• /
• pp.843-849
• /
• 2003

웹 이용 마이닝은 거대한 웹 로그들을 이용하여 웹 사용자의 이용 패턴을 분석하는 데이타 마이닝 기술이다. 이러한 웹 이용 마이닝 기술을 사용하기 위해서는 전처리 과정 중의 사용자와 세션을 정확하게 구분해야 하는데, 표준 웹 로그 형식의 로그 파일만으로는 완전히 구분할 수 없다. 사용자와 세션을 구분하기 위해서는 로컬캐시, 방화벽, ISP, 사용자 프라이버시, 쿠키 등과 같은 많은 문제들이 있지만, 이 문제를 해결하기 위한 명확한 방법은 아직 없다. 특히, 로컬캐시 문제는 웹 마이닝 시스템의 입력으로 사용되는 사용자 세션을 구분하는데 가장 어려운 문제이다 본 연구에서는 참조 로그와 에이전트 로그, 그리고 액세스 로그 둥의 서버측 클릭스트림 데이타만을 이용하여 로컬캐시 문제를 해결하고, 사용자 세션을 구분하고 세션을 보정하는 휴리스틱 방법을 제안한다.

• 한국전자통신학회논문지
• /
• 제18권1호
• /
• pp.107-114
• /
• 2023

본 연구는 건축 부재 사용량 예측을 위한 인공지능 기반의 학습모델을 설계 및 구현하는 방법에 대하여 기술하였다. 인공지능(Artifical intelligence : AI) 은 기술의 발전에 힘입어 다양한 분야에서 폭넓게 활용되고 있지만, 건축설계분야 데이터의 특수성 및 빅데이터 수집의 어려움으로 인해 현장 활용도가 매우 저조한 상태이다. 따라서 건축설계분야에서 인공지능 기술을 도입할 수 있도록 건축 부재 단위의 AI문제를 발굴해 내었으며, 해당분야 데이터가 가지는 특이성을 해결하기 위한 새로운 전처리 기법을 고안하였다. 고안된 전처리 기법을 토대로 인공지능 모델을 구현하였고, 구현된 인공지능 모델의 건축 부재 사용량 예측 정확도가 실제 산업에 사용할 수 있는 수준임을 확인하였다.

• International Journal of Computer Science & Network Security
• /
• 제24권4호
• /
• pp.60-66
• /
• 2024

Host's data during transmission. Data tempering results in loss of host's sensitive information, which includes number of VM, storage availability, and other information. In the distributed cloud environment, each server (computing server (CS)) configured with Local Resource Monitors (LRMs) which runs independently and performs Virtual Machine (VM) migrations to nearby servers. Approaches like predictive VM migration [21] [22] by each server considering nearby server's CPU usage, roatative decision making capacity [21] among the servers in distributed cloud environment has been proposed. This approaches usage underlying server's computing power for predicting own server's future resource utilization and nearby server's resource usage computation. It results in running VM and its running application to remain in waiting state for computing power. In order to reduce this, a decentralized decision making hybrid model for VM migration need to be proposed where servers in decentralized cloud receives, future resource usage by analytical computing system and takes decision for migrating VM to its neighbor servers. Host's in the decentralized cloud shares, their detail with peer servers after fixed interval, this results in chance to tempering messages that would be exchanged in between HC and CH. At the same time, it reduces chance of over utilization of peer servers, caused due to compromised host. This paper discusses, an roatative decisive (RD) approach for VM migration among peer computing servers (CS) in decentralized cloud environment, preserving confidentiality and integrity of the host's data. Experimental result shows that, the proposed predictive VM migration approach reduces extra VM migration caused due over utilization of identified servers and reduces number of active servers in greater extent, and ensures confidentiality and integrity of peer host's data.

• 전기학회논문지
• /
• 제67권3호
• /
• pp.460-466
• /
• 2018

For the efficient energy consumption in an urban railway station, it is necessary to know the patterns of electrical loads for each usage in detail. The electrical loads in an urban railway station have different characteristics from other normal electrical load, such as the peak load timing during a day. The lighting, HVAC, communication, and commercial loads make up large amount of electrical load for equipment in an urban railway station, and each of them has the unique specificity. These loads for each usage were estimated without measuring device by the polynomial regression method with big data such as total amount of electrical load and weather data. In the simulation with real data, the optimal polynomial regression model was third order polynomial regression model with 9 or 10 independent variables.