• 복식문화연구
• /
• 제24권6호
• /
• pp.803-816
• /
• 2016

The purposes of this study were to investigate the influences of channel assessments on the usage of multi-channels by product types, and the differences in the usage of multi-channels among product types in buying decision making process for fashion products. Data were collected from 510 consumers in their 20s to 50s with purchasing experiences through multi-channel distribution system and living in Seoul and Kyunggi province; 491 were analyzed after deleting incomplete questionnaires. Factor analysis, multiple regression analysis and one-way ANOVA were used for statistical analysis by using SPSS 18.0. The results were as follows: 5 factors were extracted for channel assessment: utility, accuracy, risk, price benefit and sharing information. Price benefits, utility and sharing information for online channel tended to influence positively on the usage of online channel and online+offline channels. Accuracy and low perceived risk of offline influenced positively on offline and on+offline channel usages. The usage levels of on-line and off-line channels for cosmetics were significantly lower than the usage levels for clothes and accessories on information search, evaluation of alternatives, and purchase stages. Significant differences were also found in the usage levels of multi-channels (on+off-line) on information search and evaluation of alternatives stages. The usage levels of the multi-channels for clothes were the highest followed by those of accessories and cosmetics in order.

• 벤처창업연구
• /
• 제11권6호
• /
• pp.61-69
• /
• 2016

본 연구는 사회적 기업의 과업-기술 적합성(TTF)이 소셜네트워크서비스(SNS) 이용의도에 미치는 영향에 대해 검증하는 것이 목적이다. 사회적 기업, 소셜네트워크서비스, 과업-기술 적합성, 기술수용모형(TAM)에 관한 이론적 배경을 바탕으로 연구모형과 연구가설을 설정하였다. 본 연구에서는 인증 사회적 기업 86개를 대상으로 Smart PLS 2.0을 이용하여 구조방정식 모형을 분석하였다. 본 연구의 분석결과를 요약하면 다음과 같다. 첫째, 과업-기술 적합성이 지각된 유용성, 지각된 이용용이성, SNS 이용의도에 정(+)의 영향을 미치는 것으로 나타났다. 둘째, 지각된 유용성은 SNS 이용의도에 정(+)의 영향을 미치는 것으로 나타났지만, 지각된 이용용이성은 SNS 이용의도에 유의한 영향을 미치지 않는 것으로 나타났다. 본 연구의 결과는 과업-기술 적합성 측면에서 SNS가 사회적 기업의 업무에 적합한지에 대해 분석하여 다른 정보기술 분야의 이용의도에 적용할 수 있는 이론적 시사점과 사회적 기업에게 실무적인 시사점을 제공할 것이다.

• 국토계획
• /
• 제53권6호
• /
• pp.39-59
• /
• 2018

This study examines the relationship between the usage of public bike and physical environment factors around the public bike stations using the public bike rental history data from 2016 to 2017 in Seoul, Korea. Focusing on the different influences of determinant factors by distance to public bike station, this study identifies influential factors that affect the usage of public bike. The results of the analysis are as follows. First, both the land use and physical environmental variables of bike station areas show strong associations with the usage of public bike. Second, the usage of public bike is also associated with neighborhood living facilities, business facilities, land use mix, the distance to subway station, public facilities and universities. This finding indicates that public bike has played a role as a transportation mode for the short-distance travel and commuting purposes in everyday life. Third, this study shows that the usage of public bike is strongly associated with the average slope, traffic volume around public bike stations, distance to streams or rivers, and the types of bike lane. This finding also indicates that surrounding environmental factors play an important role in the usage of public bike. Finally, this study identifies the different influences of determinant factors on the usage of public bike by distance to public bike station. This study suggests policy implications for the potential locations of public bike stations in the future.

• Human Ecology Research
• /
• 제59권2호
• /
• pp.233-243
• /
• 2021

This study examined the longitudinal effects of media usage by early school-age children and of maternal parenting stress on children's school adjustment. The study focused on the mediating effect of executive function difficulty. Longitudinal data to examine the hypothetical model were drawn from the eighth (2015) through tenth (2017) waves of the Panel Study of Korean Children (PSKC) collected by the Korea Institute of Child Care and Education (KICCE). A total of 581 children (293 boys and 288 girls) and their mothers were included. Confirmatory factor analysis, structural equation model, and bootstrapping analysis were applied using SPSS 25.0 and Amos 26.0. The results are as follows. First, no significant correlation was found between early school-age children's media usage and maternal parenting stress. Second, neither media usage by early school-age children nor maternal parenting stress were found to directly affect children's school adjustment. Third, media usage by early school-age children and maternal parenting stress were shown to indirectly affect children's school adjustment via executive function difficulties. In other words, higher levels of media usage by early school-age children and maternal parenting stress during the first grade lead to greater executive function difficulties after a year, which, in turn, lead to a lower level of school adjustment in the third grade. This study indicates the need to develop practical support for the psychological wellbeing of mothers while they are performing their role as a parent and for children in maintaining suitable levels of media usage during early childhood.

• 한국수자원학회논문집
• /
• 제57권1호
• /
• pp.1-8
• /
• 2024

우리나라는 기후변화의 영향으로 지속되는 가뭄으로 인해 물 부족 문제가 심화되고 있다. 제1차 국가물관리기본계획에 따르면, 생활 및 공업용수 부족량은 과거 최대 가뭄빈도(50년) 기준으로 0.07억 m³/년으로 전망되고 있다. 이러한 물 부족 문제에 효과적으로 대응하기 위해서는 장기적인 용수 수요 전망이 필수적이다. 공업용수의 경우 월별 사용량이 비교적 일정하지만, 생활용수의 경우 월별 패턴이 뚜렷하기 때문에 연단위 분석이 아닌 월단위 분석을 수행해야 한다. 본 연구는 충청권역을 대상으로 2017~2021년의 월별 용수 이용량 자료에 대해 패턴을 분석하고, 기후 변수와의 상관성을 이용하여 용수 분배 비율을 계산하였다. 그 결과 월별 생활용수 이용량을 연 이용량으로 나눈 월별 용수 이용률을 다시 평균기온으로 나누는 분법으로 계산한 경우가 절대오차가 가장 작게 산정되었으며, 이를 활용하여 충청권역의 월별 분배 비율을 산정하였다. 또한 충청권역의 월별 분배 비율에 SSP5-8.5 시나리오의 평균기온을 곱해 충청권역의 미래 월별 용수 이용률을 전망하였다. 그 결과, 최댓값의 평균은 1.16에서 1.29로 증가하고 최솟값의 평균은 0.86에서 0.84로 감소하였으며, 1사분위수는 0.95에서 0.93으로 감소하고 3사분위수는 1.04에서 1.06으로 증가하였다. 따라서 미래에는 현재와 비슷한 패턴을 유지할 것으로 보이지만, 월별 용수 이용률의 변동성은 커질 것으로 예상된다.

• 산업공학
• /
• 제25권4호
• /
• pp.472-479
• /
• 2012

Before an aircraft is delivered to customers, manufacturers have to verify required reliability for the aircraft. In usual, reliability of electronic equipments in military aircraft are predicted based on MIL-HDBK-217. But the specification has not been revised since 1995. Some alternatives including SR-332 and 217PLUS are suggested in this study. The processes and methods specified in MIL-HDBK-217 are compared with those of SR-332. Additionally, the predicted reliability of aircraft electronic equipment between usage data and field data are investigated using MIL-HDBK-217. The results show that predicted reliability of MIL-HDBK-217 is more conservative (underestimated) than that of usage data and field data.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2019년도 추계학술발표대회
• /
• pp.817-819
• /
• 2019

다양한 학습 모델이 발전하고 있는 지금, 학습을 통한 다양한 시도가 진행되고 있다. 이중 에너지 분야에서 많은 연구가 진행 중에 있으며, 대표적으로 BEMS(Building energy Management System)를 볼 수 있다. BEMS의 경우 건물을 기준으로 건물에서 생성되는 다양한 DATA를 이용하여, 에너지 예측 및 제어하는 다양한 기술이 발전해가고 있다. 하지만 FEMS(Factory Energy Management System)에 관련된 연구는 많이 발전하지 못했으며, 이는 BEMS와 FEAMS의 차이에서 비롯된다. 본 연구에서는 실제 공장에서 수집한 DATA를 기반으로 하여, 전력량 예측을 하였으며 예측을 위한 기술로 시계열 DATA 분석 방법인 LSTM 알고리즘을 이용하여 진행하였다.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2020년도 추계학술발표대회
• /
• pp.689-692
• /
• 2020

People have studied English using online English dictionaries when they looked for the meaning of English words or the example sentences. These days, as the AI technologies such as machine learning have been developing, documents can be translated in real time with Kakao, Papago, Google translators and so on. But, there has still been some problems with the accuracy of translation. The AI secretaries can be used for real-time interpreting, so this kind of systems are being used to translate such the web pages, papers into Korean. In this paper, we researched on the usage frequency of the combined English phrases from dictionaries by analyzing the number of the searched results on Google. With the result of this paper, we expect to help the people to use more English fluently.

• Journal of Platform Technology
• /
• 제11권6호
• /
• pp.3-12
• /
• 2023

In today's system operation, it is difficult to detect failures and take immediate action in the case of a shortage of manpower compared to the number of equipment or failures in vulnerable time zones, which can lead to delays in failure recovery. In addition, various algorithms exist to detect abnormal symptom data, and it is important to select an appropriate algorithm for each problem. In this paper, an ensemble-based isolation forest model was used to efficiently detect multivariate point anomalies that deviated from the mean distribution in the data set generated to predict system failure and minimize service interruption. And since significant changes in memory space usage are observed together with changes in CPU usage, the problem is solved by using LSTM-Auto Encoder for a collective anomaly in which another feature exhibits an abnormal pattern according to a change in one by comparing two or more features. did In addition, evaluation indicators are set for the performance evaluation of the model presented in this study, and then AI model evaluation is performed.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권6호
• /
• pp.1957-1980
• /
• 2021

The significant aim of this research has always been to evaluate the mechanism for efficient and inherently aware usage of vitality in-home devices, thus improving the information of smart metering systems with regard to the usage of selected homes and the time of use. Advances in information processing are commonly used to quantify gigantic building activity data steps to boost the activity efficiency of the building energy systems. Here, some smart data mining models are offered to measure, and predict the time series for energy in order to expose different ephemeral principles for using energy. Such considerations illustrate the use of machines in relation to time, such as day hour, time of day, week, month and year relationships within a family unit, which are key components in gathering and separating the effect of consumers behaviors in the use of energy and their pattern of energy prediction. It is necessary to determine the multiple relations through the usage of different appliances from simultaneous information flows. In comparison, specific relations among interval-based instances where multiple appliances use continue for certain duration are difficult to determine. In order to resolve these difficulties, an unsupervised energy time-series data clustering and a frequent pattern mining study as well as a deep learning technique for estimating energy use were presented. A broad test using true data sets that are rich in smart meter data were conducted. The exact results of the appliance designs that were recognized by the proposed model were filled out by Deep Convolutional Neural Networks (CNN) and Recurrent Neural Networks (LSTM and GRU) at each stage, with consolidated accuracy of 94.79%, 97.99%, 99.61%, for 25%, 50%, and 75%, respectively.