• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.11
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• pp.1900-1911
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• 2010

This study focuses on clothing as one of the most seasonal products and investigates consumer behavior related to climate change adaptation. This study addressed four objectives: (1) to identify the clothing behavior of consumers for the adaptation to climate change; (2) to identify the effects of fashion involvement and climate sensitivity on clothing attitude for the adaptation to climate change; (3) to identify the effect of clothing purchase time on climate sensitivity and clothing attitude for the adaptation to climate change; and (4) to identify the effect of consumer demographics on climate sensitivity and clothing attitude for the adaptation to climate change. A survey questionnaire was developed and implemented to collect data for measuring clothing involvement, fashion involvement, and climate sensitivity. In addition, clothing involvement, clothing assortment needs, and clothing worn for the adaptation to climate change were measured. A total of 349 responses were analyzed by t-test, ANOVA and path analysis with SPSS18.0. The results of the analysis are as follows. Changes in temperature were considered more important than changes in weather for the functional needs of clothing, purchase needs, and assortment items needs. The assortment items wearing for the adaptation to climate change varied depending on the temperature and weather. Fashion involvement directly influenced clothing assortment needs and indirectly influenced the clothing worn for the adaptation to climate change. In terms of clothing purchase time, those purchasing clothing before the season begins, tended to have a high fashion involvement and clothing attitude for the adaptation to climate change. Those in their twenties and single, tended to be more sensitive to climate change. This study also discusses the implications for merchandising strategies.

• Proceedings of KOSOMES biannual meeting
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• 2006.05a
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• pp.137-140
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• 2006

황해와 동중국해의 해황 변동에 관한 연구는 현장관측을 중심으로 체계적으로 많이 수행되어 왔지만, 인공위성자료를 이용한 황해와 동중국해의 해황 변동 연구는 미비한 실정이다. 이것은 인공위성자료를 통해 얻을 수 있는 관측항목이 표층수온자료에 국한되어 있었기 때문이다. 그러나 SeaWiFS 해색위성과 같은 인공위성자료들을 이용하여 부유물 농도, 엽록소 농도 등이 원활하게 생산되고 있으며 최근 연구결과에 의해 염분과 유향성분 등도 추정 및 추출이 가능케 되었으므로 이들 인공위성자료를 이용한 황해와 동 중국해의 해황 변동에 관한 연구를 수행하게 되었다. 특히 2004 년도는 계절변동에 있어서 이상기후의 해라고 점철되고 있다. 2004년 봄철의 폭설과 일시적인 고온현상, 여름철에는 10 년만의 무더위, 겨울철에는 36년만에 가장 포근한 날씨가 지속되었다. 이러한 이상기후의 발생은 해양과 대기의 상호작용에 의해서 기인했을 것이라고 생각되어 한반도 주변 해역에서 황해와 동중국해의 해황변동이 연안 해역의 해황변동과 어떠한 연관성이 존재하고, 이러한 요인들은 2004년도에 발생한 이상기후와 어떤 상관관계를 갖는지 연구하기 위한 기초연구를 진행하였다. 2003년 12월 - 2004년 2월과 2004년 12월 - 2005년 2월에 동일한 시기에 관측된 NOAA 표층수온 분포 영상 자료들을 황해와 동중국해 해역을 중심으로 월별로 비교해보면 2003년 12월 2004년 1월에 관측된 표층수온 분포값보다 2004녀 12월 - 2005년 1월에 관측된 표층수온 분포값이 상대적으로 높은 분포 특성을 나타내고 있었다. 이와 같은 현상은 국립수산과학원의 2004년 10월과 12월의 정선관측자료에서도 나타나고 있었다. 그러나 이와는 반대로 2004년 2월에 관측된 표층수온 분포값보다 2005년 2월에 관측된 표층수온 분포값이 상대적으로 낮은 분포 특성을 나타내고 있었다. 따라서 인공위성자료를 이용한 황해의 2004년 해황 분석 결과는 이상수온 상승의 원인이 쿠로시오 해류의 변동과 관련성이 높다고 판단되며 이에 대한 지속적인 연구가 현재 진행중에 있다.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.684-690
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• 2010

Digitalized Image Information is variously used like to substitute or help human's visual ability. Unmanned observation Camera is useful for the preventing disaster, risk factor and object observation but it is mostly to depend on awareness for human's vision. The purpose of this paper is to show that Unmanned Aerial Camera carries out object recognition and autonomous position tracking. when the informations about a specific object are given. For this purpose, we have to solve complicated problems like change according to object movement and variation of color and brightness information with refraction, interference and scattering of light and noise from environmental factors like weather. But, as the first step we limit the scope of this study with simplified environment in this paper. Our goal is the study and experience about object recognition and tracking via simplified environment with unmanned aerial camera. We obtained successful results of this study and experiment.

• Journal of the Korean Society of Food Science and Nutrition
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• v.21 no.4
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• pp.460-470
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• 1992

Thermogenesis in brown adipose tissue (BAT) can serve the animal in the regulation of its body temperature and of its body weight. Thermogenesis can be switched on by exposure of the animal to cold (non-shivering thermogenesis) or by overeating (diet-induced thermogenesis). BAT mitochondria are uniquely specialized for thermogenesis, possessing a specific proton conductance pathway that is regulated by the concentration of fatty acids in the cells of BAT. The level of fatty acids is in turn controlled by the lipolytic action of noradrenaline on the tissue. When the proton conductance pathway operates, the mitochondria are effectively uncoupled and exhibit extremely high rates of substrate oxidation with a great increase in heat production. Thus it is suggested that BAT is of importance in energy balance and human obesity treatment if thermogenesis can be stimulated specifically.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.249-257
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• 2018

The purpose of this study is to construct a virtual reality simulation environment for searching and evaluating evaluation criteria for road safety facilities with new technologies. Virtual reality simulation requires high realism and accurate behavior data extraction. To do this, we used the Unreal Engine to create the environment by dividing it into an external environment and a vehicle environment. After that, a sample simulation for the luminescent road markers and preliminary experiments were conducted. As a result, luminescent road markers showed better 5m interval than 10m interval. It can be confirmed that it can be used in the simulation for searching the evaluation criteria for the new road safety facilities that incorporate the new technology in the future. In the future, it will be possible to simulate various environments by adding modeling and sample components for other road facilities.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.317-324
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• 2000

주기적인 연관규칙은 타겟데이터베이스를 일정 단위시간으로 나누었을 때 연관규칙이 만족하는 구간이 일정한 주기마다 발생하는 패턴을 탐색하는 방법이다. 하지만, 이 방법은 엄격한 주기를 가지도록 하여 실제 데이터에 그대로 적용하기가 어려웠다. 예를 들이 편의점 데이터에서 매일 오전 7시-8시 사이에 주기적으로 발생하는 연관규칙을 발견할 때, 이러한 연관규칙을 주기적인 연관규칙이라고 한다. 하지만, 실제 데이터에서는 날씨와 같이 사람의 행동에 영향을 미치는 다른 요인 때문에 항상 일정한 주기를 가지는 연관규칙을 찾기는 어렵다. 본 논문에서는 주기가 일정하지 않은 연관규칙을 찾기 위해서 연관규칙의 주기성을 허용 오차를 포함하며 재정의하고, 오차를 허용하기 위한 탐색 알고리즘을 보완하였다. 반면에, 오차를 허용함으로써 오차를 허용하지 않는 경우보다 더 많은 주기성을 찾을 수 있을 뿐만 아니라, 동일한 주기를 가지지만 오프셋이 다른 여러 개의 비슷한 주기가지 찾게 되어 사용자가 의미 있는 연관규칙을 찾는데 방해가 된다. 본 논문에서는 이를 해결하기 위해서 오차를 허용하는 주기적 연관규칙의 오차의 정도를 측정하기 위한 단위로 집중도(intensity)와 경향성(tendency)을 제안한다. 주기적 연관규칙이 매 주기마다 정확한 세그먼트에 나타나는 정도를 나타내는 집중도와, 최소 평균오차를 의미하는 경향성을 이용하여 유사한 주기들 중에서 대표주기만을 찾을 수 있도록 한다. 또한, 오차를 허용하는 주기적 연관규칙에서 오차가 주로 발생하는 패턴을 분석함으로써 고객들의 수요 경향성을 더 잘 파악할 수 있다. 예를 들어, 평소에는 매일 오진 7시∼8시에 나타나던 연관성이 지각하는 사람들이 같은 월요일에는 1시간 늦은 8시∼9시에 나타난다는 오타 정보까지 파악할 수 있다. 이러한 월요일마다 1시간 늦게 나타나는 오차의 경향성을 나타내는 오차 주기(error cyc1e)를 이용함으로써 고객들의 수요의 경향성을 좀 더 세밀한 부분까지 파악할 수 있게 해 준다.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.54-61
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• 2019

Recently, IITS (intelligent integrated transportation system) has been important topic in Smart City related industry. As a main objective of IITS, prevention of traffic jam (due to car accidents) has been attempted with help of advanced sensor and communication technologies. Studies show that car accident has certain correlation with some factors including characteristics of location, weather, driver's behavior, and time of day. We concentrate our study on observing auto correlativity of car accidents in terms of time of day. In this paper, we performed the ARIMA tests including ADF (augmented Dickey-Fuller) to check the three factors determining auto-regressive, stationarity, and lag order. Summary on forecasting of hourly car crash counts is presented, we show that the traffic accident data obtained in Korea can be applied to ARIMA model and present a result that traffic accidents in Korea have property of being recurrent daily basis.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.861-866
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• 2022

Seoul introduced the shared bicycle system, "Seoul Public Bike" in 2015 to help reduce traffic volume and air pollution. Hence, to solve various problems according to the supply and demand of the shared bicycle system, "Seoul Public Bike," several studies are being conducted. Most of the research is a strategic "Bicycle Rearrangement" in regard to the imbalance between supply and demand. Moreover, most of these studies predict demand by grouping features such as weather or season. In previous studies, demand was predicted by time-series-analysis. However, recently, studies that predict demand using deep learning or machine learning are emerging. In this paper, we can show that demand prediction can be made a little better by discovering new features or ordering the importance of various features based on well-known feature-patterns. In this study, by ordering the selection of new features or the importance of the features, a better coefficient of determination can be obtained even if the well-known deep learning or machine learning or time-series-analysis is exploited as it is. Therefore, we could be a better one for demand prediction.

• Korean Journal of Environment and Ecology
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• v.23 no.5
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• pp.418-430
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• 2009

The main purpose of this study is to investigate the relationship between the topography of land and vegetation and the preferred habitat of wintering cranes. Investigations were conducted twelve times in Cheorwon basin, South Korea, during two wintering seasons (12/2005 - 2/2006; 1/2007 - 2/2007). The density of rice grain in the middle of rice paddies was higher than that of the areas along the edge of rice paddies. However it was observed that red-naped cranes preferred to feed along the edges of rice paddies rather than to feed in the middle of the paddies. White-naped cranes, on the other hand, Preferred to feed in the middle of paddies. To be more specific, red-crowned cranes preferred feeding sites such as levees of the paddies or the areas where the level of the rice beds was comparatively more elevated. But the preference of the white-naped cranes turned out to be just the opposite. Another finding was that both red-naped cranes and white-naped cranes preferred concealed areas for their feeding site, and the frequency rate of their feeding in concealed areas has little to do with weather factors. This finding contradicts a widely accepted view that cranes prefer open spaces for their feeding site. Besides, red-crowned cranes, compared with white-naped cranes, preferred to feed in more concealed areas. The frequency rate of feeding in both concealed areas and non-concealed areas had little to do with the size of feeding flocks. There was no difference between a flock of fewer than five cranes and a flock of more than five cranes in terms of frequency rate of their feeding. In conclusion, the result of these investigations indicate that red-naped cranes comparatively prefer concealed areas for their feeding site, and white-naped cranes are less prone to them, and there is no direct connection between their preference of feeding site or frequency and the size of their flock. This is presumed to be the characteristics unique to their individual species.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.34-45
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• 2021

Weather is one of the important factors in the agricultural industry as it affects the price, production, and quality of crops. Upland crops are directly exposed to the natural environment because they are mainly grown in mountainous areas. Therefore, it is necessary to provide accurate weather for upland crops. This study examined the effectiveness of 12 forest soil factors to interpolate the weather in mountainous areas. The daily temperature and precipitation were collected by the Korea Meteorological Administration between January 2009 and December 2018. The Generalized Additive Model (GAM), Kriging, and Random Forest (RF) were considered to interpolate. For evaluating the interpolation performance, automatic weather stations were used as training data and automated synoptic observing systems were used as test data for cross-validation. Unfortunately, the forest soil factors were not significant to interpolate the weather in the mountainous areas. GAM with only geography aspects showed that it can interpolate well in terms of root mean squared error and mean absolute error. The significance of the factors was tested at the 5% significance level in GAM, and the climate zone code (CLZN_CD) and soil water code B (SIBFLR_LAR) were identified as relatively important factors. It has shown that CLZN_CD could help to interpolate the daily average and minimum daily temperature for upland crops.