• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2009년도 하계학술발표대회 논문집
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• pp.357-362
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• 2009

As a unutilized energy, treated sewage water locates widespread near urban areas. From the previous survey, the sewage water is reported to hold energy potential up to 36,000 Tcal/year, which was 2.1% of the total domestic energy consumption and 9.7% of the energy usage in the household and business sector in 2006. Temperature of the sewage water differs locally, but its range is observed in a range of $20{\sim}25^{\circ}C$ in summer and $8{\sim}13^{\circ}C$ in winter. Since the temperature range of the sewage water has a better seasonal distribution about $5{\sim}10^{\circ}C$ compared to ambient air, it is a promising heat sink for summer or heat source for winter. The sewage water is also a high quality heat source from its abundant quantity and uniform temperature. Considering the ambient temperature of Korea is very low in winter, a heat pump system using the sewage water can be an alternative to prevent problems of capacity deficiency and frost formation.

• 한국식품영양학회지
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• 제25권1호
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• pp.205-213
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• 2012

This study investigated the life cycle of menus and made suggestions on the appropriate time for when new menus should be developed. For this purpose, a total of 636 customers who visited 'T' Restaurant more than 25 times in the past three years were used for analysis. After estimating product life cycles based on sales and selling period, an empirical study was conducted. In terms of product life cycle, a growth stage was observed in the category of pasta and pizza in both stores A and B, whereas sales in the rice category stayed constant. Regarding trend in seasonal sales, a big difference was detected between the two stores. While store A was already in the decline stage of the life cycle in all menu categories, store B remained in the growth stage. In terms of menu life cycle, the product life cycle of long-lived products was observed in the pasta category in both stores A and B. While the pizza category was in the growth stage, the product life cycle of long-lived products was observed in the rice category. It is expected that the results of this study could be useful in development of new menus and product life cycle management to fulfill diverse customer needs in the dining-out business.

• Asian Journal of Business Environment
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• 제7권4호
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• pp.35-41
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• 2017

Purpose - This paper aims to examine several time series models to predict sales of department stores and discount store markets in South Korea, while other previous trial has performed sales of convenience stores and supermarkets. In addition, optimal predicted values on the underlying model can be got and be applied to distribution industry. Research design, data, and methodology - Two retailing types, under investigation, are homogeneous and comparable in size based on 86 realizations sampled from January 2010 to February in 2017. To accomplish the purpose of this research, both ARIMA model and exponential smoothing methods are, simultaneously, utilized. Furthermore, model-fit measures may be exploited as important tools of the optimal model-building. Results - By applying Holt-Winters' additive seasonality method to sales of two large-scale retailing types, persisting increasing trend and fluctuation around the constant level with seasonal pattern, respectively, will be predicted from May in 2017 to February in 2018. Conclusions - Considering 2017-2018 forecasts for sales of two large-scale retailing types, it is important to predict future sales magnitude and to produce the useful information for reforming financial conditions and related policies, so that the impacts of any marketing or management scheme can be compared against the do-nothing scenario.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2008년도 추계학술대회 논문집
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• pp.93-99
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• 2008

The SeoulMerto, operating subway line No.$1{\sim}4$, was constructed in the metropolitan Seoul with the highest population. When it was built, the design was challenged to sharp curved tracks considering the protection of buildings, cultural assets, the connection to ground roads and rivers as well as to elevated railway in some parts. Lots of residential apartments and business complex have gradually increased in the area around subway stations and railway lines according to the urban development. Consequently, Requirements of better quality of life and comfortable environment caused the citizen complain for the noise. It has become one of serious social issues. In this paper, Noise level was analyzed using noise map measured in the running train of all routes. The analysis on the noise level was conducted according to railway type, track components type, seasonal type, retirement degree of the vehicle and subway station. Especially, Noise characteristics were analyzed by noise level data measured in the inside and outside of the train with geometry types of the concrete track. This study will contribute fundamental data for the "The Development of Sound-Absorbing Block on Concrete Track" promoted on The National R&D Project.

• 산업경영시스템학회지
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• 제43권4호
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• pp.59-66
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• 2020

In this study, we consider the problem of forecasting the number of inbound foreigners visiting Korea. Forecasting tourism demand is an essential decision to plan related facilities and staffs, thus many studies have been carried out, mainly focusing on the number of inbound or outbound tourists. In order to forecast tourism demand, we use a seasonal ARIMA (SARIMA) model, as well as a SARIMAX model which additionally comprises an exogenous variable affecting the dependent variable, i.e., tourism demand. For constructing the forecasting model, we use a search procedure that can be used to determine the values of the orders of the SARIMA and SARIMAX. For the exogenous variable, we introduce factors that could cause the tourism demand reduction, such as the 9/11 attack, the SARS and MERS epidemic, and the deployment of THAAD. In this study, we propose a procedure, called Measuring Impact on Demand (MID), where the impact of each factor on tourism demand is measured and the value of the exogenous variable corresponding to the factor is determined based on the measurement. To show the performance of the proposed forecasting method, an empirical analysis was conducted where the monthly number of foreign visitors in 2019 were forecasted. It was shown that the proposed method can find more accurate forecasts than other benchmarks in terms of the mean absolute percentage error (MAPE).

• The Journal of Asian Finance, Economics and Business
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• 제8권1호
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• pp.431-442
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• 2021

The purpose of this study is to identify the effect of seasonality on the tourism and hospitality industry in ArugamBay after the civil unrest across the different firms in tourism. This study uses both quantitative and qualitative analyses using primary data. Fifty questionnaires give valid responses that were used for analysis. Out of 80 questionnaires, the average response rate was 62.5%. An exploratory study, descriptive analysis, and an Independent Sample Test were used to identify the potentials of tourism, the overall impact of seasonality, and the impact of seasonality across different travel and tourism sector of the study area. According to the results, 83%, 75%, 68%, and 59.9% of firms agreed on the impact of seasonality on environment, workers, supply, and quality of services, respectively in ArugamBay. It also concluded that the impact of seasonality on workers, supply, and quality of services is not the same among all the categories of firms except environment. The variation in seasonality in the travel and tourism sector is because of the lack of regional planning considering the types of firms in the tourism sector. Also, insufficient resources and lack of consistent capacity between various firms in the sectors are also course variations because of the effect of seasonality.

• 한국컴퓨터정보학회논문지
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• 제27권8호
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• pp.219-224
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• 2022

한국 기상청은 '생활산업 기상정보서비스'나 '위기탈출 안전날씨'와 같은 일상에 관련된 정보를 제공하고 있다. 한편, 해외에서는 독일의 '신체기상정보', 영국의 '건강 기상정보'와 같이 인간의 신체와 감성에 영향을 미치는 기상정보 역시 제공하고 있다. 비록 인간의 감성 변화가 심리학 연구 영역에서 다양하고 방대하게 이루어져 왔지만, 빅 데이터 분석 기반에 근거한 기상정보에 따른 인간의 감성 예측모형은 요원한 상태이다. 이 연구에서는 기상요소에 따른 인간의 감성변화를 예측할 수 있는 모형을 기상청의 기상 데이터셋과 SNS상 크롤링된 일자별 텍스트를 통해 개발하고 검증하고자 한다. 연구 결과 기상 요소들로 인간의 감성변화를 예측할 수 있는 모형을 만들고 검증할 수 있었으며 이는 기존 연구와 그 결을 같이한다고 볼 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권4호
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• pp.1162-1181
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• 2023

Tourism flow is not only the manifestation of tourists' special displacement change, but also an important driving mode of regional connection. It has been considered as one of significantly topics in many applications. The existing research on tourism flow prediction based on tourist number or statistical model is not in-depth enough or ignores the nonlinearity and complexity of tourism flow. In this paper, taking Nanjing as an example, we propose a prediction method of urban tourism flow based on deep learning methods using travel diaries of domestic tourists. Our proposed method can extract the spatio-temporal dependence relationship of tourism flow and further forecast the tourism flow to attractions for every day of the year or for every time period of the day. Experimental results show that our proposed method is slightly better than other benchmark models in terms of prediction accuracy, especially in predicting seasonal trends. The proposed method has practical significance in preventing tourists unnecessary crowding and saving a lot of queuing time.

• 한국식생활문화학회지
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• 제24권1호
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• pp.23-32
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• 2009

This study was conducted to generate fundamental data required by food coordinators and food space creators for planning and directing table settings. The results of this study were then used to suggest an ideal model of table settings for Korean-style food equipped with simple, sophisticated, and practical characteristics. Specifically, this study evaluated the importance of hygiene (safety, cleanness, arrangement), decoration (dignity, form, stylishness, presentation of food on plates), naturalness (seasonal beauty, comfortableness, natural beauty), and modernity (modern style, chic style, urban style). These factors were evaluated according to the preference of the table setting and the characteristics of the meeting, which fit various meal cultures, times, places, and objectives. The results of this study indicate that people prefer hygiene and decoration for family meetings (bansang setting), hygiene and modernity for friendly meetings (simple buffet setting), hygiene and decoration for company meetings (simple buffet setting), and hygiene and decoration for academic meetings (tea party). Hygiene and decoration were highly evaluated in most cases, which indicates that individuals at meetings for special purposes give weight to the meeting's atmosphere, but also consider the hygiene and cleanliness of the food.

• Asian Journal of Business Environment
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• 제14권3호
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• pp.1-11
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• 2024

Purpose: This study analyzes the impact of weather conditions, holidays, and sporting events on beer sales, providing insights for market strategy and inventory management in the beer industry. Research design, data and methodology: Beer types were classified into Lagers and Ales, with further subcategories. The study utilized weekly retail sales data from January 2018 to August 2020, provided by Nielsen Korea. An ARMAX model was employed for time-series analysis. Results: The analysis revealed that increasing temperatures positively influence sales of Pilsners and Pale Lagers. Conversely, higher precipitation levels negatively affect overall Lager sales. Among Ales, only Stout sales showed a significant decrease with increased rainfall. Sunshine duration did not significantly impact sales for any beer type. Humidity generally had little effect on beer sales, with the exception of Amber Lagers, which showed sensitivity to humidity changes. Holidays and sporting events were found to significantly boost sales across most beer types, although the specific impacts varied by beer category. Conclusions: This study offers a detailed analysis of how weather conditions and specific events influence different beer type sales. The findings provide valuable insights for breweries, beer processors, and retailers to optimize their market strategies and inventory management based on weather forecasts and seasonal events. By understanding the consumption patterns of each beer type in relation to environmental factors, businesses can better anticipate demand fluctuations and tailor their operations accordingly.