• 한국항해항만학회지
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• 제46권5호
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• pp.449-457
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• 2022

The Port of Busan is currently ranked as the seventh largest container port worldwide in terms of cargo throughput. However, port competition in the Far-East region is fierce. The growth rate of container throughput handled by the port of Busan has recently slowed down. In this study, we analyzed how economic conditions and multiple external shocks could influence cargo throughput and identified potential implications for port business. The aim of this study was to build a model to accurately forecast port throughput using the ARIMA model, which could incorporate external socio-economic shocks, and the VEC model considering causal variables having long-term effects on transshipment cargo. Findings of this study suggest that there are three main areas affecting container throughput in the port of Busan, namely the Russia-Ukraine war, the increased competition for transshipment cargo of Chinese ports, and the weaker growth rate of the Korean economy. Based on the forecast, in order for the Port of the Port of Busan to continue to grow as a logistics hub in Northeast-Asia, policy intervention is necessary to diversify the demand for transshipment cargo and maximize benefits of planned infrastructural investments.

• The Journal of Asian Finance, Economics and Business
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• 제9권8호
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• pp.7-17
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• 2022

The article discusses the problems caused by inflation in the developing Asia-Pacific region during the time of the worldwide pandemic and suggests innovative solutions to the problem. The reality is that some of the commodity groups from the consumer basket (e.g., non-seasonal fruits, electronics, furniture, hotel, and restaurant services, etc.) fail to reflect the needs of the low-income earners, which make the majority in developing countries. At the same time, the inflation targeting regime has become outdated and not reliable, because of uncontrolled exogenic factors (imported inflation, fluctuation in oil prices, supply chain disruption, Russia-Ukraine war, etc.) prevailing on endogenic factors and thus making it impossible to control the price stability, especially in developing countries. Since, the old-fashioned inflation index and inflation targeting mechanisms regrettably fail to fully reflect both the society and governmental/central banks' expectations, based on which we first should have better care and second create better policies; we propose to use a combination of already well-known indexes and policies, with the new statistical indicators, which reflects price fluctuations on the medication, utilities, and nutrition.

• 한국조리학회지
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• 제8권3호
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• pp.1-20
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• 2002

The rapidly changing environments of today's hospitality industry lays more and more emphasis on the management of food & beverage sector. Hotel restaurants changes their menus 2 times a year. But they tend to modify or complement old items, or imitate other restaurants'menus, rather than try new ones. In addition, the change cycles are determined without any systematic and scientific criteria. Based on the survey, a plan for managing menu change cycles is proposed. The proposed plan is summarized as follows: First, the survey result demonstrates that the appropriate frequency of menu changes is: twice a year for the fixed menu; four times for the seasonal menu; four times for the promotion menu; twice for the business menu; and, three times for the event menu. Second, under the management maintained by consistent monitoring of menu change. Third, menu change should be managed through the menu analyses on its profitability, popularity, and the potential for further growth. Fourth, menu change should be managed through the periodic investigations of the tastes and preferences of the customers. fifth, a unique system for the menu change should be constructed by analyzing of other competitive restaurants or restaurant chain stores.

• 한국멀티미디어학회논문지
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• 제18권6호
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• pp.772-779
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• 2015

Advancing information technology have rapidly changed our service environment of life, culture, and industry. Computer information communication system is applied in medical, health, distribution, and business transaction. Smart is using new information by combining ability of computer and information. Although agriculture is labor intensive industry that requires a lot of hands, agriculture is becoming knowledge-based industry today. In agriculture field, computer communication system is applied on facilities farming and machinery Agricultural. In this paper, we designed and implemented application that provides personalized agriculture related information at the actual farming field. Also, this provides farmer a system that they can directly auction or sell their produced crops. We designed and implemented a system that parsing information of each seasonal, weather condition, market price, region based, crop, and disease and insects through individual setup on ubiquitous environment using location-based sensor network and processing data.

• 신재생에너지
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• 제4권4호
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• pp.23-29
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• 2008

Wind farm development project contains high business risks because that a wind farm, which is to be operating for 20 years, has to be designed and assessed only relying on a year or little more in-situ wind data. Accordingly, long-term correction of short-term measurement data is one of most important process in wind resource assessment for project feasibility investigation. This paper shows comparison of general Measure-Correlate-Prediction models and neural network, and presents new method using neural network for increasing prediction accuracy by accommodating multiple reference data. The proposed method would be interim step to complete long-term correction methodology for Korea, complicated Monsoon country where seasonal and diurnal variation of local meteorology is very wide.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권1호
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• pp.331-343
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• 2015

We propose a distributed medium access control protocol for cognitive radio networks to opportunistically utilize multiple channels. Under the proposed protocol, cognitive radio nodes forecast and rank channel availability observing primary users' activities on the channels for a period of time by time series analyzing using smoothing models for seasonal data by Winters' method. The proposed approach protects primary users, mitigates channel access delay, and increases network performance. We analyze the optimal time to sense channels to avoid conflict with the primary users. We simulate and compare the proposed protocol with the existing protocol. The results show that the proposed approach utilizes channels more efficiently.

• Industrial Engineering and Management Systems
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• 제14권2호
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• pp.196-209
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• 2015

Retail sales forecast is a special area of forecasting. Its unique characteristics call for unique data models and treatment, and unique forecasting processes. In this paper, we will address lessons learned and challenges encountered in retail sales forecast from a practical and technical perspective. In particular, starting with the data models of retail sales data, we proceed to address issues existing in estimating and processing each component in the data model. We will discuss how to estimate the multi-seasonal cycles in retail sales data, and the limitations of the existing methodologies. In addition, we will talk about the distinction between business events and forecast events, the methodologies used in event detection and event effect estimation, and the difficulties in compound event detection and effect estimation. For each of the issues and challenges, we will present our solution strategy. Some of the solution strategies can be generalized and could be helpful in solving similar forecast problems in different areas.

• Quantitative Bio-Science
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• 제37권2호
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• pp.91-101
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• 2018

This study has analyzed applicable characteristics on big data of the meteorology and climate depending on press releases in the media. As a result, more than half of them were conducted by governmental departments and institutions (26.9%) and meteorological administration (25.0%). Most articles were written by journalists, especially the highest portion stems from straight articles focusing on delivering simple information. For each field, the number of cases had listed in order of rank to be exposed to the media; information service, business management, farming, livestock, and fishing industries, and disaster management, but others did rank far behind; insurance, construction, hydrology and energy. Application of big data about meteorology and climate differed depending on the seasonal change, it was directly related to temperature information during spring, to weather phenomenon such as monsoon and heat wave during summer, to meteorology and climate information during fall, and to weather phenomenon such as cold wave and heavy snow during winter.

• Communications for Statistical Applications and Methods
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• 제29권3호
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• pp.353-371
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• 2022

This paper analyzes death counts after World War II of several countries to identify and to compare their stochastic structures. The stochastic structures that this paper entertains are three structural time series models, a local level with a random walk model, a fixed local linear trend model and a local linear trend model. The structural time series models assume that a time series can be formulated directly with the unobserved components such as trend, slope, seasonal, cycle and daily effect. Random effect of each unobserved component is characterized by its own stochastic structure and a distribution of its irregular component. The structural time series models use the Kalman filter to estimate unknown parameters of a stochastic model, to predict future data, and to do filtering data. This paper identifies the best-fitted stochastic model for three types of death counts (Female, Male and Total) of each country. Two diagnostic procedures are used to check the validity of fitted models. Three criteria, AIC, BIC and SSPE are used to select the best-fitted valid stochastic model for each type of death counts of each country.

• 풍력에너지저널
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• 제4권2호
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• pp.34-39
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• 2013

The wind resource assessment for measured wind data over 1 year by using the meteorological mast should be a prerequisite for business feasibility of the wind farm development. Even though the direction of boom mounting the wind vane and anemometer is carefully engineered to escape the interference of wakes generated from the met-mast structures, the shadow effect is not completely avoided due to seasonal winds in the Korean Peninsula. The shadow effect should be properly calibrated because it is able to distort the wind resources. In this study a calibration method is introduced for the measured wind data at Julpo in Jeonbuk Province. Each sectoral terrain conditions along the selected wind direction nearby the met-mast is investigated, and the distorted wind data due to shadow effects can be calibrated effectively. The correction factor is adopted for quantitative calibration by carrying out the WindSim analysis.