• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.407-407
• /
• 2019

According to Asian Development Bank report Pakistan is among water scarce countries. Climate scenario on the basis IPCC fifth assessment report (AR5) revealed that annual mean temperature of Pakistan from year 2010-2019 was $17C^o$ which will rise up to $21C^o$ at the end of this century, similarly almost 10% decrease of annual rainfall is expected at the end of the century. It is a changing task in underdeveloped countries like Pakistan to meet the water demands of rapidly increasing population in a changing climate. While many studies have tackled scarcity and stream flow forecasting of the Upper Indus Basin (UIB) Pakistan, very few of them are related to socio-economic and climate change impact on sustainable water management of UIB. This study investigates the pattern of current and future surface water availability for various demand sites (e.g. domestic, agriculture and industrial) under different socio-economic and climate change scenarios in Upper Indus Basin (UIB) Pakistan for a period of 2010 to 2050. A state-of-the-art planning tool Water Evaluation and Planning (WEAP) is used to analyze the dynamics of current and future water demand. The stream flow data of five sub catchment (Astore, Gilgit, Hunza, Shigar and Shoyke) and entire UIB were calibrated and validated for the year of 2006 to 2011 using WEAP. The Nash Sutcliffe coefficient and coefficient of determination is achieved ranging from 0.63 to 0.92. The results indicate that unmet water demand is likely to increase severe threshold and the external driving forces e.g. socio-economic and climate change will create a gap between supply and demand of water.

• Journal of IKEEE
• /
• v.23 no.1
• /
• pp.134-142
• /
• 2019

As the development of internet of energy (IoE) technologies and spread of various electronic devices have diversified patterns of energy consumption, the reliability of demand prediction has decreased, causing problems in optimization of power generation and stabilization of power supply. In this study, we propose a deep learning method, 1-Dimention-Convolution and Bidirectional Long Short-Term Memory (1D-ConvBLSTM), that combines a convolution neural network (CNN) and a Bidirectional Long Short-Term Memory(BLSTM) for highly reliable demand forecasting by effectively extracting the energy consumption pattern. In experimental results, the demand is predicted with the proposed deep learning method for various number of learning iterations and feature maps, and it is verified that the test data is predicted with a small number of iterations.

• The Journal of Fisheries Business Administration
• /
• v.41 no.1
• /
• pp.25-52
• /
• 2010

The purpose of this paper is to suggest major strategies and necessary new projects for the medium- and long-term development of the Korean Fisheries Outlook Project. To suggest the Korean Fisheries Outlook Center with the above purpose, this paper employs Analytic Hierarchy Process analysis based on surveys obtained by special groups related with the KFOP. The survey is broadly composed of two goals; the medium- and long-term development directions and setting up of new furtherance projects. Each goal has upper and lower strategies respectively. The first goal, the medium- and long-term development directions, has four factors as upper strategies. The upper strategies are composed of accuracy, efficiency, timeliness, and political effectiveness of the fisheries outlook information. In addition, each upper strategy has three lower strategies respectively. For example, accuracy of the fisheries outlook information includes strength of data collection function, strength of satellite photography function, and strength of data analysis function. The second goal, setting up of new furtherance projects, has three factors as upper strategies. The upper strategies consist of accuracy promotion of outlook information using high-technique, field expansion of outlook species, and strength of analyzing function on oversea fisheries information. Each upper strategy has three lower strategies respectively. For instant, accuracy promotion of outlook information using high-technique has strength of information analysis function covered from production to consumption, strength of satellite information function, and structure of forecasting model on demand and supply by outlook species. The above upper and lower strategies were analytically drawn out through insightful interviews with special groups such as officials of the government, presidents of the producer and distributor groups, and researchers of the Korea Maritime Institute and other research institutes. As a result of AHP analysis, first, priorities of upper strategies with the medium- and long-term development directions are analyzed as accuracy, timeliness, political effectiveness, and efficiency in order. Also, priorities of all lower strategies reflecting priorities of upper strategies are examined as includes strength of data collection function on the fisheries outlook information, delivery of rapid information on outlook products for all people interested, strength of data analysis function on fisheries outlook information, strength of consumption outlook function on fish products, and strength of early warning system for domestic fish products in order. Second, priorities of upper strategies with the setting up of new furtherance projects are analyzed as accuracy promotion of outlook information using high-technique, field expansion of outlook species, and strength of analysis function on oversea fisheries information in order. In addition, priorities of all lower strategies reflecting priorities of upper strategies are examined as building up of forecasting model on demand and supply by outlook species, strength of information analysis function covering all steps from production to consumption, expansion of consumption outlook for consumers, strength of movement analysis function of oversea farming industry, and outlook expansion of farming species.

• Journal of Energy Engineering
• /
• v.28 no.4
• /
• pp.82-93
• /
• 2019

In this study, a new model is proposed to improve the problem of the decline of predict rate of heat demand on a particular date, such as a public holiday for the conventional heat demand forecasting system. The proposed model was the Four Season Mixed Heat Demand Prediction Neural Network Model, which showed an increase in the forecast rate of heat demand, especially for each type of forecast date (weekday/weekend/holiday). The proposed model was selected through the following process. A model with an even error for each type of forecast date in a particular season is selected to form the entire forecast model. To avoid shortening learning time and excessive learning, after each of the four different models that were structurally simplified were learning and a model that showed optimal prediction error was selected through various combinations. The output of the model is the hourly 24-hour heat demand at the forecast date and the total is the daily total heat demand. These forecasts enable efficient heat supply planning and allow the selection and utilization of output values according to their purpose. For daily heat demand forecasts for the proposed model, the overall MAPE improved from 5.3~6.1% for individual models to 5.2% and the forecast for holiday heat demand greatly improved from 4.9~7.9% to 2.9%. The data in this study utilized 34 months of heat demand data from a specific apartment complex provided by the Korea District Heating Corp. (January 2015 to October 2017).

• Journal of Korean Society of Transportation
• /
• v.22 no.7 s.78
• /
• pp.7-16
• /
• 2004

The homogeneous road section is defined as one consisted of similar traffic characteristics focused on demand and supply. The criteria, in the aspect of demand, are the diverging rate and the ratio of green time to cycle time at signalized intersection, and distance between the signalized intersections. The criteria, in that or supply, are the traffic patterns such as traffic volume and its speed. In this study, the effective method to generate valuable data, pointing out the problems of removal method of obscure data, is proposed using data collected from Gonjiam IC to Jangji IC on the national highway No.3. Travel times are collected with licence matching method and traffic volume and speed are collected from detectors. Futhermore, the method of selecting homogeneous road section is proposed considering demand and supply aspect simultaneously. This method using outlier filtering algorithm can be applied to generate the travel time forecasting model and to revise the obscured of missing data transmitting from detectors. The point and link data collected at the same time on the rational highway can be used as a basis predicting the travel time and revising the obscured data in the future.

• International journal of advanced smart convergence
• /
• v.12 no.1
• /
• pp.193-198
• /
• 2023

The rapid aging of the veterans has reached a level that cannot handle the demand for veterans care through the existing veterans care infrastructure. Therefore, it is urgent to improve the quality of the overall service of veterans due to the deterioration of the quality of nursing services for veterans with various underlying diseases compared to general patients and the long-term waiting for admission to the veterans care center. In this situation, about 640,000 people are admitted to veterans care institutions, but only about 5% of them can enter the veterans care center smoothly. As of June 2020, the number of people waiting to enter the veterans care center exceeds 1,000, including 520 at Suwon Veterans Nursing Home, 1 at Gwangju Veterans Nursing Home, 47 at Gimhae Veterans Nursing Home, 39 at Daegu Veterans Nursing Home, 86 at Namyangju Veterans Nursing Home.. Therefore, in order to predict those who want to enter the Veterans Nursing Home and wait for admission, and to find an important basis for resolving the long-term atmosphere, the ratio of future care providers is predicted in 2022-2050 and 2022-2024 to establish a cooperative system. As a result, 6,988 people in 2022, 6,797 people in 2023, and 6,606 people in 2024 can be admitted when 'preferred linkage', and 12,057 people in 2022 when 'expanded linkage'. It was found that 11,837 people in 2023 and 11,618 people in 2024 could be admitted. This was derived by estimating the percentage of people who wish to enter the Veterans Nursing Home when linking private nursing homes, and eventually "additional acceptance" of 22.5% in 2022, 20.9% in 2023, 19.4% in 2024, and 38.8% in 2023, 36.3% in 2023, and 34.1% in 2024 are most efficiently available.

• Health Policy and Management
• /
• v.34 no.2
• /
• pp.120-128
• /
• 2024

From February to now 2024, there continues to be controversy over the expansion of admission number to medical school. Some of the controversy arises from a mix of present and future time points. In the present time point, the controversy over whether physicians are some shortages or not has various aspects. Some aspects are presented as evidence of the physician shortage and others as non-shortage. Also, the presenting evidence of shortage is being disputed, and so is the evidence of the contrary. This controversy over whether there is a shortage or not in the present time point makes it difficult to reach a consensus. In 10 years, the shortage of doctors will increase due to the rapid increase in the elderly population, so the admission number of medical schools will need to be increased. However, the increase must be such that there is minimal deterioration in the quality of medical education. More admission numbers should be allocated to medical schools with a high quality of medical education. This study suggests that large-scale medical schools increase the admission number by 20%-30%, and small-scale medical schools increase the admission number by 40%-50%, if so, the total increasing number is 760 to 1,066. If the 2,000-person increase is enforced, the quality of medical education must be carefully evaluated and the results should be reflected in adjusting the admission number of medical schools. In 20 years later, the admission number of medical schools will have to be reduced. This is because the physician supply is changing to a linear function and the physician demand (medical care demand) is changing to a quadratic function. Even if the current number is maintained, there will be an excess of doctors from 2048, so the medical school admission number must be reduced and its size will be reduced to about 2,000, a 30% reduction from the current number. Because the same reduction rate for all medical schools will result in many small-scale medical schools, the M&A (mergers and acquisitions) strategy should be considered with 40 medical schools and 12 Korean medical schools. In Korea, the main contributor to estimating physician demand is the change in population structure. Due to the rapid decrease in the total fertility rate, future population projections are uncertain. The recent rapid increase in healthcare utilization should be reexamined in the forecasting of physician demand. Since the various factors that affect the estimate of doctor supply and demand are unclear, the estimate of physician supply and demand must be continuously conducted every five years, and the Health Care Workforce Committee must be established and operated. The effects of increasing the admission number of medical schools should be evaluated and adjusted annually.

• The KIPS Transactions:PartD
• /
• v.10D no.1
• /
• pp.161-166
• /
• 2003

Information lead time is defined as the time spent by processing orders from some buyers, whereas order lead time is defined as producing and supplying the products. The information lead time significantly serve to magnify the increase in variability due to demand forecasting. This paper models a decentralized supply chain composed of cascade type which has four type phases (or divisions) such as retailer, wholesaler, distributor, and factory. Each phases is managed by different centers individually with their own local inventory information. We investigate whether each phase's Information lead time affects companies networked a value chain. In particular, on several experiments performed with a programmed simulation (like a MIT beer game), we study the following question ; Can information lead times do better than material lead times in cost-benefit perspective\ulcorner Can more much Information lead times in downstream reasonably do worser than in upstream when playing the simulation\ulcorner In the conclusion, we show the importance of information lead time on a SC and, besides, guarantee that improvement of information lead time in upstream do more effective than one in downstream in cost-benefit perspective.

• Journal of Korea Port Economic Association
• /
• v.33 no.1
• /
• pp.75-87
• /
• 2017

The purpose of this study is to utilize the system dynamics to carry out a medium and long-term forecasting analysis of the bunker price. In order to secure accurate bunker price forecast, a quantitative analysis was established based on the casual loop diagram between various variables that affects bunker price. Based on various configuration variables such as crude oil price which affects crude oil consumption & production, GDP and exchange rate which influences economic changes and freight rate which is decided by supply and demand in shipping and logistic market were used in accordance with System Dynamics to forecast bunker price and then objectivity was verified through MAPEs. Based on the result of this study, bunker price is expected to rise until 2029 compared to 2016 but it will not be near the surge sighted in 2012. This study holds value in two ways. First, it supports shipping companies to efficiently manage its fleet, offering comprehensive bunker price risk management by presenting structural relationship between various variables affecting bunker price. Second, rational result derived from bunker price forecast by utilizing dynamic casual loop between various variables.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.25 no.7
• /
• pp.819-826
• /
• 2019

To accurately forecast the supply and demand of harbor pilots, it is necessary to derive the determinants of demand because they are directly linked to securing the safety of ships and ports. The securing of an appropriate numbers of harbor pilots can create conflicts of interest among the pilots, the Ministry of Oceans and Fisheries, and users of pilotage services as it is also a matter directly related to harbor pilots' income. Therefore, a measure is needed to ensure a suitable number of pilots can be maintained, through which high quality pilotage services can be provided. This can be achieved by deriving reasonable determinants for estimating and forecasting demand, which satisfy all stakeholders involved in pilotage service. To reveal the challenges posed by the current determinants regarding the demand for harbor pilots used by the Central Pilotage Operation Council, and arrive at solutions, this study derived three determining factors, namely the total annual average piloting time, the average working hours of pilots, and the current number of pilots. These were used to determine the demand for harbor pilots. This study used a survey and analysis of current determining factors, a questionnaire survey administered to the interested parties, a case study of selected countries, and so on, as the research methodology.