• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.3
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• pp.92-101
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• 2012

Trip demands and patterns on weekends have been changed significantly over the past decade due to the income growth and the spread of the 5-day workweek in Korea. The increased weekend trips for shopping, leisure activities, entertainment and friendship have exacerbated traffic congestion in major highways or principal arterial roads from Friday afternoon through Sunday. Therefore, it is necessary to focus on travel demand forecasts and transport policies for weekend trips by investigating specific characteristics of the trips. Previous research efforts focus on simple analysis of characteristics of weekend trips and comparison of travel characteristics between weekdays and weekends. The paper analyzes the differences between weekday and weekend trips via statistical analyses to derive multiple types of characteristics of weekend trips, and develops Tobit models to identify key factors that may affect the number of trips, using Seoul city's weekend trip survey data in 2006. The model results show that weekend trips appear differently from weekdays by household or individual characteristics. Age, residence area and type of residence affected the number of trips, regardless of the type of the day, whereas gender, occupation, income, presence of household vehicle showed different impacts on trips between weekdays and weekends.

• Management & Information Systems Review
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• v.19
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• pp.49-81
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• 2006

The private college education plays a crucial role both in training and supplying manpower needed for national economic growth and in increasing employability and personal labor earnings of individual workers. In oder for private college education to effectively respond to the rapid changes in industrial and occupational structures, it is necessary to secure appropriate level of investment funds and manage them efficiently. For this, it is required to discuss the structure, magnitude and management mechanism of the current private college education finance, changes in future demand for private college education and resultant changes in budget estimates, and new financial resources and allocation schemes. This study attempted to analyze current status and problems of private college education finance in Korea and, based on this analysis, to suggest future policy directions to improve private college education finance system. In order to make the private college education system in Korea competent and competitive enough to survive in international market, it is prerequisite to provide enough budget for the private college education and to manage the private college education finance in more efficient ways. First, for securing the adequacy and stability of investment budget for the private college education, it is recommended to 1) increase the government budget and put emphasis on the private college education; 2) diversify financial resources and induce financial contribution from private sector such as school juridical persons and enterprises. Second, for higher efficiency of financial management, it is recommended 1) make valid allocation standards and mechanism; 2) introduce competition system; 3) develop and utilize evaluation mechanism for the private college education finance to check adequacy, efficiency, accountability, and effectiveness; 4) apply consumer-oriented financial management scheme. In addition to the above policy measures, it is necessary to 1) make scientific forecasts of industrial and occupational structures periodically and apply these analyses to medium & long-term the private college education planning; and 2) redesign budget accounting system and develop the private college education performance indicators for the evaluation of accountability of the private college education institutions and administration institutes.

• STI Policy Review
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• v.1 no.1
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• pp.1-21
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• 2010

To achieve the "low carbon green growth" vision, the first step is securing core technologies. Therefore, S&T policy direction for green technology development is urgently needed. As of 2008, investment in green technology (GT) development hovered around 10% of the government's total R&D budget. Thus, the Korean government developed a plan to increase that percentage to 15%, by 2013. To develop reasonable investment strategies for green technology development, targeted strategies that reflect technology and market changes by green technology area are needed. However, the overall planning and coordination of national GT development is currently split among, approximately, 10 government ministries. To establish an efficient green technology development system, the so-called "Green Technology R&D Council" should be launched in collaboration with the Presidential Committee on Green Growth and the National Science and Technology Council. Furthermore, to build a solid foundation for commercializing the outcomes of GT development projects and promote GT transfer, the government should undertake two initiatives. First, the government should reinforce GT R&D performance management, by establishing a GT R&D performance management and evaluation system. Second, the government should implement the "customized packaged support for promoting green technology business rights and commercialization" and present "e-marketplace for market-oriented green technologies". Creating a pan-ministerial policy for GT development policy would necessitate restructuring the HR(Human Resources) development system, which is currently separated by technology area. Based upon mid/long-term HR supply and demand forecasts, the government should design differentiated HR development projects, continuously evaluate those projects, and reflect the evaluation results in future policy development. Finally, to create new GT-related industries, the "Green TCS (Testing, Certification, and Standards) System" needs to be implemented. For objective evaluation and diffusion of R&D results by green technology area, a common standardization plan for testing, analysis, and measurement, like the "Green TCS", should be developed and integrated.

• Journal of Korea Water Resources Association
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• v.52 no.8
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• pp.565-573
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• 2019

An optimization model of water intake planning is developed based on a linear programming (LP) for the intelligent water purification plant operation system. The proposed optimization model minimizes the water treatment costs of raw water purification by considering a time-delay of treatment process and hourly electricity tariff, which is subject to various operation constraints, such as water intake limit, storage tank capacity, and water demand forecasts. For demonstration, the developed model is applied to H water purification center. Here, we have tested three optimization strategies and the results are compared and analyzed in economic and safety aspects. The optimization model is expected to be used as a decision support tool for optimal water intake scheduling of domestic water purification centers.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.243-243
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• 2015

Low-flow simulation and forecasting is one of the emerging issues in hydrology due to the increasing demand of water in dry periods. Even though low-flow simulation and forecasting remains a difficult issue for hydrologists better simulation and earlier prediction of low flows are crucial for efficient water management. The UN has never stated that South Korea is in a water shortage. However, a recent study by MOLIT indicates that Korea will probably lack water by 4.3 billion m3 in 2020 due to several factors, including land cover and climate change impacts. The two main situations that generate low-flow events are an extended dry period (summer low-flow) and an extended period of low temperature (winter low-flow). This situation demands the hydrologists to concentrate more on low-flow hydrology. Korea's annual average precipitation is about 127.6 billion m3 where runoff into rivers and losses accounts 57% and 43% respectively and from 57% runoff discharge to the ocean is accounts 31% and total water use is about 26%. So, saving 6% of the runoff will solve the water shortage problem mentioned above. The main objective of this study is to present the hydrological modelling approach for low-flow simulation and forecasting using a model that have a capacity to represent the real hydrological behavior of the catchment and to address the water management of summer as well as winter low-flow. Two lumped hydrological models (GR4J and CAT) will be applied to calibrate and simulate the streamflow. The models will be applied to Seolmacheon catchment using daily streamflow data at Jeonjeokbigyo station, and the Nash-Sutcliffe efficiencies will be calculated to check the model performance. The expected result will be summarized in a different ways so as to provide decision makers with the probabilistic forecasts and the associated risks of low flows. Finally, the results will be presented and the capacity of the models to provide useful information for efficient water management practice will be discussed.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.9-13
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• 2023

In this study, we explored the potential of integrating interactive AI callbot technology into the medical consultation domain as part of a broader service development initiative. Aimed at enhancing patient satisfaction, the AI callbot was designed to efficiently address queries from hospitals' primary users, especially the elderly and those using phone services. By incorporating an AI-driven callbot into the hospital's customer service center, routine tasks such as appointment modifications and cancellations were efficiently managed by the AI Callbot Agent. On the other hand, tasks requiring more detailed attention or specialization were addressed by Human Agents, ensuring a balanced and collaborative approach. The deep learning model for voice recognition for this study was based on the Transformer model and fine-tuned to fit the medical field using a pre-trained model. Existing recording files were converted into learning data to perform SSL(self-supervised learning) Model was implemented. The ANN (Artificial neural network) neural network model was used to analyze voice signals and interpret them as text, and after actual application, the intent was enriched through reinforcement learning to continuously improve accuracy. In the case of TTS(Text To Speech), the Transformer model was applied to Text Analysis, Acoustic model, and Vocoder, and Google's Natural Language API was applied to recognize intent. As the research progresses, there are challenges to solve, such as interconnection issues between various EMR providers, problems with doctor's time slots, problems with two or more hospital appointments, and problems with patient use. However, there are specialized problems that are easy to make reservations. Implementation of the callbot service in hospitals appears to be applicable immediately.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.451-456
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• 2024

This study aims to diagnose the military manpower shortage problem caused by the rapid decline in fertility and aging population in South Korea and explore countermeasures. To this end, it analyzes the trends of demographic changes and military manpower supply and demand forecasts in Korea, and evaluates major alternatives such as expanding female soldiers, introducing a voluntary recruitment system, and adopting advanced weapons. It also seeks to derive implications through case studies of military manpower policies in major countries such as the United States, Japan, and Germany. The results show that in order to secure sustainable manpower for the Korean military, it is necessary to increase the proportion of female soldiers, review the voluntary recruitment system from a long-term perspective, minimize the power gap due to troop reduction, strengthen incentives for skilled manpower, and draw social consensus on improving the military service system and defense reform. This study is expected to contribute to the establishment of future military manpower policies in Korea.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.4
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• pp.73-85
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• 2014

Approaching to aging society with increasing transportation vulnerable, most developed countries has positively promote low-floor bus. Such circumstance in Korea has plan to introduce low-floor bus to intra-city bus system which accounted for 30 percent of total number of buses however there is no specific operating plan for this matter. According to the revealed preference study on bus service, the study shows that the efficiency of low-floor is relatively low than that of other buses, therefore, it is necessary to establish feasible plan for bus route selection. Thus, this study is to conduct research on analyzing trip characteristics of transportation vulnerable and establish bus route selection measures for low-floor bus. The result from the survey in Jeollabuk-do Province reveals that the trip purpose of transportation vulnerable is mainly for welfare and medical service, which was made less than 6 times a week. Futhermore, 37.6 percent of transportation vulnerable use buses, thus, it is essential to improve its service quality for enhancing user's convenience and safety. In that transportation vulnerable O-D needs to be established and forecasts future demand for selecting optimal bus route. According to the estimation, route passing through densely populated areas with transportation vulnerable should take the first priority, city circular and other route would be next. Moreover, it is economically efficient that areas populated more than 200,000 with fixed route and less than 200,000 with limited route responsive to demands would be feasible plans. This study will have greater an impact on transportation planning and further research on transportation vulnerable.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.96-110
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• 2018

As the development of ICT has made it easier to collect various traffic information, research on creating new traffic attributes is drawing attention. Estimation and forecasts of demand and traffic volume are one of the main indicators that are essential to traffic operation, assuming that the traffic pattern at a particular node or link is repeated. Traditionally, a survey method was used to demonstrate this similarity on trip behavior. However, the method was limited to achieving high accuracy with high costs and responses that relied on the respondents' memory. Recently, as traffic data has become easier to gather through ETC system, smart card, studies are performed to identify the regularity of trip in various ways. In, this study, route-level trip data collected in Daegu metropolitan city were analyzed to confirm that individual traveler forms a spatially similar trip chain over several days. For this purpose, we newly define the concept of spatial trip regularity and assess the spatial difference between daily trip chains using the sequence alignment algorithm, Dynamic Time Warping. In addition, we will discuss the applications as the indicators of fixed traffic demand and transportation services.

• The Journal of Bigdata
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• v.8 no.2
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• pp.189-200
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• 2023

At the beginning of the COVID-19 pandemic, Korea's wine market had shrunk as other countries. However, right after the pandemic, Korea's imported wine consumption had been increased 69.6%. Because of the ban on overseas travel, wine was consumed in the domestic market. And consumption of high-end wines were increased significantly due to revenge spending and home drinking. However, from 2022 Korea's wine market has begun to shrink sharply again. Therefore this study forecasts the size of imported wine market by 2032 to provide useful information to wine related business entities. KITA(Korea International Trade Association)'s 95 time-series data per quarter from Q1 of 2001 to Q3 of 2023 was utilized in this research. The accuracy of model was tested based on value of MAPE. And ARIMA model was chosen to forecast the size of market value and Winter's multiplicative model was used for the size of market volume. The result of ARIMA model for the value (MAPE=10.56%) shows that the size of market value in 2032 will be increased up to USD $1,023,619, CAGR=6.22% which is 101% bigger than its size of 2023. On the other hand, the volume of imported wine market (MAPE=10.56%) will be increased up to 64,691,329 tons, CAGR=-0.61% which is only 15.12% bigger than its size of 2023. The result implies that the value of Korea's wine market will continue to grow despite the recent decline. And the high-end wine market will account for most of the increase.