• Journal of the Korean Society for Railway
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• v.12 no.2
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• pp.302-308
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• 2009

This paper presents a comprehensive analysis of intercity rail passengers' and travel patterns based on the 2001 Seoul-Busan rail passengers' Travel Survey. Results representing personal characteristics such as age and income seem to affect on destination the income was not seen to be a critical effect on destination choice. The variables such as travel time, transfer status, and date for travel seem to be and recreation activity. However, the destination choice would be relationship between Seoul and all four destination cities. The insights gained of an activity-based rail travel demand model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.719-727
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• 2013

Four-step travel-demand modeling based on a trip-level has been widely used over many decades. However, there has been a wide variance between forecasted- and real-travel demands, which leads less reliable on the model implications. A primary reason is that person's real travel behavior is not properly captured throughout the model developments. An activity-based modeling (ABM) approach was proposed and developed toward increasing the accuracy and reality of person's travel behavior in the U.S. since 1990', and stands as a good alternative to replace the existing trip-based approach. The paper contributes to the understanding of how the ABM approaches are dissimilar to the trip-based modeling approach in terms of estimation units, estimation process, their pros and cons and etc. We examined three activity-based travel demand model systems (DaySim, CT-Ramp, and CEMDAP) that are most commonly applied by many MPOs (Metropolitan Planning Organization). We found that the ABM approach can effectively explain multi-dimensional travel decision-makings and be expected to increase the predictive accuracy. Overall, the ABM approach can be a good substitute for the existing travel-demand methods having unreliable forecasts.

• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.544-553
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• 2014

Activity-based models analyze individuals' various daily activities that are identified as a decision-making unit for transportation planning. In other words, it is the model that determines the types of activities according to the social, economic and situational characteristics of the groups with the same activity patterns and predicts individuals' activity time, distance, spatial movement and transportation mode. The activity-based model is a method of estimating more efficient and realistic demand in transportation forecasting because traffic is regarded as a complex decision-making process that an individual and other people participate in. In this paper, we grasp the factors affecting choice behavior of activity pattern and analyze choice behavior of activity pattern based on multi-dimensional characteristic of each person. First, we classify activity types of reviewing the trip chain and activity purpose. Next, we identified preferable activity types using complicated characteristics of main agent of activity. We concluded that choice behavior of activity pattern is dependent on complex characteristics of each agent, and further multi-dimensional characteristics of each person are affected over the whole decision process of activity schedule.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.79-85
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• 2002

In this paper, multilevel models are adopted to identify interactions among household members in trip making behaviors. The multilevel approach is a proper methodology to handle samples, which are extracted from a hierarchical structure universe. PSTP dataset is used in developing models and understand proportion of variations among individuals and household. The results of this study show that for activity participation and travel behavior household level variance is more than 1/4 of person level variance and therefore not negligible. The results confirm the importance of multilevel model in travel behavior analysis.

• Journal of Korean Library and Information Science Society
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• v.34 no.4
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• pp.179-202
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• 2003

Reading is a typical representative knowledge and information activities. It is a put of the presents man and by itself Read-learning is the cognitive and social activities of the creating platonic world. However, in the education training of students become a visible problems of read-learning too many. To solve the problems have to pull off a systematical plan in read activities. This aims to purpose the model of the union reading contents management as the method for the read activity based on the problems analysis of read-learning activity. It is reading contents management as the model knowledge cresting processes.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.163-174
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• 2008

The conventional four-step travel demand model is still widely used as the state-of-practice in most transportation planning agencies even though it does not provide reliable estimates of travel demand. In order to improve the accuracy of travel demand estimation, implementing an alternative approach would be critical as much as acquiring reliable socioeconomic and travel data. Recently, the role of travel demand model is diverse to satisfy the needs of microscopic analysis regarding various policies of travel demand management and traffic operations. In this context, the activity-based approach for travel demand estimation is introduced and a case study of developing a spatial-temporal activity presence-based approach that estimates travel demand through forecasting number of people present at certain place and time is accomplished. Results show that the spatial-temporal activity presence-based approach provides reliable estimates of both number of people present and trips actually people made. It is expected that the proposed approach will provide better estimates and be used in not only long-term transport plans but short-term transport impact studies with respect to various transport policies. Finally, in order to introduce the spatial-temporal activity presence-based approach, the data such as activity-based travel diary and land use based on geographic information system are essential.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.685-687
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• 1999

기존 교수 연수체제는 전이 효과가 떨어지며 교사의 업무에 지장을 초래하게 된다. 이에 선정된 컴퓨터교육내용을 원격교육체제로 전환하여 기존 교사 연수의 단점을 극복하여, 효율성을 기할 수 있다. 컴퓨터교육내용을 원격 교육체제로 구축함에 있어서 다양한 원격교육매체의 특징과 가능한 학습 활동, 컴퓨터교육 내용의 특징에 따라서 원격 컴퓨터교육의 모형을 탐색하여 보았다. 그 모형은 자기주도적 학습활동에 기반한 코스웨어 모형, 토의 학습활동에 기반한 토의학습 모형, 대체 학습모형으로 일체학습 모형, 원격 교육의 모든 매체를 활용할 수 있는 문제결학습모형으로 분류하여 제시하여 보았다.

• Proceedings of the Korea Contents Association Conference
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• 2014.11a
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• pp.157-158
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• 2014

본 연구는 여가활동 참여과정을 설명할 수 있는 여가활동 참여과정 모형을 개발하는데 그 목적이 있다. 이를 위해 레크리에이션 전문화, 진지한 여가, 여가제약, 여가제약협상, 여가촉진 등 다양한 여가학 이론 및 선행연구들을 심도 있게 고찰하였으며, 다양한 분야의 관련 이론 및 모형들을 고찰하였다. 이를 통해, 레크리에이션 전문화를 근간으로 9개 영역($3{\times}3$)으로 구성된 여가활동 참여과정 모형을 최종적으로 제시하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.344-347
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• 2016

유비쿼터스 환경 시대에 맞춰 현재 스마트 디바이스의 발달과 시장의 확대로 스마트 미디어 기기의 보급이 급속도로 확산되고 있으며 많은 교육용 어플리케이션 또한 개발되고 있는 중이다. 이러한 교육용 어플리케이션들은 지식기반사회의 학습도구로서 지식접근 및 창출에 중요한 요소인 인터넷과 웹을 활용하게 되고 이동성과 편의성을 추구하는 모바일기기를 통해 학습이 가능하도록 지원하는 프로그램이다. 본 연구는 모바일러닝 기반의 '창의적 문제해결(CPS, Creative Problem Solving)' 모형을 활용하는 교육용 앱에 대한 설계방안을 제시하고자 하며 연구의 목적은 대학 교육에서 학생들의 창의적 사고와 문제해결능력 향상을 돕는 모바일러닝 기반의 학습환경을 설계하는 데 있다. 제안하는 학습지원 도구는 모바일 앱 형태로 제작되며 학습활동에 있어 다양한 창의적 사고과정 활동과 표현방식, 상호작용성 등의 기능을 통해 학습자의 고차원적인 사고능력을 향상시키는 인지적 도구로서 활용될 수 있도록 설계하였다. 개발환경은 안드로이드용 앱 인벤터 프로그램을 사용하였으며 앱 인벤터 서버환경에서 제공되는 컴포넌트와 이벤트 핸들러를 이용하여 교수자모드와 학습자모드의 앱을 각각 설계하였다. 교수자 앱은 학습활동 제공을 의미하는 프로바이더(Provider) 모드 기능이 포함되며 학습자 앱은 CPS 활동을 위한 학습활동 모드 기능이 설계된다. 대부분의 창의성 관련 앱들은 그래픽작업을 통한 두뇌활동 향상 프로그램, 체험활동 위주의 프로그램 등으로 출시가 되어 있으나 교수-학습 활동을 위한 창의적 문제해결활동 관련 앱은 존재하지 않는 상태이므로 수업활동에서의 활용측면에서 가치가 있을 것으로 기대된다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.44-53
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• 2016

The era of Big Data has come and the importance of Big Data has been rapidly growing. The part of transportation, the Four-Step Travel Demand Model(FSTDM), a traditional Trip-Based Model(TBM) reaches its limit. In recent years, a traffic demand forecasting method using the Activity-Based Model(ABM) emerged as a new paradigm. Given that transportation means the spatial movement of people and goods in a certain period of time, transportation could be very closely associated with spatial data. So, I mined Spatial Big Data from SNS. After that, I analyzed the character of these data from SNS and test the reliability of the data through compared with the attributes of TBM. Finally, I built a database from SNS for the operation of ABM and manipulate an ABM simulator, then I consider the result. Through this research, I was successfully able to create a spatial database from SNS and I found possibilities to overcome technical limitations on using Spatial Big Data in the transportation planning process. Moreover, it was an opportunity to seek ways of further research development.