• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2003년도 Proceeding
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• pp.113-117
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• 2003

As the wireless communication technology advances rapidly, a personalization technology can be incorporated with the mobile Internet environment, which is based on location-based services to support more accurate personalized services. A location-based personalized recommender system is one of the essential technologies of the location-based application services, and is also a crucial technology for the ubiquitous environment. In this paper we propose a framework of a location-based personalized recommender system for the mobile Internet environment. The proposed system consists of three modules the interface module, the neighbor selection module and the prediction and recommendation module. The proposed system incorporates the concept of the recommendation system in the Electronic Commerce along with that of the mobile devices for possible expansion of services on the mobile devices. Finally a service scenario for entertainment recommendation based on the proposed recommender system is described.

• 대한음성학회지:말소리
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• 제57호
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• pp.139-152
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• 2006

In this paper, we present a phrase break prediction method using CRF(Conditional Random Fields), which has good performance at classification problems. The phrase break prediction problem was mapped into a classification problem in our research. We trained the CRF using the various linguistic features which was extracted from POS(Part Of Speech) tag, lexicon, length of word, and location of word in the sentences. Combined linguistic features were used in the experiments, and we could collect some linguistic features which generate good performance in the phrase break prediction. From the results of experiments, we can see that the proposed method shows improved performance on previous methods. Additionally, because the linguistic features are independent of each other in our research, the proposed method has higher flexibility than other methods.

• 한국통신학회논문지
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• 제32권6A호
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• pp.550-557
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• 2007

인과 관계에 대한 직관적인 개념으로 Bayesian Networks 알고리즘이나 트리 구조 추측 알고리즘 그리고 유전자 알고리즘을 사용하여 다양한 구조의 상황을 예측을 하게 된다. 하지만 이런 예측 알고리즘들을 상황인지 서비스 구현에 적용하기에는 실제 구현의 어려움과 실시간 환경에서 트레이닝 데이터 처리에서 오는 시간 지연 문제 등이 발생하게 된다. 이 때문에 특정 목적의 상황인지 시스템에서 이 알고리즘들이 어느 정도의 예측 정확도와 신뢰도를 가지고 상황 정보에 부합하는지 미지수이다. 따라서 본 논문에서는 기존의 예측 알고리즘과는 다른 접근 방식을 통해, 사용자의 습관이나 행동양식을 데이터베이스로 만들어 이를 고려함으로써 상황인지 시스템의 상황 정보와 부합되는 Flexible Window 기법을 이용한 위치 예측 알고리즘을 제안한다. 제안된 Flexible Window 기법을 이용한 위치 예측 알고리즘은 동일한 실험 조건 아래, Fixed Window 기법을 이용한 위치 예측 알고리즘보다 평균적으로 5.10% 더 우수한 성능을 보인다. 이 방식은 기하급수적으로 늘어나는 상황 정보를 감안했을 때 알고리즘 수행 시 처리 시간의 감소와 예측 정확도를 향상 시킬 수 있다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.321-324
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• 2007

It is commonly believed that a gigantic earthquake (Tokai Earthquake) could occur in Shizuoka Prefecture in the near future. The Shizuoka Prefecture Government made the prediction report of Tokai Earthquake disaster damage. But this report does not pay attention to the ground conditions. The authors make a prediction map using GIS of Tokai Earthquake disaster damage in Asada-cho and Hirosawa Ni-chome in the central Hamamatsu City and revealed the location of dangerous houses and dangerous points in road networks in each town. These information could be useful when people try to find escape routes in an earthquake.

• Journal of Information Processing Systems
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• 제15권6호
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• pp.1335-1349
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• 2019

Crowdsensing technologies can improve the efficiency of smart parking system in comparison with present sensor based smart parking system because of low install price and no restriction caused by sensor installation. A lot of sensing data is necessary to predict parking lot saturation in real-time. However in real world, it is hard to reach the required number of sensing data. In this paper, we model a saturation predication combining a time-based prediction model and a sensing data-based prediction model. The time-based model predicts saturation in aspects of parking lot location and time. The sensing data-based model predicts the degree of saturation of the parking lot with high accuracy based on the degree of saturation predicted from the first model, the saturation information in the sensing data, and the number of parking spaces in the sensing data. We perform prediction model learning with real sensing data gathered from a specific parking lot. We also evaluate the performance of the predictive model and show its efficiency and feasibility.

• Journal of information and communication convergence engineering
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• 제5권2호
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• pp.83-87
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• 2007

This research studies real time interaction and dynamic data shared through 3D scenes in virtual network environments. In a distributed virtual environment of client-server structure, consistency is maintained by the static information exchange; as jerks occur by packet delay when updating messages of dynamic data exchanges are broadcasted disorderly, the network bottleneck is reduced by predicting the movement path by using the Dead-reckoning algorithm. In Dead-reckoning path prediction, the error between the estimated and the actual static values which is over the threshold based on the shared object location requires interpolation and multicasting of the previous location by the ESPDU of DIS. The shared dynamic data of the 3D virtual environment is implementation using the VRML.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 추계학술대회 논문집
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• pp.1505-1510
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• 2007

In this paper, the power simulation is used for the prediction of regenerative energy and examination of install location of regenerative inverter for DC railway system. The power simulation was composed to train performance simulation(TPS) and power flow simulation. We performed the power simulation for Seoul subway line 5 and 7, calculation of regenerative energy and examination of substations where regenerative inverter is installed.

• International Journal of Control, Automation, and Systems
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• 제3권4호
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• pp.509-523
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• 2005

We are developing a novel framework, PRIDE (PRediction In Dynamic Environments), to perform moving object prediction (MOP) for autonomous ground vehicles. The underlying concept is based upon a multi-resolutional, hierarchical approach which incorporates multiple prediction algorithms into a single, unifying framework. The lower levels of the framework utilize estimation-theoretic short-term predictions while the upper levels utilize a probabilistic prediction approach based on situation recognition with an underlying cost model. The estimation-theoretic short-term prediction is via an extended Kalman filter-based algorithm using sensor data to predict the future location of moving objects with an associated confidence measure. The proposed estimation-theoretic approach does not incorporate a priori knowledge such as road networks and traffic signage and assumes uninfluenced constant trajectory and is thus suited for short-term prediction in both on-road and off-road driving. In this article, we analyze the complementary role played by vehicle kinematic models in such short-term prediction of moving objects. In particular, the importance of vehicle process models and their effect on predicting the positions and orientations of moving objects for autonomous ground vehicle navigation are examined. We present results using field data obtained from different autonomous ground vehicles operating in outdoor environments.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2009년도 세계 도시지반공학 심포지엄
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• pp.233-242
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• 2009

Based on the data obtained from field investigation and soil testing to slope hazards occurrence section and non-occurrence section in crystalline rocks like gneiss, granite, and so on, a prediction model was developed by the use of a decision tree model. The classification standard of the selected prediction model is composed of the slope angle, the coefficient of permeability and the void ratio in the order. The computer program, SHAPP ver. 1.0 for prediction of slope hazards around an important national facilities using GIS technique and the developed model. To prove the developed prediction model and the computer program, the field data surveyed from Jumunjin, Gangneung city were compared with the prediction result in the same site. As the result of comparison, the real occurrence location of slope hazards was similar to the predicted section. Through the continuous study, the accuracy about prediction result of slope hazards will be upgraded and the computer program will be commonly used in practical.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2008년도 학술대회 1부
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• pp.298-303
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• 2008

사용자의 과거 이동 경로 자료는 사용자의 현재 이동 위치를 예측하고 이외 관련된 서비스를 제공하는데 유용하게 사용될 수 있다. 본 논문에서는 사용자의 과거 이동 경로의 분석을 통하여 이동 중인 사용자의 시공간 위치예측 기술을 제안한다. 환경으로부터 발생한 사용자의 이동 경로를 수집하고 수집된 데이터에서 이동 경로 요약(Path Summarization)과 이동 경로 선택(Path Selection) 방법을 제안한다. 이동 경로 요약 방법은 환경으로부터 수집한 사용자의 이동 경로를 군집 분류하고, 이동 경로 선택 방법은 이동 중에 발생한 경로의 거리, 시간, 방향의 요소와 동적 정합법을 사용하여 유사성(Similarity)을 측정하며 유사성이 가장 높은 경로를 선택한다. 선택된 경로는 시간에 따른 공간 정보 빚 위치에 따른 시간 예측 서비스를 위하여 사용가능 하며, 실험을 통하여 유사성이 높은 이동 경로를 선택하는 모습을 확인하였다.