• 재활간호학회지
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• 제6권1호
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• pp.79-89
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• 2003

Purpose: This research with one group pre-post design was carried out to test the practical feasibility to administrate the Music Movement program developed for the stroke patients. Subjects: 12 stroke survivors at "J" Public Health Center in Seoul. were participated in. The average age was 68 years old, the ratio of sex was almost 5.8:4.2, the duration of was almost over 1 year. Method: Music Movement program was conducted for 2 hours ${\times}$ 1day ${\times}$ 6 weeks. The contents of Music Movement program were consisted of the preparatory activities, main activities and the wrap up activities. The preparatory activities are ice braking, greeting, explanation of the aims of music movement program, and introduction of stroke disease and ROM exercise. The main activities are the body motions with singing and playing musical instruments. The wrap up activities are stretching and joints and discussion of home activities. Data Collection: The outcome variables are muscle strength, finger pinch power, ROMs, flexibility, depression, and life satisfaction. Depression was measured by CES-D(Kim, I. J., 1999), life satisfaction by ladder scale(McDowell & Newell, 1996), and ADL state(Holbrook & Skilbeck, 1983). Data Analysis: SPSS/PC 10.0 for Window was used. Wilcoxon Signed Ranks Test was used to analyze outcome measures. The level of statistical significance was set at p<.05. Results: This program was effective to decrease the depression level of subjects(p<.05). The muscle strength, hand grip power, ROMs, life satisfaction, and rehabilitation state of the subjects were slightly increased but no significant differences were found between the pre and post test. Additionally every patient replied that they were very satisfied and expressed their appreciation for this program very much. Of course they strongly want to continue to participate in and meet the peer group again. Conclusion: Considering these results, the practical feasibility of Music Movement program can be supported. Therefore, this Music Movement program can be examined with the quasi-experimental design with control group and ongoing reviews. After that, this program would be applied in public health centers, medical institutes, and welfare centers for the rehabilitation of stroke patients.

• 수산해양기술연구
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• 제55권1호
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• pp.29-38
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• 2019

In order to investigate the behavioral characteristics of Pacific cod (Gadus macrocephalus) released at the entrance of Jinhae Bay, Korea, the direction and range of movement, swimming speed of the fish were measured with an acoustic telemetry techniques in winter, 2015. Three wild Pacific codes WC1 to WC3 (total length 66.0, 75.0, 76.0 cm; body weight 2.84, 2.79, 3.47 kg, respectively) were tagged with the acoustic transmitter. WC1 tagged with an acoustic transmitter internally by surgical method, WC2 and WC3, externally with the acoustic data logger and a micro data logger for recording audible sound waves including timer release unit. The movement routes of the tagged fish were measured more than five hours using VR100 receiver and a directional hydrophone. The directionality of the fish movement was tested by Rayleigh's z-Test, the statistical analysis, and a statistical program SPSS. Three tagged fishes were individually released on the sea surface around the entrance to the Jinhae Bay on 10 to 24 January 2015. WC1 moved about 13.32 km with average swimming speed of 0.63 m/s for six hours. The average swimming depth and water depth of the seabed on the route of WC1 were 7.2 and 32.9 m, respectively. The movement range of WC2 and WC3 were 7.95 and 11.06 km, approximately, with average swimming speed of 0.44 and 0.58 m/s for 5.1 and 5.3 hours, respectively. The average swimming depth of WC2 and WC3 were 18.7 and 5.0 m, and the water depth on the route, 34.4 and 29.8 m, respectively. Three fishes WC1 to WC3 were shown significant directionality in the movement (p < 0.05). Movement mean angles of WC1 to WC3 were 77.7, 76.3 and $88.1^{\circ}$, respectively. There was no significant correlation between the movement direction of fish (WC1 and WC2) and the tidal currents during the experimental period (p >= 0.05). Consequently, three tagged fishes were commonly moved toward outside of the entrance and headed for eastward of the Korean Peninsula, approximately, after release. It may estimate positively that the tidal current speed may affect to the swimming speed of the Pacific cod during the spring tide than the neap tide.

• International Journal of Internet, Broadcasting and Communication
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• 제15권3호
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• pp.176-184
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• 2023

Points of interest (POIs) are widely used in tourism recommendations and to provide information about areas of interest. Currently, situation judgement using POI and GPS data is mainly rule-based. However, this approach has the limitation that inferences can only be made using predefined POI information. In this study, we propose an algorithm that uses POI data, GPS data, and schedule information to calculate the current speed, location, schedule matching, movement trajectory, and POI coverage, and uses machine learning to determine whether to stay or go. Based on the input data, the clustered information is labelled by k-means algorithm as unsupervised learning. This result is trained as the input vector of the SVM model to calculate the probability of moving and staying. Therefore, in this study, we implemented an algorithm that can adjust the schedule using the travel schedule, POI data, and GPS information. The results show that the algorithm does not rely on predefined information, but can make judgements using GPS data and POI data in real time, which is more flexible and reliable than traditional rule-based approaches. Therefore, this study can optimize tourism scheduling. Therefore, the stay detection algorithm using GPS movement trajectories and POIs developed in this study provides important information for tourism schedule planning and is expected to provide much value for tourism services.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.458-459
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• 2021

최근, 실내 위치 기반 서비스에서 정확한 서비스를 위해 Wi-Fi 핑거프린트 기반의 딥러닝 기술을 이용한 연구가 이루어지고 있다. 딥러닝 모델 중에서 과거의 정보를 기억할 수 있는 RNN 모델은 실내측위에서 연속된 움직임을 기억할 수 있어 측위 오차를 줄일 수 있다. 이때 학습 데이터로서 연속적인 순차 데이터를 필요로 한다. 그러나 일반적으로 Wi-Fi 핑거프린트 데이터의 경우 특정 위치에 대한 신호들만으로 관리되기 때문에 RNN 모델의 학습데이터로 사용이 부적절하다. 본 논문은 RNN 모델의 순차적인 입력 데이터의 생성을 위해 클러스터링을 통한 영역 데이터로 확장된 Wi-Fi 핑거프린트 데이터 기반 이동 경로의 예측을 통한 경로 생성 방법에 대해 제안한다.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2003년도 봄 학술발표회 논문집
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• pp.663-670
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• 2003

Urban tunnelling need to consider not only the stability of tunnel itself but also the ground movement regarding adjacent structures. This paper present 3-D behavior of adjacent structures due to tunnelling induced ground movements by means of field measuring data and nonlinear FEM tunnel analysis. The results of the analytical methods from Mohr-Coulomb model are compared with the site measurement data obtained during the twin tunnel construction. It was found that the location and stiffness of the structure influence greatly the shape and pattern of settlement trough. The settlement trough for Greenfield condition was different from the trough for existing adjacent structures. Therefore the load and stiffness of adjacent structures should be taken into account for the stability analysis of the structures.

• 한국컴퓨터산업학회논문지
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• 제3권5호
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• pp.623-630
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• 2002

본 논문에서는 Legacy 데이터베이스 사이의 데이터 이동을 지원하는 XML Gateway를 설계하고 구현하는 방법을 제안한다. 이를 위해 XML 기술, Oracle XML Utility, 그리고 JDeveloper를 사용한다. 그리고 데이터를 추출하기 위해 XSQL 페이지를 사용하고, 이를 파싱하고 XSL 변환을 거친 후 XSQL 서블릿의 XMLHttpRequest 객체를 사용하여 저장한다. 구현된 시스템을 사용함으로써 업무담당자는 SQL＊Plus 도구를 이용하여 작업을 처리하지 않아도 되며 시스템이 제공하는 익숙한 Web 환경 인터페이스를 사용하여 데이터 이동을 편리하게 처리할 수 있게 되었다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.217-219
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• 2004

In recent years, the smart card is wifely applied for wireless communication, tracking, transportation logistics, diagnostic monitoring, access control and security. RF-ID system is universally applicable. Passive RF-ID system consists from reader and passive tag. The reader transmits energy and simple information to a tag by wireless and the power from the reader is transformed for controller, FRAM and Bluetooth module. in this paper, an analysis and design of smart card for the transmission of the car movement data is presented.

• 한국정보처리학회논문지
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• 제1권3호
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• pp.290-298
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• 1994

본 논문은 p(p= $n^{1-x}$, 0〈x〈1)개 프로세서가 존재하는 EREW-PRAM 모델 병 렬 컴퓨터에서 시간 복잡도가 0( $n^{x}$ log n)이며 비용 (최악의 실행시간*프로세서 수)은 0(nlogn)이고, 자료 이동도가 0( $n^{1-}$x＋ $n^{x}$ )인 병렬 정렬 알고리즘을 제안한다. 병렬 정렬 알고리즘은 리스트를 p개 특정키를 중심으로 분리한 다음 블럭 의 크기를 거의 일정하게 할 수 있는 엔코딩 기법을 사용했다.다.

• 한국컴퓨터정보학회논문지
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• 제22권11호
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• pp.97-104
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• 2017

Location prediction has been successfully utilized to provide high quality of location-based services to customers in many applications. In its usual form, the conventional type of location prediction is to predict future locations based on user's past movement history. However, as location prediction needs are expanded into much complicated cases, it becomes necessary quite frequently to make inference on the locations that target user visited in the past. Typical cases include the identification of locations that infectious disease carriers may have visited before, and crime suspects may have dropped by on a certain day at a specific time-band. Therefore, primary goal of this study is to predict locations that users visited in the past. Information used for this purpose include user's demographic information and movement histories. Data mining classifiers such as Bayesian network, neural network, support vector machine, decision tree were adopted to analyze 6868 contextual dataset and compare classifiers' performance. Results show that general Bayesian network is the most robust classifier.

• International journal of advanced smart convergence
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• 제8권2호
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• pp.39-46
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• 2019

Human mobility estimation plays a key factor in a lot of promising applications including location-based recommendation systems, urban planning, and disease outbreak control. We study the human mobility estimation problem in the case where recent locations of a person-of-interest are unknown. Since matrix decomposition is used to perform latent semantic analysis of multi-dimensional data, we propose a human location estimation algorithm based on matrix factorization to reconstruct the human movement patterns through the use of information of persons with correlated movements. Specifically, the optimization problem which minimizes the difference between the reconstructed and actual movement data is first formulated. Then, the gradient descent algorithm is applied to adjust parameters which contribute to reconstructed mobility data. The experiment results show that the proposed framework can be used for the prediction of human location and achieves higher predictive accuracy than a baseline model.