• Therapeutic Science for Rehabilitation
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• v.7 no.4
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• pp.7-18
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• 2018

Objective: The purpose of this study was to investigate the effects of telerehabilitation on stroke patients through remotely operated intervention and monitoring. Methods: Literature from 2000 to April 2018 was collected through PubMed, Embase, Cochrane, and RISS. We used telerehabilitation, telemedicine, and stroke as the search terms in regard to foreign literature, and the terms telerehabilitation, stroke, and CVA in regard to Korean literature. A total of 406 foreign and 15 Korean published studies were found. As a result, a total of seven documents was selected for the analysis. Results: As a result of the analysis, all the interventions applied through telerehabilitation were provided remotely, and significant effects were reported between pre-post assessments. In addition, the significant effects of telerehabilitation were reported through analyzing pre-post(n=7) and between groups(n=4) assessments. The monitoring used could be categorized according to purpose, that is, for checking (n=3) and as an intervention (n=4). Conclusions: This study confirmed, within limits, that the application of telerehabilitation could be a potential alternative for stroke patients with limited rehabilitation services. In order to apply telerehabilitation in Korea, it is necessary to study the cost effectiveness, according to the current domestic situation, and confirm the most effective monitoring method based on the intervention.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.499-501
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• 2004

교육의 새로운 방향은 가상 학교나 WBI와 같은 교육적 활용분야로 확대되고 있으나, e-Learning 상에서 이뤄지는 평가의 응시자에 대한 신뢰 확보는 어려운 상황이다. 기존의 인증이란 사용자가 E와 Password를 타인에게 공개하지 않는 한 본인임을 인증하였다. 하지만 온라인상에서 시험 응시자는 본인의 ID와 Password를 타인에게 알려주어 대리시험이 가능하게 함은 물론 시험문제의 공유 또는 다수의 응시자가 한 곳에 모여 문제를 풀어 감으로서 평가에 대한 신뢰도에 의문을 갖지 않을 수 없게 되었다. 이에 인터넷으로 원격조정이 가능한 PC카메라와 얼굴인식 프로그램 그리고 원격제어프로그램을 이용하여 응시자를 인증함으로써 부정행위를 원천적으로 봉쇄하고, 감독자가 언제 어디서나 웹을 통하여 쉽게 감독할 수 있도록 LMS 기능의 보완이 요구된다. 본 논문을 통해서는 채팅기능을 통한 상호 대화가 가능하고 응시 장면을 동영상으로 압축 저장하여 사후 감독이 가능토록 함으로서 e-Learning상에서의 평가 및 학사관리의 공정성 및 신뢰도를 높일 수 있는 방안을 제시하였다.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.33-36
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• 2007

토지피복분류， 식생분류， 식물피복도 분류 등 원격탐사 영상자료의 주된 이용분야에서 지상자료는 매우 중요한 부분을 차지하고 있다. 가령 감독분류를 위한 training site 에 대한 측정이나 또는 분류 정확도 검증을 위한 측면에서도 지상측정은 반드시 필요한 부분이다. 본 논문에서는 피복분류 과정에서 반드시 필요한 지상측정을 위한 표본조사에서 유의하여야 할 통계학적 측면에서 고려해야 할 사항을 검토한다.

• Proceedings of the KSEEG Conference
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• 1999.04a
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• pp.71-73
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• 1999

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.185-191
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• 2007

Remote sensing images are multispectral image data collected from several band divided by wavelength ranges. The classification of remote sensing images is the method of classifying what has similar spectral characteristics together among each pixel composing an image as the important algorithm in this field. This paper presents a pattern classification method of remote sensing images by applying a possibilistic fuzzy c-means (PFCM) algorithm. The PFCM algorithm is a hybridization of a FCM algorithm, which adopts membership degree depending on the distance between data and the center of a certain cluster, combined with a PCM algorithm, which considers class typicality of the pattern sets. In this proposed method, we select the training data for each class and perform supervised classification using the PFCM algorithm with spectral signatures of the training data. The application of the PFCM algorithm is tested and verified by using Landsat TM and IKONOS remote sensing satellite images. As a result, the overall accuracy showed a better results than the FCM, PCM algorithm or conventional maximum likelihood classification(MLC) algorithm.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.184-186
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• 2022

자율운항선박의 도입이 가시화됨에 따라 자율운항선박의 운항을 관리·감독하는 원격운항자의 운항능력에 대한 관심도 증가하고 있다. IMO에서는 원격운항자의 상시 모니터링과 비상시 원격지원을 기반으로 하는 자율운항 선박모델을 제시하고 있다. 특히 선박의 자동화 시스템으로 대응할 수 없는 복잡한 상황에 직면할 경우 해당상황을 해결하기 위해 원격운항자의 판단력과 지식이 요구되는 상황이 발생할 수 있다. 따라서 원격운항자는 선체와 주변 상황을 원격으로 인식하는 상황인식능력이 필요하며, 원격운항자의 상황인식능력은 기존 항해사의 상황인식능력과는 상이한 부분이 존재할 수 있다. 본 연구에서는 자율운항선박의 도입으로 인해 발생하는 운항환경의 변화에 따라 원격운항자에게 요구되는 상황인식 요구사항을 분석하고 이를 기존 선원의 상황인식 모델과 비교하여 자율운항선박의 안전한 도입을 위한 기초자료로 활용하고자 한다.

• Korean Journal of Remote Sensing
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• v.30 no.2
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• pp.207-218
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• 2014

The information on the land cover along stream corridor is important for stream restoration and maintenance activities. This study aims to review the different classification methods for mapping the status of stream corridors in Seom River using airborne RGB and CIR digital ortho imagery with a ground pixel resolution of 0.2m. The maximum likelihood classification, minimum distance classification, parallelepiped classification, mahalanobis distance classification algorithms were performed with regard to the improvement methods, the skewed data for training classifiers and filtering technique. From these results follows that, in aerial image classification, Maximum likelihood classification gave results the highest classification accuracy and the CIR image showed comparatively high precision.

• Korean Journal of Remote Sensing
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• v.18 no.6
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• pp.369-376
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• 2002

This paper presents a method to enhance the performance of supervised classification by separating the spectral signature of the training data sets for each class. Using clustering technique, a training data set is divided into several subsets which show a pattern of the normal distribution with small value of spectral variances. Then a supervised classification is applied with the divided training data set as training data for the temporary subclasses of the original class. The proposed method is applied to a Landsat TM image of Busan area for the applicability test. The result shows that the proposed method produces better classified results than the conventional statistical classification methods. It is expected that the proposed method will reduce the effort and expense for selecting the training data set for each class in an area which has spectrally homogeneous signature.

• Korean Journal of Remote Sensing
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• v.15 no.1
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• pp.39-50
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• 1999

It is complicate and time-consuming process to classify a multi-band satellite imagery according to the application. In addition, classification rate sensitively depends on the selection of training data set and features in a supervised classification process. This paper introduced a classification network adopting a fuzzy-based $\gamma$-model in order to select a training data set and to extract feature which highly contribute to an actual classification. The features used in the classification were gray-level histogram, textures, and NDVI(Normalized Difference Vegetation Index) of target imagery. Moreover, in order to minimize the errors in the classification network, the Gradient Descent method was used in the training process for the $\gamma$-parameters at each code used. The trained parameters made it possible to know the connectivity of each node and to delete the void features from all the possible input features.

• Korean Journal of Remote Sensing
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• v.35 no.3
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• pp.359-373
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• 2019

Bursaphelenchus xylophilus(Pine wilt disease) is a serious threat to the pine forest in Korea. However, dead wood observation by Pine wilt disease is based on field survey. Therefore, it is difficult to observe large-scale forests due to physical and economic problems. In this paper, high resolution images were obtained using the unmanned aerial vehicle (UAV) in the area where the pine wilt disease recurred. The damaged tree due to pine wilt disease was detected using Artificial Neural Network (ANN), Support Vector Machine (SVM) supervision classification technique. Also, the accuracy of supervised classification results was calculated. After conducting supervised classification on accessible forests, the reliability of the accuracy was verified by comparing the results of field surveys.