• Journal of International Academy of Physical Therapy Research
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• v.11 no.1
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• pp.2005-2011
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• 2020

Background: Motor imagery is the mental representation of an action without overt movement or muscle activation. However, few previous studies have demonstrated motor imagery training effects as an objective assessment tool in patients with early stroke. Objective: To investigate the effect of motor imagery training on Somatosensory Evoked Potentials (SSEP) and upper limb function of stroke patients. Design: A quasi-experimental study. Methods: Twenty-four patients with stroke were enrolled in this study. All subjects were assigned to the experimental or control group. All participants received traditional occupational therapy for 30 minutes, 5 times a week. The experimental group performed an additional task of motor imagery training (MIT) 20 minutes per day, 5 days a week, for 4 weeks. Both groups were assessed using the SSEP amplitude, Fugl-Meyer assessment of upper extremity (FMA UE) and Wolf motor function test. Results: After the intervention, the experimental group showed significant improvement in SSEP amplitude and FMA UE than did the control group. Conclusion: These findings suggest that the MIT effectively improve the SSEP and upper limb function of stroke patients.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.30-30
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• 2018

Research on mapping levees is an important task for assessing levee stability. The drone imagery acquired in river basins is useful for generating real-time levee maps. This research proposes a robust methodology for mapping levees in river basins using the drone imagery. In the first step, the multiple imagery taken in the test bed was acquired by the drone. Then, the orthorectified image and DEM (Digital Elevation Model) were generated by the photogrammetry and image processing process. Finally, the significant features on levee surfaces such as levee tops, levee lines, levee slopes, eroded areas were detected from the generated DEM and orthorectified image by manual labors and automatic methods. In future research, the automatic procedure for identifying the significant levee features from the drone imagery would be proposed.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.642-645
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• 2009

Brain Computer Interface (BCI) is a communication pathway between devices (computers) and human brain. It treats brain signals in real-time basis and discriminates some information of what human brain is doing. In this work, we develop a EEG BCI system using a feature extraction such as common spatial pattern (CSP) and a classifier using Fisher linear discriminant analysis (FLDA). Two-class EEG motor imagery movement datasets with both cued and uncued are tested to verify its feasibility.

• Proceedings of the KSRS Conference
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• v.1
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• pp.163-165
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• 2006

We aim to archive all the satellite images that had been scattered into Satellite Imagery Information System with setting naming rules and metadata. More than one million of scenes were collected, rectified into error-free status with metadata . Converting various formats into HDF format after considering GEOTIFF and HDF. Intranet and Internet System had been development to allow all the images to be searched and downloaded with less effort. These system will expand the usage of meteorological satellite images for expert groups and the public outside of KMA.

• Proceedings of the KGS Conference
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• 2004.05a
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• pp.56-56
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• 2004

The ability to detect urban heat islands in satellite imagery is a function of spatial, spectral, and temporal resolutions. Imagery from the satellite-mounted Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor acquired since December 1999 allows us to view the Earth at a higher spectral resolution in the thermal infrared (TIR) portion of the electromagnetic spectrum than most other satellite systems (e.g., AVHRR, Landsat TM). (omitted)

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.365-368
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• 2003

In this study, we get a digital imagery about the objective road and visualize it as three dimensional so called 3D. That is to say that we manage the road trough computerized data or 3D and we can expect to get efficiency of the human resources and economical, timely efficiency which is needed to maintain and manage the road.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.67-68
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• 2010

Segmentation of LiDAR data is an important procedure in building modeling. Therefore, in this study, aerial imagery is used to group LiDAR data for both improving segmentation accuracy and modeling detail surface patches of the roofs. The results show that the proposed method is efficient to analyze and to model various types of roof shape.

• Korean Journal of Remote Sensing
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• v.6 no.1
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• pp.25-37
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• 1990

Methods of geometric correction for the Advanced Very High Resolution Radiometer imagery of NOAA satellites were developed and applied to the software for image processing of meteorological satellite data. The software for finding the earth location of each scan position and the software for gridding on original imagery were dedigned. On the assumption of circular orbits and the spherical earth, the methods developed were sufficiently accurate in the purpose of most meteorological data analyses.

• Korean Journal of Remote Sensing
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• v.27 no.6
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• pp.717-728
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• 2011

An efficient method for the unsupervised classification of high resolution imagery is suggested in this paper. It employs pixel-linking and merging based on the adjacency graph. The proposed algorithm uses the neighbor lines of 8 directions to include information in spatial proximity. Two approaches are suggested to employ neighbor lines in the linking. One is to compute the dissimilarity measure for the pixel-linking using information from the best lines with the smallest non. The other is to select the best directions for the dissimilarity measure by comparing the non-homogeneity of each line in the same direction of two adjacent pixels. The resultant partition of pixel-linking is segmented and classified by the merging based on the regional and spectral adjacency graphs. This study performed extensive experiments using simulation data and a real high resolution data of IKONOS. The experimental results show that the new approach proposed in this study is quite effective to provide segments of high quality for object-based analysis and proper land-cover map for high resolution imagery of urban area.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.26-29
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• 2005

In order to compute cloud coverage statistics over Asian region, an operational scheme for masking cloud-contaminated pixels in Advanced Very High Resolution Radiometer (AVHRR) daytime data was developed, evaluated and presented. Dynamic thresholding was used with channell, 2 and 3 to automatically create a cloud mask for a single image. Then the IO-day cloud coverage imagery was generated over the whole Asian region along with cloud-free composite imagery. Finally the monthly based statistics were computed based on the derived cloud coverage imagery in terms of land cover and country. As a result, it was found that 20-day is required to acquire the cloud free data over the whole Asia using NOAA AVHRR. The to-day cloud coverage and cloud-free composite imagery derived in this research is available via the web-site http://webpanda.iis.u-tokyo.ac.jp/CloudCover/.