• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.4
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• pp.98-108
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• 2004

The concept of community capacity is regarded as the ability of people and communities to do works associated with the determinant factors and indicators of the circumstances of socio-economic, environmental and physical contexts. Building capacity of communities to effectively analyze our problematic issues and planning of community development is often required to scrutinize current status of community of socio-economic and infrastructural capacity development with GIS. We consider community development as a planned effort to build assets that increase the capacity of communities. Spatial asset mapping is the process enabling to identify and make inventories of tangible and intangible assets. This mapping requires developing a capacity inventory that collects individual organizational and community capacities in view of human, socio-cultural, natural, financial, digital, and physical capacity. The purpose of this research is not only designed to suggest a new concept capacity building, but also proposes a more creative framework of asset-based community cap linking to parcel-based spatial asset mapping and capacity mapping process.

• PNF and Movement
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• v.4 no.1
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• pp.37-44
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• 2006

Purpose : Improved walking is a common goal after stroke. Although the neurodevelopmental intervention(PNF) is the most widely used approach in the walking training of hemiparetic subjects. There is little neurophysiological evidence for its presumed effects on gait symmetry and facilitation of paretic muscles during the therapeutic intervention. The study, therefore, investigated the immediate effects of gait entrainment by a PNF techniques. Methods : Included persons with stroke who were living in the community. Sixteen subjects were assigned to the experimental group participated in a measures design that evaluated the subjects with pre-treatment, post-treatment(8 weeks). Temporal-spatial parameter of gait were analysed for using the computerized GAITRite system. Intervention : Training for the experimental group was carried out 3 times a week for 8 weeks. The training sessions were comprised of 50 minutes of walking with pattern and techniques in PNF. Results : The experimental group had improvements in the functional walking ability after 8 weeks treatment and Post-treatment test scores were more significant than the pre-treatment score. The treatment group demonstrated significantly post-treatment test improvement in gait velocity, cadence and FAP. Post-treatment test scores were more significant than the pre-treatment score(p<0.05). Conclusion : The results of this study showed that the PNF exercise intervention can improve functional gait ability. This study provides evidence for the efficacy of PNF treatment at improving locomotor function in chronic stroke.

• Journal of Intelligence and Information Systems
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• v.14 no.3
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• pp.25-39
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• 2008

The objective of this study is to forecast the operational continuous ability using Artificial Neural Networks in battalion defensive operation for the commander decision making support. The forecasting of the combat result is one of the most complex issue in military science. However, it is difficult to formulate a mathematical model to evaluate the combat power of a battalion in defensive operation since there are so many parameters and high temporal and spatial variability among variables. So in this study, we used company combat power level data in Battalion Command in Battle Training as input data and used Feed-Forward Multilayer Perceptrons(MLP) and General Regression Neural Network (GRNN) to evaluate operational continuous ability. The results show 82.62%, 85.48% of forecasting ability in spite of non-linear interactions among variables. We think that GRNN is a suitable technique for real-time commander's decision making and evaluation of the commitment priority of troops in reserve.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1295-1297
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• 2003

Owing to the higher temporal resolution, meteorological satellite data is widely used to monitor the disasters happened on the earth's surface. However, the precision of identifying disaster information is limited by the poor spatial resolution. As known, GIS technology is good at processing and analyzing the geographic information. The result shows, integrating with GIS technology, the ability of monitoring forest fire using meteorological satellite data has been greatly improved.

• 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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• 2010.04a
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• pp.379-380
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• 2010

GIS has the basic ability to process high-dense and precise digital data like LiDAR. But the software that common users can use when necessary is expensive and practically impossible for actual use. Thus this study set out to research the methodologies to process and service time series LiDAR data for landslide monitoring.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.393-394
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• 2006

This paper lists various error resilience tools and analyzes performance in IP Datacast over DVB-H systems and schemes are proposed. Experiments shows that, in DVB-H environment, encoding with macroblock line intra update can achieve the best error correction ability, because this tool can make full use of spatial correlation for intra prediction and reduce the requirement of bit rate.

• Tuberculosis and Respiratory Diseases
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• v.55 no.3
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• pp.239-249
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• 2003

Multi-detector row CT (MDCT) provides faster speed, longer coverage in conjunction with thin slices, improved spatial resolution, and ability to produce high quality muliplanar and three-dimensional (3D) images. MDCT has revolutionized the non-invasive evaluation of the central airways. Simultaneous display of axial, multiplanar, and 3D images raises precision and accuracy of the radiologic diagnosis of central airway disease. This article introduces central airway imaging with MDCT emphasizing on the emerging role of multiplanar and 3D reconstruction.

• Korean Journal of Remote Sensing
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• v.35 no.6_3
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• pp.1273-1283
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• 2019

This paper proposes an advanced crop classification model that combines a procedure for weighted combination of spatial features extracted from multi-scale input images with a conventional convolutional neural network (CNN) structure. The proposed model first extracts spatial features from patches with different sizes in convolution layers, and then assigns different weights to the extracted spatial features by considering feature-specific importance using squeeze-and-excitation block sets. The novelty of the model lies in its ability to extract spatial features useful for classification and account for their relative importance. A case study of crop classification with multi-temporal Landsat-8 OLI images in Illinois, USA was carried out to evaluate the classification performance of the proposed model. The impact of patch sizes on crop classification was first assessed in a single-patch model to find useful patch sizes. The classification performance of the proposed model was then compared with those of conventional two CNN models including the single-patch model and a multi-patch model without considering feature-specific weights. From the results of comparison experiments, the proposed model could alleviate misclassification patterns by considering the spatial characteristics of different crops in the study area, achieving the best classification accuracy compared to the other models. Based on the case study results, the proposed model, which can account for the relative importance of spatial features, would be effectively applied to classification of objects with different spatial characteristics, as well as crops.

• Journal of the Korean earth science society
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• v.40 no.1
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• pp.86-106
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• 2019

The purpose of this study is to develop an astronomy education program reflecting astronomical thinking to be used at science museum and to investigate the effect of the program on the improvement of astronomical thinking ability of high school students. After selecting the components of astronomical thinking through literature studies, we developed an astronomy education program consisting of four stages: demonstration and observation, and question and thinking, support and group discussion, demonstration and assessment. In order to verify the effectiveness of the program, we conducted a covariance analysis on the pre- and post-tests of the experimental group and control group to examine the level of students' thinking before and after using the program in teaching and learning. As a result, it was confirmed that the astronomy education program reflecting astronomical thinking was effective in promoting students' astronomical thinking ability. In particular, this program was effective in enhancing the ability of modeling by reconstructing the observed astronomical phenomenon from the viewpoint of the universe with respect to spatial thinking in the astronomy domain. It was also effective to improve the ability of organizing the system by grasping the relationship between the elements constituting the astronomical system in relation to the system thinking in the astronomy domain. This study is significant in suggesting a specific teaching and learning program to develop students' astronomical thinking.