• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.3
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• pp.61-74
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• 2016

The purpose of this paper is to analyze the relationship between the location of the epicenter of a medium-sized earthquake(magnitude 4.8) that occurred on January 20, 2007 in the Odaesan area with lineament features using a shaded relief map(1/25,000 scale) and satellite images from LANDSAT-8 and KOMPSAT-2. Previous studies have analyzed lineament features in tectonic settings primarily by examining two-dimensional satellite images and shaded relief maps. These methods, however, limit the application of the visual interpretation of relief features long considered as the major component of lineament extraction. To overcome some existing limitations of two-dimensional images, this study examined three-dimensional images, produced from a Digital Elevation Model and drainage network map, for lineament extraction. This approach reduces mapping errors introduced by visual interpretation. In addition, spline interpolation was conducted to produce density maps of lineament frequency, intersection, and length required to estimate the density of lineament at the epicenter of the earthquake. An algorithm was developed to compute the Value of the Relative Density(VRD) representing the relative density of lineament from the map. The VRD is the lineament density of each map grid divided by the maximum density value from the map. As such, it is a quantified value that indicates the concentration level of the lineament density across the area impacted by the earthquake. Using this algorithm, the VRD calculated at the earthquake epicenter using the lineament's frequency, intersection, and length density maps ranged from approximately 0.60(min) to 0.90(max). However, because there were differences in mapped images such as those for solar altitude and azimuth, the mean of VRD was used rather than those categorized by the images. The results show that the average frequency of VRD was approximately 0.85, which was 21% higher than the intersection and length of VRD, demonstrating the close relationship that exists between lineament and the epicenter. Therefore, it is concluded that the density map analysis described in this study, based on lineament extraction, is valid and can be used as a primary data analysis tool for earthquake research in the future.

• Tuberculosis and Respiratory Diseases
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• v.50 no.1
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• pp.42-51
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• 2001

Background : Recently, cardiopulmonary exercise testing (CPX) has become a popular diagnostic method for differentiating the main cause of exertional dyspnea or exercise limitation. We evaluated the difference in the CPX results according to interpretative algorithms and the methals of exercise in Korea. Method : Sixty-six patients with chronic lung disease and 48 adults with dyspneic symptoms, but with no abnormalities in a spirometry performed symptom limited CPX, were included in this study. The results were interpreted using both Wasserman's(WA) and Eschenbacher's algorithm (EA), and a comparison between both algorithms was made. Thirty-three healthy medical students performed the CPX with a cycle ergometer and treadmill. The results were interpreted with EA and the concurrence in interpretations was evaluated accord ing to the methods of exercise. Results : 1. In patients with chronic lung disease, the overall concordance rate between the two algorithms was 63.6%. The concordance rates waw 69.8% in patients with obstructive, 25.0% in those with restrictive, and 66.7% in those with mixed pulmonary insufficiency. In patients with dyspneic symptoms but normal findings in resting spirometry, the concordance rate was 60.4%. 2. In healthy medical students, in results inter preted with EA, the concordance rate between the cycle ergometer and treadmill exercise was 25.0%. Conclusion : Both interpretative algorithms and methods of exercise may affect the CPX results. In using CPX as a diagnostic test for the causes of dyspnea in the Korean population. the interpretative algorithms and method of exercise need to be standardized, and a predictive $VO_2$max equation needs to be established.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.561-568
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• 2006

WPS(Wearable Personal Station) for next generation PC can define as a core terminal of 'Ubiquitous Computing' that include information processing and network function and overcome spatial limitation in acquisition of new information. As a way to acquire significant dynamic gesture data of user from haptic devices, traditional gesture recognizer based on desktop-PC using wire communication module has several restrictions such as conditionality on space, complexity between transmission mediums(cable elements), limitation of motion and incommodiousness on use. Accordingly, in this paper, in order to overcome these problems, we implement hand gesture recognition system using fuzzy algorithm and neural network for Post PC(the embedded-ubiquitous environment using blue-tooth module and WPS). Also, we propose most efficient and reasonable hand gesture recognition interface for Post PC through evaluation and analysis of performance about each gesture recognition system. The proposed gesture recognition system consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data 2) Relational Database Management System(hereafter, RDBMS) module to segment significant gestures from input data and 3) 2 each different recognition modulo: fuzzy max-min and neural network recognition module to recognize significant gesture of continuous / dynamic gestures. Experimental result shows the average recognition rate of 98.8% in fuzzy min-nin module and 96.7% in neural network recognition module about significantly dynamic gestures.