• Journal of the Korean association of regional geographers
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• v.20 no.4
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• pp.357-378
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• 2014

The concern on new regional geography in Korea has emerged in the 1990s under the influence of paradigm shift of Western geography, that is, the withering of positivist geography and the introduction of grand social theories into geography. New regional geography in Korea also seems to have developed in the rapidly changing process of glocalization of capitalism which has accompanied with the transformation toward post-Fordism with high-tech innovation, development of transportation and communication technology with time-space compression, and increasing social and cultural mobility with change of identity. But it can be pointed out that discussion on methodology for regional geography in Korea has been shrunken since the mid 2000s, and there has been relatively little empirical research with synthetic approach to region. But more concern on methodology in terms of place, territory, network, scale, etc. rather than the concept of region itself has increased, and empirical researches on regions in specific fields of human geography have been promoted. It is argued that the traditional distinction between synthetic and analytic approaches seems no longer significant. But geographers need to extend the concept of region in relation to other diverse spatial concepts, and to purse simultaneously structural analysis on glocalization process and practical strategies responding positively to the process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.521-529
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• 2020

Forest fires are one of the most important environmental risks that have adverse effects on many aspects of life, such as the economy, environment, and health. The early detection, quick prediction, and rapid response of forest fires can play an essential role in saving property and life from forest fire risks. For the rapid discovery of forest fires, there is a method using meteorological data obtained from local sensors installed in each area by the Meteorological Agency. Meteorological conditions (e.g., temperature, wind) influence forest fires. This study evaluated a Data Mining (DM) approach to predict the burned area of forest fires. Five DM models, e.g., Stochastic Gradient Descent (SGD), Support Vector Machines (SVM), Decision Tree (DT), Random Forests (RF), and Deep Neural Network (DNN), and four feature selection setups (using spatial, temporal, and weather attributes), were tested on recent real-world data collected from Gyeonggi-do area over the last five years. As a result of the experiment, a DNN model using only meteorological data showed the best performance. The proposed model was more effective in predicting the burned area of small forest fires, which are more frequent. This knowledge derived from the proposed prediction model is particularly useful for improving firefighting resource management.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.227-238
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• 2006

Line density index(LDI) was developed to quantify a densely isothermal line rate as standard index in the ocean environment. Theoretical background on the LDI development process restricting index range 0 to 100 was described. And validation test was done for the LDI application condition that total line length is not greater than 1/10 of unit area. NOAA SST(Sea Surface Temperature) data were used for the experimental application of LDI in the South Sea of Korea. Using GIS, $0.1^{\circ}C$ isothermal lines were linearized as vector data form SST raster data, and unit area were built as polygon data. For the LDI calculation, spatial overlapping(line in polygon) was implemented. To analyze the effect of unit area size for the LDI distribution, two cases of unit area size were designed and descriptive statistics was calculated including performing normality test. The results showed no change of LDI's essential characteristics such as mean and normality except for the range of value, variance and standard deviation. Accordingly, it was found that complex structure of thermal front and even smaller scale of front width than unit area size could influence on the LDI distribution. Also, correlation analysis performed between LDI and difference of temperature(${\Delta}T^{\circ}C$), and horizontal thermal gradient(${\Delta}T^{\circ}C/km$) on the front was obtained from linear regression model. This obtained value was compared with the results from previous researches. Newly developed LDI can be used to compare the thermal front regions changing spatio-temporally in the ocean environment using absolute index value. It is considered to be significant to analyze the relationship between thermal front and marine environment or front and marine organisms in a quantitative approach described in this study.

• Journal of Digital Convergence
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• v.15 no.10
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• pp.327-337
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• 2017

The purpose of this study is to investigate patient satisfaction for the spacial environment of the rehabilitative facilities, and by this to examine areas of patients' needs to develop patient-friendly improvement in spacial environment. 308 patients were surveyed at physical therapy centers of 6 hospitals or rehabilitative institutions in Daejeon with patient satisfaction questionnaire. The spatial environment satisfaction was categorized into 7 constructs and the data were statistically analyzed and compared by t-test and ANOVA according to the patient characteristics. As a result, inter-floor transfer was found to be the area with the least satisfaction, especially in the in-patient group. Locating floor level was the second lowest satisfied construct. Comfort was relatively highly satisfied construct overall, but patients with neurological disease had less satisfaction than with musculoskeletal disease. Patients in 20's were less satisfied in wayfinding than 60's. Satisfaction for interior design was lower in subject in 50's than 70's. These findings can be used as evidences to improve spacial environment design for rehabilitative facilities to the better patient satisfaction.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.110-122
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• 2014

As multimedia technologies develop, three-dimensional (3D) technologies are attracting increasing attention from researchers. In particular, video quality assessment (VQA) has become a critical issue in stereoscopic image/video processing applications. Furthermore, a human visual system (HVS) could play an important role in the measurement of stereoscopic video quality, yet existing VQA methods have done little to develop a HVS for stereoscopic video. We seek to amend this by proposing a 3D visual attention (3DVA) model which simulates the HVS for stereoscopic video by combining multiple perceptual stimuli such as depth, motion, color, intensity, and orientation contrast. We utilize this 3DVA model for pooling on significant regions of very poor video quality, and we propose no-reference (NR) stereoscopic VQA (SVQA) method. We validated the proposed SVQA method using subjective test scores from our results and those reported by others. Our approach yields high correlation with the measured mean opinion score (MOS) as well as consistent performance in asymmetric coding conditions. Additionally, the 3DVA model is used to extract information for the region-of-interest (ROI). Subjective evaluations of the extracted ROI indicate that the 3DVA-based ROI extraction outperforms the other compared extraction methods using spatial or/and temporal terms.

• Journal of the Korean Geographical Society
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• v.41 no.1 s.112
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• pp.1-21
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• 2006

Abstract The purpose of this paper is to analyze production and innovation networks of manufacturers in the rural, long-live areas of Gangwon Jeju and to suggest an ideal regional development model of rural areas in the knowledge-based information age. For this purpose, we compared the areas of Gangwon Jeju with the long-live belt areas in the rural pan of the Honan region and Gwangju Jeonju, the urban part of Honam. The findings from the study are summarized as follows. Firstly, the stronger the local networks in terms of supply of the necessary input materials and labor, the more successful the manufacturing industry is in the given area. Secondly, the more diverse and lasting the networks (in terms of the location of manufacturers, local area and national area) and cooperation agents(businesses, research institutions, the local government, the central government) they have, the more prosperous the manufacturing industry is. These results indicate that the successful development model for rural areas requires that we take the approach of fostering potential innovation capabilities of total areas by fully utilizing their innate resources so as to create an internal cooperative network and further build extensive networks encompassing external entities to create a virtual innovation cluster.

• Journal of the Korean Geographical Society
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• v.49 no.2
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• pp.113-138
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• 2014

Despite the growing numbers of regional problems (e.g. conflicts between the state and localities, inter-local conflicts, etc.) associated with the state-led developmental projects, the Korean social sciences have been unable to offer satisfying explanations and solutions to the regional problems. This is mainly because the existing works, which have been taken captured by the assumptions of "methodological nationalism", significantly lack the socio-spatial understandings of the state actions and the relations between the state and localities, thereby seeing the issues of regional development mainly in terms of either the economic efficiency defined at the national scale, or the plan rationality of the national bureaucrats. With this problem orientation in mind, this paper aims to explore the ways in which the state and localities are interacting, conflicting and negotiating with one another through the mediation of the state-led developmental projects. Focusing on the developmental processes of Masan Export Processing Zone from the mid-1960s to the early 1970s, it examines the multi-scalar processes through which the state-led industrial complex developmental processes have been influenced by the complex and dynamic interactions among social forces and actors acting at diverse geographical scales (e.g. the global, national, local, urban, etc.). This analysis shows that the regional policies of the Korean developmental state were more heavily influenced by the interactions, contestations, and collaborations among social forces and actors, acting in and through the state, at various geographical scales, rather than by the economic and techno-bureaucratic rationality.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.1-8
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• 2017

In this paper, we introduce a technique to retarget human motion data to the humanoid body in a constrained environment. We assume that the given motion data includes detailed interactions such as holding the object by hand or avoiding obstacles. In addition, we assume that the humanoid joint structure is different from the human joint structure, and the shape of the surrounding environment is different from that at the time of the original motion. Under such a condition, it is also difficult to preserve the context of the interaction shown in the original motion data, if the retargeting technique that considers only the change of the body shape. Our approach is to separate the problem into two smaller problems and solve them independently. One is to retarget motion data to a new skeleton, and the other is to preserve the context of interactions. We first retarget the given human motion data to the target humanoid body ignoring the interaction with the environment. Then, we precisely deform the shape of the environmental model to match with the humanoid motion so that the original interaction is reproduced. Finally, we set spatial constraints between the humanoid body and the environmental model, and restore the environmental model to the original shape. To demonstrate the usefulness of our method, we conducted an experiment by using the Boston Dynamic's Atlas robot. We expected that out method can help the humanoid motion tracking problem in the future.

• Journal of the Korea Computer Graphics Society
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• v.26 no.1
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• pp.17-25
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• 2020

We present a novel multi-core CPU based parallel algorithm for the cell-connectivity information extraction algorithm, which is one of the preprocessing steps for volume rendering of unstructured grid data. We first check the synchronization issues when parallelizing the prior serial algorithm naively. Then, we propose a 3-step parallel algorithm that achieves high parallelization efficiency by removing synchronization in each step. Also, our 3-step algorithm improves the cache utilization efficiency by increasing the spatial locality for the duplicated triangle test process, which is the core operation of building cell-connectivity information. We further improve the efficiency of our parallel algorithm by employing a memory pool for each thread. To check the benefit of our approach, we implemented our method on a system consisting of two octa-core CPUs and measured the performance. As a result, our method shows continuous performance improvement as we add threads. Also, it achieves up to 82.9 times higher performance compared with the prior serial algorithm when we use thirty-two threads (sixteen physical cores). These results demonstrate the high parallelization efficiency and high cache utilization efficiency of our method. Also, it validates the suitability of our algorithm for large-scale unstructured data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.1-14
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• 2013

Annual average daily traffic (AADT) serves the important basic data in transportation sector. Despite of its importance, AADT is estimated through permanent traffic counts (PTC) at limited locations because of constraints in budget and so on. At most of locations, AADT is estimated using short-term traffic counts (STC). Though many studies have been carried out at home and abroad in an effort to enhance the accuracy of AADT estimate, the method to simplify average STC data has been adopted because of application difficulty. A typical model for estimating AADT is an adjustment factor application model which applies the monthly or weekly adjustment factors at PTC points (or group) with similar traffic pattern. But this model has the limit in determining the PTC points (or group) with similar traffic pattern with STC. Because STC represents usually 24-hour or 48-hour data, it's difficult to forecast a 365-day traffic variation. In order to improve the accuracy of traffic volume prediction, this study used the geostatistical approach called co-kriging and according to their reports. To compare results, using 3 methods : using adjustment factor in same section(method 1), using grouping method to apply adjustment factor(method 2), cokriging model using previous year's traffic data which is in a high spatial correlation with traffic volume data as a secondary variable. This study deals with estimating AADT considering time and space so AADT estimation is more reliable comparing other research.