• Progress in Medical Physics
• /
• v.21 no.2
• /
• pp.153-164
• /
• 2010

To determine the clinical target volumes considering vascularity and cellularity of tumors, the software was developed for mapping of the analyzed biological clinical target volumes on anatomical images using regional cerebral blood volume (rCBV) maps and apparent diffusion coefficient (ADC) maps. The program provides the functions for integrated registrations using mutual information, affine transform and non-rigid registration. The registration accuracy is evaluated by the calculation of the overlapped ratio of segmented bone regions and average distance difference of contours between reference and registered images. The performance of the developed software was tested using multimodal images of a patient who has the residual tumor of high grade gliomas. Registration accuracy of about 74% and average 2.3 mm distance difference were calculated by the evaluation method of bone segmentation and contour extraction. The registration accuracy can be improved as higher as 4% by the manual adjustment functions. Advanced MR images are analyzed using color maps for rCBV maps and quantitative calculation based on region of interest (ROI) for ADC maps. Then, multi-parameters on the same voxels are plotted on plane and constitute the multi-functional parametric maps of which x and y axis representing rCBV and ADC values. According to the distributions of functional parameters, tumor regions showing the higher vascularity and cellularity are categorized according to the criteria corresponding malignant gliomas. Determined volumes reflecting pathological and physiological characteristics of tumors are marked on anatomical images. By applying the multi-functional images, errors arising from using one type of image would be reduced and local regions representing higher probability as tumor cells would be determined for radiation treatment plan. Biological tumor characteristics can be expressed using image registration and multi-functional parametric maps in the developed software. The software can be considered to delineate clinical target volumes using advanced MR images with anatomical images.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.43 no.5 s.311
• /
• pp.89-100
• /
• 2006

The carotid intima-media thickness (IMT) is very important, because the severity of it is an independent predictor of transient cerebral ischemia, stroke, and coronary events such as myocardial infarction. The conventional image processing to measure the IMT has not been satisfactory, because the methods have relied on the manual section drawing and a regional segmentation by differential estimation. We propose a new image processing technology effective to extract features from the carotid artery image whose pixels have the directional vector properties with composed color distribution. The technique we presented here is not by differential variation but by verification of the layer properties of carotid artery image. Iterated vertical and horizontal analysis and segmentation of the IMT image show the vector characteristics. This new technique makes it possible to cluster the layers statistically, and to classify mathematical correlation between regions and resulting in correct measurements of thickness and its variation. The advantages and effectiveness of this approach are applicable to region process and character extraction of such a vector image.

• Journal of the Korean Geographical Society
• /
• v.49 no.3
• /
• pp.405-422
• /
• 2014

Two important issues in hedonic model are to specify accurate model and delineate submarkets. While the former has experienced much improvement over recent decades, the latter has received relatively little attention. However, the accuracy of estimates from hedonic model will be necessarily reduced when the analysis does not adequately address market segmentation which can capture the spatial scale of price formation process in real estate. Placing emphasis on improvement of performance in hedonic model, this paper tried to segment real estate markets in Gangnam-gu and Jungrang-gu, which correspond to most heterogeneous and homogeneous ones respectively in 25 autonomous districts of Seoul. First, we calculated variable coefficients from mixed geographically weighted regression model (mixed GWR model) as input for clustering, since the coefficient from hedonic model can be interpreted as shadow price of attributes constituting real estate. After that, we developed a spatially constrained data-driven methodology to preserve spatial contiguity by utilizing the SKATER algorithm based on a minimum spanning tree. Finally, the performance of this method was verified by applying a multi-level model. We concluded that submarket does not exist in Jungrang-gu and five submarkets centered on arterial roads would be reasonable in Gangnam-gu. Urban infrastructure such as arterial roads has not been considered an important factor for delineating submarkets until now, but it was found empirically that they play a key role in market segmentation.

• Journal of Korea Water Resources Association
• /
• v.56 no.4
• /
• pp.245-259
• /
• 2023

The agricultural reservoir is a critical water supply system in South Korea, providing approximately 60% of the agricultural water demand. However, the reservoir faces several issues that jeopardize its efficient operation and management. To address this issues, we propose a novel deep-learning-based water level recognition model that uses CCTV image data to accurately estimate water levels in agricultural reservoirs. The model consists of three main parts: (1) dataset construction, (2) image segmentation using the U-Net algorithm, and (3) CCTV-based water level recognition using either CNN or ResNet. The model has been applied to two reservoirs G-reservoir and M-reservoir with observed CCTV image and water level time series data. The results show that the performance of the image segmentation model is superior, while the performance of the water level recognition model varies from 50 to 80% depending on water level classification criteria (i.e., classification guideline) and complexity of image data (i.e., variability of the image pixels). The performance of the model can be improved if more numbers of data can be collected.

• Journal of Korean Society for Geospatial Information Science
• /
• v.23 no.4
• /
• pp.25-33
• /
• 2015

The study of ecosystem assessment(ES) is based on land cover information, and primarily it is performed at the global scale. However, these results as data for decision making have a limitation at the aspects of range and scale to solve the regional issue. Although the Ministry of Environment provides available land cover data at the regional scale, it is also restricted in use due to the intrinsic limitation of on screen digitizing method and temporal and spatial difference. This study of objective is to generate UAV land cover map. In order to classify the imagery, we have performed resampling at 5m resolution using UAV imagery. The results of object-based image segmentation showed that scale 20 and merge 34 were the optimum weight values for UAV imagery. In the case of RapidEye imagery;we found that the weight values;scale 30 and merge 30 were the most appropriate at the level of land cover classes for sub-category. We generated land cover imagery using example-based classification method and analyzed the accuracy using stratified random sampling. The results show that the overall accuracies of RapidEye and UAV classification imagery are each 90% and 91%.

• Journal of the Korean Regional Science Association
• /
• v.34 no.4
• /
• pp.61-74
• /
• 2018

This study aims to analyze the convergence change of smart city industries in Korea. Industries of Smart city can be defined ICTs and Knowledge embedded construction industry. The input output model and structural path analysis have been done using the input output tables published by Bank of Korea in 1980 and 2014. GDP deflator was applied to the input output tables. 403 industries were reclassified into 27 industries and 8 industries categories: Agriculture and Mining(AM), Non-IT Manufacture(NITM), IT Manufacture(ITM), Energy Supply(EnS), Construction as smart city(C), IT Service(ITS), Knowledge Service(KS), Etc. Service(EtS). The results are as follows; First, the input output coefficient analysis showed that The information and communication service industry(ITS) and the energy supply industry(EnS) have increased input to the construction industry(C). On the other hands, knowledge service industry(KS) and etc. service industries(EtS) decreased. Second, the multiplier analysis revealed that construction industry(C) led by smart city had a great influence on ITS, EnS, ITM and NITM directly and indirectly. Furthermore, The IT industry had the biggest change from 1980 to 2014. Third, the smart city industry has created a new convergence of 117, and it has been leading to segmentation of the structure. Change of convergence has been proceeding mainly in the ITS and EnS, NITM, ITM industries.

• Journal of Integrative Natural Science
• /
• v.11 no.3
• /
• pp.139-147
• /
• 2018

Hippocampal atrophy is a well-established imaging biomarker of Alzheimer disease (AD). However, hippocampus is a non-homogenous structure with cytoarchitecturally and functionally distinct sub-regions or subfield, with each region performing distinct functions. Certain regions of the subfield have shown selective vulnerability to AD. Here, we are interested in studying the effects of normal aging and mild cognitive impairment on these sub-regional volumes. With a reliable automated segmentation technique, we segmented these subregions of the hippocampus in 101 cognitively normal (CN), 135 early mild cognitive impairment (EMCI), 67 late mild cognitive impairment (LMCI) and 48 AD subjects. Thereby, dividing the hippocampus into hippocampal tail (tail), subiculum (SUB), cornu ammonis 1 (CA1), hippocampal fissure (fissure), presubiculum (PSUB), parasubiculum (ParaSUB), molecular layer (ML), granule cells/molecular layer/dentate gyrus (GCMLDG), cornu ammonis 3(CA3), cornu ammonis 4(CA4), fimbria and hippocampal-amygdala transition area (HATA). In this cross sectional study of 351 ADNI subjects, no differences in terms of age, gender, and years of education were observed among the groups. Though, the groups had statistically significant differences (p < 0.05 after the multiple comparison correction) in the Mini-Mental State Examination (MMSE) scores. There was asymmetrical volume loss in the early stages of AD with the left hemisphere showing volume loss in regions that were unaffected in the right hemisphere. Bilateral parasubiculum, right cornu ammonis 1, 3 and 4, right fimbria and right HATA regions did not show any volume loss till the late MCI stages. Our findings suggest that the hippocampal subfield regions are selectively vulnerable to AD and also that these vulnerabilities are asymmetrical especially during the early stages of AD.

• Journal of Distribution Science
• /
• v.17 no.3
• /
• pp.49-55
• /
• 2019

Purpose - The purpose of this study was to develop a motivation scale for participation sport tourism and to produce implications of potential use of MSPST for sport tourism distribution emphasizing the needs of sport tourists and the functions required to satisfy those needs. Research design, data, and methodology - The Motivation Scale for Participation Sport Tourism (MSPST) was developed in three stages. A literature review generated 8 dimensions with 42-items in the first stage. Second, an expert review phase refined the initial item pool, which resulted in 35 items. Result - Exploratory factor analysis was employed to produce an 8-factor, 28 item pool. The reduced version was confirmed via structural equation modeling, indicating an acceptable model of fit. The final MSPST consisted of 8 dimensions of motivation, including friendship, family, solitude, challenges, intrinsic, achievement, nature, and competition. Conclusions - The MSPST is a valid and reliable scale of tourists' motives for participating in sports. The results supported the suggested measures of motives associated with participation sport tourism regarding construct, convergent and discriminant validity. A body of knowledge about motives provides insights for policy-makers seeking to support distributional industries for sport tourism and finally to promote economy on both regional and national levels.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.12
• /
• pp.4292-4307
• /
• 2021

For the research field of night infrared surveillance video, the target imaging in the video is easily affected by the light due to the characteristics of the active infrared camera and the classical ViBe algorithm has some problems for moving target extraction because of background misjudgment, noise interference, ghost shadow and so on. Therefore, an improved ViBe algorithm (I-ViBe) for moving target extraction in night infrared surveillance video is proposed in this paper. Firstly, the video frames are sampled and judged by the degree of light influence, and the video frame is divided into three situations: no light change, small light change, and severe light change. Secondly, the ViBe algorithm is extracted the moving target when there is no light change. The segmentation factor of the ViBe algorithm is adaptively changed to reduce the impact of the light on the ViBe algorithm when the light change is small. The moving target is extracted using the region growing algorithm improved by the image entropy in the differential image of the current frame and the background model when the illumination changes drastically. Based on the results of the simulation, the I-ViBe algorithm proposed has better robustness to the influence of illumination. When extracting moving targets at night the I-ViBe algorithm can make target extraction more accurate and provide more effective data for further night behavior recognition and target tracking.

• Asia Marketing Journal
• /
• v.17 no.4
• /
• pp.63-88
• /
• 2016

K-Pop is hugely promoted offline/online in East Asia, while efforts to promote it elsewhere are kept to a minimum. Whilst addressing the role of digital marketing in the promotion of K-Pop in the Brazilian music industry this study aims to demonstrate that K-pop will provide its audience with a unique and engaging experience if it thinks globally and acts locally in its marketing and communication strategies. A survey of K-Pop's world fan base was carried out online with 1,074 fans to determine the validity of the hypothesis. The results have demonstrated the need to adapt global and intercultural strategies to local markets with increasing brand awareness through utilizing digital marketing. For example, to increase K-Pop's popularity and market share in Brazil, it is not required to sing in Brazilian Portuguese, contrary to what might be perceived but fully singing in English would help breaking into the market dominated by domestic music as songs would have a higher probability to be included in the international soundtrack of a Brazilian telenovela and promote the K-Pop artist not only across Brazil but also give the artist exposure in all the markets the Brazilian telenovela is exported to, opening an entry door to those markets. K-Pop audience segmentation and psychographic profiling is crucial to the understanding of each market's consumer's preferences, likes, dislikes and their buying habits as it was proven through Brazil's digital media, social media, digital music market and K-Pop market analysis within the global context of the study. It should be also considered that brand extensions are not standard everywhere and that there are cultures where different product categories are not directly associated with its main corporate owner which requires extensive local market knowledge to succeed. The primary and secondary data research that we conducted for this study intended to demonstrate that K-Pop can be successful in Brazil and in Latin America and increase their local and regional market share if digital marketing and communication strategies are tailored to each individual market.