• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1439-1441
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• 2003

The World Health Organisation has identified ‘Fluorosis’as a serious bone disease caused by groundwater. Though the fluoride content in groundwater is a natural phenomenon, when the permissible limit of fluoride is exceeded the consequences may be fatal. This study is identified areas of high fluoride content in the Dharmapuri district of India, which is one of the major districts severely affected by fluorosis (WHO). The approach to this problem is by using GIS as a tool to locate areas of high risk. Ground Water samples collected from 35 randomly located wells (open / bore wells) in the district were analysed for fluoride content. The results were compared with the standards of WHO (World Health Organisation ), ICMR (Indian Council of Medical Research ), BIS (Bureau of Indian Standard) and PHE (Public Health Engineering) and interpolated using IDW and spline methods using Arcview GIS 3.2 a. A computer based automated information system was developed in Arcview Avenue 3.2a, so as to enable the user to visit the risk areas at his desktop and to remediate measures as and when required.

• Journal of Oriental Neuropsychiatry
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• v.22 no.4
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• pp.77-86
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• 2011

Objectives : These days assaults and other natural and human disasters are increasing. But oriental medical treatment researches in Korea are limited in car accident PTSD patients only. Our object is to explore an oriental medical intervention model for the evidence-based approach to PTSD after diverse trauma including disasters. Methods : Domestic papers for Korean researches are obtained from oriental medical related journals by internet searching. International materials are obtained from PubMed searching and a publication from Department of Veterans' Affairs. After assorting searched articles into RCTs and non-RCTs, we analyzed the articles according to the elapsed time from trauma. Results : We confirmed that acupuncture, CBT, and PMR were effective in acute stage after traumatic event. And EMDR, EFT, and relaxation therapy were effective in chronic stage after traumatic event. Building on the findings, we proposed a model of oriental medicine for Disaster Mental Health. Conclusions : Analyzing previous researches about oriental medicine on PTSD, several interventions were confirmed the effectiveness on specific treatment stage. We could find the possibility of Oriental Medicine as a Disaster Mental Heath and proposed a model of Oriental medicine for Disaster Mental Health.

• Journal of Korea Multimedia Society
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• v.3 no.2
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• pp.157-163
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• 2000

Introduction of motion video including live video into network virtual reality systems makes virtual spaces more attractive. To handle live video in networked virtual reality s)'stems based on VRML, the scalability of networked virtual reality systems becomes very important on the internet where the performance of the network and the end systems varies dynamically. In this paper, a new quality control algorithm suitable for scalable networked virtual reality systems with live video capability is proposed. Our approach is to introduce the notion of the importance of presence (IoP) which represents the importance of objects in virtual spaces. According to IoPs, the degree of the deterioration of each object presentation will be determined in case of the starvation of system resources.

• Korean Journal of Remote Sensing
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• v.17 no.4
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• pp.319-334
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• 2001

Extracting primitives from imagery plays an important task in visual information processing since the primitives provide useful information about characteristics of the objects and patterns. The human visual system utilizes features without difficulty for image interpretation, scene analysis and object recognition. However, to extract and to analyze feature are difficult processing. The ultimate goal of digital image processing is to extract information and reconstruct objects automatically. The objective of this study is to develop robust method to achieve the goal of the image processing. In this study, an adaptive strategy was developed by implementing Gabor filters in order to extract feature information and to segment images. The Gabor filters are conceived as hypothetical structures of the retinal receptive fields in human vision system. Therefore, to develop a method which resembles the performance of human visual perception is possible using the Gabor filters. A method to compute appropriate parameters of the Gabor filters without human visual inspection is proposed. The entire framework is based on the theory of human visual perception. Digital images were used to evaluate the performance of the proposed strategy. The results show that the proposed adaptive approach improves performance of the Gabor filters for feature extraction and segmentation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.389-395
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• 2019

Unlike aerial images covering small region, satellite data show high potential to detect urban scale geospatial changes. The change detection using satellite images can be carried out using single image or stereo images. The single image approach is based on radiometric differences between two images of different times. It has limitations to detect building level changes when the significant occlusion and relief displacement appear in the images. In contrast, stereo satellite data can be used to generate DSM (Digital Surface Model) that contain information of relief-corrected objects. Therefore, they have high potential for the object change detection. Therefore, we carried out a study for the change detection over an urban area using stereo satellite data of two different times. First, the RPC correction was performed for two DSMs generation via stereo image matching. Then, D-DSM (Differential DSM) was generated by differentiating two DSMs. The D-DSM was used for the topographic change detection and the performance was checked by applying different height thresholds to D-DSM.

• Asia-Pacific Journal of Business
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• v.13 no.3
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• pp.1-18
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• 2022

Purpose - The purpose of this study is to take fitness APP users as the research object from the perspective of user experience to explore the influence of fitness APP user experience factors on product trust and purchase intention. Design/methodology/approach - The study collected data on 275 customers who had experience buying and using fitness apps. To test the hypothesis, SPSS 27.0 and AMOS 26.0 statistical packages were used based on the collected data. Findings - The results showed that the user experience factors (usefulness, ease to use, enjoyment, interaction) of fitness APP and the relationship between product trust had a positive effect, and product trust had a positive effect on purchase intention. In addition, exercise experience, showed a moderating effect in the relationship between the usefulness, easy to use of user experience and product trust. Research implications or Originality - This study provided research model among user experience factors of fitness APP, product trust and purchase intention. This study can help sports and fitness companies with product optimization and marketing decisions.

• Journal of Astronomy and Space Sciences
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• v.38 no.2
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• pp.119-134
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• 2021

The data set collected during the night of the discovery of a minor body constitutes a too-short arc (TSA), resulting in failure of the differential correction procedure. This makes it necessary to recover the object during subsequent nights to gather more observations that will allow a preliminary orbit to be calculated. In this work, we present a recovery technique based on sampling the admissible region (AdRe) by the constrained Delaunay triangulation. We construct the AdRe in its topocentric and geocentric variants, using logarithmic and exponential metrics, for the following near-Earth-asteroids: (3122) Florence, (3200) Phaethon, 2003 GW, (1864) Daedalus, 2003 BH84 and 1977 QQ5; and the main-belt asteroids: (1738) Oosterhoff, (4690) Strasbourg, (555) Norma, 2006 SO375, 2003 GE55 and (32811) Apisaon. Using our sampling technique, we established the ephemeris region for these objects, using intervals of observation from 25 minutes up to 2 hours, with propagation times from 1 up to 47 days. All these objects were recoverable in a field of vision of 95' × 72', except for (3122) Florence and (3200) Phaethon, since they were observed during their closest approach to the Earth. In the case of 2006 SO375, we performed an additional test with only two observations separated by 2 minutes, achieving a recovery of up to 28 days after its discovery, which demonstrates the potential of our technique.

• Journal of Information Technology Services
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• v.21 no.6
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• pp.53-72
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• 2022

As a trend of modern service industry, self-service has been widely concerned by all walks of life, but there is a lack of literature on systematic management of the overall research in this field. Recently, people's lifestyle has been forced to change due to the influence of COVID-19, while there have been some changes in the field of self-service research. Based on the Web of Science data source, this study takes the literature of self-service field before and after the outbreak of COVID-19 as the research object, and summarizes the development process, research status and future research trend of self-service field through the Citespace visualization tool. The research shows that firstly, academic circles continue to be enthusiastic about self-service field research, cooperation between countries is becoming more and more diversified. Secondly, the communication between researchers is becoming more and more intensive, and the cooperation between different disciplines gradually becomes the mainstream. Third, related research gradually shifted to the practical application of technology, the research perspective gradually shifted from the initial traditional retail perspective industries such as tourism services. Finally, the role of customer experience and participation behavior in self-service process is gradually emphasized.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.142-146
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• 2023

We present a method for generating 3D structures and rendering objects by combining VAE (Variational Autoencoder) and GAN (Generative Adversarial Network). This approach focuses on generating and rendering 3D models with improved quality using residual learning as the learning method for the encoder. We deep stack the encoder layers to accurately reflect the features of the image and apply residual blocks to solve the problems of deep layers to improve the encoder performance. This solves the problems of gradient vanishing and exploding, which are problems when constructing a deep neural network, and creates a 3D model of improved quality. To accurately extract image features, we construct deep layers of the encoder model and apply the residual function to learning to model with more detailed information. The generated model has more detailed voxels for more accurate representation, is rendered by adding materials and lighting, and is finally converted into a mesh model. 3D models have excellent visual quality and accuracy, making them useful in various fields such as virtual reality, game development, and metaverse.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.670-684
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• 2024

3D Cross-Modal Retrieval (3DCMR) is a task that retrieves 3D objects regardless of modalities, such as images, meshes, and point clouds. One of the most prominent methods used for 3DCMR is the Cross-Modal Center Loss Function (CLF) which applies the conventional center loss strategy for 3D cross-modal search and retrieval. Since CLF is based on center loss, the center features in CLF are also susceptible to subtle changes in hyperparameters and external inferences. For instance, performance degradation is observed when the batch size is too small. Furthermore, the Mean Squared Error (MSE) used in CLF is unable to adapt to changes in batch size and is vulnerable to data variations that occur during actual inference due to the use of simple Euclidean distance between multi-modal features. To address the problems that arise from small batch training, we propose a Noisy Center Loss (NCL) method to estimate the optimal center features. In addition, we apply the simple Siamese representation learning method (SimSiam) during optimal center feature estimation to compare projected features, making the proposed method robust to changes in batch size and variations in data. As a result, the proposed approach demonstrates improved performance in ModelNet40 dataset compared to the conventional methods.