• Journal of the Korea Computer Graphics Society
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• v.7 no.1
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• pp.1-9
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• 2001

We present a scheme and a data structure that decompose the space into adaptive-sized cells to improve the visualization of soft objects. Soft objects are visualized through the evaluation of the field functions at every point of the space. According to the propsed scheme, the affecting soft objects for a point in the space is searched through the data structure called interval tree based on the bounding volume of the components, which represent a soft object whose defining primitive(skeleton) is a simple geometric object such as point or line segment. The bounding volume of each component is generated with respect to the radius of a local field function of the component, threshold value, and the relations between the components and other neighboring components. The proposed scheme can be used in many applications for soft objects such as modeling and rendering, especially in interactive modeling process.

• Journal of Korea Multimedia Society
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• v.12 no.9
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• pp.1342-1350
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• 2009

Until today, the uses of digital display system mostly included demonstration, observation, and exhibition of simple images. The strengths were that the images that changes in line with the music played could be reinterpreted as a different work. Also, it could stimulate the sensibility of the users. However, the range of the uses of the system is very limited and users could easily lose their interest. Therefore, it is necessary to develop a system that could continuously induce and motivate user interaction. Therefore, the RSS based digital folding screen system proposed by this paper has an objective of being used as an interactive media system which overcome the limitations of former eight-sided folding screen used for simple observation purposes. It also applied the main function of RSS in which the user could collect and read newly registered messages without visiting the blogs or corresponding websites. Therefore, it is capable of sending the information needed by the user. Generally, we can observe the contents for mere observation purposes and when necessary, it could also be utilized for advertisement or exhibition purposes. It could also be used as a information transfer system in public facilities.

• Women's Health Nursing
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• v.26 no.3
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• pp.205-212
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• 2020

Purpose: This study aimed to identify the components of preterm birth (PTB) through women's personal narratives and to visualize clinical symptom expressions (CSEs). Methods: The participants were 11 women who gave birth before 37 weeks of gestational age. Personal narratives were collected by interactive unstructured storytelling via individual interviews, from August 8 to December 4, 2019 after receiving approval of the Institutional Review Board. The textual data were converted to PDF and analyzed using the MAXQDA program (VERBI Software). Results: The participants' mean age was 34.6 (±2.98) years, and five participants had a spontaneous vaginal birth. The following nine components of PTB were identified: obstetric condition, emotional condition, physical condition, medical condition, hospital environment, life-related stress, pregnancy-related stress, spousal support, and informational support. The top three codes were preterm labor, personal characteristics, and premature rupture of membrane, and the codes found for more than half of the participants were short cervix, fear of PTB, concern about fetal well-being, sleep difficulty, insufficient spousal and informational support, and physical difficulties. The top six CSEs were stress, hydramnios, false labor, concern about fetal wellbeing, true labor pain, and uterine contraction. "Stress" was ranked first in terms of frequency and "uterine contraction" had individual attributes. Conclusion: The text network analysis of narratives from women who gave birth preterm yielded nine PTB components and six CSEs. These nine components should be included for developing a reliable and valid scale for PTB risk and stress. The CSEs can be applied for assessing preterm labor, as well as considered as strategies for students in women's health nursing practicum.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.3
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• pp.11-16
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• 2004

Recently, collaborative works are increased more and more over the distributed heterogeneous computing environments. The availability of high-speed wide-area networks has also enabled collaborative multimedia applications such as video conferencing, distributed interactive simulation and collaborative visualization. Distributed high performance computing and collaborative multimedia applications, it is extremely important to efficiently perform group communication over a heterogeneous network. Typical group communication patterns are broadcast and Multicast. Heuristic algorithms such as FEF, ECEF, look-ahead make up the message transmission tree for the broadcast and multicast over the distributed heterogeneous systems. But, there are some shortcomings because these select the optimal solution at each step, it may not be reached to the global optimum In this paper, we propose a new heuristic algerian that constructs tree for efficiently collective communication over the previous heterogeneous communication model which has heterogenity in both node and network. The previous heuristic algorithms my result in a locally optimal solution, so we present more reasonable and available criterion for choosing edge. Through the performance evaluation over the various communication cost, improved heuristic algorithm we proposed have less completion time than previous algorithms have, especially less time complexity than look-ahead approach.

• Structural Engineering and Mechanics
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• v.7 no.6
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• pp.589-599
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• 1999

This paper presents the development and applications of the software package JIFEX, a new finite element system which can be used for structural analysis and optimum design by the modern computer hardware and software technologies such as MS Windows95/NT and Pentium PC platforms. The complete system of JIFEX is programmed with $C/C^{++}$ language to make full use of advanced facilities of MS Windows95/NT. In the system, the finite element data pre-processing, based on the most popular CAD package AutoCAD (R13, R14), has been implemented, so that the finite element modeling could be integrated with geometric modeling of CAD. The system not only has interactive graphics facility for data post-processing, but also realizes the real-time computing visualization by means of the Dynamic Data Exchange (DDE) technique. Running on the Pentium computers, JIFEX can solve large-scale finite element analysis problems such as the ones with more than 60000 nodes in the finite element model.

• Journal of Korean Neurosurgical Society
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• v.65 no.5
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• pp.697-709
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• 2022

Objective : The present study aimed to identify the function of ischemic stroke (IS) patients' peripheral blood and its role in IS, explore the pathogenesis, and provide direction for clinical research progress by comprehensive bioinformatics analysis. Methods : Two datasets, including GSE58294 and GSE22255, were downloaded from Gene Expression Omnibus database. GEO2R was utilized to obtain differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed using the database annotation, visualization and integrated discovery database. The protein-protein interaction (PPI) network of DEGs was constructed by search tool of searching interactive gene and visualized by Cytoscape software, and then the Hub gene was identified by degree analysis. The microRNA (miRNA) and miRNA target genes closely related to the onset of stroke were obtained through the miRNA gene regulatory network. Results : In total, 36 DEGs, containing 27 up-regulated and nine down-regulated DEGs, were identified. GO functional analysis showed that these DEGs were involved in regulation of apoptotic process, cytoplasm, protein binding and other biological processes. KEGG enrichment analysis showed that these DEGs mediated signaling pathways, including human T-cell lymphotropic virus (HTLV)-I infection and microRNAs in cancer. The results of PPI network and cytohubba showed that there was a relationship between DEGs, and five hub genes related to stroke were obtained : SOCS3, KRAS, PTGS2, EGR1, and DUSP1. Combined with the visualization of DEG-miRNAs, hsa-mir-16-5p, hsa-mir-181a-5p and hsa-mir-124-3p were predicted to be the key miRNAs in stroke, and three miRNAs were related to hub gene. Conclusion : Thirty-six DEGs, five Hub genes, and three miRNA were obtained from bioinformatics analysis of IS microarray data, which might provide potential targets for diagnosis and treatment of IS.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.4
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• pp.414-420
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• 2018

The digital convergence looking for new ways to engage visitors by superimposing virtual content on projection over the real world captured media contents. This paper propose the Light ID based interactive 3D immersive exhibition things view using HMD AR technology. This approach does not required to add any additional infrastructure to be built-in to enable service and uses the installed Lighting or displays devices in the exhibit area. In this approach, the Light ID can be used as a Location Identifier and communication medium to access the content unlike the QR Tag which supports provide the download information through web interface. This utilize the advantages of camera based optical wireless communication (OWC) to receive the media content on smart device to deliver immersive 3D content visualization using AR. The proposed exhibition method is emulated on GALAXY S8 smart phone and the visual performance is evaluated for Jeonju Hanok Village. The experimental results shows that the proposed method can give immersive 3D view for exhibit things in real-time.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.722-729
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• 2010

Prediction problems are widely used in medical domains. For example, computer aided diagnosis or prognosis is a key component in a CDSS (Clinical Decision Support System). SVMs with nonlinear kernels like RBF kernels, have shown superior accuracy in prediction problems. However, they are not preferred by physicians for medical prediction problems because nonlinear SVMs are difficult to visualize, thus it is hard to provide intuitive interpretation of prediction results to physicians. Nomogram was proposed to visualize SVM classification models. However, it cannot visualize nonlinear SVM models. Localized Radial Basis Function (LRBF) was proposed which shows comparable accuracy as the RBF kernel while the LRBF kernel is easier to interpret since it can be linearly decomposed. This paper presents a new tool named VRIFA, which integrates the nomogram and LRBF kernel to provide users with an interactive visualization of nonlinear SVM models, VRIFA visualizes the internal structure of nonlinear SVM models showing the effect of each feature, the magnitude of the effect, and the change at the prediction output. VRIFA also performs nomogram-based feature selection while training a model in order to remove noise or redundant features and improve the prediction accuracy. The area under the ROC curve (AUC) can be used to evaluate the prediction result when the data set is highly imbalanced. The tool can be used by biomedical researchers for computer-aided diagnosis and risk factor analysis for diseases.

• Design Convergence Study
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• v.15 no.6
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• pp.195-214
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• 2016

Predictive analysis is based on a probabilistic learning algorithm called pattern recognition or machine learning. Therefore, if users want to extract more information from the data, they are required high statistical knowledge. In addition, it is difficult to find out data pattern and characteristics of the data. This study conducted statistical data analyses and visual data analyses to supplement prediction analysis's weakness. Through this study, we could find some implications that haven't been found in the previous studies. First, we could find data pattern when adjust data selection according as splitting criteria for the decision tree method. Second, we could find what type of data included in the final prediction model. We found some implications that haven't been found in the previous studies from the results of statistical and visual analyses. In statistical analysis we found relation among the multivariable and deducted prediction model to predict high box office performance. In visualization analysis we proposed visual analysis method with various interactive functions. Finally through this study we verified final prediction model and suggested analysis method extract variety of information from the data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.2963-2978
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• 2017

The Top-K query is currently played a key role in a wide range of road network, decision making and quantitative financial research. In this paper, a Top-K recommendation algorithm is proposed to solve the cold-start problem and a tag generating method is put forward to enhance the semantic understanding of the OLAP session. In addition, a recommendation system for OLAP sessions called "OLAP4R" is designed using collaborative filtering technique aiming at guiding the user to find the ultimate goals by interactive queries. OLAP4R utilizes a mixed system architecture consisting of multiple functional modules, which have a high extension capability to support additional functions. This system structure allows the user to configure multi-dimensional hierarchies and desirable measures to analyze the specific requirement and gives recommendations with forthright responses. Experimental results show that our method has raised 20% recall of the recommendations comparing the traditional collaborative filtering and a visualization tag of the recommended sessions will be provided with modified changes for the user to understand.