• Journal of Industrial Convergence
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• v.20 no.10
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• pp.61-69
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• 2022

Posttraumatic growth literature has been rapidly expanding in multiple academic disciplines. Purpose of this study is to examine the knowledge structure of posttraumatic growth utilizing a network analysis. Papers published between 1996 and 2018 were searched on the Web of Science, focusing on terms related to posttraumatic growth. One thousand six-hundred and fifty-nine keywords were published 6,343 times in 1,780 papers; thus, a total of 322 keywords (5,195 appearances) were selected for the final analysis. The network analysis and network visualization tool used were NodeXL and PFnet, respectively. The keywords which appeared the most frequently were "Posttraumatic growth," followed by "Posttraumatic Stress Disease," "Cancer," and "Trauma." A total of 322 nodes have been reduced to 175 nodes and divided into a total of five groups. The five groups were "Posttraumatic Growth in Cancer, Chronic/Serious Illness, and Disability," "Posttraumatic Growth-related Psychological Variables and Psychotherapy," "Posttraumatic Growth in the Context of Death," "Cognitive Mechanisms of Posttraumatic Growth," and "Vicarious Posttraumatic Growth." This study provides a systematic overview on the knowledge structure of posttraumatic growth by quantitatively network analysis.

• Genomics & Informatics
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• v.19 no.4
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• pp.49.1-49.11
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• 2021

Nowadays, Genomic data constitutes one of the fastest growing datasets in the world. As of 2025, it is supposed to become the fourth largest source of Big Data, and thus mandating adequate high-performance computing (HPC) platform for processing. With the latest unprecedented and unpredictable mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the research community is in crucial need for ICT tools to process SARS-CoV-2 RNA data, e.g., by classifying it (i.e., clustering) and thus assisting in tracking virus mutations and predict future ones. In this paper, we are presenting an HPC-based SARS-CoV-2 RNAs clustering tool. We are adopting a data science approach, from data collection, through analysis, to visualization. In the analysis step, we present how our clustering approach leverages on HPC and the longest common subsequence (LCS) algorithm. The approach uses the Hadoop MapReduce programming paradigm and adapts the LCS algorithm in order to efficiently compute the length of the LCS for each pair of SARS-CoV-2 RNA sequences. The latter are extracted from the U.S. National Center for Biotechnology Information (NCBI) Virus repository. The computed LCS lengths are used to measure the dissimilarities between RNA sequences in order to work out existing clusters. In addition to that, we present a comparative study of the LCS algorithm performance based on variable workloads and different numbers of Hadoop worker nodes.

• Journal of Korea Entertainment Industry Association
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• v.13 no.4
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• pp.119-129
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• 2019

Traditional speech training in acting education focused on the technical aspects of expressing the lines such as finding long/short syllables in the word, exercising articulation of consonants and vowels, and practicing diction etc. There was a limit on this education to transform written words to vivid verbal words. The lines become live when the actor sees the concrete mental images hidden in the words while speaking the lines. I will bring the knowledge of cognitive brain science and NLP(Neural Linguistic Programming) to investigate what mental images are and why mental images are fundamental elements of thought and emotion. In addition to that, I will examine how the muscles of the body react in the process of visualization of delicate mental images (subordinate form) and how to use the responsive muscles to express speaking materials such as intensity, pause, pitch, intonation etc. Conclusion, I will enumerate the obstacles encountered by actors in the course of practicing mental images, and suggest 'activation of breathing' as a thesis of the follow-up paper to eliminate those obstacles. This process, I intend to make mental images to be the concrete and practical information that can be applied to speak the dialogue in the play.

• Korean Chemical Engineering Research
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• v.55 no.5
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• pp.646-651
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• 2017

Size and shape of carbon nanotube (CNT) agglomerates in the dilute phase of a bubbling fluidized bed ($0.15m\;i.d{\times}2.6m\;high$) have been determined by the laser sheet technique. Axial solid holdup distribution of the CNT particles showed S curve with dense phase and dilute phase in bubbling fluidization regime. Heywood diameter and Feret diameter of the CNT agglomerates in the dilute phase of bubbling fluidized bed increased with increasing gas velocity. The CNT particle number in the agglomerates increased with increasing of gas velocity. Aspect ratio increased and circularity, roundness and solidity decreased with increasing of gas velocity. A possible mechanism of agglomerates formation was proposed based on the obtained information.

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.19-25
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• 2017

In this paper, we designed and implemented IoT sensors based badminton motion analysis and training system that can be readily used by badminton players with PC. Unlike the traditional badminton training system which uses signals of the flags by coach, the proposed electronic training system used IoT sensors to automatically detect and analysis the motions for badminton players. The proposed badminton motion analysis and training system has the advantage with low power, because it communicates with the program through BLE communication. The badminton motion analysis system automatically measures the training time according to the player's movement, so it is possible to collect objective result data with less errors than the conventional flag signal based method by coach. In this paper, training data of 5 athletes were collected and it provides the feedback function through the visualization of each section of the training results by the players which can enable the effective training. For the weakness section of each player, the coach and the player can selectively and repeatedly perform the training function with the proposed training system. Based on this, it is possible to perform the repeated training on weakness sections and they can improve the response speed for these sections. Continuous research is expected to be able to compare more various players' agility and physical fitness.

• The KIPS Transactions:PartB
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• v.12B no.5 s.101
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• pp.543-552
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• 2005

This paper proposes the extraction of coronary arteries based on DSA(Digital Subtraction Angiography) through a texture analysis of background in the angiography. DSA is a well established modality for the visualization of coronary arteries. DSA involves the subtraction of a mask image - an image of the heart before injection of contrast medium - from live image. However, this technique is sensitive to the movement of background and can result to a wrong detection by the variance of background gray-level intensity between two images. Therefore, this paper solves a structural problem resulted from a background movement bV selecting an image which has the least difference of movement through an analysis of the similarity of background texture and proposes a method to extract only the blood vessel efficiently through local gray-level correction of the selected image. Using the coronary angiogram of 5 patients clinical data, we proved that the proposed method has the lower false-detection rate, approximately $2\%$, and the higher accuracy than the existing methods.

• Journal of Contemporary Eastern Asia
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• v.18 no.1
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• pp.7-29
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• 2019

This study describes an approach for comparative bibliometric analysis of scientific publications related to (i) individual or several departments comprising a university, and (ii) broader integrated subject areas using multiple disciplinary schemes. It uses a custom dataset of scientific publications (ca. 15,000 articles and reviews, published during 2009-2013, and recorded in the Web of Science Core Collections) with author affiliations to the research departments, dedicated to science, technology, engineering, mathematics, and medicine (STEMM), of a comprehensive university. The dataset was subjected, at first, to the department level and discipline level analyses using the newly available KAKEN-L3 classification (based on MEXT/JSPS Grants-in-Aid system), hierarchical clustering, correspondence analysis to decipher the major departmental and disciplinary clusters, and visualization of the department-discipline relationships using two-dimensional stacked bar diagrams. The next step involved the creation of subsets covering integrated subject areas and a comparative analysis of departmental contributions to a specific area (medical, health and life science) using several disciplinary schemes: Essential Science Indicators (ESI) 22 research fields, SCOPUS 27 subject areas, OECD Frascati 38 subordinate research fields, and KAKEN-L3 66 subject categories. To illustrate the effective use of the science mapping techniques, the same subset for medical, health and life science area was subjected to network analyses for co-occurrences of keywords, bibliographic coupling of the publication sources, and co-citation of sources in the reference lists. The science mapping approach demonstrates the ways to extract information on the prolific research themes, the most frequently used journals for publishing research findings, and the knowledge base underlying the research activities covered by the publications concerned.

• The Journal of Korean Medicine
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• v.43 no.1
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• pp.73-86
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• 2022

Objectives: In the health care industry, the influence of online reviews is growing. As medical services are provided mainly by providers, those services have been managed by hospitals and clinics. However, direct promotions of medical services by providers are legally forbidden. Due to this reason, consumers, like patients and clients, search a lot of reviews on the Internet to get any information about hospitals, treatments, prices, etc. It can be determined that online reviews indicate the quality of hospitals, and that analysis should be done for sustainable hospital marketing. Method: Using a Python-based crawler, we collected reviews, written by real patients, who had experienced Korean medicine, about more than 14,000 reviews. To extract the most representative words, reviews were divided by positive and negative; after that reviews were pre-processed to get only nouns and adjectives to get TF(Term Frequency), DF(Document Frequency), and TF-IDF(Term Frequency - Inverse Document Frequency). Finally, to get some topics about reviews, aggregations of extracted words were analyzed by using LDA(Latent Dirichlet Allocation) methods. To avoid overlap, the number of topics is set by Davis visualization. Results and Conclusions: 6 and 3 topics extracted in each positive/negative review, analyzed by LDA Topic Model. The main factors, consisting of topics were 1) Response to patients and customers. 2) Customized treatment (consultation) and management. 3) Hospital/Clinic's environments.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.61-70
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• 2004

It is difficult to find an appropriate web site because exponentially growing web contains millions of web documents. Personalization of web search can be realized by recommending proper web sites using user profile but more efficient method is needed for estimating preference because user's evaluation on web contents presents many aspects of his characteristics. As user profile has a property of non-linearity, estimation by classifier is needed and combination of classifiers is necessary to anticipate diverse properties. Structure adaptive self-organizing map (SASOM) that is suitable for Pattern classification and visualization is an enhanced model of SOM and might be useful for web mining. Fuzzy integral is a combination method using classifiers' relevance that is defined subjectively. In this paper, estimation of user profile is conducted by using ensemble of SASOM's teamed independently based on fuzzy integral and evaluated by Syskill ＆ Webert UCI benchmark data. Experimental results show that the proposed method performs better than previous naive Bayes classifier as well as voting of SASOM's.

• Archives of design research
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• v.18 no.1 s.59
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• pp.195-204
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• 2005

Due to the of evolution of digital technology, trends are moving toward personalization and customization in design (art), media, science. Existing mass media has been broadcasting to the general public due to technical and economic limitation and art works also communicate one-sidedly with spectators in the gallery or stage. But nowaday, it is possible for spectators to participate directly. We can make different products depending on the tastes of individuals who demand media or art. The essence of technology which makes it possible is 'interactive technology'. A goal of this research is to find out the true nature of the interactive design in multimedia contents and find the course of interactive communication design research. In this paper, we pass through two stages to solve this kind of problem. At first, we studied the concept of multimedia contents from the aspect of information revolution. Next, we decided our research topic to be 'visual reacting with audio' and made audio-visual art work as graphic designers. Through this research we can find the possibility to promote 'communication' in a broad sense, with appropriate interactive design.