• Phonetics and Speech Sciences
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• v.15 no.3
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• pp.37-44
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• 2023

This study investigates perceptual confusions of English fricatives among 121 Korean elementary school English as a foreign language (EFL) learners with shorter periods of learning English. The objective is to examine how they perceive English fricative consonants and to provide educational guidelines. Two sets of English fricative identification tasks-voiceless fricatives and voiced fricatives-were administered to participants in a High Variability Phonetic Training (HVPT) setting. Their phonemic awareness of the fricatives was visualized in perceptual confusion maps via multidimensional scaling analysis. The findings are explored in terms of the impacts of Korean EFL learners' L1 linguistic aspects and a comparison with L1 learners. Learners' phonemic awareness patterns are then compared with their relative importance in speech intelligibility based on a functional load hierarchy. The results indicated that Korean elementary EFL learners recognized English fricatives in a manner largely akin to L1 learners, suggesting their ongoing acquisition progress. Additionally, the findings demonstrated that the young EFL learners possess sufficient phonemic awareness for most high functional load segments but encounter some difficulties with one high and one low functional pair. The findings of this study offer suggestions for diagnosing language learners' phonemic awareness abilities, thereby aiding in the development of practical guidelines for language instructional design and helping educators make informed decisions regarding teaching priority in L2 classes.

• Journal of the Korean Institute of Landscape Architecture
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• v.25 no.4
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• pp.1-17
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• 1998

Most of the tourist resort facilities in our country cannot be used in the winter season, and only a few spa resorts and sky resorts are available in the winter. To ameliorate this problem, various types of winter resort facilities have been constructed since 1970s and the massive development of winter resort facilities changed the resort market from a seller's market to a buyer's market. There has been however,few researches on marketing strategies for winter resorts, and there is a growing need for a rational method to maximize tourists' satisfaction and developers'profit at the same time. This research aims to develop a positining strategy to engance the marketability of winter resorts by classifying the resort market with the self-image types of users, and by analyzing the structure of the market, users' preferences, and locational factors. A survey was conducted with cases of Yong-Pyung resort, Mu-Ju resort, Alps resort, Bears resort, Back-Am spa resort, Su-An-Bo spa resort, and I-Chon spa resort. A list of questions in five categories -- similarity, characteristics, preferences, self-image, and personal characteristics of the respondents -- was constructed and tested. Among the 750 copies of questionnaire distributed, 700 were returned by only 378 were analyzed after screening missing or reckless answers. The statistical analysis of the data were conducted using techniques of correlation analysis, frequency analysis, factor analysis. Factor analysis and cluster analysis were used to group the cluster of self-image and a discriminant analysis were used to confirm this classification. The demographical characteristics were identified by frequency analysis, and resorts attributes were analyzed by oneway ANOVA analysis. Multidimensional scaling methods such as KYST, PROFIT, and PREFMAP were used for the positioning strategy.

• Korean Institute of Interior Design Journal
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• v.16 no.5
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• pp.38-46
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• 2007

In the late 1970s, the method of quantitative and scientific space structural analysis based on graph theory was introduced to the process of space design, which arranges design and functional elements, as relying heavily on intuition could produce errors due to unverified experiences and prejudices of the designer. As the method of space analysis is complex and hard to express visually and requires repetitive operations, it was discussed theoretically only. However, with the development of computer performance and graphic in recent years, visualization became possible. But the method of visual structural analysis of space is at the level of two dimensions and it is not easy to get accurate data when it is applied to limited three dimensional space such as an interior space. For the visual structural analysis of space, this study presents 4 indices including visibility volume level, pure visibility connection frequency, effective visibility connection frequency, and path visibility connection frequency. This study also presents space division using three dimensional arrangement rather than the existing vector operation method and raytracing algorithm at the lattice constant. Based on this, an analysis tool for the visible regions of three dimensional space that is capable of evaluating at multiple points by using three dimensional game engine and presentation tool that allows the analyzer to interpret the data effectively is made. It is applied to 2 prototype models by displacing Z axis, and the results are compared with UCL Depthmap to verify the validity of data and evaluate its usefulness as a multidimensional, multi-view space analysis tool.

• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.565-573
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• 2017

The ex-post evaluation of governmental crisis management is an important issues since it is necessary to prepare for the future disasters and becomes the cornerstone of our success as well. In this paper, we propose a data cube model with data mining techniques for the analysis of governmental crisis management strategies and ripple effects of foot-and-mouth(FMD) disease using the online news articles. Based on the construction of the data cube model, a multidimensional FMD analysis is performed using on line analytical processing operations (OLAP) to assess the temporal perspectives of the spread of the disease with varying levels of abstraction. Furthermore, the proposed analysis model provides useful information that generates the causal relationship between crisis response actions and its social ripple effects of FMD outbreaks by applying association rule mining. We confirmed the feasibility and applicability of the proposed FMD analysis model by implementing and applying an analysis system to FMD outbreaks from July 2010 to December 2011 in South Korea.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.155-162
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• 2022

In this paper, we examined the research trends and characteristics related to the metaverse in global journals published between 2000 and 2022 from the Web of Science database. The analysis included descriptive statistics, multidimensional scaling, keyword network analysis, and visualization. In addition, semantic network models were constructed, and centrality (betweenness and degree) analysis was performed using R and KH coder in two separate categories based on the trends and aspects of the publication: analysis period 1 (Jan 2000 to Dec 2020) and period 2 (Jan 2021 to Jun 2022). The results showed that the recent global research trends related to the metaverse could be quantitatively characterized using the semantic network analysis. Also, the results could be applied to suggest future research topics in the field of metaverse based on quantitative and empirical data.

• Journal of the Korea Convergence Society
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• v.10 no.12
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• pp.315-325
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• 2019

The purpose of this study is to design and construct a data mart that anyone can easily analyze subway OD movement patterns. Subway OD data of the year 2017 was downloaded from the Seoul Open Data Plaza and used as the source data. A multidimensional model was designed, and Gaussian mixed cluster analysis and visualization analysis using Tableau were performed. Interestingly, movement between suburban and Seoul accounts for 23% of the total traffic. The passengers of Suwon Station move to the suburbs much more than Seoul, while Pangyo Station mostly moves to Seoul. As a result of Gaussian mixed cluster, eight clusters of OD segments were found, and the characteristics of each cluster were characterized by segment distance and passenger size.

• Journal of Preventive Medicine and Public Health
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• v.38 no.1
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• pp.61-70
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• 2005

Objectives : To develop a tool for multidimensional measurement of the quality of life, which was psychometrically sound, short, and easy to administer for patients with hypertension. Methods : A sample of 1,115 hypertensive patients aged 20 or above in Cheong-Song County was studied from June 1997 to October 1998. In the development of the instrumental stage, the authors first conceptualized the quality of life. Item generation, item reduction, and questionnaire formatting were followed. Item-level (item descriptive, missing%, item internal consistency, item discriminant validity) analysis, scale-level (scale descriptive, floor and ceiling effect) analysis, and other tests(Cronbach's alpha, inter-dimension correlations, factor analysis, clinical validity) were performed to evaluate the validity and reliability of the new measurement scale. After 1 year, responsiveness and confirmatory factor analysis were performed. Results : The results of both item-level and scale-level analyses were acceptable. An acceptable degree of internal consistency was observed for each of the dimensions (Cronbach's alpha was 0.60 or higher). Inter-dimension correlations were below 0.50 and the factor analysis result was the same as the intended dimension structure. Correlation coefficients between perceived health status, stress and dimensions were proven to be acceptable. The result of comparing dimensional score means among ADL and MMSE-K groups above 60 years was statistically significant(p<0.05). The result of confirmatory factor analysis concluded that the dimensional structure model was well fitted. However, the result of responsiveness test using sensitivity and specificity was unsatisfactory. Conclusions : The newly developed measurement scale is psychometrically reliable and valid instrument for measuring quality of life in hypertensive patients.

• Steel and Composite Structures
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• v.25 no.6
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• pp.663-670
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• 2017

The problem of layup optimization of the composite laminates involves a very complex multidimensional solution space which is usually non-exhaustively explored using different heuristic computational methods such as genetic algorithms (GA). To ensure the convergence to the global optimum of the applied heuristic during the optimization process it is necessary to evaluate a lot of layup configurations. As a consequence the analysis of an individual layup configuration should be fast enough to maintain the convergence time range to an acceptable level. On the other hand the mechanical behavior analysis of composite laminates for any geometry and boundary condition is very convoluted and is performed by computational expensive numerical tools such as finite element analysis (FEA). In this respect some studies propose very fast FEA models used in layup optimization. However, the lower bound of the execution time of FEA models is determined by the global linear system solving which in some complex applications can be unacceptable. Moreover, in some situation it may be highly preferred to decrease the optimization time with the cost of a small reduction in the analysis accuracy. In this paper we explore some machine learning techniques in order to estimate the failure of a layup configuration. The estimated response can be qualitative (the configuration fails or not) or quantitative (the value of the failure factor). The procedure consists of generating a population of random observations (configurations) spread across solution space and evaluating using a FEA model. The machine learning method is then trained using this population and the trained model is then used to estimate failure in the optimization process. The results obtained are very promising as illustrated with an example where the misclassification rate of the qualitative response is smaller than 2%.

• Molecules and Cells
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• v.42 no.3
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• pp.237-244
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• 2019

Understanding the mechanisms of cancer drug resistance is a critical challenge in cancer therapy. For many cancer drugs, various resistance mechanisms have been identified such as target alteration, alternative signaling pathways, epithelial-mesenchymal transition, and epigenetic modulation. Resistance may arise via multiple mechanisms even for a single drug, making it necessary to investigate multiple independent models for comprehensive understanding and therapeutic application. In particular, we hypothesize that different resistance processes result in distinct gene expression changes. Here, we present a web-based database, CDRgator (Cancer Drug Resistance navigator) for comparative analysis of gene expression signatures of cancer drug resistance. Resistance signatures were extracted from two different types of datasets. First, resistance signatures were extracted from transcriptomic profiles of cancer cells or patient samples and their resistance-induced counterparts for >30 cancer drugs. Second, drug resistance group signatures were also extracted from two large-scale drug sensitivity datasets representing ~1,000 cancer cell lines. All the datasets are available for download, and are conveniently accessible based on drug class and cancer type, along with analytic features such as clustering analysis, multidimensional scaling, and pathway analysis. CDRgator allows meta-analysis of independent resistance models for more comprehensive understanding of drug-resistance mechanisms that is difficult to accomplish with individual datasets alone (database URL: http://cdrgator.ewha.ac.kr).

• Science of Emotion and Sensibility
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• v.16 no.2
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• pp.149-156
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• 2013

In this study, the Model of Emotion Evaluation, an emotional analysis actively applied in environmental assessment, was divided into two parts, the abbreviated model and the inferential model, through pilot study and experiment. In addition, an analysis was conducted through the experiment on the attributes of the evaluation vocabularies of two additional types of representative models, the EPA Model and PAD Model, and the results show a huge difference in the development approach and lexical constitution of the two models. It was also identified through factor analysis that the vocabularies were abbreviated according to the respective models. Similarity relationships were analyzed using multidimensional scaling and the results show that mutual relationship was established to some degree. Based on this, we can conclude that, rather than a biased use of the Model of Emotion Evaluation in emotion evaluation, a more objective image analysis is possible by analyzing the characteristics of the model before applying it. In this study, the evaluation target was confined only to the environmental assessment of streetscape and continuous research on the Model of Emotion Evaluation that allows for the comparison of evaluation models in various areas is needed.