• Journal of Korean Medicine Rehabilitation
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• v.32 no.1
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• pp.89-106
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• 2022

Objectives In this study, a scoping review was conducted to inform decision-making related to traditional Korean medicine for people with disabilities in the future. Methods Seven databases were searched to find previous studies on traditional Korean medicine for people with disabilities. Studies published until August 2021 were considered. Using the methodology of scoping review, research on traditional Korean medicine for people with disabilities was reviewed with the following steps: 1) drawing research questions, 2) searching for related studies, 3) selecting studies, 4) extracting data, and 5) analyzing and reporting results. Results Out of 2,072 studies, 7 research papers and 10 reports were finally selected. The research papers included 5 cases studies, 1 survey study, and 1 chart review. Most studies used herbal medicine and acupuncture treatment, but the reports on the interventions were not detailed. The reports included policy studies, project performance guidelines, and project results reports, and most of the evaluation indicators tended to be standardized. Conclusions This study reviewed the literature on traditional Korean medicine for people with disabilities. It presents future directions for clinical research on traditional Korean medicine for people with disabilities and can be used to inform healthcare policies and clinical practice. In the future, quantitative research such as clinical trials, meta-analysis, and health insurance big data analysis is needed to understand the current status and effects of traditional Korean medicine for people with disabilities. In addition, qualitative research is necessary to identify unmet demands of traditional Korean medicine for people with disabilities.

• Journal of The Korean Association For Science Education
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• v.42 no.1
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• pp.33-49
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• 2022

This study aims to explore, using both quantitative and qualitative data analyzing the structural relationship between creative process and product, the types of elementary students' scientific creativity. For this, 105 fifth-graders responded to a scientific creativity test that assesses creative process and product, and four students who scored the highest were interviewed. In the interview, they were asked about the cognitive process they used in generating the creative product. Then, correlation analysis and structural equation modeling were used, along with the interview data, to type the students. The main findings of the study are as follows. First, the structural equation modeling of creative process and product gave satisfactory results in absolute and incremental fit indexes. Second, among the three components of creative process - knowledge, inquiry skill-observation, and creative thinking skills -, only creative thinking skills had significant effects on creative product. Third, divergent thinking skills had the strongest correlation with the creative product, followed by convergent thinking skills. Associational thinking skills did not have significant correlation. Fourth, elementary students' scientific creativity could be categorized into Creative Type, Useful Type, Original Type, and Non-creative Type, based on their creative product. The Non-creative Type could be further classified into Common Type, Repetitive Type, Non-response Type, Irrelevant Type, and Abstract Type. Fifth, most students used either knowledge or observation in their creative process, making them either Knowledge-oriented Type or Observation-oriented Type. In addition, there were DT Type, DT-CT Type, and DT-CT-AT Type among the students, based on the kinds of creative thinking skills they mainly used in the process. This study provides implications for educators and researchers in scientific creativity education.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.4
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• pp.35-50
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• 2023

As urbanization progresses, there is a growing and continuous demand for green spaces that provide ecosystem services. However, increasing the quantity of green spaces within major cities is challenging. Therefore, it is essential to pursue qualitative improvements that consider ecological characteristics of existing green spaces. In this study, we focus on local neighborhood parks in Seoul and present the following two questions through an evaluation utilizing ecological design indicators and land use data: 1. Which factor, design or location, has a greater influence on the ecological quality of neighborhood parks in Seoul? 2. Additionally, when evaluating ecological characteristics, is there similarity between assessments based on land-use data and those utilizing ecological design indicators? For this study, we conducted research on 30 neighborhood parks in Seoul and classified them into mountainous types (adjacent to mountains, natural terrain parks) and urban types (independently designed within 300m without existing forests) based on previous studies. Firstly, we conducted evaluations according to park location types. When comparing the evaluation scores of urban types (14 parks) and mountainous types (16 parks), significant differences were observed with scores of 16.86 and 35.94, respectively. Statistical analysis showed a significant difference between park types. In terms of habitat quality, the average values for urban and mountainous parks were 0.33 and 0.53, respectively, and statistically significant differences were observed between park types indicating differences in ecological potential according to park location. Secondly, when comparing the results of ecological potential evaluations based on park design and external connectivity, a correlation was found between habitat quality and total scores according to evaluation indicators. The correlation analysis showed significant linear relationships between habitat quality and total scores, biodiversity scores, and ecosystem function scores, with high positive correlation coefficients of 0.829, 0.861, and 0.802, respectively. This study holds significance in analyzing the ecological aspects of urban parks through the lens of both park location characteristics and design indicators. The analysis results underscore the importance of planning and managing ecologically sound urban parks contingent upon their location. Moreover, the utilization of appropriate ecological design indicators can help alleviate environmental limitations surrounding parks. Integrating these considerations could enhance the ecological quality and ecosystem services of urban green spaces.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.151-176
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• 2021

As the information technology industry develops, various kinds of data are being created, and it is now essential to process them and use them in the industry. Analyzing and utilizing various digital data collected online and offline is a necessary process to provide an appropriate experience for customers in the industry. In order to create new businesses, products, and services, it is essential to use customer data collected in various ways to deeply understand potential customers' needs and analyze behavior patterns to capture hidden signals of desire. However, it is true that research using data analysis and UX methodology, which should be conducted in parallel for effective service development, is being conducted separately and that there is a lack of examples of use in the industry. In thiswork, we construct a single process by applying data analysis methods and UX methodologies. This study is important in that it is highly likely to be used because it applies methodologies that are actively used in practice. We conducted a survey on the topic to identify and cluster the associations between factors to establish customer classification and target customers. The research methods are as follows. First, we first conduct a factor, regression analysis to determine the association between factors in the happiness data survey. Groups are grouped according to the survey results and identify the relationship between 34 questions of psychological stability, family life, relational satisfaction, health, economic satisfaction, work satisfaction, daily life satisfaction, and residential environment satisfaction. Second, we classify clusters based on factors affecting happiness and extract the optimal number of clusters. Based on the results, we cross-analyzed the characteristics of each cluster. Third, forservice definition, analysis was conducted by correlating with keywords related to happiness. We leverage keyword analysis of the thumb trend to derive ideas based on the interest and associations of the keyword. We also collected approximately 11,000 news articles based on the top three keywords that are highly related to happiness, then derived issues between keywords through text mining analysis in SAS, and utilized them in defining services after ideas were conceived. Fourth, based on the characteristics identified through data analysis, we selected segmentation and targetingappropriate for service discovery. To this end, the characteristics of the factors were grouped and selected into four groups, and the profile was drawn up and the main target customers were selected. Fifth, based on the characteristics of the main target customers, interviewers were selected and the In-depthinterviews were conducted to discover the causes of happiness, causes of unhappiness, and needs for services. Sixth, we derive customer behavior patterns based on segment results and detailed interviews, and specify the objectives associated with the characteristics. Seventh, a typical persona using qualitative surveys and a persona using data were produced to analyze each characteristic and pros and cons by comparing the two personas. Existing market segmentation classifies customers based on purchasing factors, and UX methodology measures users' behavior variables to establish criteria and redefine users' classification. Utilizing these segment classification methods, applying the process of producinguser classification and persona in UX methodology will be able to utilize them as more accurate customer classification schemes. The significance of this study is summarized in two ways: First, the idea of using data to create a variety of services was linked to the UX methodology used to plan IT services by applying it in the hot topic era. Second, we further enhance user classification by applying segment analysis methods that are not currently used well in UX methodologies. To provide a consistent experience in creating a single service, from large to small, it is necessary to define customers with common goals. To this end, it is necessary to derive persona and persuade various stakeholders. Under these circumstances, designing a consistent experience from beginning to end, through fast and concrete user descriptions, would be a very effective way to produce a successful service.

• Journal of The Korean Association For Science Education
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• v.40 no.6
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• pp.657-670
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• 2020

The knowledge-information-processing competency is the most essential competency in a knowledge-information-based society and is the most fundamental competency in the new problem-solving ability. Data-driven science inquiry, which emphasizes how to find and solve problems using vast amounts of data and information, is a way to cultivate the problem-solving ability in a knowledge-information-based society. Therefore, this study aims to develop a teaching-learning model and strategy for data-driven science inquiry and to verify the validity of the model in terms of knowledge information processing competency. This study is developmental research. Based on literature, the initial model and strategy were developed, and the final model and teaching strategy were completed by securing external validity through on-site application and internal validity through expert advice. The development principle of the inquiry model is the literature study on science inquiry, data science, and a statistical problem-solving model based on resource-based learning theory, which is known to be effective for the knowledge-information-processing competency and critical thinking. This model is titled "Exploratory Scientific Data Analysis" The model consisted of selecting tools, collecting and analyzing data, finding problems and exploring problems. The teaching strategy is composed of seven principles necessary for each stage of the model, and is divided into instructional strategies and guidelines for environment composition. The development of the ESDA inquiry model and teaching strategy is not easy to generalize to the whole school level because the sample was not large, and research was qualitative. While this study has a limitation that a quantitative study over large number of students could not be carried out, it has significance that practical model and strategy was developed by approaching the knowledge-information-processing competency with respect of science inquiry.

• Asia pacific journal of information systems
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• v.18 no.2
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• pp.95-114
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• 2008

Recent interests in data mining result from the expansion of the amount of business data and the growing business needs for extracting valuable knowledge from the data and then utilizing it for decision making process. In particular, recent advances in association rule mining techniques enable us to acquire knowledge concerning sales patterns among individual items from the voluminous transactional data. Certainly, one of the major purposes of association rule mining is to utilize acquired knowledge in providing marketing strategies such as cross-selling, sales promotion, and shelf-space allocation. In spite of the potential applicability of association rule mining, unfortunately, it is not often the case that the marketing mix acquired from data mining leads to the realized profit. The main difficulty of mining-based profit realization can be found in the fact that tremendous numbers of patterns are discovered by the association rule mining. Due to the many patterns, data mining experts should perform additional mining of the results of initial mining in order to extract only actionable and profitable knowledge, which exhausts much time and costs. In the literature, a number of interestingness measures have been devised for estimating discovered patterns. Most of the measures can be directly calculated from what is known as a contingency table, which summarizes the sales frequencies of exclusive items or itemsets. A contingency table can provide brief insights into the relationship between two or more itemsets of concern. However, it is important to note that some useful information concerning sales transactions may be lost when a contingency table is constructed. For instance, information regarding the size of each market basket(i.e., the number of items in each transaction) cannot be described in a contingency table. It is natural that a larger basket has a tendency to consist of more sales patterns. Therefore, if two itemsets are sold together in a very large basket, it can be expected that the basket contains two or more patterns and that the two itemsets belong to mutually different patterns. Therefore, we should classify frequent itemset into two categories, inter-pattern co-occurrence and intra-pattern co-occurrence, and investigate the effect of the market basket size on the two categories. This notion implies that any interestingness measures for association rules should consider not only the total frequency of target itemsets but also the size of each basket. There have been many attempts on analyzing various interestingness measures in the literature. Most of them have conducted qualitative comparison among various measures. The studies proposed desirable properties of interestingness measures and then surveyed how many properties are obeyed by each measure. However, relatively few attentions have been made on evaluating how well the patterns discovered by each measure are regarded to be valuable in the real world. In this paper, attempts are made to propose two notions regarding association rule measures. First, a quantitative criterion for estimating accuracy of association rule measures is presented. According to this criterion, a measure can be considered to be accurate if it assigns high scores to meaningful patterns that actually exist and low scores to arbitrary patterns that co-occur by coincidence. Next, complementary measures are presented to improve the accuracy of traditional association rule measures. By adopting the factor of market basket size, the devised measures attempt to discriminate the co-occurrence of itemsets in a small basket from another co-occurrence in a large basket. Intensive computer simulations under various workloads were performed in order to analyze the accuracy of various interestingness measures including traditional measures and the proposed measures.

• Journal of Conservation Science
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• v.32 no.3
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• pp.385-394
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• 2016

A fabric excavated from tombs or passed down is not easy to find its original color as it degrades and discolors by UV and visible rays, oxygen and microorganisms. LC-MS analysis is commonly used for separating and analyzing colors, but color extraction process is complicated and important in dye-qualitative analysis. To extract red colors from a fabric which is dyed with safflower and lac, solvents; hydrogen chloride, pyridine and oxalic acid are used and oxalic acid was the most effective solvent. Meanwhile, dyed samples were put in degradation condition; UV-A for 168 hours and analyzed with LC-MS to find out its colors'chemical changes. As a result, carthamin is detected in $T_R$ 13 min and laccaic acid A is detected in $T_R$ 10 min. However carthamin is not detected in a degraded fabric dying with safflower, it could be identified as a safflower fabric by the molecular weight of m/z 931. Through this study the most optimal method for red color extraction is found so it is expected to be used as a base line data for red color LC-MS analysis.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.457-460
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• 2002

The image quality of three-dimensional (3D) images has been widely investigated by the qualitative analysis method. A need remains for an objective and quantitative method to assess the image quality of 3D volume-rendered images. The purpose of this study was to evaluate the quantitative accuracy of distance measurements on 3D volume-rendered images of a dry human skull by using multi-detector computed tomography (MDCT). A radiologist measured five times the twenty-one direct measurement line items composed among twelve reference points on the skull surface with a digital vernier caliper. The water filled skull specimen was scanned with a MDCT according to the section thicknesses of 1.25, 2.50, 3.75, and 5.00 mm for helical (high quality; pitch 3:1) scan mode. MDCT data were reconstructed with its acquisition section thickness and with 1.25 mm section thickness for all scans. An observer also measured seven times the corresponding items on 3D volume-rendered images with measuring tools provided by volumetric analysis software. The quantitative accuracy of distance measurements on the 3D volume-rendered images was statistically evaluated (p-value < 0.05) by comparatively analyzing these measurements with the direct distance measurements. The accuracy of distance measurements on the 3D volume-rendered MDCT images acquired with 1.25, 2.50, 3,75 and 5.00 mm section thickness and reconstructed with its section thickness were 48%, 33%, 23%, and 14%, respectively. Meanwhile, there were insignificant statistical differences in accuracy of distance measurements among 3D volume-rendered images reconstructed with 1.25 mm section thickness for the each acquisition section thickness. MDCT images acquired with thick section thickness and reconstructed with thin section thickness in helical scan mode should be effectively used in medical planning of 3D volume-rendered images. The quantitative analysis of distance measurement may be a useful tool for evaluating the quantitative accuracy and the defining optimal parameters of 3D volume-rendered CT images.

• Science of Emotion and Sensibility
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• v.19 no.1
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• pp.39-48
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• 2016

This research aims to identify innovative companies' attention to the emotion and sensibility and its application by analyzing the contents of the corporate annual reports. Annual report is a good reference data because it describes not only various current products and services' annual activities and business performance but also corporate future direction. Sensibility is interpreted and used with various words internationally: various related terms such as sensibility, sense, emotion, feeling and affection are analyzed not only by the definition but also the interrelationship among them, and included for the contents analysis. To select the innovative companies, the researcher used 'Fast company' that is the economic journal and deducted the companies list via 'The world's 50 most innovative companies' in 2009 and 2014. Listed companies' 2009 and 2014 annual reports' contents were analyzed to identify the rate of the recognition and the application of sensibility to their business. Even though the quantitative result of the content analysis indicates not a strong relationship between corporate innovativeness and 'sensibility' qualitative result identifies companies are paying more attention to the 'sense' and 'feeling' during five years. In conclusion, the innovation that company pursues strategically is shifting from differentiation and the technological leadership to satisfying user experiences and the number of companies which express and measure user feeling and emotions are increasing.

• Journal of Distribution Science
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• v.13 no.4
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• pp.89-98
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• 2015

Purpose - In today's globalized and modern business environment, corporate social responsibility (CSR) activities are considered to be essential for the sustainable development of enterprises. In addition, the corporate philanthropy that is related to CSR practices, as well as their being capable of reducing the anti-corporate sentiment of people have facilitated a qualitative forward leap into the quantitative growth phase. This study aims to undertake a comparative evaluation of corporate philanthropy through the Importance-Performance Analysis (IPA) method focusing on service and manufacturing industries, and to eventually determine a differentiated approach that is needed for corporate philanthropy. Research design, data, and methodology - The survey responses were collected through online research on specialized companies from consumers nationwide who were aged from 20 to 60 and who are aware of corporate philanthropy. A total of 408 sheets of questionnaire survey were used. Frequency analysis was undertaken in this study. The interviewees had demographic characteristics of gender: 206 males (50.5%) and 202 females (49.5%). They also had demographic characteristics of age: 82 people were over 20 (20.1%), 96 over 30 (23.5%), 105 over 40 (25.7%), and 125 over 50 (30.7%) years of age. The distribution of interviewees' residences is as follows: 154 persons (37.7%) in the Special City, 102 persons (25.0%) in the Metropolitan City, and 152 persons (37.3%) in the Provincial Region. The interviewees have been working for the following companies: 34 persons (8.3%) in LG Display, 80 (19.6%) in KT&G, 49 (12.0%) in Amore Pacific, 42 (10.3%) in KIA Motors, 47 (11.5%) in SBS, 52 (12.8%) in Shinhan Bank, 86 (21.1%) in Asiana Airlines, and 18 (4.4%) in Hyundai Department Store. We applied the paired t-test for the IPA analysis. PASW Statistics 18 was used for statistical analysis. Results - The results of IPA analysis indicated that the importance and performance degrees in both manufacturing and service industries were significantly different. Major empirical results showed that, in consumer, social, economic, philanthropic, and environmental dimensions, in the sub-factors of philanthropy activities in both manufacturing and service industries, the importance degree was found to be higher than performance degree. Further, the average difference between importance degree and performance degree by the sub-factors of philanthropy activities. On the other hand, the average difference of environmental dimension was found to be highest in both service and manufacturing industries. Thus, while consumers consider the philanthropy activities of the environmental dimension as most important, actual companies treat performance of philanthropy activities of the environmental dimension insufficiently or negligibly to some degree. Conclusions - The differentiated approach method that is required for corporate philanthropy may be proposed to uplift corporate accomplishments by analyzing the IPA of the attributes of the sub-factors of corporate philanthropy. This is, to an extent, insufficient in the existing studies related to the use of the IPA technique, and it shows the items that are to be conducted intensively.