As interest in the sustainable fashion industry continues to increase along with climate issues, it is necessary to identify research trends in sustainable fashion and seek new development directions. Therefore, this study aims to analyze research trends on sustainable fashion. For this purpose, related papers were collected from the KCI (Korean Citation Index) and Scopus, and 340 articles were used for the study. The collected data went through data transformation, data preprocessing, topic modeling analysis, core topic derivation, and visualization through a Python algorithm. A total of eight topics were obtained from the comprehensive analysis: consumer clothing consumption behavior and environment, upcycle product development, product types by environmental approach, ESG business activities, materials and material development, process-based approach, lifestyle and consumer experience, and brand strategy. Topics were related to consumption, production, and education of sustainable fashion, respectively. KCI analysis results and Scopus analysis results derived eight topics but showed differences from the comprehensive analysis results. This study provides primary data for exploring various themes of sustainable fashion. It is significant in that the data were analyzed based on probability using a research method that excluded the subjective value of the researcher. It is recommended that follow-up studies be conducted to examine social trends.
Kaloop, Mosbeh R.;Elrahman, Mohamed Abd;Hu, Jong Wan
Advances in nano research
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v.12
no.1
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pp.1-23
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2022
To date, nondestructive tests (NDT) applications and advances in detecting the dispersion and defections of the nano concrete (NC) materials fields are very limited. The current paper provides a review of the dispersion efficiency of nanomaterials in cement-based materials and how NDT can be efficiently used in detecting and visualizing the defections and dispersions of NC. The review identifies the characteristics of different types of nanoparticles used in NC. Nanomaterials influences on concrete characteristics and their dispersion degree are presented and discussed. The main aim of this article is to present and compare the common NDT that can be used for detecting and visualizing the defections and dispersions of different kinds of nanomaterials utilized in NC. The different microscopy and X-ray methods are explicitly reviewed and compared. Based on the collected data, it can be concluded that the fully detecting and visualizing of NC defections and dispersions have not been fully discovered and that needs further investigations. So, the distinction of this paper lies in defining NDT that can be employed for detecting and/or visualizing NC defections and dispersions.
The purpose of this study is to examine consumers' perceptions of domestic infertility support policies based on infertility-related keywords and the trends of their changes. To this end, Momsholic, a mom cafe which has the most active infertility-related bulletin boards on Naver, was selected as the analysis target, and 'infertility' was selected as a keyword for data search. The data was collected for three months. In addition, network analysis and visualization were performed using R for data collection and analysis, and cross-validation was attempted using the NetDraw function of 'textom 1.0' and the UCINET6 program. As a result of the analysis, the main keywords were cost, artificial insemination, in vitro fertilization, freezing, harvest, ovulation, and how much. Next, looking at the central value of the degree of connection, it was found that the degree of connection between the words cost, cost, how much, problem, public health center, and artificial insemination was high. According to the results of this study, women who visit mom cafes due to infertility in Korea are more interested in the cost. It is believed to be closely related to infertility treatment as well as in vitro fertilization and egg freezing. Therefore, by examining keywords related toinfertility, it has academic significance in that it is possible to identify major factors that end users are interested in. Furthermore, it is possible to redefine the guidelines for domestic infertility support policies by presenting infertility support policies that reflect the factors of interest of end consumers.
Purpose Recently, as a new business marketing tool, short form content focused on fun and interest has been shared as hashtags. By extracting positive and negative keywords from media audiences through comment analysis of social media news, various stakeholders aim to quickly and easily grasp users' opinions on major news. Design/methodology/approach YouTube videos were searched using the YouTube Data API and the results were collected. Video comments were crawled and implemented as HTML elements, and the collection results were checked on the web page. The collected data consisted of video thumbnails, titles, contents, and comments. Comments were word tokenized with the R program, comparing positive and negative dictionaries, and then quantifying polarity. In addition, social network analysis was conducted using divided positive and negative comments, and the results of centrality analysis and visualization were confirmed. Findings Social media users' opinions on issue news were confirmed by analyzing and visualizing the centrality of keywords through social network analysis by dividing comments into positive and negative. As a result of the analysis, it was found that negative objective reviews had the highest effect on information usefulness. In this way, previous studies have been reaffirmed that online negative information has a strong effect on personal decision-making. Corporate marketers will analyze user comments on social network services (SNS) to detect negative opinions about products or corporate images, which will serve as an opportunity to satisfy customers' needs.
Mathematical, verbal, and spatial abilities are known as three important indicators for the success in the STEM disciplines. In this study, Purdue Spatial Visualization Test-Rotation, College Entrance Scholastic Aptitude Test- Math and Verbal score of engineering freshmen students have been used to find the relationships among these areas. In addition, gender differences in spatial visualization, verbal achievement and mathematical achievement have been investigated, too. In this research, I found that gender difference was highest in spatial visualization ability, followed by verbal achievement and smallest in mathematical achievement. Substantial number of male students possess high level of spatial abilities, but only half of female students were at the same level where their male colleagues were. The correlation between spatial ability and mathematical ability was negligible, contrary to former researches on elementary and middle school students. But the correlation was stronger for female students than male students. The correlation between mathematical achievement and verbal achievement was negative. It reflects the fact that when one section of SAT score is low, score of other sections should be higher to get admitted to college. Gender difference in mathematics was smallest for high achieving spatial ability group. For low spatial ability group gender difference in mathematics achievement has been observed, too. To find the combined contribution of spatial and verbal abilities to mathematics achievement, students were divided into 4 ability groups. Mathematics achievement decreased in the order of (1) high spatial -low verbal group, (2) low spatial - low verbal group, (3) high spatial - high verbal group, (4) low spatial - high verbal group.
Korean biopharmaceutical industry is a high value-added industries of the country as a key business strategy of the country. The overseas market is accelerating rapidly due to drug demand according to population aging, new drug R&D investment performance visualization, changes in biopharmaceutical R&D center, strategic foreign technology exports, and the active support of government. Therefore, the domestic pharmaceutical companies also should enhance the competitiveness as global pharmaceutical companies and need to build the image of their own company that can be trusted by consumers. This study compared and analyzed visual characteristics shown in the CI symbol mark and age-specific preferences of domestic pharmaceutical companies recognizing the importance of CI as a marketing tool. As a result, preference for the symbol mark had been shown to be significantly higher preference of the old logotype as the age group is higher being proportional to awareness. In addition, the picture-type symbol mark was totally preferred rather than the word mark. Among the picture-type symbol mark, the form of the nature was strongly preferred rather than abstract form. The company also requires a sense of responsibility for recognizing changes in the mass to the globalization. It is hoped that this study will help to develop symbol mark direction as the basis for the identity strategies to improve the image of domestic pharmaceutical companies with global competitiveness.
Moon, Seong Joon;Jo, Nak Won;Oh, Se Doo;Lee, Ho Kil;Park, Kyoung Woo
Transactions of the Korean Society of Mechanical Engineers B
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v.40
no.3
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pp.127-138
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2016
Diesel vehicles should be equipped with urea-selective catalytic reduction(SCR) system as a high-performance catalyst, in order to reduce harmful nitrogen oxide emissions. In this study, a three-dimensional Eulerian-Lagrangian CFD analysis was used to numerically predict the multiphase flow characteristics of the urea-SCR system, coupled with the chemical reactions of the system's transport phenomena. Then, the numerical spray structure was modified by comparing the results with the measured values from spray visualization, such as the injection velocity, penentration length, spray radius, and sauter mean diameter. In addition, the analysis results were verified by comparison with the removal efficiency of the nitrogen oxide emissions during engine and chassis tests, resulting in accuracy of the relative error of less than 5%. Finally, a verified CFD analysis was used to calculate the interanl flow of the urea-SCR system, thereby analyzing the characteristics of pressure drop and velocity increase, and predicting the uniformity index and overdistribution positions of ammonia.
Journal of the Korea Institute of Information and Communication Engineering
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v.22
no.9
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pp.1228-1236
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2018
Recently, the maritime environment contaminated by the abandoned fishing gears. To solve this problem, there requires systematic management techniques for the fishing gears based on ICT technologies. The existed systems are optionally used by owners, but the systems need to adopt the monitoring and control architecture for integrated national surveillance. To do this, we designed an architecture for effective monitoring and management which collects position and state information using automatic identification buoy (AIB) device, to send the fishing ship, administrator ship, and shore side control center based on the IoT networks. Especially, in this paper, we developed the ENC-based integrated control system for efficient management which provides functions for position indication, state information display and loss alarm of fishing gears. Also, we conduct performance tests for data processing and visualization functions of the system to use a virtual buoy generation module.
This study analyzed research trends on smart logistics in Korea by conducting social network analysis (SNA) using R. The purpose of this study is to enhance the understanding of the smart logistics field along with the smart logistics status and policy review, and to suggest implications and future research tasks. The analysis period and subjects were 128 academic journal papers on smart logistics-related topics over the past 10 years (2011-2020), and the results were divided into the first half (2011-2015) and the second half (2016-2020). The analysis of the study was carried out step-by-step through frequency analysis, network centrality analysis, and visualization. As a result of the study, the quantitative increase and diversification of the research field were confirmed. It was also confirmed that the concentration of research on core areas increased by increasing the proportion of duplicate keywords. In addition, keywords with high betweenness centrality and degree centrality score such as Logistics, Authentication, Smart, Service, RFID, Technology, and Revolution were presented. Lastly, this study reviewed the structure with a focus on betweenness centrality after visualizing the network with main keywords. As a result, early research was focused on the field of logistics, and after 2016, it was confirmed that the center of research was diversifying and expanding with the development of the 4th industrial revolution and major technologies.
Knowledge map is widely used to represent knowledge in many domains. This paper presents a method of integrating the national R&D data and assists of users to navigate the integrated data via using a knowledge map service. The knowledge map service is built by using a lightweight ontology and a topic modeling method. The national R&D data is integrated with the research project as its center, i.e., the other R&D data such as research papers, patents, and reports are connected with the research project as its outputs. The lightweight ontology is used to represent the simple relationships between the integrated data such as project-outputs relationships, document-author relationships, and document-topic relationships. Knowledge map enables us to infer further relationships such as co-author and co-topic relationships. To extract the relationships between the integrated data, a Relational Data-to-Triples transformer is implemented. Also, a topic modeling approach is introduced to extract the document-topic relationships. A triple store is used to manage and process the ontology data while preserving the network characteristics of knowledge map service. Knowledge map can be divided into two types: one is a knowledge map used in the area of knowledge management to store, manage and process the organizations' data as knowledge, the other is a knowledge map for analyzing and representing knowledge extracted from the science & technology documents. This research focuses on the latter one. In this research, a knowledge map service is introduced for integrating the national R&D data obtained from National Digital Science Library (NDSL) and National Science & Technology Information Service (NTIS), which are two major repository and service of national R&D data servicing in Korea. A lightweight ontology is used to design and build a knowledge map. Using the lightweight ontology enables us to represent and process knowledge as a simple network and it fits in with the knowledge navigation and visualization characteristics of the knowledge map. The lightweight ontology is used to represent the entities and their relationships in the knowledge maps, and an ontology repository is created to store and process the ontology. In the ontologies, researchers are implicitly connected by the national R&D data as the author relationships and the performer relationships. A knowledge map for displaying researchers' network is created, and the researchers' network is created by the co-authoring relationships of the national R&D documents and the co-participation relationships of the national R&D projects. To sum up, a knowledge map-service system based on topic modeling and ontology is introduced for processing knowledge about the national R&D data such as research projects, papers, patent, project reports, and Global Trends Briefing (GTB) data. The system has goals 1) to integrate the national R&D data obtained from NDSL and NTIS, 2) to provide a semantic & topic based information search on the integrated data, and 3) to provide a knowledge map services based on the semantic analysis and knowledge processing. The S&T information such as research papers, research reports, patents and GTB are daily updated from NDSL, and the R&D projects information including their participants and output information are updated from the NTIS. The S&T information and the national R&D information are obtained and integrated to the integrated database. Knowledge base is constructed by transforming the relational data into triples referencing R&D ontology. In addition, a topic modeling method is employed to extract the relationships between the S&T documents and topic keyword/s representing the documents. The topic modeling approach enables us to extract the relationships and topic keyword/s based on the semantics, not based on the simple keyword/s. Lastly, we show an experiment on the construction of the integrated knowledge base using the lightweight ontology and topic modeling, and the knowledge map services created based on the knowledge base are also introduced.
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