• Korean Medical Education Review
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• v.19 no.3
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• pp.158-168
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• 2017

There is a more urgent call for educational methods of machine learning in medical education, and therefore, new approaches of teaching and researching machine learning in medicine are needed. This paper presents a case using machine learning through text analysis. Topic modeling of news articles with the keyword 'asbestos' were examined. Two hypotheses were tested using this method, and the process of machine learning of texts is illustrated through this example. Using an automated text analysis method, all the news articles published from January 1, 1990 to November 15, 2016 in South Korea which included 'asbestos' in the title and the body were collected by web scraping. Differences in topics were analyzed by structured topic modelling (STM) and compared by press companies and periods. More articles were found in liberal media outlets. Differences were found in the number and types of topics in the articles according to the partisanship and period. STM showed that the conservative press views asbestos as a personal problem, while the progressive press views asbestos as a social problem. A divergence in the perspective for emphasizing the issues of asbestos between the conservative press and progressive press was also found. Social perspective influences the main topics of news stories. Thus, the patients' uneasiness and pain are not presented by both sources of media. In addition, topics differ between news media sources based on partisanship, and therefore cause divergence in readers' framing. The method of text analysis and its strengths and weaknesses are explained, and an application for the teaching and researching of machine learning in medical education using the methodology of text analysis is considered. An educational method of machine learning in medical education is urgent for future generations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.63-69
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• 2023

'Carbon-neutrality Assessment based on Technology Application Scenario (CATAS)' provides an analysis of greenhouse gas (GHG) reduction effectiveness when applying carbon-neutrality technology to areas such as energy conversion, transportation, and buildings at certain spatial levels. As for the development scope of the model, GHG emission sources were analyzed for direct GHG emissions, and the boundary between direct and indirect emissions are set according to the spatial scope. The technical scope included nine technologies and forest sinks in the transition sector that occupies the largest portion of GHG emissions in the 2050 carbon neutral scenario. The carbon neutrality rate evaluation methodology consists of four steps: ① analysis of GHG emissions, ② prediction of energy production according to technology introduction, ③ calculation of GHG reduction, and ④ calculation of carbon neutrality rate. After the web-based CATAS-BASIC was developed, an analysis was conducted by applying the new and renewable energy distribution goals presented in the ｢2050 Greenhouse Gas Reduction Promotion Plan｣ of the Seoul Metropolitan Government. As a result of applying solar power, hydrogen fuel cell, and hydrothermal, the introduction of technology reduced 0.43 million tCO₂eq of 1.49 million tCO₂eq, which is the amount of emissions from the conversion sector in Seoul, and the carbon neutrality rate in the conversion sector was analyzed to be 28.94 %.

• Korean Journal of Construction Engineering and Management
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• v.12 no.4
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• pp.59-69
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• 2011

Construction works have become larger and more complex, improving productivity by introducing Information Technology (IT) is pursued. In this circumstance, many different kinds of project management system is being introduced, and various IT technologies are applied such as Personal Digital Assistant (PDA), Bar Code, Radio Frequency Identification (RFID), Web Camera, and so on. However, these kinds of technologies might cause reprocessing of information and ineffectiveness of project because of lack of real time information processing technology or separation between construction sites and management offices. Therefore, this research aims to develop Application that can be applied efficiently for construction material management, by understanding problems of former management system with questionnaires and extracting functions with analysis of requirements. This will be possible to input information automatically, to process and check material information in real time, and to identify the location of necessary material. Then, the problem of separation between construction sites and management offices are solved, and as a result, more efficient management of materials in construction sites will become possible.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.1
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• pp.86-95
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• 2014

Productivity improvement of a shipbuilding company depends on how efficiently its limited resources are managed and utilized. Recently, research on modeling and simulation (M&S) to support shipyard production management system has been being under study. The production management based on M&S rejects decision making on experience, and it can establish productivity improvement method based on quantitative and specific data. In this paper, M&S is applied to the long-term plan as a part of the production planning in shipyards. To this end, the long-term plan processes and related management systems are analyzed. Based on the analysis, a simulation model and an application system using commercial simulation software are suggested. And basic structure of the suggested system is based on web technology such as Rich Internet Application, web services protocol for compatibility with existing shipyard enterprise systems. Utilizing the results of this study, it is expected that shipyard production planners can settle down work flow, in which one can establishes the production plan, simulates the plan, and analyzes the results, enabling a more reliable production plans.

• Convergence Security Journal
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• v.23 no.2
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• pp.47-54
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• 2023

The global popularity of K-content(Korean Wave) has led to a continuous increase in copyright infringement cases involving domestic works, not only within the country but also overseas. In response to this trend, there is active research on technologies for detecting illegal distribution sites of domestic copyrighted materials, with recent studies utilizing the characteristics of domestic illegal distribution sites that often include a significant number of advertising banners. However, the application of detection techniques similar to those used domestically is limited for overseas illegal distribution sites. These sites may not include advertising banners or may have significantly fewer ads compared to domestic sites, making the application of detection technologies used domestically challenging. In this study, we propose a detection technique based on the similarity comparison of links and text trees, leveraging the characteristic of including illegal sharing posts and images of copyrighted materials in a similar hierarchical structure. Additionally, to accurately compare the similarity of large-scale trees composed of a massive number of links, we utilize Graph Neural Network (GNN). The experiments conducted in this study demonstrated a high accuracy rate of over 95% in classifying regular sites and sites involved in the illegal distribution of copyrighted materials. Applying this algorithm to automate the detection of illegal distribution sites is expected to enable swift responses to copyright infringements.

• Journal of the Korea Society of Computer and Information
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• v.26 no.9
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• pp.13-25
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• 2021

In the age of digital innovation based on the Internet, Information and Communication and Artificial Intelligence technologies, huge amounts of datasets are being generated, collected, accumulated, and opened on the web by various public institutions providing useful and public information. In order to analyse, gain useful insights and information from data, Formal Concept Analysis(FCA) has been successfully used for analyzing, classifying, clustering and visualizing data based on the binary relation between objects and attributes in the dataset. In this paper, we present an approach for enhancing the analysis of relational attributes of data within the extended framework of FCA, which is designed to classify, conceptualize and visualize sets of objects described not only by attributes but also by relations between these objects. By using the proposed tool, RCA wizard, several experiments carried out on some public open datasets demonstrate the validity and usability of our approach on generating and visualizing conceptual hierarchies for extracting more useful knowledge from datasets. The proposed approach can be used as an useful tool for effective data analysis, classifying, clustering, visualization and exploration.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.231-238
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• 2021

In this paper, we suggest a method of analysis for daily food delivery & consumption trends through big data of the post-Covid-19 era. Through analysis of big data and the database system, four analyzed factors, excluding weather, was proved to have significant correlation with delivery sales for 'Baedarui Minjok' of a catering delivery application. The research found that KBS, MBC and SBS Media showed remarkable results in food delivery & consumption sales soaring up to about 60 percent increase on the day after the Covid-19 related new article was issued. In addition, it proved that mobile media and web surfing were the main factors in increasing sales of food delivery & consumption applications, suggesting that viral marketing and emotional analysis by crawling data from SNS used by Millennials might be an important factor in sales growth. It can contribute the companies in the economic recession era to survive by providing the method for analyzing the big data and increasing their sales.

• Korea Trade Review
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• v.46 no.5
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• pp.65-81
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• 2021

The technological development in the era of the 4th industrial revolution is changing the paradigm of various industries. Various technologies such as big data, cloud, artificial intelligence, virtual reality, and the Internet of Things are used, creating synergy effects with existing industries, creating radical development and value creation. Among them, the logistics sector has been greatly influenced by quantitative data from the past and has been continuously accumulating and managing data, so it is highly likely to be linked with big data analysis and has a high utilization effect. The modern advanced technology has developed together with the data mining technology to discover hidden patterns and new correlations in such big data, and through this, meaningful results are being derived. Therefore, data mining occupies an important part in big data analysis, and this study tried to analyze data mining techniques that can contribute to the logistics field and common logistics using these data mining technologies. Therefore, by using the AHP technique, it was attempted to derive priorities for each type of efficient data mining for logisticalization, and R program and R Studio were used as tools to analyze this. Criteria of AHP method set association analysis, cluster analysis, decision tree method, artificial neural network method, web mining, and opinion mining. For the alternatives, common transport and delivery, common logistics center, common logistics information system, and common logistics partnership were set as factors.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.2
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• pp.49-67
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• 2021

The school library provides a mobile web service that allows access to the library catalog system, and provides services that reflect the needs of search and consider the characteristics of mobile devices. Therefore, this study conducted a literature review, an analysis of the current status of school library mobile web services, and a survey of the mobile service user experience of students and teachers to find the contents and service plans for school library mobile app services that meet the school library mobile needs. Based on the survey, the contents and design plan of the school library DLS mobile service was prepared. First, the steps were reduced from step 4 to step 3. In the first step, solution of screen clipping errors in registering as a member and various login platforms for accessibility are needed. In the second step, integrated search and detailed search, provision of materials for use and reading education, post-booking activities, guides and announcements on the use of the affiliated school library, inter-loan, and e-books are provided as main menu. In the third step, it was proposed to provide related functions such as reservations as well as the display of the detailed screen of the search results of the collection. This study can be used not only to develop dedicated mobile app services, but also to change current web-based mobile services.

• Journal of The Korean Association of Information Education
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• v.20 no.5
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• pp.451-464
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• 2016

The purpose of this paper is to review recent articles on applying smart learning for elementary students with learning disabilities. The search procedures through the Web-database system were implemented to find the proper research. Finally, a total of 10 articles met the criteria and were included in this review. Each study was analyzed according to the categories of the population, setting, research design, and intervention. The results indicated that research design implemented as case study and single subject design. Results founded strategies applying smart learning leaned too much towards using the skill-based application as learning contents. Based on analysis results, considerations for smart learning for elementary students with learning disabilities were suggested.