• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.325-345
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• 2023

In the rapidly evolving domain of e-commerce, our study presents a cohesive approach to enhance customer satisfaction prediction from online reviews, aligning methodological innovation with practical insights. We integrate the RFE-SHAP feature selection with LDA topic modeling to streamline predictive analytics in e-commerce. This integration facilitates the identification of key features-specifically, narrowing down from an initial set of 28 to an optimal subset of 14 features for the Random Forest algorithm. Our approach strategically mitigates the common issue of overfitting in models with an excess of features, leading to an improved accuracy rate of 84% in our Random Forest model. Central to our analysis is the understanding that certain aspects in review content, such as quality, fit, and durability, play a pivotal role in influencing customer satisfaction, especially in the clothing sector. We delve into explaining how each of these selected features impacts customer satisfaction, providing a comprehensive view of the elements most appreciated by customers. Our research makes significant contributions in two key areas. First, it enhances predictive modeling within the realm of e-commerce analytics by introducing a streamlined, feature-centric approach. This refinement in methodology not only bolsters the accuracy of customer satisfaction predictions but also sets a new standard for handling feature selection in predictive models. Second, the study provides actionable insights for e-commerce platforms, especially those in the clothing sector. By highlighting which aspects of customer reviews-like quality, fit, and durability-most influence satisfaction, we offer a strategic direction for businesses to tailor their products and services.

• Korean Journal of Construction Engineering and Management
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• v.25 no.1
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• pp.32-41
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• 2024

In the construction industry, not only safety accidents, but also various complex risks such as construction delays, cost increases, and environmental pollution occur, and management technologies are needed to solve them. Among them, process risk management, which directly affects the project, lacks related information compared to its importance. This study tried to develop a MATM tunnel process risk classification system to solve the difficulty of risk information retrieval due to the use of different classification systems for each project. Risk collection used existing literature review and experience mining techniques, and DB construction utilized the concept of natural language processing. For the structure of the classification system, the existing WBS structure was adopted in consideration of compatibility of data, and an RBS linked to the work species of the WBS was established. As a result of the research, a risk classification system was completed that easily identifies risks by work type and intuitively reveals risk characteristics and risk factors linked to risks. As a result of verifying the usability of the established classification system, it was found that the classification system was effective as risks and risk factors for each work type were easily identified by user input of keywords. Through this study, it is expected to contribute to preventing an increase in cost and construction period by identifying risks according to work types in advance when planning and designing NATM tunnels and establishing countermeasures suitable for those factors.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.232-243
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• 2024

Purpose: Recently, large-scale forest fires caused by climate change, natural disasters, and human factors have been increasing every year in the East Coast and Taebaek Mountains region. Although forest fire extinguishing using helicopters is currently increasing, the need to introduce air force transport aircraft has continued to be raised due to the importance of early fire extinguishment to respond to large forest fires and the difficulty of extinguishing forest fires between sheep. This study seeks to present a plan for developing a post-fire management system for several aspects - achieving operational objectives, overcoming the operating environment, selecting a staging area, and efficient operation measures - to efficiently perform forest fire extinguishing missions using Air Force transport aircraft. Method: Based on literature research on forest fire extinguishing, forest fire extinguishing experiments using fixed-wing aircraft, and the operation status and operation method of forest fire extinguishing helicopters, the pros and cons of helicopter operation and the effects of large forest fire extinguishing using a large transport aircraft (C-130) Analyze the effectiveness of operation through analysis. Results: When extinguishing a large forest fire, an effective CM (Consequence Management) application plan was derived, including effective operation, control, command system, dispatch request, and forest fire extinguishment when integrating helicopter and fixed-wing aircraft (C-130). Conclusion: The application of the concept of CM (Consequence Management) is partially applied to some areas of chemical, biological, and radiological (CBRNE) protection in Korea, but efficient operation, control, and command systems are established when integrated operation of helicopters and large aircraft (C-130) in forest fire extinguishment. the concept of CM (Consequence Management), which is operated in advanced countries, was applied for safety management, dispatch requests, and forest fire extinguishing, thereby contributing to the establishment of a more advanced disaster and post-disaster management system.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.287-297
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• 2024

The purpose of this study is to develop a design thinking-based program to enhance the core competencies of creative problem-solving, collaboration, and communication for college students and to verify its effectiveness. To this end, a design thinking-based program was developed according to the instructional systems design (ISD) model consisting of learning content analysis, class activity design, evaluation tool development, implementation, evaluation and revision. After applying to the target (88 college students), competencies in creative problem-solving, collaboration, and communication were tested to verify quantitative effectiveness and the collected data was analyzed by t-test. In order to verify the qualitative effectiveness, the reflective logs submitted by each group as a final project report were analyzed. The results of the t-test conducted to verify the change in students' means in the pre-post competency test, showed that there were statistically significant increase in creative problem solving skill (t=-4.955, p<.01), collaboration skill (t=-3.179, p<.01), and communication skills(t=- 4.293, p<.01). And the design thinking-based program enabled students to have optimal learning experiences. Especially, learners in the program positively appreciated the experience of sharing various ideas with other members, strengthening cognitive flexibility, and acquiring performance.

• Journal of Soil and Groundwater Environment
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• v.11 no.1
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• pp.54-64
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• 2006

Chromated copper arsenate (CCA), a wood preservative, has been widely used to protect wood products from attacks by bacteria, fungi and insects. However, the use of CCA is currently forbidden or limited to some applications in many countries because the toxic elements (Cr, Cu, and As) of CCA are released into the environments during outdoor uses, which may cause adverse health effects on humans and ecological systems. This study was conducted to investigate the distributions of chromium, copper and arsenic in soils adjacent to two CCA-treated wood structures. In a 7 month old pond entry structure, ten surface soil samples (0-2.5 cm) were collected at lateral distances of 0, 0.5, and 1 m from the stairway, and nine surface soil samples were collected beneath the deck. Nine top soil samples were taken from a 2 year old sound barrier structure at lateral distances of 0, 1, and 2 m. Background surface soil samples were also collected from each structure. Samples were analyzed for some physicochemical properties such as pH, electrical conductivity, organic matter content, and soil texture. Following the extraction of the elements with a microwave digestion system, samples were analyzed for Cr, Cu, and As. The concentrations of the three elements in soils adjacent to the structures were significantly elevated compared to the background levels, indicating that the elements have been leached out of the structures. Released e1ements showed lateral concentration gradients within 1 m. The elevations of the three elements in soils underneath the deck did not seem different (background-corrected concentrations: Cr, 5.01 mg/kg; Cu, 5.50 mg/kg; As, 4.91 mg/kg), while the elements in soils near the sound barrier were elevated in the order of As>Cu>Cr with measured concentrations of 49.7, 44.7 and 52.5 mg/kg, respectively. Background As, Cu, and Cr concentrations near the sound barrier were 9.88, 30.8, and 46.5 mg/kg, respectively. These results showed that CCA constituents are released into the environment and it is suggested that risk assessment need to be conducted to investigate harmful effects of the released elements on humans and ecological systems.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.4
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• pp.340-347
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• 2001

Seasonal variation of the elemental and biochemical composition of the suspended particulate matter (SPM) was investigated in terms of quantity and quality of diets for suspension feeders from July 1999 to August 2000 in two coastal bay systems of Gosung and Kangjin Bays in Korea. No clear patterns in the seasonal variations of SPM concentration were found in these two bay systems. The results indicated that the seasonal variation of SPM could not be considered the variation of food available to suspension-feeders. The simultaneous peaks in chlorophyll a and biochemical components in summer indicated that the quantity of the particulate organic matter primarily depended on phytoplankton productivity. However, no correlation between chlorophyll a and biochemical components [particulate protein (PPr), carbohydrate (PCHO) and lipid] were found, indicating that other processes might also contribute to the particulate organic matter in the period when the phytoplankton biomass was low. High C: Chl a and C:N, and carbohydrate peaks during the autumn to spring period suggested that resuspension of surface sediments was a probable process to supply the particulate organic matter. The food material, represented by summing up the total quantity of three biochemical components, was highest in spring with minor peaks during the period from autumn to the next spring, The food index, calculated as the ratio of food material to total SPM, did not generally exceed $6\%$ with short peaks during the year. Therefore, nutritional quality of SPM in the bays are relatively poor than in other more productive coastal waters in the world. Our results confirm that the measurement of a single chemical variable cannot describe fully the nutritive value of the seston available to suspension-feeders as previously proposed, and the biochemical composition of SPM can provide effective information on its origin and nutritive Quality.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1849-1858
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• 2021

We analyzed the monthly and annual trends of the meteorological factors(wind speeds and directions and air temperatures) measured at an automated synoptic observation system (ASOS) and fine particle (PM₁₀ and PM_2.5) concentrations measured at the air quality monitoring systems(AQMSs) in Suwon. In addition, we investigated how the fine particle concentrations were related to the meteorological factors as well as urban morphological parameters (fractions of building volume and road area). We calculated the total volume of buildings and the total area of the roads in the area of 2 km × 2 km centered at each AQMS using the geographic information system and environmental geographic information system. The analysis of the meteorological factors showed that the dominant wind directions at the ASOS were westerly and northwesterly and that the average wind speed was strong in Spring. The measured fine particle concentrations were low in Summer and early Autumn (July to September) and high in Spring and Winter. In 2020, the annual mean fine particle concentration was lowest at most AQMSs. The fine particle concentrations were negatively and weakly correlated with the measured wind speeds and air temperatures (the correlation between PM_2.5 concentrations and air temperatures was relatively strong). In Suwon city, at least for 6 AQMSs except for the RAQMS 131116 and AQMS 131118, the PM₁₀ concentrations were affected mainly by the transport from outside rather than primary emission from mobile sources or wind speed decrease caused by buildings and, in the case of PM_2.5, vise versa.

• Korea Science and Art Forum
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• v.37 no.1
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• pp.87-97
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• 2019

The study began in recent years with the aim of grasping the nation's medical status following the fast-growing trend of international medical tourism and attracting foreign patients, among other things, Busan, which ranks second in attracting foreign patients after the nation's capital, Seoul, has been highly active in the past eight years, with foreign patients rising by about 426 percent, and Russian patients entering the sea. In addition, Gimhae and Changwon, the Busan-based Gyeongsangnam-do region, ranked first and second in number of foreign residents, and are inhabited by a variety of foreign workers. Medical institutions, such as hospitals, should be able to find directions within hospitals. It is also a space where information in various languages, including Korean, English, Chinese, or Russian, must be delivered in a single medium. Based on this research, the purpose of this research is to provide converged information that helps foreigners who are not familiar with Korean language easily understand the proposed recognition system when visiting hospitals. Therefore, this paper is applied to a multi-language survey of six medical institutions (A, B, C, D, E, F) at the university hospital in Busan, and 10 medical institutions (R, J) in Gimhae, South Gyeongsang Province with high foreign residents. Research results and contents are as follows. First, the results of analyzing the design of the sinusoidal system show that the font uses colorless Gothic fonts, arrows, and pictograms to introduce the design of a typical hospital sign system. Second, the results of the multi-lingual situation were found to have only two languages in the system, such as Korean and English, and to have four languages, including Korean, English, Chinese, and Russian, according to their geographical location. However, it was judged that most medical institutions currently have only two languages (Korean, English) that may cause some discomfort in terms of language for foreign patients in non-English speaking countries. Based on these findings, it is necessary to propose designs that are considered by Koreans as well as foreign users in the use of multilingual hospital sign systems.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.63-88
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• 2019

The goal of this paper is to investigate changes in North Korea's domestic and foreign policies through automated text analysis over North Korea represented in South Korean mass media. Based on that data, we then analyze the status of text mining research, using a text mining technique to find the topics, methods, and trends of text mining research. We also investigate the characteristics and method of analysis of the text mining techniques, confirmed by analysis of the data. In this study, R program was used to apply the text mining technique. R program is free software for statistical computing and graphics. Also, Text mining methods allow to highlight the most frequently used keywords in a paragraph of texts. One can create a word cloud, also referred as text cloud or tag cloud. This study proposes a procedure to find meaningful tendencies based on a combination of word cloud, and co-occurrence networks. This study aims to more objectively explore the images of North Korea represented in South Korean newspapers by quantitatively reviewing the patterns of language use related to North Korea from 2016. 11. 1 to 2019. 5. 23 newspaper big data. In this study, we divided into three periods considering recent inter - Korean relations. Before January 1, 2018, it was set as a Before Phase of Peace Building. From January 1, 2018 to February 24, 2019, we have set up a Peace Building Phase. The New Year's message of Kim Jong-un and the Olympics of Pyeong Chang formed an atmosphere of peace on the Korean peninsula. After the Hanoi Pease summit, the third period was the silence of the relationship between North Korea and the United States. Therefore, it was called Depression Phase of Peace Building. This study analyzes news articles related to North Korea of the Korea Press Foundation database(www.bigkinds.or.kr) through text mining, to investigate characteristics of the Kim Jong-un regime's South Korea policy and unification discourse. The main results of this study show that trends in the North Korean national policy agenda can be discovered based on clustering and visualization algorithms. In particular, it examines the changes in the international circumstances, domestic conflicts, the living conditions of North Korea, the South's Aid project for the North, the conflicts of the two Koreas, North Korean nuclear issue, and the North Korean refugee problem through the co-occurrence word analysis. It also offers an analysis of South Korean mentality toward North Korea in terms of the semantic prosody. In the Before Phase of Peace Building, the results of the analysis showed the order of 'Missiles', 'North Korea Nuclear', 'Diplomacy', 'Unification', and ' South-North Korean'. The results of Peace Building Phase are extracted the order of 'Panmunjom', 'Unification', 'North Korea Nuclear', 'Diplomacy', and 'Military'. The results of Depression Phase of Peace Building derived the order of 'North Korea Nuclear', 'North and South Korea', 'Missile', 'State Department', and 'International'. There are 16 words adopted in all three periods. The order is as follows: 'missile', 'North Korea Nuclear', 'Diplomacy', 'Unification', 'North and South Korea', 'Military', 'Kaesong Industrial Complex', 'Defense', 'Sanctions', 'Denuclearization', 'Peace', 'Exchange and Cooperation', and 'South Korea'. We expect that the results of this study will contribute to analyze the trends of news content of North Korea associated with North Korea's provocations. And future research on North Korean trends will be conducted based on the results of this study. We will continue to study the model development for North Korea risk measurement that can anticipate and respond to North Korea's behavior in advance. We expect that the text mining analysis method and the scientific data analysis technique will be applied to North Korea and unification research field. Through these academic studies, I hope to see a lot of studies that make important contributions to the nation.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.49-71
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• 2021

Users who intend to utilize knowledge to actively solve given problems proceed their jobs with cross- and sequential exploration of associated knowledge related each other in terms of certain criteria, such as content relevance. A knowledge map is the diagram or taxonomy overviewing status of currently managed knowledge in a knowledge-base, and supports users' knowledge exploration based on certain relationships between knowledge. A knowledge map, therefore, must be expressed in a networked form by linking related knowledge based on certain types of relationships, and should be implemented by deploying proper technologies or tools specialized in defining and inferring them. To meet this end, this study suggests a methodology for developing the knowledge graph-based knowledge map using the Graph DB known to exhibit proper functionality in expressing and inferring relationships between entities and their relationships stored in a knowledge-base. Procedures of the proposed methodology are modeling graph data, creating nodes, properties, relationships, and composing knowledge networks by combining identified links between knowledge. Among various Graph DBs, the Neo4j is used in this study for its high credibility and applicability through wide and various application cases. To examine the validity of the proposed methodology, a knowledge graph-based knowledge map is implemented deploying the Graph DB, and a performance comparison test is performed, by applying previous research's data to check whether this study's knowledge map can yield the same level of performance as the previous one did. Previous research's case is concerned with building a process-based knowledge map using the ontology technology, which identifies links between related knowledge based on the sequences of tasks producing or being activated by knowledge. In other words, since a task not only is activated by knowledge as an input but also produces knowledge as an output, input and output knowledge are linked as a flow by the task. Also since a business process is composed of affiliated tasks to fulfill the purpose of the process, the knowledge networks within a business process can be concluded by the sequences of the tasks composing the process. Therefore, using the Neo4j, considered process, task, and knowledge as well as the relationships among them are defined as nodes and relationships so that knowledge links can be identified based on the sequences of tasks. The resultant knowledge network by aggregating identified knowledge links is the knowledge map equipping functionality as a knowledge graph, and therefore its performance needs to be tested whether it meets the level of previous research's validation results. The performance test examines two aspects, the correctness of knowledge links and the possibility of inferring new types of knowledge: the former is examined using 7 questions, and the latter is checked by extracting two new-typed knowledge. As a result, the knowledge map constructed through the proposed methodology has showed the same level of performance as the previous one, and processed knowledge definition as well as knowledge relationship inference in a more efficient manner. Furthermore, comparing to the previous research's ontology-based approach, this study's Graph DB-based approach has also showed more beneficial functionality in intensively managing only the knowledge of interest, dynamically defining knowledge and relationships by reflecting various meanings from situations to purposes, agilely inferring knowledge and relationships through Cypher-based query, and easily creating a new relationship by aggregating existing ones, etc. This study's artifacts can be applied to implement the user-friendly function of knowledge exploration reflecting user's cognitive process toward associated knowledge, and can further underpin the development of an intelligent knowledge-base expanding autonomously through the discovery of new knowledge and their relationships by inference. This study, moreover than these, has an instant effect on implementing the networked knowledge map essential to satisfying contemporary users eagerly excavating the way to find proper knowledge to use.