• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.356-366
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• 2021

The high-tech industry, a leader in the national economy, has a larger investment cost compared to general buildings, a shorter construction period, and requires continuous investment. Therefore, accurate construction cost prediction and quick decision-making are important factors for efficient cost and process management. Overseas, the construction information classification system has been standardized since 1980 and has been continuously developed, improving construction productivity by systematically collecting and utilizing project life cycle information. At domestic construction sites, attempts have been made to standardize the classification system of construction information, but it is difficult to achieve continuous standardization and systematization due to the absence of a standardization body and differences in cost and process management methods for each construction company. Particular, in the case of the high-tech industry, the standardization and systematization level of the construction information classification system for high-tech facility construction is very low due to problems such as large scale, numerous types of work, complex construction and security. Therefore, the purpose of this study is to construct a construction information classification system suitable for high-tech facility construction through collection, classification, and analysis of related project data constructed in Korea. Based on the WBS (Work Breakdown Structure) and CBS (Cost Breakdown Structure) classified and analyzed through this study, a code system through hierarchical classification was proposed, and the cost model of buildings by linking WBS and CBS was three-dimensionalized and the utilized method was presented. Through this, an information classification system based on inter-relationships can be developed beyond the one-way tree structure, which is a general construction information classification system, and effects such as shortening of construction period and cost reduction will be maximized.

• Journal of Physiology & Pathology in Korean Medicine
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• v.36 no.2
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• pp.73-78
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• 2022

Since Traditional Korean medicine (TKM) doctors use various knowledge systems during treatment, diagnosis results may differ for each TKM doctor. However, it is difficult to explain all the reasons for the diagnosis because TKM doctors use both explicit and implicit knowledge. In this study, an upgraded random forest (RF)-based evaluation tool was proposed to extract clinical knowledge of TKM doctors. Also, it was confirmed to what extent the professor's clinical knowledge was delivered to the trainees by using the evaluation tool. The data used to construct the evaluation tool were targeted at 106 people who visited the Sasang Constitutional Department at Kyung Hee University Korean Medicine Hospital at Gangdong. For explicit knowledge extraction, four TKM doctors were asked to express the importance of symptoms as scores. In addition, for implicit knowledge extraction, importance score was confirmed in the RF model that learned the patient's symptoms and the TKM doctor's constitutional determination results. In order to confirm the delivery of clinical knowledge, the similarity of symptoms that professors and trainees consider important when discriminating constitution was calculated using the Jaccard coefficient. As a result of the study, our proposed tool was able to successfully evaluate the clinical knowledge of TKM doctors. Also, it was confirmed that the professor's clinical knowledge was delivered to the trainee. Our tool can be used in various fields such as providing feedback on treatment, education of training TKM doctors, and development of AI in TKM.

• Journal of Korean Home Economics Education Association
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• v.34 no.2
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• pp.129-152
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• 2022

The purpose of this study was to develop a sustainable dietary education program for middle school home economics subject using a teaching strategy to improve the empowerment of adolescents and to verify and evaluate the effectiveness of the program. To achieve the purpose of this study, the program was developed and evaluated according to the ADDIE teaching design model. The contents related to the dietary area were extracted from the technical & home economics curriculum of the 2015 revised middle school and SDGs, and their relevance was analyzed to select the contents of dietary education. The program developed based on the analysis results is 'dietary life together' and consists of five learning topics: 'living together in the global village', 'maintaining healthy diet', 'creating a dietary culture together', 'living with nature and people', and 'maintaining a safe diet'. As a strategy for improving empowerment, we presented four situations, each of which represents value judgment, prediction of results, responsible behavior choice, and decision making. The developed program was reviewed by experts and applied to 17 unit classes for 17 weeks (1 unit hour per week) to the third graders of middle schools in Gyeonggi-do. Significant differences were found between before and after the class measurements of the personal empowerment and the political and social empowerment, which shows the classes were effective in improving empowerment. However, since there was no significant difference in interpersonal empowerment before and after the program, suggestions were made to utilize strategies to facilitate discussion and cooperative learning when implementing the program. The students who participated in the class evaluated the program positively as a whole. The program was evaluated to have helped the students believe they could change society through solving dietary problems.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.135-144
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• 2021

Recently, data-driven decision-making technology has become a key technology leading the data industry, and machine learning technology for this requires high-quality training datasets. However, real-world data contains missing values for various reasons, which degrades the performance of prediction models learned from the poor training data. Therefore, in order to build a high-performance model from real-world datasets, many studies on automatically imputing missing values in initial training data have been actively conducted. Many of conventional machine learning-based imputation techniques for handling missing data involve very time-consuming and cumbersome work because they are applied only to numeric type of columns or create individual predictive models for each columns. Therefore, this paper proposes a new data imputation technique called 'Denoising Self-Attention Network (DSAN)', which can be applied to mixed-type dataset containing both numerical and categorical columns. DSAN can learn robust feature expression vectors by combining self-attention and denoising techniques, and can automatically interpolate multiple missing variables in parallel through multi-task learning. To verify the validity of the proposed technique, data imputation experiments has been performed after arbitrarily generating missing values for several mixed-type training data. Then we show the validity of the proposed technique by comparing the performance of the binary classification models trained on imputed data together with the errors between the original and imputed values.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.4
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• pp.128-134
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• 2022

Nakdong river estuary is being operated with the goal of expanding the period of seawater inflow from this year to 2022 every month and creating a brackish water area within 15 km of the upstream of the river bank. In this study, the deep learning algorithm Long Short-Term Memory (LSTM) was applied to predict the salinity of the Nakdong Bridge (about 5 km upstream of the river bank) for the purpose of rapid decision making for the target brackish water zone and prevention of salt water damage. Input data were constructed to reflect the temporal and spatial characteristics of the Nakdong River estuary, such as the amount of discharge from Changnyeong and Hamanbo, and an optimal model was constructed in consideration of the hydraulic characteristics of the Nakdong River Estuary by changing the degree according to the sequence length. For prediction accuracy, statistical analysis was performed using the coefficient of determination (R-squred) and RMSE (root mean square error). When the sequence length was 12, the R-squred 0.997 and RMSE 0.122 were the highest, and the prior prediction time showed a high degree of R-squred 0.93 or more until the 12-hour interval.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.84-95
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• 2022

The landscaping of Amore-Pacific's new building has received various awards since its construction. This study attempted to identify the mechanisms of planning, design, and construction of this project through the ground theory. The results of the study are summarized as follows. The client's place attachment of the sites, which was the company's parent, was the driving force for an international design competiton in which architecture and landscaping were integrated. After that, in the detailed design stage for the actual implementation of the contest-winning plan, competent local designers and contractors were selected, and a consultative body was operated to engage in various opinions and promote rational decision-making. As for consultative body's operation method, simulation, physical model production, and detailed drawings were created after sharing opinions, and landscape design supervision played a major role. Establishing consistency in design and construction through integrated planning and landscape design supervision is required to cultivate craftsmanship and foster landscape coordinators in today's industrialized practice. The accumulation of related follow-up studies and supplementation of the system is anticipated.

• Smart Media Journal
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• v.11 no.11
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• pp.49-62
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• 2022

Recently, with the development of Smart City Solutions such as Big data, AI, IoT, Autonomous driving, and Digital twins around the world, the proliferation of various smart devices and social media, and the record of the deeds that people have left everywhere, the construction of Smart Cities using the "Big Data" environment in which so much information and data is produced that it is impossible to gauge the scale is actively underway. The Purpose of this study is to construct an objective and systematic analysis Model based on Big Data to improve the transportation convenience of citizens and formulate efficient policies in Urban Information and Public Transportation accessibility in sustainable Smart Cities following the 4th Industrial Revolution. It is also to derive the methodology of developing a Big Data-Based public transport accessibility and policy management Platform using a sustainable Urban Public DB and a Private DB. To this end, Detailed Living Areas made a division and the accessibility of basic living amenities of Gwangju Metropolitan City, and the Public Transportation system based on Big Data were analyzed. As a result, it was Proposed to construct a Big Data-based Urban Information and Public Transportation accessibility Platform, such as 1) Using Big Data for public transportation network evaluation, 2) Supporting Transportation means/service decision-making based on Big Data, 3) Providing urban traffic network monitoring services, and 4) Analyzing parking demand sources and providing improvement measures.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.5
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• pp.367-377
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• 2016

The purpose of the projects for strengthening the Service Business Competitiveness, which had been sponsored by the Ministry of Trade, Industry and Energy, and managed by the NIPA, is to support for combining the whole business process of the SMEs with the business model considering the scientific aspects of the services, to enhance the productivity of them and to add the values of their activities. 5 organizations are selected in 2014, and 4 in 2015 as leading organizations for these projects. This study analyzed the efficiency of these projects using DEA. Throughout the analysis of the prior researches, this study used the amount of government-sponsored money as the input variable, and the number of new customer business, the sales revenue, and the number of new employment as the output variables. And the result of this analysis showed that the decision making unit 12, 15, and 21 was efficient. And from this study, we found out two more performance indicators such as, the number of new employment and the amount of sales revenue, besides the number of new customer businesses.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6B
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• pp.651-660
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• 2006

Although a harbor may be constructed with calmness in harbor in mind, which satisfies the design standard, it is frequently reported that the motion of moored ships disrupt the cargo handling. This is because of current design standard, which only deals with the wave height in the decision making process of cargo handling, and, now, a new kind of estimation method of operating ratio for calmness based on the motion of moored ship is in need. In this research, a computational method that analyses the harbor operation rate in harbor was put forward by considering the relation of allowable quantity of motion for cargo handling and the computation of the motion of moored ship at wharf by using moored ship motion analysis model. Here, a new estimetion method was applied at Onsan harbor, and it was compared with the current estimation method, and, then, the difference between the two methods was showed. The harbor operating ratio gained by a new method was dropped by 2~11% at ENE and NE directions when it was compared with the operating ratio based on the current design standard. However, when a harbor structure layout is to be designed, a harbor operating ratio test according to the wave height and a harbor operation rate test, which considers the motion of moored ship, are to be run side by side at a harbor designing process.

• Knowledge Management Research
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• v.24 no.3
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• pp.95-125
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• 2023

As the aviation industry has rapidly been grown, there are more factors for customers to consider when choosing an airline. In response, airlines are trying to increase customer value by providing high-quality services and differentiated experiential value. While early customer value research centered on utilitarian value, which is the trade-off between cost and benefit in terms of utility for products and services, the importance of experiential value has recently been emphasized. However, experiential value needs to be studied in a specific context that fully represents customer preferences because what constitutes customer value changes depending on the product or service context. In addition, customer value has an important influence on customers' decision-making, so it is necessary for airlines to accurately understand what constitutes customer value. In this study, we collected customer reviews and ratings from Skytrax, a website specializing in airlines, and utilized the BERTopic technique to derive factors of customer value. The results revealed nine factors that constitute customer value in airlines, and six of them are related to customer satisfaction. This study proposes a new methodology that enables a granular understanding of customer value and provides airlines with specific directions for improving service quality.