• Journal of the Korea Concrete Institute
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• v.24 no.5
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• pp.543-551
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• 2012

Road pavements in Korea generally show shorter service life than the predicted one. There are many reasons for this phenomenon including increased traffic load and other attacks from exposure conditions. In order to extend a service life and upgrade the pavement, a new multi-functional composite pavement system is being developed in Korea. This study is to investigate the performances of fiber-reinforced lean concrete for pavement base. This study considered mineral admixtures of fly ash and reject ash. The reject ash is defined as ash that does not meet the specifications for fly ash so that it cannot be used as a supplemental material for cement replacement. Due to the inherent property of lean concrete, compaction during the fabrication of specimens is a key factor. Therefore, this study suggests an appropriate compaction method. From the test results, the compressive strengths of the concrete satisfied the required limit of 5 MPa at 7 days. When a compaction roller was used to mimic actual field conditions, the strength development seemed to be influenced by the compaction energy rather than hydration of cement itself.

• Journal of the Korea Society of Computer and Information
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• v.5 no.4
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• pp.41-47
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• 2000

In modern dynamic management environment, there is growing recognition that information & knowledge management systems are essential for CEO's efficient/effective decision making. As a key component to cope with this current, we suggest the management performance data-mining system based on IT(Information Technology). This system measures management performance that is considered with both VA(Value-Added), which represents stakeholder's point of view and EVA(Economic Value-Added), which represents shareholder's point of view. The relationship between management performance and 85 financial ratios is analyzed, and then important financial ratios are drawn out. In analyzing the relationship, we applied the explanation-based Gas(Genetic Algorithms) that consider predictability, understanability (lucidity) and reasonability factors simultaneously. To demonstrate the performance of the system, we conducted a case study using financial data over the 16-years from 1981 to 1996 of Korean automobile industry which is taken from database of KISFAS(Korea Investors Services Financial Analysis System).

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.691-704
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• 2021

The development of AI technology has brought about a big change in our lives. The importance of AI and data education is also growing as AI's influence from life to society to the economy grows. In response, the OECD Education Research Report and various domestic information and curriculum studies deal with data literacy and present it as an essential competency. However, the definition of data literacy and the content and scope of the components vary among researchers. Thus, we analyze the semantic similarity of words through Word2Vec deep learning natural language processing methods along with the definitions of key data literacy studies and analysis of word frequency utilized in components, to present objective and comprehensive definition and components. It was revised and supplemented by expert review, and we defined data literacy as the 'basic ability of knowledge construction and communication to collect, analyze, and use data and process it as information for problem solving'. Furthermore we propose the components of each category of knowledge, skills, values and attitudes. We hope that the definition and components of data literacy derived from this study will serve as a good foundation for the systematization and education research of AI education related to students' future competency.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.2
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• pp.129-151
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• 2022

In the current work, a series of three-dimensional finite element analyses have been carried out to understand the behaviour of piles when the adjacent tunnelling passes underneath grouped piles with a reinforced pile cap. In the current study, the numerical analysis studied the computed results regarding the ground reinforcement condition between the tunnel and pile foundation. In addition, several key issues, such as the pile settlements, the axial pile forces, the shear stresses and the relative displacements have been thoroughly analysed, and the IoT platform based preliminary design guidelines were also presented. The pile head settlements of the nearest pile from the tunnel without the ground reinforcement increased by about 70% compared to the farthest pile from the tunnel with the maximum level of reinforcement. The quality management factor data of the piles were provided as API (Application Programming Interface) of various forms by the collection and refinement. Hence it has been shown that it would be important to provide the appropriate API by defining the each of data flow process when the data were created. The behaviour of the grouped piles with the pile cap, depending on the amount of ground reinforcement, has been extensively analysed, and the IoT platform regarding the quality management of piles has been suggested.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.5
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• pp.30-42
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• 2022

Due to the increase in construction of tunnels, the burdens of maintenance works for tunnel structures have been increasing in Korea. In addition, the increase of traffic volume and aging of materials also threatens the safety of tunnel facilities, therefore, maintenance costs are expected to increase significantly in the future. Accordingly, automated condition assessment technologies like image-based tunnel scanning system for inspection and diagnosis of tunnel facilities have been proposed. For image-based tunnel scanning system, it is key to create a planar image through stitching of multiple images captured by tunnel scanning system. In this study, performance of feature-based stitching algorithms suitable for stitching tunnel scanning images was evaluated. In order to find a suitable algorithm SIFT, ORB, and BRISK are compared. The performance of the proposed algorithm was determined by the number of feature extraction, calculation speed, accuracy of feature matching, and image stitching result. As for stitching performance, SIFT algorithm was the best in all parts of tunnel image. ORB and BRISK also showed satisfactory performance and short calculation time. SIFT can be used to generate precise planar images. ORB and BRISK also showed satisfactory stitching results, confirming the possibility of being used when real-time stitching is required.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.453-462
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• 2022

In this paper, the artificial intelligence (AI) technology used in the medical image analysis field was analyzed through a literature review. Literature searches were conducted on PubMed, ResearchGate, Google and Cochrane Review using the key word. Through literature search, 114 abstracts were searched, and 98 abstracts were reviewed, excluding 16 duplicates. In the reviewed literature, AI is applied in classification, localization, disease detection, disease segmentation, and fit degree of registration images. In machine learning (ML), prior feature extraction and inputting the extracted feature values into the neural network have disappeared. Instead, it appears that the neural network is changing to a deep learning (DL) method with multiple hidden layers. The reason is thought to be that feature extraction is processed in the DL process due to the increase in the amount of memory of the computer, the improvement of the calculation speed, and the construction of big data. In order to apply the analysis of medical images using AI to medical care, the role of physicians is important. Physicians must be able to interpret and analyze the predictions of AI algorithms. Additional medical education and professional development for existing physicians is needed to understand AI. Also, it seems that a revised curriculum for learners in medical school is needed.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.7
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• pp.475-484
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• 2018

The propulsion control device of an electric railway vehicle is a key main component corresponding to an engine of an automobile, and a device for controlling this is a device called a GDU (Gate Drive Unit). Also, when the frequency of failure of the propulsion control system was analyzed, the nonconformity ratio of GDU was the highest. GDU was not able to access core technologies due to the introduction of foreign products, and there were general problems with overall maintenance activities due to discontinuation of GDU of the manufacturer. The GDU has reached the end of its life with 23 to 14 years of long-term use.In order to solve these problems, this study was designed to identify the proper life span by analyzing compatible GDU's acquisition and failure, and to improve the existing system of maintenance focusing on health inspection. Maintenance of the components with a short life span compared to the entire service life is essential. Most foreign parts introduced at the beginning of the construction are not replaced due to technical problems or long-term operation. However, due to the characteristics of railway vehicles with a long life span of more than 25 years, it is necessary to maintain them for a long period of time. The study should be more concrete and empirical. The replacement type GDU of capacitors was able to easily measure the life of the capacitance by removing the capacitor modules, measure the life span of each unit test, and accurately perform preventive maintenance of the capacitor.

• Animal Bioscience
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• v.37 no.7
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• pp.1168-1176
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• 2024

Objective: As a charismatic species, cashmere goats have rich genetic resources. In the Inner Mongolia Autonomous Region, there are three cashmere goat varieties named and approved by the state. These goats are renowned for their high cashmere production and superior cashmere quality. Therefore, it is vitally important to protect their genetic resources as they will serve as breeding material for developing new varieties in the future. Methods: Three breeds including Inner Mongolia cashmere goats (IMCG), Hanshan White cashmere goats (HS), and Ujimqin white cashmere goats (WZMQ) were studied. IMCG were of three types: Aerbas (AEBS), Erlangshan (ELS), and Alashan (ALS). Nine DNA samples were collected for each population, and they were genomically re-sequenced to obtain high-depth data. The genetic diversity parameters of each population were estimated to determine selection intensity. Principal component analysis, phylogenetic tree construction and genetic differentiation parameter estimation were performed to determine genetic relationships among populations. Results: Samples from the 45 individuals from the five goat populations were sequenced, and 30,601,671 raw single nucleotide polymorphisms (SNPs) obtained. Then, variant calling was conducted using the reference genome, and 17,214,526 SNPs were retained after quality control. Individual sequencing depth of individuals ranged from 21.13× to 46.18×, with an average of 28.5×. In the AEBS, locus polymorphism (79.28) and expected heterozygosity (0.2554) proportions were the lowest, and the homologous consistency ratio (0.1021) and average inbreeding coefficient (0.1348) were the highest, indicating that this population had strong selection intensity. Conversely, ALS and WZMQ selection intensity was relatively low. Genetic distance between HS and the other four populations was relatively high, and genetic exchange existed among the other four populations. Conclusion: The Inner Mongolia cashmere goat (AEBS type) population has a relatively high selection intensity and a low genetic diversity. The IMCG (ALS type) and WZMQ populations had relatively low selection intensity and high genetic diversity. The genetic distance between HS and the other four populations was relatively high, with a moderate degree of differentiation. Overall, these genetic variations provide a solid foundation for resource identification of Inner Mongolia Autonomous Region cashmere goats in the future.

• Economic and Environmental Geology
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• v.51 no.4
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• pp.381-392
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• 2018

This study examines strategies and implementation plans for commercializing $CO_2$ capture and storage, which is an effective method to achieve the national goal of reducing greenhouse gas. In order to secure cost-efficient business model of $CO_2$ capture and storage, we propose four key strategies, including 1) urgent need to select a large-scale storage site and to estimate realistic storage capacity, 2) minimization of source-to-sink distance, 3) cost-effectiveness through technology innovation, and 4) policy implementation to secure public interest and to encourage private sector participation. Based on these strategies, the implementation plans must be designed for enabling $CO_2$ capture and storage to be commercialized until 2030. It is desirable to make those plans in which large-scale demonstration and subsequent commercial projects share a single storage site. In addition, the plans must be able to deliver step-wised targets and assessment processes to decide if the project will move to the next stage or not. The main target of stage 1 (2019 ~ 2021) is that the large-scale storage site will be selected and post-combustion capture technology will be upgraded and commercialized. The site selection, which is prerequisite to forward to the next stage, will be made through exploratory drilling and investigation for candidate sites. The commercial-scale applicability of the capture technology must be ensured at this stage. Stage 2 (2022 ~ 2025) aims design and construction of facility and infrastructure for successful large-scale demonstration (million tons of $CO_2$ per year), i.e., large-scale $CO_2$ capture, transportation, and storage. Based on the achievement of the demonstration project and the maturity of carbon market at the end of stage 2, it is necessary to decide whether to enter commercialization of $CO_2$ capture and storage. If the commercialization project is decided, it will be possible to capture and storage 4 million tons of $CO_2$ per year by the private sector in stage 3 (2026 ~ 2030). The existing facility, infrastructure, and capture plant will be upgraded and supplemented, which allows the commercialization project to be cost-effective.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.65-82
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• 2015

Recently, there has been a surge of interest in finding core issues and analyzing emerging trends for the future. This represents efforts to devise national strategies and policies based on the selection of promising areas that can create economic and social added value. The existing studies, including those dedicated to the discovery of future promising fields, have mostly been dependent on qualitative research methods such as literature review and expert judgement. Deriving results from large amounts of information under this approach is both costly and time consuming. Efforts have been made to make up for the weaknesses of the conventional qualitative analysis approach designed to select key promising areas through discovery of future core issues and emerging trend analysis in various areas of academic research. There needs to be a paradigm shift in toward implementing qualitative research methods along with quantitative research methods like text mining in a mutually complementary manner. The change is to ensure objective and practical emerging trend analysis results based on large amounts of data. However, even such studies have had shortcoming related to their dependence on simple keywords for analysis, which makes it difficult to derive meaning from data. Besides, no study has been carried out so far to develop core issues and analyze emerging trends in special domains like the aviation industry. The change used to implement recent studies is being witnessed in various areas such as the steel industry, the information and communications technology industry, the construction industry in architectural engineering and so on. This study focused on retrieving aviation-related core issues and emerging trends from overall research papers pertaining to aviation through text mining, which is one of the big data analysis techniques. In this manner, the promising future areas for the air transport industry are selected based on objective data from aviation-related research papers. In order to compensate for the difficulties in grasping the meaning of single words in emerging trend analysis at keyword levels, this study will adopt topic analysis, which is a technique used to find out general themes latent in text document sets. The analysis will lead to the extraction of topics, which represent keyword sets, thereby discovering core issues and conducting emerging trend analysis. Based on the issues, it identified aviation-related research trends and selected the promising areas for the future. Research on core issue retrieval and emerging trend analysis for the aviation industry based on big data analysis is still in its incipient stages. So, the analysis targets for this study are restricted to data from aviation-related research papers. However, it has significance in that it prepared a quantitative analysis model for continuously monitoring the derived core issues and presenting directions regarding the areas with good prospects for the future. In the future, the scope is slated to expand to cover relevant domestic or international news articles and bidding information as well, thus increasing the reliability of analysis results. On the basis of the topic analysis results, core issues for the aviation industry will be determined. Then, emerging trend analysis for the issues will be implemented by year in order to identify the changes they undergo in time series. Through these procedures, this study aims to prepare a system for developing key promising areas for the future aviation industry as well as for ensuring rapid response. Additionally, the promising areas selected based on the aforementioned results and the analysis of pertinent policy research reports will be compared with the areas in which the actual government investments are made. The results from this comparative analysis are expected to make useful reference materials for future policy development and budget establishment.