• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.26 no.1
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• pp.217-231
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• 2015

This study aims to infer the gene-protein 'brings_about' chains of pancreatic cancer which were referred to in the pancreatic cancer related researches by constructing the gene-protein interaction network of pancreatic cancer. The chains can help us uncover publicly unknown knowledge that would develop as empirical studies for investigating the cause of pancreatic cancer. In this study, we applied a novel approach that grafts text mining and the main path analysis into Swanson's ABC model for expanding intermediate concepts to multi-levels and extracting the most significant path. We carried out text mining analysis on the full texts of the pancreatic cancer research papers published during the last ten-year period and extracted the gene-protein entities and relations. The 'brings_about' network was established with bio relations represented by bio verbs. We also applied main path analysis to the network. We found the main direct 'brings_about' path of pancreatic cancer which includes 14 nodes and 13 arcs. 9 arcs were confirmed as the actual relations emerged on the related researches while the other 4 arcs were arisen in the network transformation process for main path analysis. We believe that our approach to combining text mining analysis with main path analysis can be a useful tool for inferring undiscovered knowledge in the situation where either a starting or an ending point is unknown.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.8
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• pp.736-741
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• 2001

The restoration optimum image from transformation image demands compound change of image change, calender reform, and multiple solution calculation. This study presents that system actively deal with outside interference, vibration, movement, mechanical feature on the operating or before the operating and avoids complicated mathematical numerical expression and revise based on expert knowledge based which applies Fuzzy Logic which is one of Artificial Intelligent technique.

• Journal of architectural history
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• v.8 no.3 s.20
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• pp.75-89
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• 1999

Under the WTO system, global standardization of professionalism in architecture practice calls for transformation of curriculum in architectural education in Korea. This paper compares the curriculum standards of international accrediting authorities such as NAAB and RIBA based on UIA accord which defines fundamental knowledge and abilities of an architect. As a result this paper extracts 51 achievement oriented criteria of architectural education in Korea. It can be categorized as communication, design, cultural context(history and theory, human behavior and social aspects), technical systems(structural systems, environmental control systems, construction material and assemblies) and practice(project process, project economics and business management, laws and regulations). Based on this recommended Korean curriculum standards, current curriculum is analyzed focusing on the 5 architectural programs in Seoul. Through this analysis, it became clear that some area - social and economic aspects in architecture, sustainability in architecture, understanding and selection of construction material, assemblies and environmental control system, recycling of existing building, professional liability, professional rules of conduct, project economics and project management - need to be covered and emphasized to meet the international standards in professional education in architecture. The result in this paper will be used as a basic data in the process of finding the direction of restructuring curriculum for professional architectural education in Korea.

• Nuclear Engineering and Technology
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• v.45 no.4
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• pp.477-488
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• 2013

The PLC (Programmable Logic Controller) has been widely used to implement real-time controllers in nuclear RPSs (Reactor Protection Systems). Increasing complexity and maintenance cost, however, are now demanding more powerful and cost-effective implementation such as FPGA (Field-Programmable Gate Array). Abandoning all experience and knowledge accumulated over the decades and starting an all-new development approach is too risky for such safety-critical systems. This paper proposes an RPS software development process with a platform change from PLC to FPGA, while retaining all outputs from the established development. This paper transforms FBD designs of the PLC-based software development into a behaviorally-equivalent Verilog program, which is a starting point of a typical FPGA-based hardware development. We expect that the proposed software development process can bridge the gap between two software developing approaches with different platforms, such as PLC and FPGA. This paper also demonstrates its effectiveness using an example of a prototype version of a real-world RPS in Korea.

• Knowledge Management Research
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• v.23 no.4
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• pp.21-41
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• 2022

With the development of AI and digital technologies such as big data, metaverse, and the Internet of Things, Robotic Process Automation (RPA) has brought great development and change to companies. Among these realistic industrial areas by RPA, the call center service area, which consists of a combination of complex high-tech systems and professional operation groups, has now reached the stage where AI is conducting counseling. The evolution of this digital transformation has become an important direction of change in the digital-related industry sector. Along with these changes, there have been many changes in the technical stress of the members of the organization within the RPA organization and their solutions. In this study, the representative psychological mechanisms were presented as Digital Shadow Work (DSW), expressed as 'unpaid work', and Organizational Citizenship Behavior (OCB), which is 'an act that helps organizations other than their duties'. This study theoretically contributes to the extension of the DSW concept to the organizational members.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.259-267
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• 2022

With the rapid development and introduction of digital technologies, both everyday human life and technological processes of any production are changing, which stimulates the transformation of the economy and education. Digital technologies are not only a tool, but also a living environment of modern human, which opens up new opportunities: learning at any convenient time, continuing education, the ability to form individual educational learning trajectories and more. However, the digital environment requires teachers to take a modern approach to the organization of the educational process, the formation of new skills and abilities to work in the digital educational environment. As a result of the study, it was found that the system of vocational education should provide training for masters of industrial training who have a high level of digital competence. The purpose of the article is to single out, theoretically substantiate and determine the level of formation of structural components of digital competence of future masters of agricultural training. The structure of digital competence of agricultural master was analyzed on the basis of domestic and foreign scientists researches. Systematized research results indicate that digital competence consists of four components: motivational-value (combination of internal and external motives for the use of digital technologies in future professional activities), cognitive (a set of theoretical knowledge, skills and abilities of future master of industrial training to effectively build educational process with the use of digital technologies), activity-professional (expansion and deepening of knowledge, skills, necessary skills for effective implementation of digital technologies in the educational process) and evaluative-reflexive (ability to analyze and self-analyze own activities and its results taking into account professional characteristics, self-realization in professional activities through the use of digital technologies). These components are comparable with the indicators that describe the knowledge, skills and abilities needed by the future master of industrial training to organize the modern educational process. A questionnaire was conducted to determine the levels of this competence formation, which allows us to conclude that it is necessary to increase the level of formation of all components of digital competence of future masters of industrial training in agriculture. The results of the study can be used as a basis for the development of disciplines that form the special competencies of masters of industrial training in agriculture and programs of advanced training of teachers.

• Journal of Science Education
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• v.33 no.1
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• pp.56-68
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• 2009

The purpose of this study was to investigate students' ontological categories about rocks and the earth's crust and plate tectonics. A total of 169 high school students in the first grade were involved in the study, and in order to extend the boundary and tendency of the research, structuralized questions and coding frame were generated. Additionally, the results from all students were codified in four levels according to coding frame (matter, transformation, proto-process, and process). Followings are the results. First, the ontological categories of students about the concepts of this research were classified dominantly into a matter and transformation within the boundary of 67% of rocks, and 75% of the crust. The propensity of plate tectonics in terms of ontological category were analyzed by being codified into 68% of process category which proved to have relatively process-oriented perspective. Secondly, the inclination to allocate ontological categories of each students in terms of field concepts were confirmed in 16% and 31% per each student that were codified into process categories and matter categories. Most students that were codified into matter category responded to high tendency to view the world as a combination of simple substances. Moreover, the students had ontological faith that speculates only through a state or an incident in terms of concepts that form a structure of knowledge.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.4
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• pp.77-87
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• 1994

This paper deals with an automated forming sequence design system by which designers can determine desirable operation sequences even if they have little experience in the design of cold forging process. The forming sequence design in the cold forging is very important and requires many kinds of technical and empirical knowledge. They system isproposed, which generates forming sequence plans for the multistage cold forging of axisymmtrical solid products. Since the process of metal forming can be considered as a transformation of geometry, treatment of the geometry of the product is a key in planning process. To recognize the geometry of the product section, section entity representation and primitive geometries were used. Section entity representation can be used for the calculation of maximum diameter, maximum height, and volume. Forming sequence for the part can be determined by means of primitive geometries such as cylinder, cone, convex, and concave. By utilizing this geometrical characteristics (diameter, height, and radius), the product geometry is expressed by a list of the priitive geometries. Accordingly the forming sequence design is formulated as the search problem which starts with a billet geometry and finishes with a given product one. Using the developed system, the sequence drawing with all dimensions, which includes the proper sequence of operations for the part, is generated under the environment of AutoCAD. Based on the results of forming sequence, process variables(strain, punch pressure, die inner pressure, and forming load) are determined.

• Journal of the Korean Institute of Gas
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• v.26 no.4
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• pp.41-57
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• 2022

The global demand for carbon neutrality in response to climate change is in a situation where it is necessary to prepare countermeasures for carbon trade barriers for some countries, including Korea, which is classified as an export-led economic structure and greenhouse gas exporter. Therefore, digital transformation, which is one of the predictable ways for the carbon-neutral transition model to be applied, should be introduced early. By applying digital technology to industrial gas manufacturing facilities used in one of the major industries, high-tech manufacturing industry, and hydrogen gas facilities, which are emerging as eco-friendly energy, abnormal detection, and diagnosis services are provided with cloud-based predictive diagnosis monitoring technology including operating knowledge. Here are the trends. Small and medium-sized companies that are in the blind spot of carbon-neutral implementation by confirming the direction of abnormal diagnosis predictive monitoring through optimization, augmented reality technology, IoT and AI knowledge inference, etc., rather than simply monitoring real-time facility status It can be seen that it is possible to disseminate technologies such as consensus knowledge in the engineering domain and predictive diagnostic monitoring that match the economic feasibility and efficiency of the technology. It is hoped that it will be used as a way to seek countermeasures against carbon emission trade barriers based on the highest level of ICT technology.