• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.43-61
• /
• 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 Life Science
• /
• v.29 no.5
• /
• pp.537-544
• /
• 2019

Genome editing technology employing gene scissors has generated interest in molecular breeding in various fields, and the development of the third-generation gene scissors of the clustered, regularly interspaced short palindromic repeat (CRISPR) system has accelerated the field of molecular breeding through genome editing. In this study, we analyzed the possibility of silkworm molecular breeding using gene scissors by genomic and phenotypic analysis after editing the biogenesis of lysosome-related organelles (BmBLOS) gene of Bakokjam using the CRISPR/Cas9 system. Three types of guide RNAs (gRNA) were synthesized based on the BmBLOS gene sequence of Bakokjam. Complexes of the prepared gRNA and Cas9 protein were formed and introduced into Bombyx mori BM-N cells by electroporation. Analysis of the gene editing efficiency by T7 endonuclease I analysis revealed that the B4N gRNA showed the best efficiency. The silkworm genome was edited by microinjecting the Cas9/B4N gRNA complex into silkworm early embryos and raising the silkworms after hatching. The hatching rate was as low as 18%, but the incidence of mutation was over 40%. In addition, phenotypic changes were observed in about 70% of the G0 generation silkworms. Sequence analysis showed that the BmBLOS gene appeared to be a heterozygote carrying the wild-type and mutation in most individuals, and the genotype of the BmBLOS gene was also different in all individuals. These results suggest that although the possibility of silkworm molecular breeding using the CRISPR/Cas9 system would be very high, continued research on breeding and screening methods will be necessary to improve gene editing efficiency and to obtain homozygotes.

• Korea Science and Art Forum
• /
• v.37 no.4
• /
• pp.297-308
• /
• 2019

Air pollution due to the fine dust level updating every day, and the problem of indoor air pollution due to ventilation difficulties and indoor discharge pollutants is also serious. In order to improve the indoor air quality, the air purification effect using the plants is prominent. In this study was started to investigated the living environment of modern people, the risk of indoor air pollution and the improvement function of plants, and to activate plant application. The purpose of this study is to analyze the main functions and design status of domestic and overseas plant - related applications, and to understand the actual use of modern plant applications and to help them learn more convenient plant - related knowledge. Therefore, this paper attempted to establish a basis for suggesting a new plant application by conducting a survey on the health effects of indoor air pollution and user awareness of plant - related applications. The results and contents of the study are as follows. First, as a theoretical review, indoor air pollution is more dangerous to modern people who have a high proportion of indoor living time and adversely affects their health. In order to solve such a problem, it has been shown that air conditioning and stress reduction can be effectively achieved by placing plants in the indoor space. Second, the analysis of the previous study shows the risk of indoor air pollution and its adverse effects on health. In addition, I have been able to find some researches related to the improvement of the indoor air by using the air purifying plants, and I can see the improvement of the user's behavior through the development or improvement of the application. Third, as a result of the survey on the status of domestic and overseas plant application, the main function of the application having high installation number was watering notification, provision of basic information of plants, and most of the functions were plant discerment through cameras. Fourth, most of the survey respondents have either raised or raised plants. Those who have little experience with plant applications have also shown positive feedback in the future on the use of plant-related applications. In addition, due to social problems such as air pollution, air purification using plants and functional plants showed high interest. Based on these results, we propose the need for a multi-functional plant application that can improve the indoor air pollution and facilitate the provision of information related to it.

• Journal of Ginseng Culture
• /
• v.3
• /
• pp.90-118
• /
• 2021

Gaeseong fostered the conditions necessary for modern capitalism, as huge capital was accumulated through the cultivation and trade of ginseng, which were activities that flourished in the 18th century. During the Japanese colonial era, ginseng merchants were not simply limited to acquiring landowner capital from ginseng trade but actively converted such resource to productive and financial capital, thereby becoming modern entrepreneurs. Ginseng merchants led the joint management and investment of Gaeseong Electric Co., Ltd., Daehan Cheonil Bank, Gaeseong Brewing Co., Ltd., and Songgo Textile Company, founded in the early 20th century. They pursued corporate profits and, as leading individuals of society, spearheaded regional development by supporting educational and cultural projects in Gaeseong. These projects included the establishment of the Gaeseong Commercial School, the publication of Goryeo Times, and the operation of the Gaeseong Jwa Theater. Although liberal economics prioritized shareholder interest, the 21st century witnessed an emphasis on social responsibility among stakeholders asthe major purpose of enterprises. A trend that emerged was ESG (environment, social, governance) management, in which non-financial factors are valued more highly than financial performance. A successful business, which was denoted only by high profits in the past, is now defined by whether a company fulfills its social responsibility. In the early 20th century, the corporate activities of ginseng merchants in Gaeseong reflected entrepreneurship and stakeholder-centered ESG management, which later emerged as essential elements of modern business management. The modern management philosophy ahead of its times stemmed from the regionality of Gaeseong. The political discrimination against Gaeseong residents in the Joseon Dynasty precluded them from becoming government officers, and under a strict social hierarchy, yangban ("noblemen"), the intellectuals of the Joseon Dynasty, were forced to serve as merchants. Son Bong-sang and Kong Seong-hak, aside from being representative ginseng merchants, were both Confucian scholars and writers. The second and third generations of ginseng merchant families who had received higher education abroad returned to Gaeseong to carry on with their family businesses, then established modern companies with capital accrued from the ginseng industry. An analysis of the commercial activities of ginseng merchants in the early 20th century confirmed that these individuals were pioneering entrepreneurs who adopted the ESG management philosophy. In ginseng merchants, one sees a dimension of capitalism with a human face, as with ginseng thatsaves human life.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.151-176
• /
• 2021

As the information technology industry develops, various kinds of data are being created, and it is now essential to process them and use them in the industry. Analyzing and utilizing various digital data collected online and offline is a necessary process to provide an appropriate experience for customers in the industry. In order to create new businesses, products, and services, it is essential to use customer data collected in various ways to deeply understand potential customers' needs and analyze behavior patterns to capture hidden signals of desire. However, it is true that research using data analysis and UX methodology, which should be conducted in parallel for effective service development, is being conducted separately and that there is a lack of examples of use in the industry. In thiswork, we construct a single process by applying data analysis methods and UX methodologies. This study is important in that it is highly likely to be used because it applies methodologies that are actively used in practice. We conducted a survey on the topic to identify and cluster the associations between factors to establish customer classification and target customers. The research methods are as follows. First, we first conduct a factor, regression analysis to determine the association between factors in the happiness data survey. Groups are grouped according to the survey results and identify the relationship between 34 questions of psychological stability, family life, relational satisfaction, health, economic satisfaction, work satisfaction, daily life satisfaction, and residential environment satisfaction. Second, we classify clusters based on factors affecting happiness and extract the optimal number of clusters. Based on the results, we cross-analyzed the characteristics of each cluster. Third, forservice definition, analysis was conducted by correlating with keywords related to happiness. We leverage keyword analysis of the thumb trend to derive ideas based on the interest and associations of the keyword. We also collected approximately 11,000 news articles based on the top three keywords that are highly related to happiness, then derived issues between keywords through text mining analysis in SAS, and utilized them in defining services after ideas were conceived. Fourth, based on the characteristics identified through data analysis, we selected segmentation and targetingappropriate for service discovery. To this end, the characteristics of the factors were grouped and selected into four groups, and the profile was drawn up and the main target customers were selected. Fifth, based on the characteristics of the main target customers, interviewers were selected and the In-depthinterviews were conducted to discover the causes of happiness, causes of unhappiness, and needs for services. Sixth, we derive customer behavior patterns based on segment results and detailed interviews, and specify the objectives associated with the characteristics. Seventh, a typical persona using qualitative surveys and a persona using data were produced to analyze each characteristic and pros and cons by comparing the two personas. Existing market segmentation classifies customers based on purchasing factors, and UX methodology measures users' behavior variables to establish criteria and redefine users' classification. Utilizing these segment classification methods, applying the process of producinguser classification and persona in UX methodology will be able to utilize them as more accurate customer classification schemes. The significance of this study is summarized in two ways: First, the idea of using data to create a variety of services was linked to the UX methodology used to plan IT services by applying it in the hot topic era. Second, we further enhance user classification by applying segment analysis methods that are not currently used well in UX methodologies. To provide a consistent experience in creating a single service, from large to small, it is necessary to define customers with common goals. To this end, it is necessary to derive persona and persuade various stakeholders. Under these circumstances, designing a consistent experience from beginning to end, through fast and concrete user descriptions, would be a very effective way to produce a successful service.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.47-64
• /
• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

• Journal of Korean Home Economics Education Association
• /
• v.32 no.4
• /
• pp.81-101
• /
• 2020

The purpose of this study is to develop and implement a process-based evaluation program with the theme of school space design in the housing area of the middle school home economics. In order to achieve For thispurpose, a process-based evaluation program based on the theme of school space design was developed following the ADDIE instructional design model, and the program was executed to a total of 93 students. A questionnaire survey and in-depth interview were conducted for the evaluation of the program. The results of this study are as follows. First, based on the results of a 2015-Revised Curriculum analysis, a school space design program evaluation plan was established, and two evaluation tasks were developed. Accordingly, scoring criteria were prepared and 8 evaluation materials for students and 2 evaluation materials for teachers were developed. A total of 9 sessions were developed for teaching and learning activities and evaluation-linked operation procedures to perform evaluation tasks. As a result of an expert validity test for the program, all items were verified to be appropriate in content validity and content composition with an average of 3.6 to 4 points (4 points). Second, after conducting the school space design program, a survey on students were conducted, and as a result, all three areas of school space design class, process-based evaluation, interest scored high in average scores of 4.12 to 4.27 out of 5. According to the survey and interview results, the program provided new learning opportunities for school space design, the students were able to reach the suggested achievement goals, and the self-assessment, peer evaluation and teacher feedback positively affected the students during the learning process so that they could reflect on their learning and actively participate in the subsequent learning activity. This study has a limitation in generalizability in that the program was conducted on a limited number of students, and future studies are expected to expand the scope in terms of research participants, evaluation criteria, and school space design classes. This study laid the foundation for theory and practice by developing and implementing a process-based evaluation program for home economics education, and it has contribution in that it suggested the possibility that teachers and students can take the initiatives in school space design, focusing on the housing content elements of home economics.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.23 no.4
• /
• pp.374-390
• /
• 2021

Growth and yield of field vegetable crops would be affected by climate conditions, which cause a relatively large fluctuation in crop production and consumer price over years. The yield prediction system for these crops would support decision-making on policies to manage supply and demands. The objectives of this study were to compile literatures related to onion and garlic and to perform data-mining analysis, which would shed lights on the development of crop models for these major field vegetable crops in Korea. The literatures on crop growth and yield were collected from the databases operated by Research Information Sharing Service, National Science & Technology Information Service and SCOPUS. The keywords were chosen to retrieve research outcomes related to crop growth and yield of onion and garlic. These literatures were analyzed using text mining approaches including word cloud and semantic networks. It was found that the number of publications was considerably less for the field vegetable crops compared with rice. Still, specific patterns between previous research outcomes were identified using the text mining methods. For example, climate change and remote sensing were major topics of interest for growth and yield of onion and garlic. The impact of temperature and irrigation on crop growth was also assessed in the previous studies. It was also found that yield of onion and garlic would be affected by both environment and crop management conditions including sowing time, variety, seed treatment method, irrigation interval, fertilization amount and fertilizer composition. For meteorological conditions, temperature, precipitation, solar radiation and humidity were found to be the major factors in the literatures. These indicate that crop models need to take into account both environmental and crop management practices for reliable prediction of crop yield.

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

• Journal of Intelligence and Information Systems
• /
• v.28 no.2
• /
• pp.207-235
• /
• 2022

In a knowledge-based society where knowledge and information industries are the main pillars of the economy, knowledge sharing and diffusion and its systematic management are recognized as essential strategies for improving national competitiveness and sustainable social development. In the field of Information Systems (IS) research, where the convergence of information technology and management takes place in various ways, the evolution of knowledge occurs only when researchers cooperate in turning old knowledge into new knowledge from the perspective of the scientific knowledge network. In particular, it is possible to derive new insights by identifying topics of interest in the relevant research field, applied methodologies, and research trends through network-based interdisciplinary graftings such as citations, co-authorships, and keywords. In previous studies, various attempts have been made to understand the structure of the knowledge system and the research trends of the relevant community by revealing the relationship between research topics, methodologies, and co-authors. However, most studies have compared two or more journals and been limited to a certain period; hence, there is a lack of research that looked at research trends covering the entire history of IS research. Therefore, this study was conducted in the following order for all the papers (from its first issue in 1977 to the first quarter of 2022) published in the MIS Quarterly (MISQ) Journal, which plays a leading role in revealing knowledge in the IS research field: (1) After extracting keywords, (2) classifying the extracted keywords into research topics, methodologies, and theories, and (3) using topic modeling and keyword network analysis in order to identify the changes from the beginning to the present of the IS research in a chronological manner. Through this study, it is expected that by examining the changes in IS research published in MISQ, the developing patterns of IS research can be revealed, and a new research direction can be presented to IS researchers, nurturing the sustainability of future research.