• Convergence Security Journal
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• v.21 no.2
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• pp.67-79
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• 2021

Lessons Learned(LL) is a military term defined as all activities that promote future development by finding problems and need improvement in education and reality in the field of warfare development. In this paper, we focus on presenting actual examples and applying AI analysis inference techniques to solve revealed problems in promoting LL activities, such as long-term analysis, budget problems, and necessary expertise. AI legal advice services using cognitive computing-related technologies that have already been practical and in use, were judged to be the best examples to solve the problems of LL. This paper presents intelligent LL inference techniques, which utilize AI. To this end, we want to explore theoretical backgrounds such as LL analysis definitions and examples, evolution of AI into Machine Learning, cognitive computing, and apply it to new technologies in the defense sector using the newly proposed L²-OODA ensemble algorithm to contribute to implementing existing power improvement and optimization.

• The Korean Journal of Archival Studies
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• no.62
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• pp.77-107
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• 2019

There have been constant requests for urgently recruiting professionals in the archives to establish archival management systems by reflecting public institutional feature as well as reinforcing expertise and independence of them. However, it is true that some even adequate professional manpower haven't been secured at each level of public institutions due to ambiguous standards for the placement of professionals in the field of records management followed by the current [Public Records Management Act]. Thereupon, this study is to create records management task model for the archival management institutions with the workload of records management induced by the model, and to present reasonable scale of workforce to deal with the assignment. Moreover, here is shown which professional staff should be allocated for better efficiency and systems to carry out the task of records management in each relevant institution.

• Land and Housing Review
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• v.11 no.4
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• pp.51-65
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• 2020

The purpose of this study was to identify the problems related to the amendment and preservation of the lien system and to suggest a feasible and efficient improvement plan. The Analytic Hierarchy Process (AHP) and descriptive statistical analyses were used in this study. The survey subjects were divided into three groups based on their expertise: "Administrative Experts, Practical Experts, and Financial Institution Experts" and compared to find the results. The results show that 1) the procedural aspect was the most important for the large classification, 2) the supplementary disclosure system was the most important for the legislative aspect, and 3) the supplementation of the abuse of the lien report was the most important for the intermediate classification. Furthermore, the study showed that the most important finding was the reinforcement of punishment for the right of false reporting and illegal acts, followed by the registration order system (the creditor alone application), and the registration system (bond, debtor, joint application). The implications and suggestions of this study are as followed. With regard to the current lien system, illegal acts such as false liens and the misuse of multiple reporting were considered as the biggest problems. In terms of the effective improvement plan of the lien system, the misuse of reporting liens and improvement in the procedural aspects of reporting rights should be given top priority. Therefore, the most important course of action is to strengthen the punishment for false liens, improve the disclosure system and make it mandatory to report rights.

• The Korean Journal of Archival Studies
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• no.67
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• pp.57-97
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• 2021

The purpose of this study is to investigate the transformation of archival appraisal theories in the digital environment. It is clear that the archival appraisal in the degital information technology era, characterized by the mass production of data type records on the information infrastructure will be fundamentally different from before. As the meaning of selecting in appraisal will be reduced, the existing archival appraisal theories need to be reviewed again. We can expect the decentralization of appraising centered on the national archives, considering the social proliferation of digital information technology. Meanwhile, expertise in archival appraisal will also be changed to a new professional acceptance model for digital technology. Digital technology will give us opportunities for a paradigm shift that may be difficult to understand with existing thinking of archival appraisal.

• The Korean Journal of Archival Studies
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• no.67
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• pp.267-318
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• 2021

The purpose of this study is to analyze how the "memory approach" has affected archival methodology and activities, and suggest the directions of archival activities in each field. Although there have been many discussions on the memories and collective memories in Archival Studies, it is necessary to analyze them more practically from the viewpoint of archival activism. In this study, the memory approaches in archival discourse are classified into four categories in terms of archival activism; i) the role of archives as social memory organizations, ii) the memory struggle for finding out the truth of the past, iii) archival activities of restorative justice for people who suffer from trauma memories after social disasters and human rights violations, and iv) the memory process of communities' archiving for strengthening community identities. The meaning and issues are analyzed for each category, and the practice based on archival expertise and political and social practices are examined together as necessary competencies for archival activism.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2049-2068
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• 2021

AI combined with NLP techniques has promoted the use of Virtual Assistants and have made people rely on them for many diverse uses. Conversational Agents are the most promising technique that assists computer users through their operation. An important challenge in developing Conversational Agents globally is transferring the groundbreaking expertise obtained in English to other languages. AI is making it possible to transfer this learning. There is a dire need to develop systems that understand secular languages. One such difficult language is Hindi, which is the fourth most spoken language in the world. Semantic similarity is an important part of Natural Language Processing, which involves applications such as ontology learning and information extraction, for developing conversational agents. Most of the research is concentrated on English and other European languages. This paper presents a Corpus-based word semantic similarity measure for Hindi. An experiment involving the translation of the English benchmark dataset to Hindi is performed, investigating the incorporation of the corpus, with human and machine similarity ratings. A significant correlation to the human intuition and the algorithm ratings has been calculated for analyzing the accuracy of the proposed similarity measures. The method can be adapted in various applications of word semantic similarity or module for any other language.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.590-601
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• 2021

The current study explored how robot's persuasive intent and its' physical distance affect consumers' evaluaton on the robot and the product that the robot advertises. This study administered a 2 (level of pursasion intent: low vs. high) × 2 (physical distance: normal vs. close) between-subjects factorial design experiment. The findings revealed that consumers evaluated the robot' expertise and trustworthiness more negatively and reported lower intentions to buy the produce when they perceived robot's persasive intent saliently high. Consumers were also found to show more negative attitude toward the robot and lower intentions to buy the produce when the robot approached to their personal space more closely. The theoretical and practical implications about human-robot interaction in marketing context were discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.579-586
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• 2021

This study examines the application of big data and tasks of tourism based on the case of Jeju Special Self-Governing Province, which used big data for regional tourism policy. Through the use of big data, it is possible to understand rapidly changing tourism trends and trends in the tourism industry in a timely and detailed manner. and also could be used to elaborate existing tourism statistics. In addition, beyond the level of big data analysis to understand tourism phenomena, its scope has expanded to provide a platform for providing real-time customized services. This was made possible by the cooperative governance of industry, government, and academia for data building, analysis, infrastructure, and utilization. As a task, the limitation of budget dependence and institutional problems such as the infrastructure for building personal-level data for personalized services, which are the ultimate goal of smart tourism, and the Personal Information Protection Act remain. In addition, expertise and technical limitations for data analysis and data linkage remain.

• The Mathematical Education
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• v.60 no.3
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• pp.341-362
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• 2021

The purpose of this study is to explore the qualitative characteristics of pre-service teachers' motivation while they are participating in group activities for developing mathematical essay assessment problem and revising it. For this purpose, we analyzed individual factors about group learning activities as well as contextual factors about practical competency (in developing and revising mathematical essay assessment problem through collecting data of student responses to the problem). As results of data analyses, autonomy, among individual factors regarding group learning activities, was one of the main characteristics in attainment value, utility value, and intrinsic value, whereas task, authority, and grouping, among contextual factors regarding practical competency, appeared to have a positive impact on task value. These results suggest how to think of specific ideas and articulate them in designing a curriculum to develop student-evaluation expertise for pre-service teachers.

• Journal of Korean Library and Information Science Society
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• v.52 no.2
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• pp.65-84
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• 2021

This study aimed to analyze the overall operation status of the Bank of Korea library representing the economic library in Korea, investigate user satisfaction and demand, and to propose a direction for the development of the economic library in the future. To this end, a case study was conducted on changes in the external environment of major libraries at home and abroad, and a user survey was conducted. As a result, the future tasks include introducing smart systems, robotics some library services, non-face-to-face service response spaces that reflect the times, introducing big data analysis services, strengthening user-tailored systems, and activating SNS communication. It proposed developing specialized libraries, online reference and research support services, and providing original DBs for publications to strengthen expertise, maintaining and expanding cloud services, maintaining and expanding cooperative projects, and collecting national knowledge and information.