• Journal of Korean Philosophical Society
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• v.147
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• pp.333-356
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• 2018

Shang Yang was a person who, as a representative of the former School of Law, not only had an effect of thought on Han Fei Tzu, but also put a cornerstone of Qin Shi Huang's great universal unification by placing small and weak Qin Dynasty in a border area in the rank of a newly rising powerful nation. He is especially regarded as a person who valued laws and established the theoretical framework of legalist thought of School of Law systematically. To begin with, this writing examines the contents of the enforcement of legal reforms relevant to the prerequisite of Shang Yang's legal thought in historical archives, and confirms that Shang Yang succeeded in accomplishing legal reforms twice and that the aim of the legal reforms was to realize national prosperity and military power for the universal unification. This writing also takes notice of the fact that Shang Yang's legal thought went through specific steps for unifying the legal authority and the power of the monarch. Especially this writing focuses on applying the three-step theory of norms that was presented in the western social and political norm theory to Shang Yang's legal thought and on examining the characteristic and meaning explicitly. In short, the social and political norms go through emergence, cascade, and internalization. This writing aims to confirm that Shang Yang's legal thought also went through these three steps and was specified. Specifying this critical mind, this writing is a result which discusses that Shang Yang's legal thought went though the steps of the selective prescriptivism of emergence, the monarchical absolutism through sever punishment, and the internal monarchism for national prosperity and military power, and that the thought was systemized. Finding that the contents of Shang Yang's legal thought correspond to the three-step theory of norms and produce the individual meaning is the independent characteristic of this writing. It is the aim of this writing that the system and meaning of Shang Yang's legal thought will be confirmed more explicitly through this contextual examination.

• Korean Journal of Heritage: History & Science
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• v.49 no.1
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• pp.146-165
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• 2016

With the introduction of the system of recognizing masters of craft and performance skills in 1970, the principle of "preserving the original form," which was already in general use, was adopted as a legal principle in the Cultural Heritage Protection Act. While the concept "original form" can be related to tangible elements of heritage through the Act, the intangibility of craft and performance skills does not allow their pinpointing at a particular temporal period or the identification of a particular master from the past as the basis of an original form. Therefore, those craft or performance skills that are available at the point of recognition of relevant masters must serve as the basis of the original form for the intangible heritage concerned. This means that the principle of preserving the original form of intangible heritage has been implemented not based on a fundamental form of materiality, but rather on the craft or performance skills that may be held by a master at the time of his/her recognition as a "temporary original form." This principle has been observed through intangible heritage transmission and education policies for recognized masters and their trainees, contributing to establish an elitist transmission environment in which public were denied to join the education on intangible heritage. Even with policies guided by the principle of preserving the original form, designated craft and performance skills have been transformed contingent upon given social and environmental conditions, thus hindering the preservation of the original form. Despite the intrinsic limitations of the principle of preserving the original form when applied to intangible heritage, this principle has served as a practical guideline for protecting traditional Korean culture from external influences such as modernization and Westernization, and also as an ultimate goal for the safeguarding of intangible heritage, engendering actual policy effects. The Act on the Safeguarding and Promotion of Intangible Cultural Heritage that comes into effect in March 2016 takes the constantly evolving nature of intangible heritage into consideration and resultantly adopts a concept of "essential form" (jeonhyeong) in place of "original form" (wonhyeong). This new concept allows for any transformations that may take place in the environment surrounding the intangible heritage concerned, and is intended to mitigate the rigidity of the concept of "original form." However, it should be noted that "essential form," which is manifested as the unique significance, knowledge, and skills delivered by the intangible heritage concerned, should be maintained according to the guidelines and principles related to heritage conservation. Therefore, the new concept can be understood not as a rupture, but more as a continuum of the concept of "original form."

• Journal of Life Science
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• v.28 no.12
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• pp.1416-1423
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• 2018

With strong biotin binding affinity ($K_D=10^{-14}M$), the tetrameric feature of streptavidin could be used to increase the antigen binding activity of a camel heavy chain (VHH) antibody through their fusion, here stained with biotinylated horseradish peroxidase and subsequent immunoassays ELISA and Western blot analysis. For this application, we cloned the streptavidin gene amplified from the Streptomyces avidinii chromosome by PCR, and this was fused to the gene of the 8B9 VHH antibody which is specific to green fluorescent protein (GFP) antigens. To express a soluble fusion protein in Escherichia coli, we used the pUC119 plasmid-based expression system which uses the lacZ promoter for induction by IPTG, the pelB leader sequence at the N-terminus for secretion into the periplasmic space, and six polyhistidine tags at the C-terminus for purification of the expressed proteins using an $Ni^+$-NTA-agarose column. Although streptavidin is toxic to E. coli because of its strong biotin binding property, this soluble fusion protein was expressed successfully. In SDS-PAGE, the size of the purified fusion protein was 122.4 kDa in its native condition and 30.6 kDa once denatured by boiling, suggesting the tetramerization of the monomeric subunit by non-covalent association through the streptavidin moiety fusing to the 8B9 VHH antibody. In addition, this fusion protein showed biotin binding activity similar to streptavidin as well as GFP antigen binding activity through both ELISA and Western blot analysis. In conclusion, the protein resulting from the fusion of an 8B9 VHH antibody with streptavidin was successfully expressed and purified as a soluble tetramer in E. coli; it showed both biotin and GFP antigen binding activity suggesting the possible production of a tetrameric and bifunctional VHH antibody.

• Journal of agricultural medicine and community health
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• v.44 no.1
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• pp.11-27
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• 2019

Dementia is major epidemic disease of the 21st century in the world. Dementia is one of the major issues in public health globally. Also in Korea, the estimated prevalence of dementia was 8.7%(0.47 million) in 2010, the number will reach the 1 million mark in 2024, it will become a 15.1%(2.71 million) by 2050. Among Koreans aged 65 or older, 725,000 are estimated to be suffering from dementia in 2017. Against dementia, Korea developed three National Dementia Plans in 2008, 2012, and 2016. The 1st plan was came into effect in 2008 and focused on prevention, early diagnostic, development and coordination of infrastructures and management, and improving awareness. The 2nd plan was launched in 2012, addressed the same priorities but had a stronger focus on supporting family members. In 2012 the Dementia Management Act established a statutory basis for organization of the National Dementia Plans. Under the Dementia Management Act, the government is required to produce a comprehensive plan for dementia every 5 years. The Act also orders that the government should register the dementia patients and collect statistics on epidemiology and the management of the dementia conditions. The Dementia Management Act of Korea required the operation of the National Institute of Dementia and Metropolitan/Provincial Dementia Centers to make and carry out dementia management plans throughout the nation. The Act also mandate to establish Dementia Counselling Centers in every public health center and the National Dementia Helpline. The 3rd National Dementia Plan of 2016 aims to build a dementia friendly community to ensure people with dementia and their carer live well. This plan focus on community-based prevention and management of dementia, convenient and safe diagnosis, treatment, and care for people with dementia, the reduction of the care burden for family care-givers of people with dementia, and support for dementia research through research, statistics and technology. In 2017, Moon's government will introduce the "National Dementia Responsibility System," which guarantees most of the burden caused by dementia. This plan include that the introduction of a ceiling on self-pay for dementia diseases, expansion of the application of dementia care standards through alleviating the support criteria for long-term care insurance for mild dementia, expansion of dementia support centers, expansion of national and public dementia care facilities. In the meantime, Korea has accomplished many accomplishments by establishing many measures related to dementia and promoting related projects in a short time, but there are still many challenges.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.239-251
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• 2019

Statistical methods such as moving averages, Kalman filtering, exponential smoothing, regression analysis, and ARIMA (autoregressive integrated moving average) have been used for stock market predictions. However, these statistical methods have not produced superior performances. In recent years, machine learning techniques have been widely used in stock market predictions, including artificial neural network, SVM, and genetic algorithm. In particular, a case-based reasoning method, known as k-nearest neighbor is also widely used for stock price prediction. Case based reasoning retrieves several similar cases from previous cases when a new problem occurs, and combines the class labels of similar cases to create a classification for the new problem. However, case based reasoning has some problems. First, case based reasoning has a tendency to search for a fixed number of neighbors in the observation space and always selects the same number of neighbors rather than the best similar neighbors for the target case. So, case based reasoning may have to take into account more cases even when there are fewer cases applicable depending on the subject. Second, case based reasoning may select neighbors that are far away from the target case. Thus, case based reasoning does not guarantee an optimal pseudo-neighborhood for various target cases, and the predictability can be degraded due to a deviation from the desired similar neighbor. This paper examines how the size of learning data affects stock price predictability through k-nearest neighbor and compares the predictability of k-nearest neighbor with the random walk model according to the size of the learning data and the number of neighbors. In this study, Samsung electronics stock prices were predicted by dividing the learning dataset into two types. For the prediction of next day's closing price, we used four variables: opening value, daily high, daily low, and daily close. In the first experiment, data from January 1, 2000 to December 31, 2017 were used for the learning process. In the second experiment, data from January 1, 2015 to December 31, 2017 were used for the learning process. The test data is from January 1, 2018 to August 31, 2018 for both experiments. We compared the performance of k-NN with the random walk model using the two learning dataset. The mean absolute percentage error (MAPE) was 1.3497 for the random walk model and 1.3570 for the k-NN for the first experiment when the learning data was small. However, the mean absolute percentage error (MAPE) for the random walk model was 1.3497 and the k-NN was 1.2928 for the second experiment when the learning data was large. These results show that the prediction power when more learning data are used is higher than when less learning data are used. Also, this paper shows that k-NN generally produces a better predictive power than random walk model for larger learning datasets and does not when the learning dataset is relatively small. Future studies need to consider macroeconomic variables related to stock price forecasting including opening price, low price, high price, and closing price. Also, to produce better results, it is recommended that the k-nearest neighbor needs to find nearest neighbors using the second step filtering method considering fundamental economic variables as well as a sufficient amount of learning data.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.49-71
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• 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
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• v.28 no.2
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• pp.191-206
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• 2022

Recently, it is a de-facto approach to utilize a pre-trained language model(PLM) to achieve the state-of-the-art performance for various natural language tasks(called downstream tasks) such as sentiment analysis and question answering. However, similar to any other machine learning method, PLM tends to depend on the data distribution seen during the training phase and shows worse performance on the unseen (Out-of-Distribution) domain. Due to the aforementioned reason, there have been many efforts to develop domain-specified PLM for various fields such as medical and legal industries. In this paper, we discuss the training of a finance domain-specified PLM for the Korean language and its applications. Our finance domain-specified PLM, KB-BERT, is trained on a carefully curated financial corpus that includes domain-specific documents such as financial reports. We provide extensive performance evaluation results on three natural language tasks, topic classification, sentiment analysis, and question answering. Compared to the state-of-the-art Korean PLM models such as KoELECTRA and KLUE-RoBERTa, KB-BERT shows comparable performance on general datasets based on common corpora like Wikipedia and news articles. Moreover, KB-BERT outperforms compared models on finance domain datasets that require finance-specific knowledge to solve given problems.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.202-217
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• 2022

Purpose: The recent increased use of Personal Mobility (PM) has been accompanied by a rise in the annual number of accidents. Accordingly, the safety requirements for PM use are being strengthened, but the laws/systems, infrastructure, and management systems remain insufficient for fostering a safe environment. Therefore, this study comprehensively searches the main problems and improvement methods through a review of previous studies that are related to PM. Then the priorities according to the importance of the improvement methods are presented through the Delphi survey. Method: The research method is mainly composed of a literature study and an expert survey (Delphi survey). Prior research and improvement cases (local governments, government departments, companies, etc.) are reviewed to derive problems and improvements, and a problem/improvement classification table is created based on keywords. Based on the classification contents, an expert survey is conducted to derive a priority improvement plan. Result: The PM-related problems were in 'non-compliance with traffic laws, lack of knowledge, inexperienced operation, and lack of safety awareness' in relation to human factors, and 'device characteristics, road-drivable space, road facilities, parking facilities' in relation to physical factors. 'Management/supervision, product management, user management, education/training' as administrative factors and legal factors are divided into 'absence/sufficiency of law, confusion/duplication, reduced effectiveness'. Improvement tasks related to this include 'PM education/public relations, parking/return, road improvement, PM registration/management, insurance, safety standards, traffic standards, PM device safety, PM supplementary facilities, enforcement/management, dedicated organization, service providers, management system, and related laws/institutional improvement', and 42 detailed tasks are derived for these 14 core tasks. The results for the importance evaluation of detailed tasks show that the tasks with a high overall average for the evaluation items of cost, time, effect, urgency, and feasibility were 'strengthening crackdown/instruction activities, education publicity/campaign, truancy PM management, and clarification of traffic rules'. Conclusion: The PM market is experiencing gradual growth based on shared services and a safe environment for PM use must be ensured along with industrial revitalization. In this respect, this study seeks out the major problems and improvement plans related to PM from a comprehensive point of view and prioritizes the necessary improvement measures. Therefore, it can serve as a basis of data for future policy establishment. In the future, in-depth data supplementation will be required for each key improvement area for practical policy application.

• Informatization Policy
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• v.30 no.2
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• pp.22-45
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• 2023

In research on the use of AI-based voice assistant services, problems related to the user's trust and privacy protection arising from the experience of service use are constantly being raised. The purpose of this study was to investigate empirically the effects of individual trust in AI and online privacy concerns on the continued use of AI-based voice assistants, specifically the impact of their interaction. In this study, question items were constructed based on previous studies, with an online survey conducted among 405 respondents. The effect of the user's trust in AI and privacy concerns on the adoption and continuous use intention of AI-based voice assistant services was analyzed using the Heckman selection model. As the main findings of the study, first, AI-based voice assistant service usage behavior was positively influenced by factors that promote technology acceptance, such as perceived usefulness, perceived ease of use, and social influence. Second, trust in AI had no statistically significant effect on AI-based voice assistant service usage behavior but had a positive effect on continuous use intention. Third, the privacy concern level was confirmed to have the effect of suppressing continuous use intention through interaction with trust in AI. These research results suggest the need to strengthen user experience through user opinion collection and action to improve trust in technology and alleviate users' concerns about privacy as governance for realizing digital government. When introducing artificial intelligence-based policy services, it is necessary to disclose transparently the scope of application of artificial intelligence technology through a public deliberation process, and the development of a system that can track and evaluate privacy issues ex-post and an algorithm that considers privacy protection is required.

• The Korean Journal of Archival Studies
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• no.16
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• pp.303-339
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• 2007

"The damage incurred from forced mobilization under the Japanese Imperialism" means the life, physical, and property damage suffered by those who were forced to lead a life as soldiers, civilians attached to the military, laborers, and comfort women forcibly mobilized by the Japanese Imperialists during the period between the Manchurian Incident and the Pacific War. Up to the present time, every effort to restore the history on such a compulsory mobilization-borne damage has been made by the damaged parties, bereaved families, civil organizations, and academic circles concerned; as a result, on March 5, 2004, Disclosure act of Forced Mobilization under the Japanese Imperialism[part of it was partially revised on May 17, 2007]was officially established and proclaimed. On the basis of this law, the Truth Commission on Forced Mobilization under the Japanese Imperialism Republic of Korea[Compulsory Mobilization Commission hence after] was launched under the jurisdiction of the Prime Minister on November 10, 2004. Since February 1, 2005, this organ has begun its work with the aim of looking into the real aspects of damage incurred from compulsory mobilization under the Japanese Imperialism, by which making the historical truth open to the world. The major business of this organ is to receive the damage report and investigation of the reported damage[examination of the alleged victims and bereaved families, and decision-making], receipt of the application for the fact-finding & fact finding; fact finding and matters impossible to make judgment; correction of a family register subsequent to the damage judgement; collection & analysis of data concerning compulsory mobilization at home and from abroad and writing up of a report; exhumation of the remains, remains saving, their repatriation, and building project for historical records hall and museum & memorial place, etc. The Truth Commission on Compulsory Mobilization has dug out and collected a variety of records to meet the examination of the damage and fact finding business. As is often the case with other history of damage, the records which had already been made open to the public or have been newly dug out usually have their limits to ascertaining of the diverse historical context involved in compulsory mobilization in their quantity or quality. Of course, there may happen a case where the interested parties' story can fill the vacancy of records or has its foundational value more than its related record itself. The Truth Commission on Compulsory mobilization generated a variety of oral history records through oral interviews with the alleged damage-suffered survivors and puts those data to use for examination business, attempting to make use of those data for public use while managing those on a systematic method. The Truth Commission on compulsory mobilization-possessed oral history archives were generated based on a drastic planning from the beginning of their generation, and induced digital medium-based production of those data while bearing the conveniences of their management and usage in mind from the stage of production. In addition, in order to surpass the limits of the oral history archives produced in the process of the investigating process, this organ conducted several special training sessions for the interviewees and let the interviewees leave their real context in time of their oral testimony in an interview journal. The Truth Commission on compulsory mobilization isn't equipped with an extra records management system for the management of the collected archives. The digital archives are generated through the management system of the real aspects of damage and electronic approval system, and they plays a role in registering and searching the produced, collected, and contributed records. The oral history archives are registered at the digital archive and preserved together with real records. The collected oral history archives are technically classified at the same time of their registration and given a proper number for registration, classification, and keeping. The Truth Commission on compulsory mobilization has continued its publication of oral history archives collection for the positive use of them and is also planning on producing an image-based matters. The oral history archives collected by this organ are produced, managed and used in as positive a way as possible surpassing the limits produced in the process of investigation business and budgetary deficits as well as the absence of records management system, etc. as the form of time-limit structure. The accumulated oral history archives, if a historical records hall and museum should be built as regulated in Disclosure act of forced mobilization, would be more systematically managed and used for the public users.