• The Korean Journal of Archival Studies
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• no.14
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• pp.91-117
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• 2006

Electronic Records need to be appraised the authenticity as well as the value itself. There has been various kinds of discussion about how records to be appraised the value of themselves, but there's little argument about how electronic records to be appraised the authenticity of themselves. Therefore this article is modeling some specific authenticity appraisal methods and showing each stages those methods should or may be applied. At the Ingest stage, integrity verification right after records creation in the organization which produced the records, quality and integrity verification about the transferred in the organization which received the records and integrity check between SIP and AIP in the organization which received and preserved the records are essential. At the Preservation stage, integrity check between same AIPs stored in different medium separately and validation of records where or not damaged and recovery damaged records are needed. At the various Processing stages, suitability evaluation after changing the record's management control meta data and changing the record's classification, integrity check after records migration and periodical validation and integrity verification about DIPs are required. For those activities, the appraisal methods including integrity verification, content consistency check, suitability evaluation about record's meta data, feasibility check of unauthorized update and physical status validation should be applied to the electronic records management process.

• The Korean Journal of Archival Studies
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• no.34
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• pp.57-105
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• 2012

The CAMS(Central Archives Management System) of NAK(National Archives of Korea) is an important system which receives and manages large amount of electronic records annually from 2015. From the point of view in database design, this paper analyzes the database schema of CAMS and discusses the direction of overall improvement of the CAMS. Firstly this research analyzes the tables for records and folders in the CAMS database which are core tables for the electronic records management. As a result, researchers notice that it is difficult to trust the quality of the records in the CAMS, because two core tables are entirely not normalized and have many columns whose roles are unknown. Secondly, this study suggests directions of normalization for the tables for records and folders in the CAMS database like followings: First, redistributing the columns into proper tables to reduce the duplication. Second, separating the columns about the classification scheme into separate tables. Third, separating the columns about the records types and sorts into separate tables. Lastly, separating metadata information related to the acquisition, takeover and preservation into separate tables. Thirdly, this paper suggests considerations to design and manage the database schema in each phase of archival management. In the ingest phase, the system should be able to process large amount of records as batch jobs in time annually. In the preservation phase, the system should be able to keep the management histories in the CAMS as audit trails including the reclassification, revaluation, and preservation activities related to the records. In the access phase, the descriptive metadata sets for the access should be selected and confirmed in various ways. Lastly, this research also shows the prototype of conceptual database schema for the CAMS which fulfills the metadata standards for records.

• Industry Promotion Research
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• v.4 no.1
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• pp.57-66
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• 2019

The extant research literature is scant in telling us how organizations actually implement lifelong learning practices and policies. Hence, the purpose of this paper is to describe how lifelong learning is grounded in practice. We do this by introducing a new conceptual framework that was developed on the basis of interviews with a number of leading edge corporations from Canada, the USA, India and Korea. At the heart of our model, and any effective lifelong learning system, is a performance management system. The performance management system allows for an ongoing interaction between managers and employees whereby challenging performance and learning goals are set, and concrete plans are made to achieve them. Those plans involve three types of learning activities. First, employees may be encouraged to engage in formal learning. This could be provided in-house, or the employee may take a leave of absence and return to school. Second, managers may deploy their subordinates to different departments or teams, so that they can take part in new work-based learning opportunities. Finally, employees may be encouraged to learn on their own time. By this we mean learning after organizational hours through firm-sponsored 5 programs, such as e-learning courses. Fueled by the performance management system, we posit that these three learning outlets lead to effective lifelong learning in organizations.

• The Korean Journal of Archival Studies
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• no.54
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• pp.81-109
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• 2017

This study suggests an analysis of the reviews provided by international archival professionals on the RiC-CM draft published by ICA EGAD. Some implications for the Korean archival management environment were also suggested. Some professional reviews were accessible through the internet. Italian archival professionals held workshops at various levels for the analysis and discussion of the draft. Duranti, the project director of InterPARES, also gave opinions about the draft in cluding the perspective of digital preservation. In the review of Artefactual, the draft was discussed in terms of system implementation. Reed, the director of Recordkeeping Innovation, also gave a feedback based on the record management experiences in Australia. Some implications can be suggested based on these professional opinions. First, we should try to build a test bed for the adoption of RiC to archival description in the Korean environment. Second, a minimum level of data elements that can secure authenticity and integrity will also be needed. Third and lastly, rich authority data for agents and functions related to archival records and records groups are essential to take full advantage of the standard.

• Journal of Industrial Convergence
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• v.22 no.8
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• pp.1-17
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• 2024

Recently, interest in edutech has been focused on its fusion with AI technology, and the market in this field is expanding. This study aims to analyze the technological competitiveness and key technological areas of major countries in the AI-edutech field. Additionally, considering that AI-edutech is a convergence of AI technology and edutech, the study seeks to examine the path dependence of AI-edutech in each country to determine whether they are based on existing AI technologies or edutech. To this end, AI-edutech patents were collected and competitiveness was analyzed using patent activity, patent impact, and market acquisition indicators. Path dependence for each country was analyzed using the hurdle negative binomial regression model. The analysis results indicate that the major countries in the AI-edutech field are China, South Korea, the United States, India, and Japan. In terms of patent activity, China had the highest level, followed by South Korea. In terms of patent impact and market securing power, the United States was high in both aspects, Japan had high market securing power, and South Korea had high patent influence. The results of the hurdle negative binomial analysis presented unique findings. The logit part results indicated that the possession of existing AI and edutech did not positively affect the emergence of current AI-edutech, but the count part results showed a positive influence. This suggests that, overall, it is difficult to assert that current AI-edutechs are based on past AI and edutechs. However, once some AI-edutechs based on existing AI and edutechs emerge, they are influenced by the existing technologies. These findings provide implications for future research and technological strategies in this field.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.119-129
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• 2004

This paper is designed to report the results of development and validation procedures in relation to the Freeway Incident Management System (FIMS) prototype development as part of Intelligent Transportation Systems Research and Development program. The central core of the FIMS is an integration of the component parts and the modular, but the integrated system for freeway management. The whole approach has been component-orientated, with a secondary emphasis being placed on the traffic characteristics at the sites. The first action taken during the development process was the selection of the required data for each components within the existing infrastructure of Korean freeway system. After through review and analysis of vehicle detection data, the pilot site led to the utilization of different technologies in relation to the specific needs and character of the implementation. This meant that the existing system was tested in a different configuration at different sections of freeway, thereby increasing the validity and scope of the overall findings. The incident detection module has been performed according to predefined system validation specifications. The system validation specifications have identified two component data collection and analysis patterns which were outlined in the validation specifications; the on-line and off-line testing procedural frameworks. The off-line testing was achieved using asynchronous analysis, commonly in conjunction with simulation of device input data to take full advantage of the opportunity to test and calibrate the incident detection algorithms focused on APID, DES, DELOS and McMaster. The simulation was done with the use of synchronous analysis, thereby providing a means for testing the incident detection module.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.111-124
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• 2018

This study aims to develop a classification model for predicting the occurrence of hyperlipidemia, one of the chronic diseases. Prior studies applying data mining techniques for predicting disease can be classified into a model design study for predicting cardiovascular disease and a study comparing disease prediction research results. In the case of foreign literatures, studies predicting cardiovascular disease were predominant in predicting disease using data mining techniques. Although domestic studies were not much different from those of foreign countries, studies focusing on hypertension and diabetes were mainly conducted. Since hypertension and diabetes as well as chronic diseases, hyperlipidemia, are also of high importance, this study selected hyperlipidemia as the disease to be analyzed. We also developed a model for predicting hyperlipidemia using SVM and meta learning algorithms, which are already known to have excellent predictive power. In order to achieve the purpose of this study, we used data set from Korea Health Panel 2012. The Korean Health Panel produces basic data on the level of health expenditure, health level and health behavior, and has conducted an annual survey since 2008. In this study, 1,088 patients with hyperlipidemia were randomly selected from the hospitalized, outpatient, emergency, and chronic disease data of the Korean Health Panel in 2012, and 1,088 nonpatients were also randomly extracted. A total of 2,176 people were selected for the study. Three methods were used to select input variables for predicting hyperlipidemia. First, stepwise method was performed using logistic regression. Among the 17 variables, the categorical variables(except for length of smoking) are expressed as dummy variables, which are assumed to be separate variables on the basis of the reference group, and these variables were analyzed. Six variables (age, BMI, education level, marital status, smoking status, gender) excluding income level and smoking period were selected based on significance level 0.1. Second, C4.5 as a decision tree algorithm is used. The significant input variables were age, smoking status, and education level. Finally, C4.5 as a decision tree algorithm is used. In SVM, the input variables selected by genetic algorithms consisted of 6 variables such as age, marital status, education level, economic activity, smoking period, and physical activity status, and the input variables selected by genetic algorithms in artificial neural network consist of 3 variables such as age, marital status, and education level. Based on the selected parameters, we compared SVM, meta learning algorithm and other prediction models for hyperlipidemia patients, and compared the classification performances using TP rate and precision. The main results of the analysis are as follows. First, the accuracy of the SVM was 88.4% and the accuracy of the artificial neural network was 86.7%. Second, the accuracy of classification models using the selected input variables through stepwise method was slightly higher than that of classification models using the whole variables. Third, the precision of artificial neural network was higher than that of SVM when only three variables as input variables were selected by decision trees. As a result of classification models based on the input variables selected through the genetic algorithm, classification accuracy of SVM was 88.5% and that of artificial neural network was 87.9%. Finally, this study indicated that stacking as the meta learning algorithm proposed in this study, has the best performance when it uses the predicted outputs of SVM and MLP as input variables of SVM, which is a meta classifier. The purpose of this study was to predict hyperlipidemia, one of the representative chronic diseases. To do this, we used SVM and meta-learning algorithms, which is known to have high accuracy. As a result, the accuracy of classification of hyperlipidemia in the stacking as a meta learner was higher than other meta-learning algorithms. However, the predictive performance of the meta-learning algorithm proposed in this study is the same as that of SVM with the best performance (88.6%) among the single models. The limitations of this study are as follows. First, various variable selection methods were tried, but most variables used in the study were categorical dummy variables. In the case with a large number of categorical variables, the results may be different if continuous variables are used because the model can be better suited to categorical variables such as decision trees than general models such as neural networks. Despite these limitations, this study has significance in predicting hyperlipidemia with hybrid models such as met learning algorithms which have not been studied previously. It can be said that the result of improving the model accuracy by applying various variable selection techniques is meaningful. In addition, it is expected that our proposed model will be effective for the prevention and management of hyperlipidemia.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.149-161
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• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.3
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• pp.26-38
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• 2011

The purpose of this study was to analyze the commemoration culture of Vietnam War Memorials (VWM) in Vietnam. Through site survey, the researcher selected 23 VWM in Vietnam and analyzed 5 categories: memorial type, design concept and narratives, location and spatial form, landscape elements, and content expressed in landscape details. The results are as follows: 1. Because of the long, drawn out Vietnam War, which lasted from 1955 to 1975, VWM were divided into 10 types mainly as soldier cemeteries based on a traditional memorial style, battlefields and places of tragedies considering sense of place, war museums representing victory and atrocity in war, and peace parks promoting reconciliation and peacemaking. 2. The analysis revealed that the main concepts and narratives of VWM were to value the victims of the Vietnam War, remember soldiers' contributions, highlight the victory in war and resistance to the United States, and express a sense of place. Peacemaking applied only to My Lai Peace Park and Han-Viet Hoa Binh Cong Vien, built by international cooperation. 3. Cemeteries and appreciation memorials were designed to follow a traditional memorial space form that highly regard both axis and symmetry. The design concept at battlefields and places where tragedies occurred depended mainly upon a sense of place and used symbolic landscape elements to compensate for the undefined concept. 4. Sculptures and towers were mainly used to highlight war victory and resistance as the representative style of a Socialist country, weapons and pictures exhibited in war museums and battlefield showed the reality and strain of war. Symbolic elements of Buddhism and Confucianism were often introduced as a way to venerate the memory of deceased persons. 5. The state and heroic actions in the Vietnam War were realistically depicted on sculptures and walls. Also, the symbolic phrase, 'TO-QUOC-GUI-CONG' meaning 'our country remember your achievement', were written on the memorial tower and 'Quagmiire' was used to metaphorically represent the difficulties faced by the U.S. military on battlefields during the war and the uncertainly that pervaded U.S. society in those days. 6. In VWM, ideologies like nationalism, patriotism, socialism, capitalism were mixed and traditional cultures like Buddhism, Confucianism, Taoism were inherent. Differing from their Confucianism culture, war heroes, particularly including women, were often described by sculpture, monument, and pictures and the conflict in and outside the country regarding the Vietnam War was shown. Further study will be required to analyze design characteristics of VWM in the u.s. and to understand the difference in commemoration cultures between Vietnam and the U.S.