• KIPS Transactions on Computer and Communication Systems
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• v.2 no.12
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• pp.541-552
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• 2013

Recently software security of the smart phone is an important issue in the field of information science and technology due to fast propagation of smart technology in our life. The smart phone as the security critical systems which are utilizing in terminal systems of the banking, ubiquitous home management, airline passengers screening, and so on are related to the risk of costs, risk of loss, risk of availability, and risk by usage. For the security issues, software hazard analysis of smart phone is the key approaching method by use of observed failures. In this paper, we propose an efficient integrative framework for software security analysis of the smart phone using Fault Tree Analysis (FTA) and Failure Mode Effect Analysis (FMEA) to gain a convergence security and reliability analysis technique on hand handle devices. And we discuss about that if a failure mode effect analysis performs simpler, not only for improving security but also reducing failure effects on this smart device, the proposed integrative framework is a key solution.

• Journal of Satellite, Information and Communications
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• v.9 no.3
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• pp.109-115
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• 2014

This paper suggest meteorological satellite processing software's structure that reduces time and efforts of modification/upgrade. This structure's key feature is "algorithm component" that works within framework and eventually to a complete Meteorological satellite processing system. Most of existing Meteorological satellite system is designed around specific function and data sets which limits range of modification and upgrade. In addition, re-use of current algorithms become difficult although re-use of similar algorithm is the case in many occasions. This inefficiency can be resolved by designing a new framework as a result of detail analysis of collected requirements. A new framework and system architecture has been designed. In addition, operational flow of Satellite image processing framework has been described.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.10
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• pp.4339-4347
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• 2014

Purpose: This study aimed at exploring treatment delay (TD) among cancer patients in China with an attempt to develop a practical methodology facilitating frontline Chinese clinicians in promoting earlier cancer diagnosis and treatment. Materials and Methods: The study comprised framework development, qualitative interviews and paired factor rating. Framework development utilized systematic literature review, soft systems thinking and consensus groups. Qualitative interviews employed a checklist of open questions soliciting information about all the domains included the framework from cancer patients drawn via stratified randomized sampling of inpatients at 10 hospitals in Hefei, China. Paired factor rating used a self-developed computer aid and the interviewed patients as referring cases to weigh the relative importance of the factors listed in the framework in terms of their contributions to specific components of total delay (TD). Results: a) A conceptual framework was proposed consisting of a 6-step path to TD and 36 category determinants. b) A total of 227 patients were interviewed; their TD was 267.3 mean or 108 median days ranging from 0 to 2475 days; average appraisal, illness, behavioral, preparation and treatment delay accounted for 52.1%, 9.4%, 0.30%, 8.8% and 29.4% of the TD respectively. Individual side factors were rated substantially more important than environmental side factors (60% vs. 40%); most influential TD factors included cancer symptoms, overall health, family relations and knowledge about cancer and health. Conclusions: The framework proposed together with the interviewing and rating approaches used provide a potential new methodology for understanding cancer patients' TD and promoting earlier cancer treatment.

• Nutrition Research and Practice
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• v.12 no.6
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• pp.459-468
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• 2018

BACKGROUND/OBJECTIVES: The Dietary Reference Intakes for Koreans (KDRIs), a set of reference intake values, have served as a basis for guiding a balanced diet that promotes health and prevents disease in the general Korean population. In the process of developing DRIs, a systematic review has played an important role in helping the DRI committees make evidence-based and transparent decisions for updating the next DRIs. Thus, the 2015 KDRI steering committee applied the systematic review framework to the revision process of the KDRIs. The purpose of this article is to summarize the revision process for the 2015 KDRIs by focusing on the systematic review framework. MATERIALS/METHODS: The methods used to develop the systematic review framework for 2015 KDRIs followed the Agency for Healthcare Research and Quality and the Tufts Evidence-based Practice Center. The framework for systematic review of the 2015 KDRIs comprised of the 3 following steps: (1) development of an analytic framework and refinement of key questions and search terms; (2) literature search and data extraction; and, (3) appraisal of the literature and summarizing the results. RESULTS: A total of 203,237 studies were retrieved through the above procedure, with 2,324 of these studies included in the analysis. General information, main results, comments of reviewers, and results of quality assessment were extracted and organized by study design. The average points of quality appraisals were 3.0 (range, 0-5) points for intervention, 6.1 (0-9) points for cohort, 6.0 (3-9) points for nested case-control, 5.4 (1-8) points for case-control, 14.6 (0-22) points for cross-sectional studies, and 7.0 (0-11) points for reviews. CONCLUSIONS: Systematic review helped to establish the 2015 KDRIs as a useful tool for evidence-based approach. Collaborative efforts to improve the framework for systematic review should be continued for future KDRIs.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.141-148
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• 2019

The advancement of digital technology accelerates intelligence, convergence, and demands better change beyond traditional methods in all aspects of business models and technologies, infrastructure, processes, and platforms. Risk management is becoming more important because of various security risks, depending on the changing business environment and aligned to business goals is emerging from the existing information asset based risk management. For business aligned risk management, it is essential to understand the risk appetite for achieving business goals, which provides a basis for decision-making in subsequent risk management processes. In this paper, we propose a framework for analyzing the risk management framework, pre - existing risk analysis, and protection motivation theory that influences decisions on security risk management. To examine the practical feasibility of the developed risk appetite framework, we reviewed the applicability and significance of the proposed risk appetite framework through an advisory committee composed of security risk management specialists.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.1
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• pp.99-111
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• 2016

This paper presents a framework to analyze the change in the research and development (R&D) efficiency of government-funded research institutes (GRIs) in Korea. Cumulative data envelopment analysis/Malmquist index method is utilized to analyze the changes in R&D efficiency of GRIs. Data analysis of the R&D activities of 10 GRIs in Korea Research Council of Fundamental Science & Technology showed that the average R&D efficiency of the 10 GRIs improved from 2009 to 2013. However, the efficiency of a few GRIs decreased in terms of the catch-up index. The proposed framework can help management teams diagnose the current state of R&D activities and determine the efficacy of strategic actions by comparing efficiencies in the past.

• Journal of KIBIM
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• v.13 no.3
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• pp.39-47
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• 2023

This study aims to introduce a model for enhancing community well-being through the utilization of public open data. To objectively assess abstract notions of residential satisfaction, text data from complaints is analyzed. By leveraging accessible public data, costs related to data collection are minimized. Initially, relevant text data containing civic complaints is collected and refined by removing extraneous information. This processed data is then combined with meaningful datasets and subjected to topic modeling, a text mining technique. The insights derived are visualized using Geographic Information System (GIS) and Application Programming Interface (API) data. The efficacy of this analytical model was demonstrated in the Godeok/Gangil area. The proposed methodology allows for comprehensive analysis across time, space, and categories. This flexible approach involves incorporating specific public open data as needed, all within the overarching framework.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.3
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• pp.71-111
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• 2014

Metadata schemas are well recognized as one of the important technological components for archiving and preservation of digital resources. However, a single standard is not enough to cover the whole lifecycle for archiving and preserving digital resources. This means that we need to appropriately select metadata standards and combine them to develop metadata schemas to cover the whole lifecycle of resources (or records). Creating a unified framework to understand the features of metadata standards is necessary in order to improve metadata interoperability that covers the whole resource lifecycle. In this study, the author approached this issue from the task-centric view of metadata, proposing a Task model as a framework and analyzing the feature of archival metadata standards. The proposed model provides a new scheme to create metadata element mappings and to make metadata interoperable. From this study, the author found out that no single metadata standard can cover the whole lifecycle and also that an in-depth analysis of mappings between metadata standards in accordance with the lifecycle stages is required. The author also discovered that most metadata standards are primarily resource-centric and the different tasks in the resource lifecycle are not reflected in the design of metadata standard data models.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.4
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• pp.23-51
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• 2013

The purpose of the study is to examine the potentialities and limits of Business Reference Model (BRM) as records classification schemes in Korean central state institutions. The analysis is based on the data collected through focus group interviews of three times, in which six records professionals from central government agencies participate. This paper begins with inquiring the framework of records classification based BRM, required by Public Records Management Act. It explores the types of benefit of BRM application to government records classification. Based on the collected data from the interviews, it investigates how records are aggregated, and how transaction level (Danwi-Gwaje) of BRM is applied in the course of records aggregation.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.140-149
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• 2018

Social data such as users' comments are unstructured in nature and up-to-date technologies for analyzing such data are constrained by the available storage space and processing time when fast storing and processing is required. On the other hand, it is even difficult in using a huge amount of dynamically generated social data to analyze the user features in a high speed. To solve this problem, we design and implement a topic association analysis system based on the latent Dirichlet allocation (LDA) model. The LDA does not require the training process and thus can analyze the social users' hourly interests on different topics in an easy way. The proposed system is constructed based on the Spark framework that is located on top of Hadoop cluster. It is advantageous of high-speed processing owing to that minimized access to hard disk is required and all the intermediately generated data are processed in the main memory. In the performance evaluation, it requires about 5 hours to analyze the topics for about 1 TB test social data (SNS comments). Moreover, through analyzing the association among topics, we can track the hourly change of social users' interests on different topics.