• Journal of Korean Society of Water and Wastewater
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• v.20 no.6
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• pp.799-811
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• 2006

As an alternative measure to replace reactive stance with proactive one, a risk based management scheme has been commonly applied to enhance public satisfaction on water service by providing a higher creditable solution to handle a rehabilitation problem of pipe having high potential risk of leaks. This study intended to examine the feasibility of a simulation model to predict a recurrence probability of pipe leaks. As a branch of the data mining technique, probabilistic neural network (PNN) algorithm was applied to infer the extent of leaking recurrence probability of water network. PNN model could classify the leaking level of each unit segment of the pipe network. Pipe material, diameter, C value, road width, pressure, installation age as input variable and 5 classes by pipe leaking probability as output variable were built in PNN model. The study results indicated that it is important to pay higher attention to the pipe segment with the leak record. By increase the hydraulic pipe pressure to meet the required water demand from each node, simulation results indicated that about 6.9% of total number of pipe would additionally be classified into higher class of recurrence risk than present as the reference year. Consequently, it was convinced that the application of PNN model incorporated with a data base management system of pipe network to manage municipal water distribution network could make a promise to enhance the management efficiency by providing the essential knowledge for decision making rehabilitation of network.

• The Journal of Korean Obstetrics and Gynecology
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• v.33 no.1
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• pp.1-18
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• 2020

Objectives: This review is aimed at assessing the efficacy and effectiveness of oriental medicine for the prevention of Ovarian Hyperstimulation Syndrome (OHSS) through literature research and overview. Methods: Database searching was conducted to identify relevant randomized controlled trials (RCTs) on oriental medicine for the prevention of Ovarian Hyperstimulation Syndrome. Studies were searched from Journal of Korean Obstetrics and Gynecology, Korean studies Information Service System, Korean Medical Database, China National Knowledge Infrastructure, Cochrane library, PubMed and EmBase up to 7^th November, 2019. Results: Ten RCTs were finally selected. Eight studies intervened with oral Chinese herb medicine, one is intervened with Chinese medicine enema and the other with acupuncture. Eight studies concluded that intervention with oriental medicine significantly decreased OHSS incidence. Five studies showed significantly higher pregnancy rate in the intervention groups. Two studies reported higher ovulation rate and other two studies showed more maturated eggs than the control groups. Four studies showed opposite results in serum Estradiol level. Vascular Endothelial Growth Factor level was significantly lower in the intervention groups in two studies. Conclusions: From ten studies, oriental medicine reduced OHSS incidence rate and showed preventable effectiveness. Further strictly designed studies and acupuncture intervened studies are needed to establish evidences.

• Journal of Contemporary Eastern Asia
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• v.18 no.1
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• pp.7-29
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• 2019

This study describes an approach for comparative bibliometric analysis of scientific publications related to (i) individual or several departments comprising a university, and (ii) broader integrated subject areas using multiple disciplinary schemes. It uses a custom dataset of scientific publications (ca. 15,000 articles and reviews, published during 2009-2013, and recorded in the Web of Science Core Collections) with author affiliations to the research departments, dedicated to science, technology, engineering, mathematics, and medicine (STEMM), of a comprehensive university. The dataset was subjected, at first, to the department level and discipline level analyses using the newly available KAKEN-L3 classification (based on MEXT/JSPS Grants-in-Aid system), hierarchical clustering, correspondence analysis to decipher the major departmental and disciplinary clusters, and visualization of the department-discipline relationships using two-dimensional stacked bar diagrams. The next step involved the creation of subsets covering integrated subject areas and a comparative analysis of departmental contributions to a specific area (medical, health and life science) using several disciplinary schemes: Essential Science Indicators (ESI) 22 research fields, SCOPUS 27 subject areas, OECD Frascati 38 subordinate research fields, and KAKEN-L3 66 subject categories. To illustrate the effective use of the science mapping techniques, the same subset for medical, health and life science area was subjected to network analyses for co-occurrences of keywords, bibliographic coupling of the publication sources, and co-citation of sources in the reference lists. The science mapping approach demonstrates the ways to extract information on the prolific research themes, the most frequently used journals for publishing research findings, and the knowledge base underlying the research activities covered by the publications concerned.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.857-866
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• 2022

The current study is a meta analysis study to identify the factors related to infection management performance and the effect size according to the factors. Data collection was included from the data of KMBASE, RISS, KISS, DBpia, National Library of Korea, Pubmed, and EMBASE. R3.5.1 was used for the data analysis. A total of 22 factors were identified. The meta analysis showed the effect size as follows: gender(.16), age(.30), education(.32), beds(.28), needs of education in infection management(.44), participating in education of infection management(.25), recognition/knowledge in infection management(.70). Based on the findings, evidence based programs need to be provided to improve the infection management performance of health workers at Long-Term Care Hospitals.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.134-146
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• 2024

This study introduces and experimentally validates a novel approach that combines Instruction fine-tuning and Low-Rank Adaptation (LoRA) fine-tuning to optimize the performance of Large Language Models (LLMs). These models have become revolutionary tools in natural language processing, showing remarkable performance across diverse application areas. However, optimizing their performance for specific domains necessitates fine-tuning of the base models (FMs), which is often limited by challenges such as data complexity and resource costs. The proposed approach aims to overcome these limitations by enhancing the performance of LLMs, particularly in the analysis precision and efficiency of national Research and Development (R&D) data. The study provides theoretical foundations and technical implementations of Instruction fine-tuning and LoRA fine-tuning. Through rigorous experimental validation, it is demonstrated that the proposed method significantly improves the precision and efficiency of data analysis, outperforming traditional fine-tuning methods. This enhancement is not only beneficial for national R&D data but also suggests potential applicability in various other data-centric domains, such as medical data analysis, financial forecasting, and educational assessments. The findings highlight the method's broad utility and significant contribution to advancing data analysis techniques in specialized knowledge domains, offering new possibilities for leveraging LLMs in complex and resource-intensive tasks. This research underscores the transformative potential of combining Instruction fine-tuning with LoRA fine-tuning to achieve superior performance in diverse applications, paving the way for more efficient and effective utilization of LLMs in both academic and industrial settings.

• Journal of the Korea Society of Computer and Information
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• v.18 no.10
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• pp.23-37
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• 2013

In this paper, the proposed movie recommender system constructs trust network, which is similar to social network, using user's trust information that users explicitly present. Recommendation on items is performed by using relation degree between users and information of recommended item is provided by a visualization method. We discover the hidden relationships via the constructed trust network. To provide visualized recommendation information, we employ Freebase which is large knowledge base supporting information such as movie, music, and people in structured format. We provide three visualization methods as the followings: i) visualization based on movie posters with the number of movies that user required. ii) visualization on extra information such as director, actor and genre and so on when user selected a movie from recommendation list. iii) visualization based on movie posters that is recommended by neighbors who a user selects from trust network. The proposed system considers user's social relations and provides visualization which can reflect user's requirements. Using the visualization methods, user can reach right decision making on items. Furthermore, the proposed system reflects the user's opinion through recommendation visualization methods and can provide rich information to users through LOD(Linked Open Data) Cloud such as Freebase, LinkedMDB and Wikipedia and so on.

• Journal of Service Research and Studies
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• v.7 no.2
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• pp.1-16
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• 2017

The service that has been recognized as both a non-productive activity and auxiliary activity of manufacturing have become the driving force of the customers' demand with the 'service' itself. The service base is expanding and evolving rapidly. It is important to look at changes in service concepts to understand service systems. Because the service system itself has a cyclic nature based on the concept of service, it can help in the study and the "how" of service by looking at changing the system according to the evolution of the service concept. The ability to organize and utilize relationships is considered to be an important factor for managers in the service economy era. However, the attention of corporate is focused on their internal capabilities and they are familiar with external resources (knowledge and competence of customers). In this case study for each type of service, we analyzed the activities of interacting service providers-consumers in service relationship, and constructed a new service system model emphasizing intangible value and long-term outcome. This study is worth re-examining the role of customers in today's service economy era and actively utilizing a new service model for business performance.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.4
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• pp.125-135
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• 2009

Logs from various security system can reveal the attack trials for accessing private data without authorization. The logs can be a kind of confidence deriving factors that a certain IP address is involved in the trial. This paper presents a rule-based expert system for derivation of privacy violation confidence using various security systems. Generally, security manager analyzes and synthesizes the log information from various security systems about a certain IP address to find the relevance with privacy violation cases. The security managers' knowledge handling various log information can be transformed into rules for automation of the log analysis and synthesis. Especially, the coverage of log analysis for personal information leakage is not too broad when we compare with the analysis of various intrusion trials. Thus, the number of rules that we should author is relatively small. In this paper, we have derived correlation among logs from IDS, Firewall and Webserver in the view point of privacy protection and implemented a rule-based expert system based on the derived correlation. Consequently, we defined a method for calculating the score which represents the relevance between IP address and privacy violation. The UI(User Interface) expert system has a capability of managing the rule set such as insertion, deletion and update.

• Journal of Gifted/Talented Education
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• v.27 no.1
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• pp.97-118
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• 2017

This paper aims to provide reference model for directions and objectives of Software(SW) gifted education. In order to achieve the goals introduced above, we conducted the research in the following steps. First, we selected the concept of ICT-based creative talented person as a base model to establish the concept of SW gifted person. The selected base model composed three core competencies which were 'knowledge and technology competencies', 'synthesizing and creativity competencies', and 'personality competencies'. Second, we developed survey tools, like questionnaires, to investigate participant's recognition of SW gifted person. The survey tools composed three components 'computational thinking', 'entrepreneurship', and 'social responsibility'. Each of the components composed seven elements. Third, after selecting the opinion poll participants as an elementary school teacher, we surveyed opinion polling. By selecting an elementary school teacher as the opinion poll participants, we wanted to identify theirs ' opinions which are thought to be the starting point for gifted education. To survey we developed on-line survey system by using Google functions. Fourth, we analyzed the collected opinion data. To identify we summarized and synthesized participant's opinions that average values and agreement level by using frequency analysis. Also, in order to compare opinions that average values and agreement level based on whether or not participant's various experiences and competencies we computed t-value, F-value, and ${\chi}^2$ verification.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.17-29
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• 2007

Inference engine that performs the brain of software agent in next generation's web with various standards based on standard language of the web, XML has to understand SWRL (Semantic Web Rule Language) that is a language to express the rule in the Semantic Web. In this research, we want to develop a forward inference engine, SMART-F (SeMantic web Agent Reasoning Tools-Forward chaining inference engine) that uses SWRL as a rule express method, and OWL as a fact express method. In the traditional inference field, the Rete algorithm that improves effectiveness of forward rule inference by converting if-then rules to network structure is often used for forward inference. To apply this to the Semantic Web, we analyze the required functions for the SWRL-based forward inference, and design the forward inference algorithm that reflects required functions of next generation's Semantic Web deducted by Rete algorithm. And then, to secure each platform's independence and portability in the ubiquitous environment and overcome the gap of performance, we developed management tool of fact and rule base and forward inference engine. This is compatible with fact and rule base of SMART-B that was developed. So, this maximizes a practical use of knowledge in the next generation's Web environment.