• Journal of Intelligence and Information Systems
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• v.8 no.2
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• pp.51-69
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• 2002

In the supply chain environment on the web, collaborative problem solving and case-based modeling has been getting more important, because it is difficult to cope with diverse problem requirements and inefficient to manage many models as well. Hence, the approach on case-based modeling is required. This paper provides a framework that generates a goal model based on multiple cases, modeling knowledge, and forward chaining and it also develops a search algorithm through sensitivity analysis to reduce the modeling effort.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.37-52
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• 2011

Supply chain management is a strategic thinking which enhances the value of supply chain and adapts more promptly for the changing environment. For the seamless partnership and value creation in supply chains, information and knowledge sharing and proper partner selection criteria must be applied. Thus, the partner selection criteria are critical to maintain product quality and reliability. Each part of a product is supplied by an appropriate supply partner. The criteria for selecting partners are technological capability, quality, price, consistency, etc. In reality, the criteria for partner selection may change according to the characteristics of the components. When the part is a core component, quality factor is the top priority compared to the price. For a standardized component, lower price has a higher priority. Sometimes, unexpected case occurs such as emergency order in which the preference may shift on the top. Thus, SCM partner selection criteria must be determined dynamically according to the characteristics of part and its context. The purpose of this research is to develop an OWL model for the supply chain partnership depending on its context and characteristics of the parts. The uncertainty of variable is tackled through fuzzy logic. The parts with preference of numerical value and context are represented using OWL. Part preference is converted into fuzzy membership function using fuzzy logic. For the ontology reasoning, SWRL (Semantic Web Rule Language) is applied. For the implementation of proposed model, starter motor of an automobile is adopted. After the fuzzy ontology is constructed, the process of selecting preference-based supply partner for each part is presented.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.441-446
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• 2001

On global interconnectivity, the activation of real-time and worldwide contents will permeate and impact all aspects of day-to-day life well throughout this century. In managing contents and models, we too will see the impact of this rapidly changing environment. The real time availability of contents pertaining to a companys supply chain through means of the Internet and mobile networks(e.g., the IMT-2000) will necessitate a change in decision-making processes for effective management of contents and models. To increase the availability of many contents and models, a management system should have adaptive function in proving adequate content and model for companies. In the respect of management of contents and models, this paper discusses a production mechanism of meta-knowledge for effectively managing contents and models. Through two experimental analyses with the production mechanism, it is proven that the system enabling adaptive contents and models provision goes beyond existing ones in view of efficiency of management of contents and models in the wire and wireless networks.

• Journal of Microbiology and Biotechnology
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• v.21 no.5
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• pp.529-535
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• 2011

Single-chain variable fragment (scFv) is a fusion protein of the variable regions of the heavy (VH) and light (VL) chains of immunoglobulin, connected with a short linker peptide of 10 to about 20 amino acids. In this study, the scFv of a monoclonal antibody against the third domain of human CD4 was cloned from OKT4 hybridoma cells using the phage display technique and produced in E. coli. The expression, production, and purification of anti-CD4 scFv were tested using SDS-PAGE and Western blot, and the specificity of anti-CD4 scFv was examined using ELISA. A 31 kDa recombinant anti-CD4 scFv was expressed and produced in bacteria, which was confirmed by SDS-PAGE and Western blot assays. Sequence analysis proved the ScFv structure of the construct. It was able to bind to CD4 in quality ELISA assay. The canonical structure of anti-CD4 scFv antibody was obtained using the SWISS_MODEL bioinformatics tool for comparing with the scFv general structure. To the best of our knowledge, this is the first report for generating scFv against human CD4 antigen. Engineered anti-CD4 scFv could be used in immunological studies, including fluorochrome conjugation, bispecific antibody production, bifunctional protein synthesis, and other genetic engineering manipulations. Since the binding site of our product is domain 3 (D3) of the CD4 molecule and different from the CD4 immunological main domain, including D1 and D2, further studies are needed to evaluate the anti-CD4 scFv potential for diagnostic and therapeutic applications.

• Advances in environmental research
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• v.1 no.1
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• pp.15-35
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• 2012

Mercury (Hg) is a global environmental pollutant that has been the cause of many public concerns. One particular concern about Hg in aquatic systems is its trophic transfer and biomagnification in food chains. For example, the Hg concentration increases with the increase of food chain level. Fish at the top of food chain can accumulate high concentrations of Hg (especially the toxic form, methylmercury, MeHg), which is then transferred to humans through seafood consumption. Various biological and physiochemical conditions can significantly affect the bioaccumulation of Hg-including both its inorganic (Hg(II)) and organic (MeHg) forms-in fish. There have been numerous measurements of Hg concentrations in marine and freshwater fish worldwide. Many of these studies have attempted to identify the processes leading to variations of Hg concentrations in fish species from different habitats. The development of a biokinetic model over the past decade has helped improve our understanding of the mechanisms underlying the bioaccumulation processes of Hg in aquatic animals. In this review, I will discuss how the biokinetic modeling approach can be used to reveal the interesting biodynamics of Hg in fish, such as the trophic transfer and exposure route of Hg(II) and MeHg, as well as growth enrichment (the increases in Hg concentration with fish size) and biomass dilution (the decreases in Hg concentration with increasing phytoplankton biomass). I will also discuss the relevance of studying the subcellular fates of Hg to predict the Hg bioaccessibility and detoxification in fish. Future challenges will be to understand the inter- and intra-species differences in Hg accumulation and the management/mitigation of Hg pollution in both marine and freshwater fish based on our knowledge of Hg biodynamics.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.1-7
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• 2019

The objective of this study is to examine the trends in big data. Research abstracts were extracted from 4,019 articles, published between 1995 and 2018, on Web of Science and were analyzed using topic modeling and time series analysis. The 20 single-term topics that appeared most frequently were as follows: model, technology, algorithm, problem, performance, network, framework, analytics, management, process, value, user, knowledge, dataset, resource, service, cloud, storage, business, and health. The 20 multi-term topics were as follows: sense technology architecture (T10), decision system (T18), classification algorithm (T03), data analytics (T17), system performance (T09), data science (T06), distribution method (T20), service dataset (T19), network communication (T05), customer & business (T16), cloud computing (T02), health care (T14), smart city (T11), patient & disease (T04), privacy & security (T08), research design (T01), social media (T12), student & education (T13), energy consumption (T07), supply chain management (T15). The time series data indicated that the 40 single-term topics and multi-term topics were hot topics. This study provides suggestions for future research.

• Journal of Distribution Science
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• v.15 no.1
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• pp.123-130
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• 2017

Purpose - This research aims to examine the effect of e-business adoption on firm's growth and profitability in the distribution industry. The value added from the distribution industry acts as the cost of other industries. As the distribution industry develops, its stage becomes shorter and the distribution margin becomes smaller. Therefore, e-business is expected to have a different effect on the distribution industry than other industries. Research design, data and methodology - The previous research generally used e-business adoption as an independent variable and firm's performance as a dependent variable. This study elaborated the model using a dynamic panel model that includes the performance variable of the previous year as an independent variable. By employing system GMM (Generalized Method of Moments), the endogeneity problem in the dynamic panel model can be solved. For the analysis, I extracted the distribution companies as the raw data in the National Statistical Office's Business Activity Survey over the period 2006 to 2012. Results - The growth rate of firms adopting e-business was 0.299%p higher than that of the non-adopter. However, only ERP (Enterprise Resource Planning), KMS (Knowledge Management System) and SCM (Supply Chain Management) contributed positively to the growth rate. In the case of profitability, it was 0.04%p higher than the distribution companies that did not adopt e-business. ERP and LMS (Learning Management System) improve profitability, while SCM reduces profitability. Consequently, while ERP improves both growth and profitability, SCM improves growth but reduces profitability. In addition, KMS improves firm's growth only, and LMS does only profitability, showing that each e-business has a differentiated effect. Conclusions - Since the distribution industry has different characteristics from manufacturing and other service industries, the introduction of e-business may not guarantee the growth and profitability of distribution companies. Careful introduction considering the characteristics of the distribution industry is required. In particular, it is necessary to select an e-business meeting the characteristics and needs of a distribution company, and thereafter, it is required for the company's own efforts to internalize it within the system.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.12
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• pp.1980-1991
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• 2010

This study proposes the O P E N Triad framework as a future set of tools and perspectives for individual members and institutes to further their professional and academic potential as well as prospect and vitalize the future of the Korean Clothing and Textiles discipline through a global perspective. The millennial generation desires On-demand, Personal, Engaging, and Networked (O P E N) experiences effecting cultural change for creative and influential interaction in transactions, communication, and education. O P E N Individuals offers a WebSphere model as a holistic learning system that has a synergizing value of education across academic courses, industries, and cultures. Through a digitalized and virtualized class, it complements relevant technologies already familiar to the student population. By employing environmental scanning approaches, the most influential and viable future global issues related to the clothing and textiles discipline are identified and dialogued within O P E N Institutes. For future clothing and textiles institutes, this scanning allows them to be open to new ideas, to focus on inter-engagements, to collaborate among individuals, to associate as a part of web of people, organizations, and ideas, to personalize an institutes curricula, and to dialogue generative knowledge. O P E N Industries reveals three dominant future issues that cross academia and industry, sustainability, supply chain management, and social networking. In-depth interviews with U.S. industry experts identified interdependent gaps in global consumer experience practices and suggested the following gaps as future research areas: a standardized business model to the entrepreneurial model, strategic management to a sustainable competitive advantage, standardized to differentiated products, services and operations, market segmentation to global consumer clusters, business-driven marketplaces to consumer-engaged marketspaces, and excellent services to optimal experience. This O P E N Triad framework empowers millennial students, universities, and industries to anticipate and prepare for a radically changing world.

• Journal of the Economic Geographical Society of Korea
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• v.4 no.1
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• pp.61-76
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• 2001

The purposes of this research are to examine the theoretical background and industrial policy issues with regard to building a Innovation System for encouraging industrial competitiveness and fostering regional industry in Korea. Knowledge has become the driving force of economic growth and the primary source of competitiveness in the world market. So since 1990s, Innovation Systems have been put emphasis on as new industrial development strategy in a knowledge-based economy. It can be understood that Innovation System is composed of National Innovation System(NIS) and Regional Innovation System(RIS) and interrelated the concept of clusters and networks, which are contribute to industry development throughout boosting innovation. As for the Korean industrial policy, when the former centralized policy decision making process became decentralized through the implementation of local autonomy, the role of local or state government in relation to regional industrial promotion intensified. But with the impotance of for fostering strategic industry in the region. new industrial policy issues in Korea are needed as follows; $\circled1$ Building a market-oriented support system for industrial cluster through providing the resource of innovation. $\circled2$ Establishing agency for regional industrial development. $\circled3$ Making a evolutionary vision for broader region including 2 or 3 province, $\circled4$ Fostering strategic industry which is selected in term of specialization and potential of the region. The RIS model for industry development is outlined in this paper but policy initiatives for building a RIS have to be extracted from further case studies.

• Journal of Gastric Cancer
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• v.14 no.4
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• pp.259-265
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• 2014

Purpose: Survival analysis of gastric cancer patients requires knowledge about factors that affect survival time. This paper attempted to analyze the survival of patients with incomplete registered data by using imputation methods. Materials and Methods: Three missing data imputation methods, including regression, expectation maximization algorithm, and multiple imputation (MI) using Monte Carlo Markov Chain methods, were applied to the data of cancer patients referred to the cancer institute at Imam Khomeini Hospital in Tehran in 2003 to 2008. The data included demographic variables, survival times, and censored variable of 471 patients with gastric cancer. After using imputation methods to account for missing covariate data, the data were analyzed using a Cox regression model and the results were compared. Results: The mean patient survival time after diagnosis was $49.1{\pm}4.4$ months. In the complete case analysis, which used information from 100 of the 471 patients, very wide and uninformative confidence intervals were obtained for the chemotherapy and surgery hazard ratios (HRs). However, after imputation, the maximum confidence interval widths for the chemotherapy and surgery HRs were 8.470 and 0.806, respectively. The minimum width corresponded with MI. Furthermore, the minimum Bayesian and Akaike information criteria values correlated with MI (-821.236 and -827.866, respectively). Conclusions: Missing value imputation increased the estimate precision and accuracy. In addition, MI yielded better results when compared with the expectation maximization algorithm and regression simple imputation methods.