• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.187-194
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• 2019

Traditional demand forecasting methods are difficult to meet the needs of companies due to rapid changes in the market and the diversification of individual consumer needs. In a diversified production environment, the right demand forecast is an important factor for smooth yield management. Many of the existing predictive models commonly used in industry today are limited in function by little. The proposed model is designed to overcome these limitations, taking into account the part where each model performs better individually. In this paper, variables are extracted through Gray Relational analysis suitable for dynamic process analysis, and statistically predicted data is generated that includes characteristics of historical demand data produced through ARIMA forecasts. In combination with the LSTM model, demand forecasts can then be calculated by reflecting the many factors that affect demand forecast through an architecture that is structured to avoid the long-term dependency problems that the neural network model has.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.10
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• pp.746-758
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• 2006

Many objects existing on wide area environments have the replication characteristics according to how to categorize using their own names or properties. From the clients' requests, the existing naming and trading services have not supported with the binding service for replicated solver object with the same service type. For this reason, we present an integrated model that can support the selection of replicated object and dynamic binding services on wide-area computing environments. This model suggests provides not only location management of replicated objects but also active binding service which enables to select a least-loaded object on the system to keep the balance of load between systems. In this purpose, constructing both the service plan and model for support solver object's binding with replication property on wide area computing environments has been researched. In this paper, we showed the test environment and analyzed the performance evaluation of client/server binding procedures via integrated binding service in federation model and verified our model under the condition to see whether load balance can be applied to our model. For the performance evaluation of suggested wide area integrated binding service federation model, evaluated the integrated binding service of each domain and analyzed the performance evaluation of process for non-replication object's under federation model environment. Also, we analyzed the performance evaluation of the federation model between domains for wide area environment. From the execution results, we showed the federation model provides lowers search-cost on the physical tree structure of network.

• Korean Journal of Construction Engineering and Management
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• v.24 no.5
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• pp.3-11
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• 2023

Building information modeling (BIM) can help to visualize and manage the building-related information at the object-based level, and it is possible to help link the tasks in the network of Hanok construction. While many studies have significant interest in using BIM for modern construction, there is only few studies to observe the use of BIM for traditional construction, commonly called Hanok construction in South Korea. Hence, the main goal of this study is to develop a system dynamic model for investigating how the BIM can be widely used for Hanok construction. To this end, this study identified the factors influencing the BIM uses for the Hanok construction, developed a causal loop diagram (CLD) to investigate the interrelationships among the factors, and provided a final model based on the mathematical definitions. Based on the scenario analysis, it is demonstrated that the support to building Hanok and education cost for BIM positively influence activating and using the BIM for the Hanok construction. Based on the dynamics of the factors identified in this study, it is important to consider expanding support for Hanok construction and education cost for BIM to successfully integrate and utilize BIM in the construction industry.

• Proceedings of the Korean Society for Applied Microbiology Conference
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• 2004.06a
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• pp.60-61
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• 2004

Metabolic engineering is now a well established discipline, used extensively to determine and execute rational strategies of strain development to improve the performance of micro-organisms employed in industrial fermentations. The basic principle of this approach is that performance of the microbial catalyst should be adequately characterised metabolically so as to clearlyidentify the metabolic network constraints, thereby identifying the most probable targets for genetic engineering and the extent to which improvements can be realistically achieved. In order to harness correctly this potential, it is clear that the physiological analysis of each strain studied needs to be undertaken under conditions as close as possible to the physico-chemical environment in which the strain evolves within the full-scale process. Furthermore, this analysis needs to be undertaken throughoutthe entire fermentation so as to take into account the changing environment in an essentially dynamic situation in which metabolic stress is accentuated by the microbial activity itself, leading to increasingly important stress response at a metabolic level. All too often these industrial fermentation constraints are overlooked, leading to identification of targets whose validity within the industrial context is at best limited. Thus the conceptual error is linked to experimental design rather than inadequate methodology. New tools are becoming available which open up new possibilities in metabolic engineering and the characterisation of complex metabolic networks. Traditionally metabolic analysis was targeted towards pre-identified genes and their corresponding enzymatic activities within pre-selected metabolic pathways. Those pathways not included at the onset were intrinsically removed from the network giving a fundamentally localised vision of pathway functionality. New tools from genome research extend this reductive approach so as to include the global characteristics of a given biological model which can now be seen as an integrated functional unit rather than a specific sub-group of biochemical reactions, thereby facilitating the resolution of complexnetworks whose exact composition cannot be estimated at the onset. This global overview of whole cell physiology enables new targets to be identified which would classically not have been suspected previously. Of course, as with all powerful analytical tools, post-genomic technology must be used carefully so as to avoid expensive errors. This is not always the case and the data obtained need to be examined carefully to avoid embarking on the study of artefacts due to poor understanding of cell biology. These basic developments and the underlying concepts will be illustrated with examples from the author's laboratory concerning the industrial production of commodity chemicals using a number of industrially important bacteria. The different levels of possibleinvestigation and the extent to which the data can be extrapolated will be highlighted together with the extent to which realistic yield targets can be attained. Genetic engineering strategies and the performance of the resulting strains will be examined within the context of the prevailing experimental conditions encountered in the industrial fermentor. Examples used will include the production of amino acids, vitamins and polysaccharides. In each case metabolic constraints can be identified and the extent to which performance can be enhanced predicted

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.195-211
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• 2014

Cloud computing services provide IT resources as services on demand. This is considered a key concept, which will lead a shift from an ownership-based paradigm to a new pay-for-use paradigm, which can reduce the fixed cost for IT resources, and improve flexibility and scalability. As IT services, cloud services have evolved from early similar computing concepts such as network computing, utility computing, server-based computing, and grid computing. So research into cloud computing is highly related to and combined with various relevant computing research areas. To seek promising research issues and topics in cloud computing, it is necessary to understand the research trends in cloud computing more comprehensively. In this study, we collect bibliographic information and citation information for cloud computing related research papers published in major international journals from 1994 to 2012, and analyzes macroscopic trends and network changes to citation relationships among papers and the co-occurrence relationships of key words by utilizing social network analysis measures. Through the analysis, we can identify the relationships and connections among research topics in cloud computing related areas, and highlight new potential research topics. In addition, we visualize dynamic changes of research topics relating to cloud computing using a proposed cloud computing "research trend map." A research trend map visualizes positions of research topics in two-dimensional space. Frequencies of key words (X-axis) and the rates of increase in the degree centrality of key words (Y-axis) are used as the two dimensions of the research trend map. Based on the values of the two dimensions, the two dimensional space of a research map is divided into four areas: maturation, growth, promising, and decline. An area with high keyword frequency, but low rates of increase of degree centrality is defined as a mature technology area; the area where both keyword frequency and the increase rate of degree centrality are high is defined as a growth technology area; the area where the keyword frequency is low, but the rate of increase in the degree centrality is high is defined as a promising technology area; and the area where both keyword frequency and the rate of degree centrality are low is defined as a declining technology area. Based on this method, cloud computing research trend maps make it possible to easily grasp the main research trends in cloud computing, and to explain the evolution of research topics. According to the results of an analysis of citation relationships, research papers on security, distributed processing, and optical networking for cloud computing are on the top based on the page-rank measure. From the analysis of key words in research papers, cloud computing and grid computing showed high centrality in 2009, and key words dealing with main elemental technologies such as data outsourcing, error detection methods, and infrastructure construction showed high centrality in 2010~2011. In 2012, security, virtualization, and resource management showed high centrality. Moreover, it was found that the interest in the technical issues of cloud computing increases gradually. From annual cloud computing research trend maps, it was verified that security is located in the promising area, virtualization has moved from the promising area to the growth area, and grid computing and distributed system has moved to the declining area. The study results indicate that distributed systems and grid computing received a lot of attention as similar computing paradigms in the early stage of cloud computing research. The early stage of cloud computing was a period focused on understanding and investigating cloud computing as an emergent technology, linking to relevant established computing concepts. After the early stage, security and virtualization technologies became main issues in cloud computing, which is reflected in the movement of security and virtualization technologies from the promising area to the growth area in the cloud computing research trend maps. Moreover, this study revealed that current research in cloud computing has rapidly transferred from a focus on technical issues to for a focus on application issues, such as SLAs (Service Level Agreements).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10B
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• pp.946-961
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• 2008

This study aims to provide guidelines on future policy for restructuring the scheme of aid programs associated with If small and medium-sized enterprises (i.e. SME) in Korea. For this purpose, we investigate an empirical dataset of recent aid programs deployed by Ministry of Information and Communication (i.e. MIC) for the last four years First, it is examined that the programs are practiced in accordance with their own policy objective by comparing matching samples between two groups such as program beneficiary and non-beneficiary companies. Second, positioning transition of programs within a same category is visualized in terms of two business portfolio analysis matrices. Third, an affiliation network matrix of (he programs is newly developed and then we attempt to analyze the programs relationship by the application of multidimensional scaling method to the affiliation network matrix. The empirical dataset is composed of two different kinds of corporate datasets. One is a corporate dataset of 8,994 beneficiary companies that are aided by MIC during the year of '03-'06. The other is also a corporate dataset of 18,354 non-beneficiary companies that have no records of the program supports during the years at all. Particularly, the matching samples of non-beneficiary companies are prepared in order to have comparable corporate age years (i.e. CAY) against beneficiary companies' CAY. Results show that; 1) up-to-date, the programs are properly assigned to IT SME conforming to their own policy objective; 2) however, as the year goes on, the following two distinct positioning transitions are revealed such as (1) both CAY and corporate sales (i.e. SAL) are increased simultaneously, (2) ratio of intangible assets (i.e. RIA) is decreased and ratio of operating gain to revenue (i.e. ROR) is increased. Hence, the role of the programs gets weakened with regard to providing seed money to technology innovation-typed IT SME so that a managerial adjustment of the programs is required consequently; 3) even though the model adequacy is not satisfactory through the analysis of multidimensional scaling method, the relationship of indirect-typed programs can relatively be stronger than that of direct-typed programs.

• Journal of Korean Society of Water and Wastewater
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• v.23 no.6
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• pp.743-752
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• 2009

One of the major problems associated with operation of domestic sewer lines involves hydraulic problems such as insufficient conveyance capacity, exceeding maximum velocity, and deficiency of minimum velocity. It has also been pointed out that influent concentration lower than design concentration of pollutants, which is mainly caused by unidentified inflow and infiltration, degrades the operational efficiency of many sewage treatment plants (STPs). A computer-added analysis method supporting a coupled simulation of sewage quality and quantity is essentially required to evaluate the status of existing STPs and to improve their efficiency by a proper sewer rehabilitation work. In this study, dynamic water quality simulations were conducted using MOUSE TRAP to investigate the principal parameters that governs the changes of BOD, ${NH_4}^+$, and ${PO_4}^{3-}$3- concentrations within the sewer networks based on data acquired through on-site and laboratory measurements. The BOD, ${NH_4}^+$ and ${PO_4}^{3-}$3- concentrations estimated by MOUSE TRAP was lower than theoretical pollution loads because of sedimentation and decomposition in the sewer. The results revealed that sedimentation is a most important factor than other biological reactions in decreasing pollutant load in the sewers of C-city. The sensitivity analysis of parameters pertaining to water quality changes indicated that the effect of the BOD decay rate, the initial DO concentration, the half-saturation coefficient of dissolved BOD, and the initial sediment depth is marginal. However, the influence of settling rate and temperature is relatively high because sedimentation and precipitation, rather than biological degradation, are dominant processes that affect water quality in the study sewer systems.

• Journal of Digital Convergence
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• v.10 no.6
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• pp.297-302
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• 2012

In this paper, we present a object detection and tracking method based on image context analysis. It is robust from the image variations such as complicated background, dynamic movement of the object. Image context analysis is carried out using the hybrid network of k-means and RBF. The proposed object detection employs context-driven adaptive Bayesian framework to relive the effect due to uneven object images. The proposed method used feature vector generator using 2D Haar wavelet transform and the Bayesian discriminant method in order to enhance the speed of learning. The system took less time to learn, and learning in a wide variety of data showed consistent results. After we developed the proposed method was applied to real-world environment. As a result, in the case of the object to detect pass outside expected area or other changes in the uncertain reaction showed that stable. The experimental results show that the proposed approach can achieve superior performance using various data sets to previously methods.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.10
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• pp.138-149
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• 2003

As the Internet is quickly evolving from best-effort networks to business quality networks, billing based on the precise traffic measurement becomes an important issue for Internet Service Providers (ISPs). Billing settlement is necessary not only between ISP and customers but also between ISPs. Currently, most ISPs use a flat rate charging policy. Besides the degree of difficulty in deriving appropriate charging policies agreeable by a concerned party, there are substantial technical challenges to come up with a good usage-based accounting system. Usage-based accounting depending on IP packet header information only is not sufficient anymore due to highly dynamic nature of the development and the use of the Internet applications such as peer-to-peer and network games. They are using port numbers dynamically and even several applications can use the same port number. Thus, more precise means of classifying them and accounting their traffic usages are required. In this paper, we propose a high performance, adaptable, configurable, and scalable content-aware application traffic measurement and analysis system which can achieve very accurate usage-based accounting.

• Journal of Korea Multimedia Society
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• v.14 no.1
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• pp.24-32
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• 2011

In ubiquitous environment, the analysis for student's learning behaviour is essential to provide students with personalized education. SCORM(Sharable Contents Object Reference Model), IMS LD (Instructional Management System Learning Design) standards provide the support function of learning design such as checking the progress. However, in case of applying these standards contain many problem to add or modify the contents. In this paper, We implement the system that manages the learner behaviour by hooking the event of web browser. Through all of this, HTML-based content can be recycled without any additional works and the problems by applying the standard can be improved because the store and analysis of the learning result is possible. It also supports the ubiquitous learning environment because of keeping track of the learning result in case of network disconnected.