• Asian-Australasian Journal of Animal Sciences
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• v.26 no.7
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• pp.995-1002
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• 2013

The effect of conjugated linoleic acid (CLA) feeding on growth performance and fatty acid profiles in thigh meat of broiler chicken was investigated using meta-analysis with a total of 9 studies. Overall effects were calculated by standardized mean differences between treatment (CLA fed) and control using Hedges's adjusted g from fixed and random effect models. Meta-regression was conducted to evaluate the effect of CLA levels. Subgroups in the same study were designated according to used levels of CLA, CP levels or substituted oils in diets. The effects on final body weight, weight gain, feed intake and feed conversion ratio were investigated as growth parameters. Total saturated and unsaturated fatty acid concentrations and C16:0, C18:0, C18:2 and C18:3 concentrations in thigh meat of broiler chicken were used as fatty acid profile parameters. The overall effect of CLA feeding on final weight was negative and it was only significant in fixed effect model (p<0.01). Significantly lower weight gain, feed intake and higher feed conversion ratio compared to control were found (p<0.05). CLA feeding on the overall increased total saturated fatty acid concentration in broilers compared to the control diet (p<0.01). Total unsaturated fatty acid concentration was significantly decreased by CLA feeding (p<0.01). As for individual fatty acid profiles, C16:0, C18:0 and C18:3 were increased and C18:2 was significantly decreased by CLA feeding (p<0.01). In conclusion, CLA was proved not to be beneficial for improving growth performance, whereas it might be supposed that CLA is effective modulating n-6/n-3 fatty acids ratio in thigh meat. However, the economical compensation of the loss from suppressed growth performance and increased saturated fatty acids with the benefit from enhanced n-6/n-3 ratio should be investigated in further studies in order to propose an appropriate use of dietary CLA in the broiler industry.

• Korean Security Journal
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• no.38
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• pp.109-136
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• 2014

Korea domestic casino industry has been experienced an explosive growth marking the highest quantity and quality with rapid growth of domestic economy since the 1960s. However there are really lack of study about presenting guideline for establishing risk management planning reflected characteristics of casino industry. Therefore, we analyzed previous studies about concept of the risk and criteria and drew dimension of safety supervision reflecting characteristics of casino industry. we, also, identified detailed safety management factors as well as classified three dimensions of environment, human and facility on the dimension of safety supervision. This study was designed to examine effect relationship between risk management factors and performance of security management organization focused on The mediation effect of atmosphere of organization We used two different tools for data analysis: SPSS 18.0 for the descriptive statistics and PLS 3.0 to validate the integrity of the research model and proposed hypotheses that is main effects from risk management factors to security management organization and mediation effects of atmosphere of organization. The data analysis confirmed the importance of risk management factors to enhanced performance of security management organization. The mediation effect of atmosphere of organization, also, supported relationship between risk management factors and performance of security management organization. It provided theoretical and practical implication for building risk management strategy well suited casino company and conducting security management.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.1077-1086
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• 2023

The searchable encryption model allows to selectively search for encrypted data stored on a remote server. In a real-world scenarios, the model must be able to support multiple search keywords, multiple data owners/users. In this paper, these models are referred to as Multi Ranked Searchable Encryption model. However, at the time this paper was written, the proposed models use fully-trusted trapdoor centers, some of which assume that the connection between the user and the trapdoor center is secure, which is unlikely that such assumptions will be kept in real life. In order to improve the practicality and security of these searchable encryption models, this paper proposes a new Multi Ranked Searchable Encryption model which uses random keywords to protect search words requested by the data downloader from an honest-but-curious trapdoor center with an external attacker without the assumptions. The attacker cannot distinguish whether two different search requests contain the same search keywords. In addition, experiments demonstrate that the proposed model achieves reasonable performance, even considering the overhead caused by adding this protection process.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.33-56
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• 2016

Many researchers have focused on developing bankruptcy prediction models using modeling techniques, such as statistical methods including multiple discriminant analysis (MDA) and logit analysis or artificial intelligence techniques containing artificial neural networks (ANN), decision trees, and support vector machines (SVM), to secure enhanced performance. Most of the bankruptcy prediction models in academic studies have used financial ratios as main input variables. The bankruptcy of firms is associated with firm's financial states and the external economic situation. However, the inclusion of qualitative information, such as the economic atmosphere, has not been actively discussed despite the fact that exploiting only financial ratios has some drawbacks. Accounting information, such as financial ratios, is based on past data, and it is usually determined one year before bankruptcy. Thus, a time lag exists between the point of closing financial statements and the point of credit evaluation. In addition, financial ratios do not contain environmental factors, such as external economic situations. Therefore, using only financial ratios may be insufficient in constructing a bankruptcy prediction model, because they essentially reflect past corporate internal accounting information while neglecting recent information. Thus, qualitative information must be added to the conventional bankruptcy prediction model to supplement accounting information. Due to the lack of an analytic mechanism for obtaining and processing qualitative information from various information sources, previous studies have only used qualitative information. However, recently, big data analytics, such as text mining techniques, have been drawing much attention in academia and industry, with an increasing amount of unstructured text data available on the web. A few previous studies have sought to adopt big data analytics in business prediction modeling. Nevertheless, the use of qualitative information on the web for business prediction modeling is still deemed to be in the primary stage, restricted to limited applications, such as stock prediction and movie revenue prediction applications. Thus, it is necessary to apply big data analytics techniques, such as text mining, to various business prediction problems, including credit risk evaluation. Analytic methods are required for processing qualitative information represented in unstructured text form due to the complexity of managing and processing unstructured text data. This study proposes a bankruptcy prediction model for Korean small- and medium-sized construction firms using both quantitative information, such as financial ratios, and qualitative information acquired from economic news articles. The performance of the proposed method depends on how well information types are transformed from qualitative into quantitative information that is suitable for incorporating into the bankruptcy prediction model. We employ big data analytics techniques, especially text mining, as a mechanism for processing qualitative information. The sentiment index is provided at the industry level by extracting from a large amount of text data to quantify the external economic atmosphere represented in the media. The proposed method involves keyword-based sentiment analysis using a domain-specific sentiment lexicon to extract sentiment from economic news articles. The generated sentiment lexicon is designed to represent sentiment for the construction business by considering the relationship between the occurring term and the actual situation with respect to the economic condition of the industry rather than the inherent semantics of the term. The experimental results proved that incorporating qualitative information based on big data analytics into the traditional bankruptcy prediction model based on accounting information is effective for enhancing the predictive performance. The sentiment variable extracted from economic news articles had an impact on corporate bankruptcy. In particular, a negative sentiment variable improved the accuracy of corporate bankruptcy prediction because the corporate bankruptcy of construction firms is sensitive to poor economic conditions. The bankruptcy prediction model using qualitative information based on big data analytics contributes to the field, in that it reflects not only relatively recent information but also environmental factors, such as external economic conditions.

• Journal of the Korea Concrete Institute
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• v.22 no.3
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• pp.409-417
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• 2010

This paper discusses a series of experiments including material improvement in order to ensure quality of grouting for the post-tensioned structure. In prestressed concrete, grouting refers to the construction procedure of filling empty space of duct enclosing with strands using cementitious material, To date, adequate quality control of the grouting has not been established in Korea because the relationship between the grouting and durability of post-tensioned structure is not well-recognized. The Korean standard does not consider the important material characteristic, wick effect, which is caused by strands in the ducts and current standard testing method unlikely quantify reasonable material segregation. As a result, the grout material, which meets the current material standards, may exhibit excessive bleeding water or shrinkage during construction. In this study, international codes and standards related to grouting were surveyed. The ratio of constituents and novel admixtures were suggested to meet equivalently with these standards. Performance of this enhanced grout was compared to common domestic grout using the international standard testing method. A series of mock-up specimens considering geometry of PC beam was constructed and grout flow pattern was observed as the grout was injected. It was observed that the grouting performance was highly influenced by material properties and filling characteristic can be varied depending on geometry of ducts.

• 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 Korean Society of Environmental Engineers
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• v.27 no.5
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• pp.468-475
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• 2005

Biofilters packed with various materials have emerged as a sustainable technology for the treatment of volatile organic compounds (VOCs); however, problems including low performance and clogging are commonly encountered. Recently, a bioactive foam reactor (BFR) using surfactants has been suggested to ensure efficient and stable VOCs removal performance. This study was mainly conducted to investigate the feasibility of BFRs using toluene as a model compound. Prior to bioreactor studies, a series of bottle tests were used to select a suitable surfactant for the BFR application. Experimental results of the batch bottle tests indicated that TritonX-100 was the most appropriate one among the surfactants tested, since it showed a minimal effect on the toluene biodegradation rate while the other surfactants lowered the toluene biodegradation rate significantly. Using the selected surfactant, the BFR performance was determined by changing operating parameters including gas residence time and toluene loading. As the gas residence time increased from 0.5 minutes to 2 minutes, the toluene removal efficiency increased from approximately 50% to 80%. In addition, an increase of the toluene loading from $38\;g/m^3/hr$ to $454\;g/m^3/hr$ resulted in a decrease of toluene removal efficiency from approximately 70% to 20%. The BFR had a maximum elimination capacity of $108\;g/m^3/hr$ for toluene, which was much higher than those generally reported in the literature. The high toluene-elimination performance indicates that the BFR be a potential alternative to the conventional, packed-type biofilters. However, the limitation of toluene solubilization and foam stability at either high or low gas flow rate are still problems to be challenged.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.202-211
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• 2015

Companies build the factory automation system to improve management effectiveness and productivity as prime strategies for sustainable growth. But most companies undergo various trials and errors while carrying out the project without elaborate preparation stage for factory automation. In this study, we tried to verify what factors are critical to effectively building distribution automation system, which is a branch of factory automation system. A consulting model for setting up a Material Handling Automation System by utilizing the Stage-Gate Process, which is product development process was studied. 29 material handling automation projects carried out between the year 1990 to 2013 at K-Company were selected. Interviews with the project managers, operators and maintenance personnels, various records and current status of the projects were used as data for structural equations based on the Milan consulting model and existing researches of factory automation, CIM for material handling automation. Creating effective basis of production, material handling system and energy saving system with expert review, when preparing a material handling automation project, help promote the project planning thus contributing to the performance of the resulting system, which appears though rather weakly in our data. Also the effect of material handling automation can be enhanced through sufficient and effective links to the relevant environments such as production logistics management and automated warehouses. More detailed planning characteristics of project promotion or some time-series data of effective Material Handling Automation System could enhace furthur studies. We propose a consulting model for setting up an efficient material handling automation system.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.6
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• pp.1-10
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• 2009

In a network-based approach such as Proxy Mobile IPv6 (PMIPv6), the serving network controls the mobility management on behalf of a Mobile Node (MN), thereby eliminating a MN from any mobility-related signaling. Although PMIPv6 is being standardized by the IETF NetLMM WG, PMIPv6 still suffers from a lengthy handover latency and the on-the-fly packet loss during a handover. Therefore, this paper presents an enhanced fast handover scheme for PMIPv6. The proposed handover scheme uses the Neighbor Discovery message of IPv6 to reduce the handover latency and packet buffering at the Mobile Access Gateway (MAG) to avoid the on-the-fly packet loss during a handover. In addition, it uses an additional packet buffering at the Local Mobility Anchor (LMA) to solve the packet ordering problem. We evaluate the performance of the proposed handover scheme using both analytical model and simulation. The numerical analysis shows that the proposed scheme has a relatively shorter handover latency. Simulation results demonstrate that the proposed scheme could avoid the on-the-fly packet loss and ensure the packet sequence.

• Journal of Distribution Science
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• v.13 no.11
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• pp.123-130
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• 2015

Purpose - Due to highly elevated levels of competition, many companies today have to face the problem of decreasing profits even when their actual sales volume is increasing. This is a common phenomenon that is seen occurring among companies that focus heavily on quantitative growth rather than qualitative growth. These two aspects of growth should be well balanced for a company to create a sustainable business model. For supply chain management (SCM) planners, the optimized, quantified flow of resources used to be of major interest for decades. However, this trend is rapidly changing so that managers can put the appropriate balance between sales volume and sales quality, which can be evaluated from the profit margin. Profit optimization is a methodology for companies to use to achieve solutions focused more on profitability than sales volume. In this study, we attempt to provide executional insight for companies considering implementation of the profit optimization system to enhance their business profitability. Research design, data, and methodology - In this study, we present a comprehensive explanation of the subject of profit optimization, including the fundamental concepts, the most common profit optimization logic algorithm -linear programming -the business functional scope of the profit optimization system, major key success factors for implementing the profit optimization system at a business organization, and weekly level detailed business processes to actively manage effective system performance in achieving the goals of the system. Additionally, for the purpose of providing more realistic and practical information, we carefully investigate a profit optimization system implementation case study project fulfilled for company S. The project duration was about eight months, with four full-time system development consultants deployed for the period. To guarantee the project's success, the organization adopted a proven system implementation methodology, supply chain management (SCM) six-sigma. SCM six-sigma was originally developed by a group of talented consultants within Samsung SDS through focused efforts and investment in synthesizing SCM and six-sigma to improve and innovate their SCM operations across the entire Samsung Organization. Results - Profit optimization can enable a company to create sales and production plans focused on more profitable products and customers, resulting in sustainable growth. In this study, we explain the concept of profit optimization and prerequisites for successful implementation of the system. Furthermore, the efficient way of system security administration, one of the hottest topics today, is also addressed. Conclusion - This case study can benefit numerous companies that are eagerly searching for ways to break-through current profitability levels. We cannot guarantee that the decision to deploy the profit optimization system will bring success, but we can guarantee that with the help of our study, companies trying to implement profit optimization systems can minimize various possible risks across various system implementation phases. The actual system implementation case of the profit optimization project at company S introduced here can provide valuable lessons for both business organizations and research communities.