• Journal of Distribution Science
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• v.9 no.3
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• pp.83-94
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• 2011

Most domestic companies, with the exclusion of major firms, are reluctant to implement a supply chain management (SCM) network into their operations. Most small- and medium-sized enterprises are not even aware of SCM. Due to the inherent total-systems efficiency of SCM, it coordinates domestic manufacturers, subcontractors, distributors, and physical distributors and cuts down on cost of inventory control, as well as demand management. Furthermore, a lack of SCM causes a decrease in competitiveness for domestic companies. The reason lies in the fundamentality of SCM, which is the characteristic of information sharing, process innovation throughout SCM, and the vast range of problems the SCM management tool is able to address. This study suggests the contemplation and reformation of the current SCM situation by analyzing the SCM strategic plan, discourses and logical discussions on the topic, and a successful case for adapting SCM; hence, the study plans to productively "process" SCM. First, it is necessary to contemplate the theoretical background of SCM before discussing how to successfully process SCM. I will describe the concept and background of SCM in Chapter 2, with a definition of SCM, types of SCM promotional activities, fields of SCM, necessity of applying SCM, and the effects of SCM. All of the defects in currently processing SCM will be introduced in Chapter 3. Discussion items include the following: the Bullwhip Effect; the breakdown in supply chain and sales networks due to e-business; the issue that even though the key to a successful SCM is cooperation between the production and distribution company, during the process of SCM, the companies, many times, put their profits first, resulting in a possible defect in demands estimation. Furthermore, the problems of processing SCM in a domestic distribution-production company concern Information Technology; for example, the new system introduced to the company is not compatible with the pre-existing document architecture. Second, for effective management, distribution and production companies should cooperate and enhance their partnership in the aspect of the corporation; however, in reality, this seldom occurs. Third, in the aspect of the work process, introducing SCM could provoke corporations during the integration of the distribution-production process. Fourth, to increase the achievement of the SCM strategy process, they need to set up a cross-functional team; however, many times, business partners lack the cooperation and business-information sharing tools necessary to effect the transition to SCM. Chapter 4 will address an SCM strategic plan and a case study of LG Electronics. The purpose of the strategic plan, strategic plans for types of business, adopting SCM in a distribution company, and the global supply chain process of LG Electronics will be introduced. The conclusion of the study is located in Chapter 5, which addresses the issue of the fierce competition that companies currently face in the global market environment and their increased investment in SCM, in order to better cope with short product life cycle and high customer expectations. The SCM management system has evolved through the adaptation of improved information, communication, and transportation technologies; now, it demands the utilization of various strategic resources. The introduction of SCM provides benefits to the management of a network of interconnected businesses by securing customer loyalty with cost and time savings, derived through the consolidation of many distribution systems; additionally, SCM helps enterprises form a wide range of marketing strategies. Thus, we could conclude that not only the distributors but all types of businesses should adopt the systems approach to supply chain strategies. SCM deals with the basic stream of distribution and increases the value of a company by replacing physical distribution with information. By the company obtaining and sharing ready information, it is able to create customer satisfaction at the end point of delivery to the consumer.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.507-517
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• 2018

The probability of T/S cargo volume to decrease is the most notable problem associated with inappropriate mix of terminal operators in Busan port. Other problems include, the deterioration of the national carriers' competitiveness from non-operation of own terminal, excessively high proportion of financial operators in the engagement of operation which may result in their passiveness in timely investment, additional cost burden to carriers' in the handling inter-terminal T/S cargo transportation and inefficiency in terminal operation by the multiplicity of operators proved to be same recognized as so through the analysis. Therefore, in order to provide solutions for the problems and to strengthen Busan port's competitiveness, this research suggests the restructuring of operators mix as follows. To achieve sustainable growth of T/S cargo, global carriers' participation in terminal operation should be of utmost priority. To enhance the operational efficiency, the operators should be integrated. Similarly, the integration of operators will play a key role in verifying that national carriers' own terminal operation is an important factor in raising its competence. Finally, BPA's active engagement in the entire operation of port is also critical in public-oriented operation of the port. Whereas in the interactive analysis by taking the merits of Busan port into consideraion, global carrier's participation in operation, integration of operators and BPA's engagement in operation proved to contribute to the increase of T/S cargo and strengthening of operational efficiencies of Busan port.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.1-17
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• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.

• Korean Chemical Engineering Research
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• v.47 no.5
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• pp.630-638
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• 2009

A computational fluid dynamics(CFD) model is developed and validated with on-site experiments for a urea-based SNCR(selective non-catalytic reduction) process to reduce the nitrogen oxides($NO_x$) in a municipal incinerator. The three-dimensional turbulent reacting flow CFD model having a seven global reaction mechanism under the condition of low CO concentration and 12% excess air and droplet evaporation is used for fluid dynamics simulation of the SNCR process installed in the incinerator. In this SNCR process, urea solution and atomizing air were injected into the secondary combustor, using one front nozzle and two side nozzles. The exit temperature($980^{\circ}C$) of simulation has the same value as in situ experiment one. The $NO_x$ reduction efficiencies of 57% and 59% are obtained from the experiment and CFD simulation, respectively at NSR=1.8(normalized stoichiometric ratio) for the equal flow rate ratio from the three nozzles. It is observed in the CFD simulations with varying the flowrate ratio of the three nozzles that the injection of a two times larger front nozzle flowrate than the side nozzle flowrate produces 8% higher $NO_x$ reduction efficiency than the injection of the equal ratio flowrate in each nozzle.

• Information Systems Review
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• v.12 no.1
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• pp.189-207
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• 2010

We applied IT ecosystem analysis to Smart Grid system in this paper and thereby compared various arguments about Smart Grid technologies against the reality of the power generation and distribution in South Korea with a special attention to the power distribution side. Our work attempts to propose policy implications in the government-level based on a firm-level analysis using the framework of the competitive strategy and advantage. The Smart Grid initiative is expected to enhance the efficiency in the power generation and distribution. In addition, the Smart Grid initiative aims at capturing the opportunities in the electric power business such as parts, components, supplies, and system products in the global arena. Prerequisites of smart distribution system include building infrastructure based on smart distribution parts, information systems, communication technologies, and developing various application programs and interfaces that would interact with the consumers. Consumers are expected to play an integral role by changing their consumption patterns in response to dynamic pricing and quality choices enabled by the smart distribution technologies. In order to induce the consumers to participate actively in the program, firms and policy makers should consider providing consumers economic incentives and proper education for better understanding of new technologies. Our work helps policy makers and firm better understand the nature of technology and stakeholders for the successful implementation of smart distribution technologies.

• Korean Journal of Construction Engineering and Management
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• v.15 no.5
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• pp.61-70
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• 2014

Various procurement systems for Architecture-Engineering service for public construction project are currently established by construction-related law. However, comprehensive framework and criteria for the selection of Architecture-Engineering firm are in absence. Even though various selection methods for Architecture-Engineering service are currently established by law, cost-based selection method is mainly used in selecting Architecture-Engineering firm for the service. This paper examined current use of procurement system for Architecture-Engineering service and drew problems in practice. Through analysis of problems and bench-marking of those systems in advanced countries and international organizations, several strategies to improve performance of Architecture-Engineering service and to maximize the efficiency were suggested. The suggestions include framework and guideline to select a procurement method for the service which is being considered for the project and way of improving current procurement system. These suggestions will be a foundation for utilizing appropriate procurement system for the specific project and can make domestic Architecture-Engineering firm more competitive in the global market by breaking form the cost-based selection method in the selection of Architecture-Engineering firms.

• Korean Journal of Construction Engineering and Management
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• v.15 no.1
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• pp.39-50
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• 2014

After the global financial crisis, domestic construction industry has gone through a rapid recession. This resulted in gradual market shift towards architectural remodeling. Architectural remodeling not only improves residential environment but it has many advantages such as increase of each unit's exclusive area, free space within the horizontal or extension of an annex building, and increase number of household through splitting the household of bigger pyeong, etc. However, in case of the Korean market for apartment remodeling, due to various regulations and problem with business promotion procedures, majority of business is slow despite the figure that remodeling volume is not that small. Also, feasibility study which decides to push ahead public house remodeling business will have a flaw using net present value's law; it has a flaw of not considering properties of each phase of remodeling business and future's uncertainty. Hence, this research will improve the problem of traditional value assessment method of net present value's law. It will also consider one of the real options such as binomial model in order to supplement NPV which is used in current feasibility study. This research was based on real successful cases of public house remodeling and it was possible for feasibility study which was more realistic and valid. This research provided foundation for development of Korean public house remodeling market. There is high anticipation of increasing the validity by improving the problems of current feasibility study and economic efficiency assessment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.10-18
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• 2010

This paper proposes an image stabilization algorithm for close watching UAV(Unmanned Aerial Vehicle) using motion separation and stabilization mode. The motion of UAV is composed of its actual navigating motion and unwanted vibrating motion so that image sequences obtained from UAV are shaken randomly. In order to stabilize these images we separate the vibrating motion component from UAV motion and remove the effect caused by it from image sequences. In the proposed algorithm the motion and global intensity change of two consecutive images are modeled with 6 motion parameters and 2 intensity change parameters respectively. These modeled parameters are estimated by non-linear least square method based on Gauss-Newton algorithm. The vibrating motion component is separated from the estimated motion using IIR filtering and the geometric deformation caused by it is removed from image sequences. In order to apply the proposed method to real aerial image sequences with many abrupt changes of camera view, we proposed a stabilizing method using two different modes named as stabilizing and non-stabilizing mode. Experimental results show that the accuracy of motion estimation is 99% and the efficiency of removing the vibrating motion component is 90%. We apply the proposed method to real aerial image sequences and verified its stabilizing performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.143-149
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• 2018

Recently, due to the large-scale damage of natural disasters caused by global climate change, a monitoring system applying remote sensing technology is being constructed in disaster areas. Among remote sensing platforms, the drone has been actively used in the private sector due to recent technological developments, and has been applied in the disaster areas owing to advantages such as timeliness and economical efficiency. This paper deals with the development of a preprocessing system that can map the drone image data in a near-real time manner as a basis for constructing the disaster monitoring system using the drones. For the research purpose, our system is based on the SURF algorithm which is one of the computer vision technologies. This system aims to performs the desired correction through the feature point matching technique between reference images and shot images. The study area is selected as the lower part of the Gahwa River and the Daecheong dam basin. The former area has many characteristic points for matching whereas the latter area has a relatively low number of difference, so it is possible to effectively test whether the system can be applied in various environments. The results show that the accuracy of the geometric correction is 0.6m and 1.7m respectively, in both areas, and the processing time is about 30 seconds per 1 scene. This indicates that the applicability of this study may be high in disaster areas requiring timeliness. However, in case of no reference image or low-level accuracy, the results entail the limit of the decreased calibration.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.2
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• pp.43-57
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• 2015

All countries of the world are promoting the creative economy policy to overcome the global economic crisis. Korean government enforces the creative economy policy for the economic growth and job creation. Especially, Technology based startup is actively supported to realize the creative economy. To maximize the efficiency of supporting start-ups, we have to analyze a perception gap of the startup success factors between technology based entrepreneur and startup facilitator. Through the analysis, the supporting policy of startup utilized efficiently the limited resources is necessary. So, the purpose of this study is analysis the difference of the startup success factors which technology based entrepreneur and startup facilitator recognize. To analysis, the start-up success factors derived from previous studies were categorized them as 1) characteristics of the founder, 2) start-up strategy, 3) characteristics of the organization, and 4) start-up environment. Also, The CEO of technology based start-ups and the researcher in national research institute to support SMEs were surveyed. Then, Survey was analyzed by utilizing the ANP methodology to priority derivation of start-up success factors. Result of analysis, Technology Based Entrepreneur was determined that 'composition and expertise of organization' is most important factor for success of startup. On the other hand, Startup facilitator was determined that 'financing strategy of organization' is most important factor for success of startup. Both groups are recognized as important strategy. And start-up environment is recognized as a relatively unimportant. On the other hand, the importance which two groups evaluate about characteristics of entrepreneur and characteristics of organization was different. This study has a academic significance to analyze the priority of the startup success factors between technology based entrepreneur and startup facilitator. Also, It can be utilized practical guideline when policy making about technology based startup.