• Journal of Environmental Policy
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• v.3 no.1
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• pp.55-69
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• 2004

Bioenergy can be obtained from various forms of biomass such as agricultural, food processing, and municipal wastes. Recently, its importance is recognized more seriously because of its positive impacts on economic and stable energy supply and environmental sustainability. Despite its advantages, bioenergy has not been used as much as it was expected, nor has it been developed to the level of attractive commercialization in energy market. The main reasons for the sluggish progress have been analyzed by comparing the bioenergy policies in Korea and U.S.A. Both Korea and U.S. governments have recognized the importance of bioenergy and put in various efforts to promote the use of bioenergy. Both governments have legislated alternative energy promotion plans that support R&D, tax reduction, rewards, and low interest loans. However, it is suggested that the bioenergy policy and plan juxtapose the financial supports (R&D, tax exemption, low interest loan, education, etc.) with strong mandates and obligations. Although imposing strong mandates prerequisites the economically attractive and feasible technologies, it can motivate and speed up more effective technology development, in turn. In addition, the bioenergy R&D support must include studies on commercialization and marketing as well as process development. R&D on the socioeconomic effects of bioenergy should also be supported. Lastly, decision making processes for the bioenergy policy, and for alternative energy overall, must include environmental agencies for taking advantage of environmental benefits of bioenergy.

• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.5
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• pp.496-510
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• 2016

Simulation technology is a type of shipbuilding product lifecycle management solution used to support production planning or decision-making. Normally, most shipbuilding processes are consisted of job shop production, and the modeling and simulation require professional skills and experience on shipbuilding. For these reasons, many shipbuilding companies have difficulties adapting simulation systems, regardless of the necessity for the technology. In this paper, the data model for shipyard production simulation model generation was defined by analyzing the iterative simulation modeling procedure. The shipyard production simulation data model defined in this study contains the information necessary for the conventional simulation modeling procedure and can serve as a basis for simulation model generation. The efficacy of the developed system was validated by applying it to the simulation model generation of the panel block production line. By implementing the initial simulation model generation process, which was performed in the past with a simulation modeler, the proposed system substantially reduced the modeling time. In addition, by reducing the difficulties posed by different modeler-dependent generation methods, the proposed system makes the standardization of the simulation model quality possible.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.9
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• pp.1378-1389
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• 2002

This study was to identify dimensions of subjective knowledge and to test the structural model of the effect of subjective knowledge on information search and evaluation rules for apparel products. A questionnaire was administered to 668 females living in Seoul, Taejon, and Cheongju, and the data were analysed by using LISREL 8. The results of this study were as follows: First, consumers' subjective knowledge regarding apparel products consisted of five factors; Style knowledge, Fashion Knowledge, Store Knowledge, Fabric/Management Knowledge, and Brand knowledge. Those factors were influenced by the experience related with apparel products. Second, the subjective knowledge influenced information searches. That is, internal search was significantly influenced by fashion knowledge and store knowledge, while external search was significantly influenced by fashion knowledge and fabric/management knowledge. Third, the subjective knowledge had indirect effects on evaluation rules via search activities (e.g., internal and external), suggesting that the internal search was mediated in relationship between subjective knowledge and compensatory rule, while the urtemal search was mediated in the relationship between subjective knowledge and noncompensatory rule. Therefore, this study implies that subjective knowledge plays an important role to explain consumers' decision making processes such as information search and evaluation.

• Journal of Technology Innovation
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• v.5 no.1
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• pp.150-180
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• 1997

This article introduces the five functions of the national innovation system(NIS). As one of social systems in the national level, the five generic functions of open system - production, boundary spanning, maintenance, adaptation, management functions - are applied to the NIS. The production function is the primary process, which produces innovative products and services of the NIS. The boundary spanning function is the function of procuring input and disposing the innovation output or aiding in these processes. Experienced R&D human resources, R&D funds, technology etc. are some of the components of the input of the NIS. The maintenance function is responsible for maintaining smooth operation and upkeeping the system in terms of various conditions. The adaptation function is to help the system change and adapt, and scan the environment for problems, opportunites, and technological developments. It has outward orientation, from the long-term view for the survival of the system. The management function carries out planning and control of the overall activities for the other four functions in order to effectiving run the system as a whole. Finally, this article discusses implications of the diagnosis of the national innovation system and the decision making process of S&T policy.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1301-1311
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• 2017

Manufacturing big data systems have supported decision making that can improve preemptive manufacturing activities through collection, storage, management, and predictive analysis of related 4M data in pre-manufacturing processes. Effective visualization of data is crucial for efficient management and operation of data in these systems. This paper presents visualization techniques that can be used to effectively show data collection, analysis, and prediction results in the manufacturing big data systems. Through the visualization technique presented in this paper, we have confirmed that it was not only easy to identify the problems that occurred at the manufacturing site, but also it was very useful to reply to these problems.

• Geomechanics and Engineering
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• v.12 no.3
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• pp.483-503
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• 2017

Uncertainty is a fact belonging to engineering practice. An important uncertainty that sets geotechnical engineering is the variability associated with the properties of soils or, more precisely, the characterization of soil profiles. The reason is due largely to the complex and varied natural processes associated with the formation of soil. Spatial variability analysis for the study of the stability of natural slopes, complementing conventional analyses, is able to incorporate these uncertainties. In this paper the characterization is performed in back-analysis for a case of landslide occurred to verify afterwards the presence of the conditions of shear strength at failure. This approach may support designers to make more accurate estimates regarding slope failure responding, more consciously, to the legislation dispositions about slope stability evaluation and future design. By applying different kriging techniques used for spatial analysis it has been possible to perform a 3D-slope reconstruction. The predictive analysis and the areal mapping of the soil mechanical characteristics would support the definition of priority interventions in the zones characterized by more critical values as well as slope potential instability. This tool of analysis aims to support decision-making by directing project planning through the efficient allocation of available resources.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.221-228
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• 2006

To reform and improve the productivity of construction industry, 1) it should be encouraged to improve the construction production process and 2) it is required to enhance reliability of construction information based on the systematic thinking process. To promote the information reliability created during construction production process, Lean Construction Research Center(LRC2) is developing a supporting system to improve processes of design/supply/construction phase, functioning to efficiently manage the information created at each phase and developing a web based construction information system that provides result management/decision making support/knowledge based information services.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.1
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• pp.44-51
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• 2016

Recently, artificial intelligence has reached the level of top information technologies that will have significant influence over many aspects of our future lifestyles. In particular, in the fields of machine learning technologies for classification and decision-making, there have been a lot of research efforts for solving estimation and control problems that appear in the various kinds of portfolio management problems via data-driven approaches. Note that these modern data-driven approaches, which try to find solutions to the problems based on relevant empirical data rather than mathematical analyses, are useful particularly in practical application domains. In this paper, we consider some applications of modern data-driven machine learning methods for portfolio management problems. More precisely, we apply a simplified version of the sparse Gaussian process (GP) classification method for classifying users' sensitivity with respect to financial risk, and then present two portfolio management issues in which the GP application results can be useful. Experimental results show that the GP applications work well in handling simulated data sets.

• International Journal of Highway Engineering
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• v.17 no.3
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• pp.13-25
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• 2015

PURPOSES : This paper aims at the implementation of a balanced scorecard that can be widely applied to modern business management for use in the public road management sector. METHODS : This study applied the newly developed LOS-based balanced scorecard system instead of a traditional Key Performance Index (KPI) for better decision making in asset management planning. As an evaluation technique, a" hierarchical alignment and cascading method" is also suggested. Finally, the suggested system has been empirically applied to a regional government. RESULTS : To provide stable and sustainable road services, the balanced scorecard informs the regional government of needed improvements in its asset management plans regarding budget optimization, structural management, the development of inner-business processes, and human resources. CONCLUSIONS : An LOS-based balanced scorecard for managing road services and organizations in a quantitative manner has been successfully developed and tested through a field study. The developed scorecard is a timely topic and a useful analytical tool for coping with the new phases of an aging infrastructure, tighter budgets, and demand for greater public accountability.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.280.2-286
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• 1998

Flood is the main natural disaster mostly in the world. It is a care problem to prevent flood disaster generally. The frequency of flood disaster is high and the distributing field is wide, the 50 percent population and 70 percent properties distribute at the threaten field of flood disaster in China. Flood disaster has caused a huge amount of economical losses and these losses have an increasing trend. Along with the development of reducing natural disaster action, it has become one of the most attentive problems for monitoring flood, preventing flood and forecasting flood efficiently. Remote sensing has the characteristics of large spatial observing areas, wide spectrum ranges, and imaging far away from the targets, imaging capabilities all weather. Spatial remote sensing information, which records the full, processes of the disaster's occurrence and development in real-time. It is a scientific basis for management, planning and decision-making. Through systemic analyzing the RS monitoring theory, based on compounding RS information, the technology and method of monitoring flood disaster are studied.