• Journal of Animal Science and Technology
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• v.44 no.5
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• pp.499-506
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• 2002

This study was conducted to estimate the heritabilities and genetic and phenotypic correlations among average daily gain, age at 90kg and backfat thickness in Yorkshire pigs. The data were obtained from 2,111 heads of Yorkshire tested at National Livestock Research Institute from May, 1994 to April, 2000. Genetic parameters were estimated with a multiple trait animal model by using DF-REML (Deri- vative-Free REstricted Maximum Likelihood). The results obtained are summarized as follows ; The means of traits studied were 0.871${\pm}$0.124 kg for average daily gain, 145.397${\pm}$11.718 days for age at 90kg and 1.476${\pm}$0.241 cm for backfat thickness. The estimated heritabilities were 0.55 for average daily gain, 0.56 for age at 90kg and 0.55 for backfat thickness. The genetic correlation of average daily gain with age at 90kg and backfat thickness were －0.82, 0.10, respectively. The genetic correlation of age at 90kg with backfat thickness was －0.25. The phenotypic correlations of average daily gain(ADG) with age at 90kg and backfat thickness and age at 90kg with backfat thickness were －0.77, 0.02 and －0.05 respectively. Though phenotypic correlation of ADG and age at 90kg was low, breeding project should be carefully considered by high genetic correlation. High heritabilities on all economic traits were obtained. Therefore, it is considered that suitable selection and management is needed successful improvement.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.3
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• pp.47-61
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• 2014

Many angel investors hesitate to invest in early-stage company. Most early-stage company has no sales and only R&D step project or in early approach of market. So it's impossible to evaluate early-stage company quantitatively. Therefore many angel investors depend on CEO's tendency to evaluate company and make decision for investment. The purpose of this study is discover the entrepreneurial characteristics of CEO and the importance level which affect on the angel investors decision making factors for investment. To identify the factors of entrepreneurial characteristics, survey was conducted by Delphi Technique which is involved by 20 experts who is angel investment club members, venture capitalists, CEOs and officers. Three rounds of survey results derived 10 elements of entrepreneurial characteristics for investment decision making factors including reliability, risk sensitivity, passion, perseverance, integrity, leadership, startup experience, organizational management skills, innovation and social networking. In addition, this study derived the importance level of elements of entrepreneurial characteristics based on the AHP(Analytic Hierarchy Process) theory and maintained the logical consistency by pair-wise comparison for each element. As a result of analyzing the importance of entrepreneurial characteristics, the sequence is reliability (18.1%), integrity (15.9%), leadership (11.7%), organizational management skills (10.0%), social networking (9.5%), passion(9.1%), perseverance(8.4%), innovation(8.1%), startup experience(5.3%) and risk sensitivity(3.9%) respectively. The significance of this study is somewhat decrease limit of the uncertainty arising from angel investors and angel investors can help a decision making, by discover factors of entrepreneurial characteristics that can be called the biggest influencing factors among Investor's investment decision-making In early stage companies and compare importance.

• Korean Journal of Construction Engineering and Management
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• v.14 no.3
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• pp.107-114
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• 2013

The interest in traditional Korean housing has greatly increasing in Korean housing market. However, it is difficult to wildly disseminate for a high construction cost reason. In order to effectively facilitate the Hanok construction, Korean government has initiated a project that develops a new style Korean housing, which meets the requirements of low cost and modernized life style. Cost of building is mainly affected by materials and construction methods. Hanok has some special commodities those significantly impact the cost. In order to effectively cut down the costs, well-organized planning for costs is very important. Also, improving the productivity by utilizing new materials and methods can result in cost down. In this context, this paper compared and analyzed two different types of Korean housing; one is a modernized Korean house which used new materials and methods, the other is a traditional Korean house which was build up by purely traditional methods. Productivity has also been compared and analyzed for 5 major commodities between two types of models. Based on these comparative data, effect of cost down by new model has been analyzed. As a result it is confirmed that by using the new materials and methods could highly effect to increasing productivity and cost down. Especially, the cost of Roofing have been more influenced by using new material while the Wood and Finishes have been influenced by new construction method. Construction cost of Foundation (Earthwork, Concrete, Masonry) and Openings were influenced both factors, changing of materials and methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.76-82
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• 2019

This study has done to search for a solution to remove risk limitedly caused by separating weapon system acquisition from operation and maintenance at the view point of Logistic Commander who's responsible for stable operation and maintenance after acquiring weapon system. At the System development stage, unverified overhaul development plan may cause additional manpower and costs after the development, and furthermore it is likely to have risk to lower reliability of the military. Thus, research and development agency should write overhaul development plan at the System development stage, and it should be verified through evaluation and verification test. Secondly, during research and development, institutional supplementation is needed to calculate human and material resources writing overhaul development plan. Thirdly, it should be able to analyze proper operation & maintenance plan and cost for overhaul plan at the pre-investigation stage. Fourthly, the base which can develop overhaul concept and overhaul factors should be included in the need and need determination document. Lastly, for the weapon system which has small amount of high power figure, project management should be performed to be able to specify at the each acquisition level of weapon system to realize Article 28, clause 3 and 4 of Defense business law.

• Asia Marketing Journal
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• v.7 no.3
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• pp.53-76
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• 2005

With rapid technological and market change, new product development (NPD) complexity is a significant issue that organizations continually face in their development projects. There are numerous factors, which cause development projects to become increasingly costly & complex. A product is more likely to be successfully developed and marketed when the complexity inherent in NPD projects is clearly understood and carefully managed. Based upon the previous studies, this study examines the nature and importance of complexity in developing new products and then identifies several issues in managing complexity. Issues considered include: definition of complexity : consequences of complexity; and methods for managing complexity in NPD projects. To achieve high performance in managing complexity in development projects, these issues need to be addressed, for example: A. Complexity inherent in NPD projects is multi-faceted and multidimensional. What factors need to be considered in defining and/or measuring complexity in a development project? For example, is it sufficient if complexity is defined only from a technological perspective, or is it more desirable to consider the entire array of complexity sources which NPD teams with different functions (e.g., marketing, R&D, manufacturing, etc.) face in the development process? Moreover, is it sufficient if complexity is measured only once during a development project, or is it more effective and useful to trace complexity changes over the entire development life cycle? B. Complexity inherent in a project can have negative as well as positive influences on NPD performance. Thus, which complexity impacts are usually considered negative and which are positive? Project complexity also can affect the entire organization. Any complexity could be better assessed in broader and longer perspective. What are some ways in which the long-term impact of complexity on an organization can be assessed and managed? C. Based upon previous studies, several approaches for managing complexity are derived. What are the weaknesses & strengths of each approach? Is there a desirable hierarchy or order among these approaches when more than one approach is used? Are there differences in the outcomes according to industry and product types (incremental or radical)? Answers to these and other questions can help organizations effectively manage the complexity inherent in most development projects. Complexity is worthy of additional attention from researchers and practitioners alike. Large-scale empirical investigations, jointly conducted by researchers and practitioners, will help gain useful insights into understanding and managing complexity. Those organizations that can accurately identify, assess, and manage the complexity inherent in projects are likely to gain important competitive advantages.

• Journal of the Korean Society for Marine Environment & Energy
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• v.12 no.4
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• pp.307-319
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• 2009

Carbon dioxide capture and storage (CCS) technology has been regarded as one of the most possible and practical option to reduce the emission of carbon dioxide ($CO_2$) and consequently to mitigate the climate change. Korean government also have started a 10-year R&D project on $CO_2$ storage in sea-bed geological structure including gas field and deep saline aquifer since 2005. Various relevant researches are carried out to cover the initial survey of suitable geological structure storage site, monitoring of the stored $CO_2$ behavior, basic design of $CO_2$ transport and storage process and the risk assessment and management related to $CO_2$ leakage from engineered and geological processes. Leakage of $CO_2$ to the marine environment can change the chemistry of seawater including the pH and carbonate composition and also influence adversely on the diverse living organisms in ecosystems. Recently, IMO (International Maritime Organization) have developed the risk assessment and management framework for the $CO_2$ sequestration in sub-seabed geological structures (CS-SSGS) and considered the sequestration as a waste management option to mitigate greenhouse gas emissions. This framework for CS-SSGS aims to provide generic guidance to the Contracting Parties to the London Convention and Protocol, in order to characterize the risks to the marine environment from CS-SSGS on a site-specific basis and also to collect the necessary information to develop a management strategy to address uncertainties and any residual risks. The environmental risk assessment (ERA) plan for $CO_2$ storage work should include site selection and characterization, exposure assessment with probable leak scenario, risk assessment from direct and in-direct impact to the living organisms and risk management strategy. Domestic trial of the $CO_2$ capture and sequestration in to the marine geologic formation also should be accomplished through risk management with specified ERA approaches based on the IMO framework. The risk assessment procedure for $CO_2$ marine storage should contain the following components; 1) prediction of leakage probabilities with the reliable leakage scenarios from both engineered and geological part, 2) understanding on physio-chemical fate of $CO_2$ in marine environment especially for the candidate sites, 3) exposure assessment methods for various receptors in marine environments, 4) database production on the toxic effect of $CO_2$ to the ecologically and economically important species, and finally 5) development of surveillance procedures on the environmental changes with adequate monitoring techniques.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.3
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• pp.229-239
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• 2015

In light of the significant increase in the quantities of goods transported and the development of the shipping industry, the frequency of usage of port structures has increased; yet, the government's budget for the shipping & port of SOC has been reduced. Port structures require systematically effective maintenance and management trends that address their growing frequency of usage. In order to construct a productive maintenance system, it is essential to develop deterioration models of port structures that consider various characteristics, such as location, type, use, constructed level, and state of maintenance. Processes for developing such deterioration models include examining factors that cause the structures to deteriorate, collecting data on deteriorating structures, and deciding methods of estimation. The techniques used for developing the deterioration models are multiple regression analysis and Markov chain theory. Multiple regression analysis can reflect changes over time and Markov chain theory can apply status changes based on a probabilistic method. Along with these processes, the deterioration models of open-type and gravity-type wharfs were suggested.

• 대한공업교육학회지
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• v.38 no.2
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• pp.1-26
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• 2013

This study inquired following research questions by a narrative research method : What was the job of an engineer in mechanical design field? How did he fulfill his job-related learning in his workplace? What were the context and the characteristic of the job-related learning in the workplace? And some implications of the job-related learning on engineering education were discussed. We identified that the research participant's career as a mechanical engineer has developed through three stages. At first, he engaged on conceptual design of a semi-conductor test machine through self-initiated learning from basic to whole system of the machine. At second stage, he leaded a design group for the concrete design of a ball type semi-conductor test machine. In this stage he learned the meaning of cooperation and cooperative learning. At third stage, he initiated to found an entrepreneur company that was specified to design a semi-conductor test machine. He became CEO of the company. He learned the R & D policy making through contacts with global company, visiting exhibition in abroad. Eventually his main task as a mechanical engineer was the problem solving in the process of machine design. He had experienced and learned through his works : project management, independent fulfilling of tasks, functional analysis and reverse engineering, conceptualizing and test, cohesive cooperation, dialogue and discussion, mediation of conflict, human relationship, leadership. The implication of the narrative analysis on engineering education is, proposed, to give the students more chances to experience and to learn such activities.

• Korean Journal of Social Welfare Studies
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• v.47 no.4
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• pp.255-280
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• 2016

This study examined sexual violence characteristics among the individuals who utilized victim support services provided by National Rape Crisis Intervention Centers in Korea. The study is the part of a Korean longitudinal study on sexual assault characteristics and its implications for post-abuse adjustments, which is supported by Korean Mental Health Technology R&D Project. Eleven national rape crisis centers nationwide and 29 NGO's participated in the study. The participating centers provided the data on sexual abuse characteristics from their standardized case management system. The cases were randomly selected from the system. Total of 1077 cases were gleaned from the system and utilized for this analysis. Results indicated that the abuse characteristics differed by victims' age (children, adolescent vs. adults) as well as relationship with perpetrator. We could identify six different profile groups based on the detailed violence characteristics. The results assured us of the importance to understand the detailed characteristics of sexual violence and the old notion that 'one size may not fit all'. The results from the profile analyses may have important implication for developing victim support programs and appropriately allocating agency resources according to the different profiles of the service users.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.