• 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.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.146-154
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• 2019

Recently, a system has been developed and applied to establish and utilize HD maps through R&D. The biggest problem, however, is the lack of a proper HD map update system, which requires the development and adoption of such a system as soon as possible. In addition, in the case of updating HD maps for automated driving, integrity and accuracy of maps are required for safe driving, so an test of these technologies and data quality is required. In April 2018, the Ministry of Land, Infrastructure and Transport implemented a project to 'Develop Technology to Demonstrate and Share the Instant Road Change Detection and Update Technology for automated driving. This paper analyzed the technology for updating map based on the investigation and analysis of relevant technology trends for the development of integrated demonstration and sharing technology of road change rapid detection and updating map technology, and put forward the criteria for road change rapid detection, integrated quality verification of update technology. It is expected that the results of this study will contribute to quality assurance of HD maps that support safety driving for automated vehicles.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.2
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• pp.31-46
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• 2019

As the importance of venture firms has increased as a new growth engine, the South Korea government makes various efforts to establish healthy ecosystems for ventures and start-ups. Especially in order to foster the competitiveness of venture firms, various support policies such as financial and R&D expenses are being expanded and promoted. In this study, the author analyzed the impact of government funding on venture firms' internal competencies and management performance by using the resource-based theory. Moreover, this study tested the moderation effect of firm's growth stages. Unlike previous studies, this study focused on qualitative rather than quantitative aspects of internal competencies and the financial and non-financial performance are used to measure the management performance of the ventures to examine the effects of government funding for venture firms in more details. For the purpose of verifying the hypothesis of this research, "The Research On The Precision Status Of Venture Firms" in 2017 from the Ministry of Small and Medium Business was utilized, which has been compiled since 1999. According to the results of this study, the government funding experience did not significantly affect the company's internal competencies and financial performance, but had a significant impact on the non-financial performance, which in turn seemed to have a significant effect on the financial performance. In addition, it was found that the technology, price, design, and quality competencies affected non-financial performance, while the organizational management and marketing competencies did not. However, the price, design, organizational management, and marketing competencies affected financial performance, while the technology competency was not. Finally, there were no differences in the effectiveness of government funding, depending on the growth stages.

• Korean Journal of Optics and Photonics
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• v.33 no.2
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• pp.74-83
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• 2022

The entire process, from the raw material to the final system qualification test, has been developed to fabricate a large-diameter, lightweight reflective-telescope system for a satellite observation. The telescope with 3 anastigmatic mirrors has an aperture of 700 mm and a total mass of 66 kg. We baked a silicon carbide substrate body from a carbon preform using a reaction sintering method, and tested the structural and chemical properties, surface conditions, and crystal structure of the body. We developed the polishing and coating methods considering the mechanical and chemical properties of the silicon carbide (SiC) body, and we utilized a chemical-vapor-deposition method to deposit a dense SiC thin film more than 170 ㎛ thick on the mirror's surface, to preserve a highly reflective surface with excellent optical performance. After we made the SiC mirrors, we measured the wave-front error for various optical fields by assembling and aligning three mirrors and support structures. We conducted major space-environment tests for the components and final assembly by temperature-cycling tests and vibration-shock tests, in accordance with the qualifications for the space and launch environment. We confirmed that the final telescope achieves all of the target performance criteria.

• Korea Trade Review
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• v.43 no.4
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• pp.155-175
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• 2018

This study estimates the technical efficiency and total factor productivity(TFP) of and analyzes the relationship between TFP and exports for Korean manufacturing companies from 2000 to 2016. Specially, TFP is decomposed into Technical Change(TC), Technical Efficiency Change (TEC), and Sale Effect(SE), and compared between large and small enterprises. First, in the case of technical efficiency, the Korean economy has been very vulnerable to external shocks, such as the sharp decline following the 2008 financial crisis. The efficiency of the electronics, automobile, and machinery sectors is low and needs to be improved. In addition, the technological efficiency of large enterprises is higher than that of SMEs in most manufacturing sub-sectors except for non-ferrous metals. In the case of TFP, most changes are due to TC, and the effective combination of labor, capital and the effect of scale have little effect, suggesting that improvement of internal structure is urgent. In addition, volatility due to the impact of the financial crisis in 2008 was much larger in SMEs than in large companies, so external economic impacts are more greater for SMEs than large enterprises. The relationship between TFP decomposition factors and exports shows that TC has a positive effect only on exports of SMEs. Therefore, in order to increase exports, in the case of SMEs, R&D support to promote technological development is needed. In the case of large companies, it is necessary to establish differentiated strategies for each export market, competitor company, and item to link efficiency and scale effect of exports.

• Safety and Health at Work
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• v.14 no.2
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• pp.141-152
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• 2023

Objective: We performed a meta-analysis of epidemiological results for the association between occupational exposure as a firefighter and cancer as part of the broader evidence synthesis work of the IARC Monographs program. Methods: A systematic literature search was conducted to identify cohort studies of firefighters followed for cancer incidence and mortality. Studies were evaluated for the influence of key biases on results. Random-effects meta-analysis models were used to estimate the association between ever-employment and duration of employment as a firefighter and risk of 12 selected cancers. The impact of bias was explored in sensitivity analyses. Results: Among the 16 included cancer incidence studies, the estimated meta-rate ratio, 95% confidence interval (CI), and heterogeneity statistic (I²) for ever-employment as a career firefighter compared mostly to general populations were 1.58 (1.14-2.20, 8%) for mesothelioma, 1.16 (1.08-1.26, 0%) for bladder cancer, 1.21 (1.12-1.32, 81%) for prostate cancer, 1.37 (1.03-1.82, 56%) for testicular cancer, 1.19 (1.07-1.32, 37%) for colon cancer, 1.36 (1.15-1.62, 83%) for melanoma, 1.12 (1.01-1.25, 0%) for non-Hodgkin lymphoma, 1.28 (1.02-1.61, 40%) for thyroid cancer, and 1.09 (0.92-1.29, 55%) for kidney cancer. Ever-employment as a firefighter was not positively associated with lung, nervous system, or stomach cancer. Results for mesothelioma and bladder cancer exhibited low heterogeneity and were largely robust across sensitivity analyses. Conclusions: There is epidemiological evidence to support a causal relationship between occupational exposure as a firefighter and certain cancers. Challenges persist in the body of evidence related to the quality of exposure assessment, confounding, and medical surveillance bias.

• The Journal of Korean Obstetrics and Gynecology
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• v.36 no.4
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• pp.96-120
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• 2023

Objectives: This study reports the findings that support the efficacy of herbal medicine (HM) for premenstrual syndrome (PMS). Methods: We conducted meta-analysis of findings from randomized controlled trials (RCTs) for PMS treated with HM. The articles were published before July 2022, located using 9 databases (Pubmed, EMBASE, Cochrane Library, CINAHL, CNKI, CiNii, SCIENCE ON, KoreaMed, OASIS). Results: We observed 2,034 studies, of which 23 RCTs met our inclusion criteria. The risk of bias in the included studies was relatively unclear or high. Meta-analysis of 3 RCTs showed that HM group had a significantly higher total effective rate than the western medicine group (RR 1.20 [95% CI 1.06, 1.36, p=0.004]). Meta-analysis of 1 RCT showed that HM group had a significantly lower symptom score (MD -3.04 [95% CI -5.36, -0.72, p=0.01]), while there was no significant difference in daily record of severity of problems scale (MD -20.52 [95% CI -49.33, 8.29, p=0.16]). Conclusions: HM significantly improved PMS symptoms than general treatment and no serious adverse events were reported. However, the evidence on the effectiveness and safety of HM for PMS was not enough to provide reliable results due to the small number and low quality of included studies. We believe that rigorous RCTs will lead to more reliable evidence of the intervention.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.2
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• pp.95-111
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• 2023

Korea has achieved a high startup rate by promoting government-led startup policies for national economic and industrial development. However, as high as the startup rate is, the closure rate of startup companies can be judged to be insufficient for the qualitative growth of the domestic startup ecosystem. This study aims to investigate how to improve the survival rate of startups by overcoming the valley of death from a location environment perspective. It analyzes the effects of technology orientation and market orientation of start-ups on management performance and the moderating effects of economic, accessibility, and network factors that constitute the location environment. To achieve the research objectives, the empirical analysis was conducted on start-up companies that received corporate support projects from innovation intermediary organizations. The results show that R&D capability of technology orientation has a significant effect on management performance, and market information generation and market information response of market orientation have a significant effect on management performance. As for the moderating effect, accessibility, a sub-factor of the location environment, has a positive moderating effect on the relationship between technological innovation and managerial performance, and the location environment (economy, accessibility, and network) has a positive moderating effect on the relationship between market information generation and managerial performance. This study compared and analyzed previous studies on the success and failure of start-ups and identified common factors. In addition, this study provides policy implications for the sustainable growth of startups through empirical analysis and interview with stakeholders. For future research, it is necessary to compare and analyze start-ups in metropolitan areas and non-metropolitan areas. In addition, it is necessary to study startups that have moved out of the region and into the metropolitan area to find ways to develop the regional startup ecosystem.

• Journal of Practical Agriculture & Fisheries Research
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• v.26 no.1
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• pp.22-29
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• 2024

In this study, we summarized the definition of smart vegetable seedling production technology, analysis of smart seedling production system, a hardware and software configuration model for smart seedling production system, research and development trends in smart seedling production system, and proposed future research and development plans for smart seedling production technology. Smart vegetable seedling production is a data-based seedling production, management, and distribution system that utilizes 4th Industrial Revolution technology to improve seedling productivity and quality. The production of vegetable seedlings using smart seedling production technology can be efficiently managed by collecting, analyzing, and managing information on seedlings, environment, and tasks at each stage of production by linking with the smart seedling integrated management system. However, there is still a lack of standardization of seedling standards and quality for each vegetable crop to establish smart seeding production technology, as well as development of smart seedling production element technology, which requires national wide R&D support.

• 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.