• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.4
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• pp.247-259
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• 2007

In this study, we examined the flux of carbon and water using an eco-hydrological model, Regional Hydro-Ecologic Simulation System (RHESSys). Our purposes were to develop a set of parameters optimized for a well-designed experimental watershed (Gwangneung Research Watershed, GN) and then, to test suitability of the parameters for predicting carbon and water fluxes of other watershed with different regimes of climate, topography, and vegetation structure (i.e Gangseonry Watershed in Mt. Jumbong, GS). Field datasets of stream flow, soil water content (SWC), and wood biomass product (WBP) were utilized for model parameterization and validation. After laborious parameterization processes, RHESSys was validated with the field observations from the GN watershed. The parameter set identified at the GN watershed was then applied to the GS watershed in Mt. Jumbong, which resulted in good agreement for SWC but poor predictability for WBP. Our study showed that RHESSys simulated reliable SWC at the GS by adjusting site-specific porosity only. In contrast, vegetation productivity would require more rigorous site-specific parameterization and hence, further study is necessary to identify primary field ecophysiological variables for enhancing model parameterization and application to multiple watersheds.

• Safety and Health at Work
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• v.8 no.2
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• pp.198-205
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• 2017

Background: There are a million ragpickers in India who gather and trade recyclable municipal solid wastes materials for a living. The objective of this study was to examine whether their occupation adversely affects their immunity. Methods: Seventy-four women ragpickers (median age, 30 years) and 65 age-matched control housemaids were enrolled. Flow cytometry was used to measure leukocyte subsets, and leukocyte expressions of $Fc{\gamma}$ receptor I (CD64), $Fc{\gamma}RIII$ (CD16), complement receptor 1 (CD35) and CR3 (CD11b/CD18), and CD14. Serum total immunoglobulin-E was estimated with enzyme-linked immunosorbent assay. Results: Compared with the controls, ragpickers had significantly (p < 0.0001) higher levels of CD8-T-cytotoxic, CD16+CD56+natural killer, and CD4+CD45RO+memory T-cells, but depleted levels of CD19+B-cells. The percentage of CD4+T-helper-cells was lower than the control group (p < 0.0001), but their absolute number was relatively unchanged (p = 0.42) due to 11% higher lymphocyte counts in ragpickers. In ragpickers, the percentages of CD14+CD16+intermediate and CD14dim CD16+nonclassical monocyte subsets were elevated with a decline in CD14+CD16-classical monocytes. The expressions of CD64, CD16, CD35, and CD11b/CD18 on both monocytes and neutrophils, and CD14 on monocytes were significantly higher in ragpickers. In addition, ragpickers had 2.7-times more serum immunoglobulin-E than the controls (p < 0.0001). After controlling potential confounders, the profession of ragpicking was positively associated with the changes. Conclusion: Ragpicking is associated with alterations in both innate (neutrophils, monocytes, and natural killer cell numbers and expression of complement and $Fc{\gamma}$ receptors) and adaptive immunity (numbers of circulating B cells, helper, cytotoxic, and memory T cells).

• Journal of Korean Society of Transportation
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• v.20 no.2
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• pp.47-58
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• 2002

This thesis is based on the speed variations which are observed both in a sing1e tunnel and a continuous tunnel. Kumdae II tunnel and Chiak I tunnel of Jungang Expressway are selected in order to analyze the characteristics of speed variations according to tunnel intervals I place importance on the computation of tunnel intervals according to the speed variations. there's a summary of the results. The results of the study reveal that speed changes occur both on 1km ahead of tunnel and within the tunnel. The speed change amounts to 7.1km/hr(6.7%) on these survey Points 2.7km/hr (2.9%) on access points, and from -3.6km/hr (-3.8%) to, +4.1km/hr(+4.7%) irregularly on egress points. The magnitude of speed chance appears small on the survey points where an interval of tunnel is short whereas the speed chance turn out to be rather significant on the points where the tunnel interval is long. The analysis of tunnel distances using multiple regression models shows that the appropriate tunnel distance turns out to be 732m. The distance of 732m seem to be providing a fecundation for uniform traffic flow in continuous tunnel conditions.

• 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.

• Journal of Microbiology and Biotechnology
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• v.18 no.4
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• pp.686-694
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• 2008

The inhibitory effects of 5,6,3',5'-tetramethoxy 7,4'-hydroxyflavone (labeled as p7F) were elucidated on the productions of proinflammatory cytokines as well as inflammatory mediators in human synovial fibroblasts and macrophage cells. p7F inhibited IL-1${\beta}$ or TNF-${\alpha}$ induced expressions of inflammatory mediators (ICAM-1, COX-2, and iNOS). p7F also inhibited LPS-induced productions of nitric oxide and prostaglandin $E_2$ in RAW 264.7 cells. In order to investigate whether p7F would inhibit IL-1 signaling, p7F was added to the D10S Th2 cell line (which is responsive to only IL-1${\beta}$ and thus proliferates), revealing that p7F inhibited IL-1${\beta}$-induced proliferation of D10S Th2 cells in a dose-response manner. A flow cytometric analysis revealed that p7F reduced the intracellular level of free radical oxygen species in RAW 264.7 cells treated with hydrogen peroxide. p7F inhibited IkB degradation and NF-${\kappa}$B activation in macrophage cells treated with LPS, supporting that p7F could inhibit signaling mediated via toll-like receptor. Taken together, p7F has inhibitory effects on LPS-induced productions of inflammatory mediators on human synovial fibroblasts and macrophage cells and thus has the potential to be an anti-inflammatory agent for inhibiting inflammatory responses.

• Journal of Korean Society of Environmental Engineers
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• v.38 no.7
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• pp.387-394
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• 2016

Commercial 28 algae removal technologies that have been applied in domestic rivers and lakes with green tide were investigated, analyzed and classified. The classification of algae removal technologies was based on the three criteria (i.e., principle, flow rate of water body, and application period). Also, algae removal technologies were evaluated in terms of cost effectiveness, field applicability, effect durability, and eco friendliness. From the analysis results, technologies using physical, chemical, biological, and convergent controls were 32.2%, 25%, 21.4%, and 21.4%, respectively. The 75% of technologies have been applied to stagnant water body (${\leq}0.2m/s$). Also, algae harvesting ship with dissolved air flotation, conveyor belt and filtration processes and natural floating coagulant were found to have better field applicability, compared to other technologies. However, proper algae removal technology in specific rivers and lakes should be chosen after the evaluation of long-term pilot scale field test. Also, development of energy and resource recovery technologies from algae biomass is warranted.

• Journal of Korean Society of Environmental Engineers
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• v.29 no.2
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• pp.163-168
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• 2007

Ecological risk assessment(ERA) to 5 abandoned mine drainage was investigated by using chemical measurement and bioassay experiment. From the results of chemical analysis, the high concentration of heavy metals are detected in most area. The Arsenite were mostly detected in Songcheon, Nakdong, and Dukum abandoned mine area, and various heavy metals were highly dispersed in Nakdong area. The study area have also high biological toxicity, resulted from the bioassay based on WET(Whole Effluent Toxicity) test by using Vibrio fisheri, Selenastrum copricornutum, and Daphnia magna. The maximum toxicity was shown in the point where the mine waters start to flow. The sensitivity of toxicity by S. capricornutum was relatively high considering the values of toxicity in all samples, from 1.3 to 32.0 TU. The different sensitivities of toxicity recommends the use of battery system, resulted from at least two test species for bioassay or ecological risk assessment of mine drainage. Besides, the results showed high hazard quotient(i.e., greater than 1 HQ value indicating potentially significant toxic risks) with regard to abandoned mine drainage area in this study. On the other hand, the biological toxicity results were sharply decreased by attenuation along further distance from discharging of mine waters. Therefore, environmental parameters including the dilution factor, dissolved organic matter, and hardness should be considered when the remediation and ERA of abandoned mine drainage is planned.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.234-251
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• 1995

본 연구에서는 EDI감사 의사결정지원시스템을 개발하였다. 이를 위해서 기존의 EDP감사 의사결정지원시스템 및 감사전문가시스템분야의 연구를 고찰했다. EDI감사를 위한 의사결정지원시스템은 통계, 위험, 회사의 개요, 테스트 항목등의 데이타를 저장한 데이타베이스 시스템이다. 시스템 개발을 위해서 E/R(Entity Relation)이나 DFD(Data Flow Diagram)분석을 통해서 논리적인 설계를 하였다. 시스템 개발은 개인용 데이타베이스팩키지인 FoxPro를 사용하였다. 이 시스템을 통해서 감사인이 필요한 테스트 결과를 조회하거난 저장할 수 있고 통제, 위험, 회사등의 상호조회를 통한 필요한 통제나 위험정도를 쉽게 조회해 볼수 있다. 회사마다 필요한 통제, 위험, 테스트 항목등의 체크리스트가 달라지는 경우에 이 시스템을 통해서 입력 저장하여 각각의 회사에 대해 다른 체크리스트를 저장하여 놓을수 있다. 본 시스템은 EDI감사뿐만 아니라 일반 EDP감사분야에도 적용가능할 것이다. 종이를 사용한 감사증적이 없음으로 인해 수작업에 의한 EDI감사는 어려움이 있고 EDP감사시스템분야의 국내 연구가 전무한 실정에서 EDI감사를 지원하는 시스템의 연구는 의의를 갖는다고 생각된다. 본 시스템을 통해서 EDI의 보안 및 감사업무의 효율성이 높아지고 EDI에 대한 위험에 효율적으로 대처할수 있게 될 것이다. 그리고 이러한 보안 및 감사기법과 통제모형을 지식베이스로 구축해서 실제의 위험노출상황에서 가능한 보안을 위한 통제방안이 여러가지가 있는 경우에 비용/편익 분석, 효율성, 회사방침 및 법률적인 문제등을 고려해서 최적의 보안통제 및 감사기법을 선택하는 것을 지원할 수 있을 것이다.고리듬을 개발 함으로써 내부점 선형계획법의 수행속도의 개선에 도움이 될 것이다.성요소들을 제시하였다.용자 만족도가 보다 높은 것으 로 나타났다. 할 수 있는 효율적인 distributed system를 개발하는 것을 제시하였다. 본 논문은 데이타베이스론의 입장에서 아직 정립되어 있지 않은 분산 환경하에서의 관계형 데이타베이스의 데이타관리의 분류체계를 나름대로 정립하였다는데 그 의의가 있다. 또한 이것의 응용은 현재 분산데이타베이스 구축에 있어 나타나는 기술적인 문제점들을 어느정도 보완할 수 있다는 점에서 그 중요성이 있다.ence of a small(IxEpc),hot(Tex> SOK) core which contains two tempegatlue peaks at -15" east and north of MDS. The column density of HCaN is (1-3):n1014cm-2. Column density at distant position from MD5 is larger than that in the (:entral region. We have deduced that this hot-core has a mass of 10sR1 which i:s about an order of magnitude larger those obtained by previous studies.previous studies.업순서들의 상관관계를 고려하여 보다 개선된 해를 구하기 위한 연구가 요구된다. 또한, 준비작업비용을 발생시키는 작업장의 작업순서결정에 대해서도 연구를 행하여, 보완작업비용과 준비비용을 고려한 GMMAL 작업순서문제를 해결하기 위한 연구가 수행되어야 할 것이다.로 이루어

• Journal of the Korean Society for Marine Environment & Energy
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• v.15 no.2
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• pp.142-149
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• 2012

This study deals with the investigation of the scale effect for the vertical-axis tidal stream turbine by evaluating the hydrodynamic efficiency of turbine rotors of different diameters at different flow conditions. Numerical analyses are made for the turbine rotors with a same shape, but different sizes obtained using the diameter evaluation equation suggested in this paper. It is shown that the performance of turbine is clearly dependent upon the rotor size and inflow velocity, i.e. Reynolds number dependency of different-scaled turbines showing better efficiency with increasing Reynolds number. The sudden decrease of efficiency is also noticed around the transition region of Reynolds number. The hydrodynamic capacity evaluation method needed at initial stage of turbine design is suggested and exercised with some test cases. It is recommended that the method is expected to be useful for turbines with demanding powers between 10 kW and 300 kW.

• KSBB Journal
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• v.24 no.5
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• pp.432-438
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• 2009

Here, we demonstrated simple nucleic acid, RNA, concentration method using polymer micro chip containing glass bead ($100\;{\mu}m$). Polymer micro chip was fabricated by PDMS ($1.5\;cm\;{\times}\;1.5\;cm$, $100\;{\mu}m$ in the height) including pillar structure ($160\;{\mu}m\;(I)\;{\times}\;80\;{\mu}m\;(w)\;{\times}\;100\;{\mu}m\;(h)$, gap size $50\;{\mu}m$) for blocking micro bead. RNA could be adsorbed on micro glass bead at low pH by hydrogen bonding whereas RNA was released at high pH by electrostatic force between silica surface and RNA. Amount of glass beads and flow rate were optimized in aspects of adsorption and desorption of RNA. Adsorption and desorption rate was measured with real time PCR. This concentrated RNA was applied to amplification micro chip in which NASBA (Nucleic Acid Sequence Based Amplification) was performed. As a result, E.coli O157 : H7 in the concentration of 10 c.f.u./10 mL was successfully detected by these serial processes (concentration and amplification) with polymer micro chips. It implies this simple concentration method using polymer micro chip can be directly applied to ultra sensitive method to measure viable bacteria and virus in clinical samples as well as environmental samples.