• 국제지역연구
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• 제14권3호
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• pp.205-219
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• 2010

지속가능성 (Sustainability) 또는 지속가능발전 (Sustainable development)에 대한 연구는 최근 G-20정상회의를 통하여 세계적인 중요의제로 부상하고 있다. 특히 중국 및 신흥국들의 급속한 경제발전과 이에 따른 원자재 부족 및 환경악화로 인한 문제가 단순한 협의안건에서 벗어나 실질적인 생존의 조건으로 부상하고 있다. 이와 같은 시각에서 특히 강조되는 것은 환경관련의제들이 외부비경제효과를 동반하는 속성상 특정국가나 기업만의 문제가 아닌 인류 사회 전체의 문제이며 이를 위해서는 지속가능성에 대한 엄정한 타당성이 검증되어야 한다는 점이다. 본 연구는 이와 같은 시각에서 경제발전과 환경보호라는 외견상 상호 갈등의 소지가 충분한 정책목표상의 균형과 조화를 위한 타당성을 모색하고 이에 대한 시사점을 도출하기 위한 목적으로 한국과 중국의 지속가능 발전모형을 유도하고 이를 실증분석하고자 한다. 본 실증분석 결과에서 나타난 점은 무엇보다 기존의 상식적인 선행연구와는 다르게 경제성장이 환경보호에도 긍정적으로 작용한다는 사실이며, 이를 통해 환경의 외부비경제적 특성에 대한 적절한 보상체계와 정부의 정책적 공조체계가 무엇보다 절실함을 지적하고 있다.

• 대한조선학회논문집
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• 제56권4호
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• pp.361-372
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• 2019

The flow pattern of air layers and skin-friction drag reduction by air injection are investigated to find the suitable multiphase flow model using unstructured finite-volume CFD solver for the Reynolds-averaged Navier-Stokes equations. In the present computations, two different multiphase flow modeling approaches, such as the Volume of Fluid (VOF) and the Eulerian Multi-Phase (EMP), are adopted to investigate their performances in resolving the two-phase flow pattern and in estimating the frictional drag reduction. First of all, the formation pattern of air layers generated by air injection through a circular opening on the bottom of a flat plate are investigated. These results are then compared with those of MMkiharju's experimental results. Subsequently, the quantitative ratios of skin-friction drag reduction including the behavior of air layers, within turbulent boundary layers in large scale and at high Reynolds number conditions, are investigated under the same conditions as the model test that has been conducted in the US Navy's William B. Morgan Large Cavitation Channel (LCC). From these results, it is found that both VOF and EMP models have similar capability and accuracy in capturing the topology of ventilated air cavities so called'air pockets and branches'. However, EMP model is more favorable in predicting quantitatively the percentage of frictional drag reduction by air injection.

• The Korean Journal of Pain
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• 제32권4호
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• pp.264-270
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• 2019

Background: To develop a rabbit epidural steroid injection (ESI) model for analyzing steroid retention in the tissue, and to assess the difference in steroid retention in the model according to the location and time elapsed after ESI. Methods: Fluoroscopy-guided ESI was performed using the interlaminar approach between the lowest two lumbar segments in 13 female New Zealand white rabbits. Four rabbits were allocated to each of three different groups according to the time of sacrifice: 3, 7, and 15 days post-ESI; the remaining rabbit was sacrificed immediately post-ESI to obtain baseline data. After sacrifice, two segments were harvested: the lowest two lumbar vertebrae and another two lumbar vertebrae immediately above these. The residual steroid amount (RSA) and residual steroid concentration (RSC) in the collected spinal columns were analyzed. A linear mixed model was used to compare RSAs and RSCs between the injected and adjacent segments, and among the number of days until sacrifice; P < 0.05 was considered statistically significant. Results: Both RSA and RSC of the injected segment were significantly higher than those of the adjacent segment (P < 0.001, both). The RSA and RSC significantly decreased over time (P = 0.009 and P = 0.016, respectively). Conclusions: The developed rabbit ESI model verified that significantly more steroid was retained at the injected segment than at the adjacent segment and the residual steroid decreased over time. This model could be useful not only for comparing current steroid medications, but also for developing new, better steroid formulations.

• 한국지반공학회논문집
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• 제35권3호
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• pp.37-46
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• 2019

최근 다른 현장시험에 비하여 비교적 정확성이 높은 CPT 기반 액상화 평가법의 사용이 증가하고 있다. CPT 기반 액상화 평가는 다양한 흙의 특성을 예측하고 이를 액상화 평가에 활용할 수 있다. 특히, 세립분 함량은 CPT 기반 액상화 평가에서 중요한 입력 변수 중 하나로 이에 대한 정확한 예측식의 사용 및 예측 변동성을 정량적으로 파악하는 것은 매우 중요하다. 본 연구에서는 2017년 포항지진 시 액상화 현상이 관측된 지점에서 수행된 CPT 자료를 이용하여 기존 세립분 함량 예측식들의 오차를 분석하고 포항지역에 적합한 세립분 함량 예측식을 선정하였다. 또한, 지반의 고유한 변동성을 분석하고 CPT의 측정오차, 선정된 예측식에 대한 변환 불확실성을 고려한 세립분 함량의 예측 변동성을 정량적으로 평가하였다.

• International Journal of Computer Science & Network Security
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• 제21권3호
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• pp.134-140
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• 2021

The development of technology speeds up the process of obtaining information and its analysis to track the level of corruption in different countries and develop countermeasures. This study examines the role of information and analytical support of anti-corruption policy as a tool for government accountability and analysis, evaluation, combating corruption in Eastern Europe. The purpose of the article is to identify the components of the information-analytical system that help reduce the level of corruption. The research methodology is based on a qualitative content analysis of the functioning of information and analytical systems of Ukraine used by anti-corruption bodies. A quantitative analysis of the CPI score was conducted, according to Transparency International, to identify the effectiveness of anti-corruption policies in developing countries. The results show similar trends in countries developing on the effect of the use of information and analytical systems in the implementation of anti-corruption policies, strategies and measures. The strategy to combat corruption mainly involves increasing the independence and powers of anti-corruption bodies. Therefore, the development of information and analytical support is aimed at automating the processes of pre-trial investigations and criminal proceedings, information protection. As a tool for accountability, information and analytical systems may be ineffective due to the abuse of power by higher anti-corruption bodies due to political pressure from elite structures. Restrictions on political will are a major problem for the effectiveness of anti-corruption policies.

• 동의생리병리학회지
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• 제35권1호
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• pp.15-21
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• 2021

Donggwaja (Benincasae Semen), the seed of Benincasa hispida (Thunb.) Cogn., has been used in Korean traditional medicine to control the body heat and water retention caused by various diseases. Both the symptoms targeted by the herbal medicine in clinic and studies with disease mouse models support the potential anti-inflammatory effect of Donggwaja. However, it is less understood how Donggwaja exerts its possible anti-inflammatory effect. Here, we present evidence that Donggwaja suppresses macrophage inflammatory reactions via expressing tumor necrosis factor a-induced protein 3 (TNFAIP3 or A20) and suppressing NF-kB activity. The ethanol extract of Donggwaja (EED) showed no toxicity when added to RAW 264.7 cells less than 100mg/ml. When treating the cells for 16 h, EED significantly suppressed the nuclear localization of NF-kB, suggesting that EED suppresses NF-kB activity. Concordantly, a semi-quantitative RT-PCR analysis showed that EED decreased the expression of prototypic pro-inflammatory cytokines, such as tumor necrosis factor (TNF)-a, IL(interleukin)-6, and IL-1b. EED induced in RAW 264.7 cells the expression of A20, a ubiquitin modulator that suppresses inflammatory signaling cascades initiated from TLR4 and TNF and IL-1 receptors, while not affecting the induction of Nrf2, an anti-inflammatory factor that could suppress the effect of NF-kB. These results suggest that EED exerts its suppressive effect on inflammation, at least in part, by expressing anti-inflammatory factor A20 and suppressing pro-inflammatory factor NF-kB activity.

• 한국ITS학회 논문지
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• 제20권1호
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• pp.86-99
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• 2021

교통혼잡을 완화하기 위한 방안 중 하나로 도로 이용자에게 교통상황 예측정보를 제공함으로써 교통량을 분산 시켜 도로 이용 효율을 증대시키는 방법이 있다. 이를 위해서는 신뢰성이 보장되고 정량적인 실시간 교통 속도 예측이 필수적이다. 본 연구에서는 상황별 교통속도 분석을 기반으로 이력 속도 데이터와 이력 속도 외의 교통류에 상관관계가 있는 데이터를 LSTM 입력 데이터로 활용하였다. 정상 교통류 상황에 대응하여 속도를 예측하는 LSTM 모델과 유고상황에 대응하여 속도를 예측하는 CNN-LSTM 모델을 개발하여 유고발생 후 1시간까지 5분 단위로 교통속도 예측을 시도하였다. 모델의 검증은 테스트 데이터를 통하여 교통상황별 예측성능을 분석하였다. 그 결과 정상 교통류에서는 평균 7.43km/h, 유고상황에서는 7.66km/h의 오차율로 각각 예측되었다.

• 한국수자원학회논문집
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• 제53권12호
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• pp.1173-1181
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• 2020

최근 단기간의 국지성호우가 빈번하게 발생하면서 단순 1차적 피해를 넘어 경제적, 사회적 영향이 커지고 있다. 기상선진국에서는 단순 기상예보로서의 정보전달이 아닌 사회 경제적 영향을 분석하여 현실적이고 신뢰할 수 있는 영향예보를 실시하고 있다. 본 논문에서는 사람의 보행에 영향을 미칠 수 있는 영향한계강우량을 산정하기 위해서 Spatial Runoff Assessment Tool (S-RAT), FLO-2D 모델을 사용하여 침수정도를 도출하였고 Grid to Grid (G2G)개념의 한계강우량을 산정하였다. 또한, 과거 의학 분야에서 많이 사용하였지만 현재는 가뭄이나 홍수 등의 자연현상 및 머신러닝에 많이 사용하는 ROC 분석 기법을 통해 정량적인 정확도분석을 실시하였다. 분석 결과 실제 침수와 모의 침수가 비슷한 시간대의 결과가 나왔으며 ROC 곡선의 결과 0.7이상으로 Fair 단계의 적정성을 확보하였다.

• 한국IT서비스학회지
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• 제20권1호
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• pp.131-143
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• 2021

Commercial transactions, one of the pillars of the capitalist economy, are occurring countless times every day, especially small and medium-sized businesses. However, small and medium-sized enterprises are bound to be the legal underdogs in contracts for commercial transactions and do not receive legal support for contracts for fair and legitimate commercial transactions. When subcontracting contracts are concluded among small and medium-sized enterprises, 58.2% of them do not apply standard contracts and sign contracts that have not undergone legal review. In order to support small and medium-sized enterprises' fair and legitimate contracts, small and medium-sized enterprises can be protected from legal threats if they can reduce the risk of signing contracts by analyzing various risks in the contract and analyzing and informing them of toxic clauses and omitted contracts in advance. We propose a risk prediction model for the machine reading-based legal contract to minimize legal damage to small and medium-sized business owners in the legal blind spots. We have established our own set of legal questions and answers based on the legal data disclosed for the purpose of building a model specialized in legal contracts. Quantitative verification was carried out through indicators such as EM and F1 Score by applying pine tuning and hostile learning to pre-learned machine reading models. The highest F1 score was 87.93, with an EM value of 72.41.

• 한국해양공학회지
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• 제35권4호
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• pp.273-286
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• 2021

In recent years, as human casualties and property damage caused by hazardous waves have increased in the East Sea, precise wave prediction skills have become necessary. In this study, the Simulating WAves Nearshore (SWAN) third-generation numerical wave model was calibrated and optimized to enhance the accuracy of winter storm wave prediction in the East Sea. We used Source Term 6 (ST6) and physical observations from a large-scale experiment conducted in Australia and compared its results to Komen's formula, a default in SWAN. As input wind data, we used Korean Meteorological Agency's (KMA's) operational meteorological model called Regional Data Assimilation and Prediction System (RDAPS), the European Centre for Medium Range Weather Forecasts' newest 5th generation re-analysis data (ERA5), and Japanese Meteorological Agency's (JMA's) meso-scale forecasting data. We analyzed the accuracy of each model's results by comparing them to observation data. For quantitative analysis and assessment, the observed wave data for 6 locations from KMA and Korea Hydrographic and Oceanographic Agency (KHOA) were used, and statistical analysis was conducted to assess model accuracy. As a result, ST6 models had a smaller root mean square error and higher correlation coefficient than the default model in significant wave height prediction. However, for peak wave period simulation, the results were incoherent among each model and location. In simulations with different wind data, the simulation using ERA5 for input wind datashowed the most accurate results overall but underestimated the wave height in predicting high wave events compared to the simulation using RDAPS and JMA meso-scale model. In addition, it showed that the spatial resolution of wind plays a more significant role in predicting high wave events. Nevertheless, the numerical model optimized in this study highlighted some limitations in predicting high waves that rise rapidly in time caused by meteorological events. This suggests that further research is necessary to enhance the accuracy of wave prediction in various climate conditions, such as extreme weather.