• Journal of Integrative Natural Science
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• v.10 no.4
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• pp.209-215
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• 2017

CXC chemokine receptor 2 (CXCR2) is a prominent chemokine receptor on neutrophils. CXCR2 antagonist may reduce the neutrophil chemotaxis and alter the inflammatory response because the neutrophilic inflammation in the lung diseases is found to be largely regulated through CXCR2 receptor. Hence, in the present study, Topomer based Comparative Molecular Field Analysis (Topomer CoMFA) was performed on a series of CXCR2 antagonist named pyrimidine-5-carbonitrile-6-alkyl derivatives. The best Topomer COMFA model was obtained with significant cross-validated correlation coefficient ($q^2$ = 0.487) and non cross-validated correlation coefficients ($r^2$ = 0.980). The model was evaluated with six external test compounds and its $r^2{_{pred}}$ was found to be 0.616. The steric and electrostatic contribution map show that presence of bulkier and electropositive group around cyclopropyl ring may contribute more for improving the biological activities of these compounds. The generated Topomer CoMFA model could be helpful for future design of novel and structurally related CXCR2 antagonists.

• Advances in Computational Design
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• v.8 no.4
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• pp.295-307
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• 2023

This paper presents an optimization of the reinforced concrete ribbed slab in terms of minimum CO₂ emissions and an economic justification of the final optimal design. The design variables are six geometry variables including the slab thickness, the ribs spacing, the rib width at the lower and toper end, the depth of the rib and the bar diameter of the reinforcement, and the seventh variable defines the concrete strength. The objective function is considered to be the minimum amount of carbon dioxide gas (CO₂) emission and at the same time, the optimal design is economical. Seven significant design constraints of American Concrete Institute's Standard were considered. A robust metaheuristic optimization method called improved dolphin echolocation and ant colony optimization (IDEACO) has been used to obtain the best possible answer. At optimal design, the three most important sources of CO₂ emissions include concrete, steel reinforcement, and formwork that the contribution of them are 63.72, 32.17, and 4.11 percent respectively. Formwork, concrete, steel reinforcement, and CO₂ are the four most important sources of cost with contributions of 67.56, 19.49, 12.44, and 0.51 percent respectively. Results obtained by IDEACO show that cost and CO₂ emissions are closely related, so the presented method is a practical solution that was able to reduce the cost and CO₂ emissions simultaneously.

• 한국연소학회:학술대회논문집
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• 2013.06a
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• pp.37-40
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• 2013

Hydrogen-dimethy ether (DME) and hydrogen-diesel compression ignition engine combustion were investigated and compared each other in a single cylinder compression ignition engine. Hydrogen and DME were used as low carbon alternative fuels to reduce green house gases and pollutant. Hydrogen was injected at the intake manifold with an injection pressure of 0.5 MPa at fixed injection timing, $-210^{\circ}CA$ aTDC. DME and diesel were injected directly into the cylinder through the common-rail injection system at injection pressure of 30 MPa. DME and diesel inejction timing was varied to find the optimum CI combustion to reduce CO, HC and NOx emissions. When DME was injected early, CO and HC emissions were high while NOx emission was low. Fuel consumption, heat release rate, and exhaust emissions were measured to analyze each combustion characteristics of each ignition promoter. Fuel consumption was decreased when diesel was used as an ignition promoter. This is due to the lower volatility of diesel which created more stratified charge than DME.

• Korean Journal of Organic Agriculture
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• v.22 no.2
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• pp.255-268
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• 2014

We are now currently facing serious climate changes such as super typhoon, flood, intense heat, severe cold, super hurricane, drought, desertification, destruction of ecosystem, marine pollution, reduction of food production, destruction of tropical forests, exhaustion of water resources, climate refugees, etc. All of the above mainly derive from greenhouse gas exhaustion. Such harmful consequence might directly affect mankind's sustainable development. If we keep using resources that emits greenhouse gases, the global temperature will rise about $3.2^{\circ}C$ by year 2050. In case of $3^{\circ}C$ rise in temperature, it will result in abnormal climate which will bring about severe property damage. Moreover, 20~50% of the ecosystem will become extinct. As Korea's economy increasingly expands, so do our energy consumption rises. And because of the consequences that can be driven by increasing rate of resource use, not just Korea itself, but also the whole world should seriously concern about greenhouse gases. Although agricultural division only takes up about 3.2% of total greenhouse gas emission, the ministry of Agriculture, Food and Rural Affairs are taking voluntary actions to gradually reduce $CO_2$ and so does each and every related organizations. In order to reduce $CO_2$, introduction of new and renewable energy in farm house warming is crucial. In other words, implementing wood-pellet boiler and geothermal heat boiler can largly reduce $CO_2$ emission compared to diesel boiler. More importantly, not only wood-pellet and geothermal heat is pollution-free but they also have economic advantages some-what. In this thesis, the economic advantage and sustainablity will be introduced and proved through comparing practical analysis of surveyed farm house under structure employing wood-pellet boiler and geothermal heat boiler with Agriculture-Economic Statistic of 2012 who uses diesel boiler.

• Journal of the Korean Institute of Gas
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• v.16 no.6
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• pp.55-66
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• 2012

The practical way to minimize the greenhouse gas is to reduce the emission of carbon dioxide. For this reason, CCS(Carbon Capture and Storage) technology, which could reduce carbon dioxide emission, has risen as a realistic alternative in recent years. In addition, the researcher is recently working into ways of applying CCS technologies with deep saline aquifer. In this study, the evaluation model on the feasibility of $CO_2$ sequestration in the deep saline aquifer using ANN(Artificial Neural Network) was developed. In order to develop the efficiency-evaluation model, basic model was created in the deep saline aquifer and sensitivity analysis was performed for the aquifer characteristics by utilizing the commercial simulator of GEM. Based on the sensitivity analysis, the factors and ranges affecting $CO_2$ sequestration in the deep saline aquifer were chosen. The result from ANN training scenario were confirmed $CO_2$ sequestration by solubility trapping and residual trapping mechanism. The result from ANN model evaluation indicated there is the increase of correlation coefficient up to 0.99. It has been confirmed that the developed model can be utilized in feasibility of $CO_2$ sequestration at deep saline aquifer.

• Clean Technology
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• v.20 no.4
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• pp.439-448
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• 2014

The potential mitigation of greenhouse gas (GHG) is studied in the Pohang steel industrial complex (PHSIC). The total GHG emission in 2010 is estimated to be in the range from 4,174,000 to 4,574,000 $tCO_2-eq$ in PHSIC. To meet the target proposed by the government, it is needed to reduce 552,000 $tCO_2-eq$ at minium by 2020. To estimate the potential amount of GHG reduction, the technologies used in the voluntary carbon reduction projects are applied to 51 companies which are subject to GHG target management. From the viewpoint of technological availability and payback period, the fuel conversion and waste heat recovery have an advantage in the short term with a possibility to reduce 160,000 $tCO_2-eq$. In the mid term, the thermal technologies in steel and iron industry have the potential to cut 229,000 $tCO_2-eq$, while the electrical technologies have the potential of 125,000 $tCO_2-eq$ reduction. The gap between the target GHG mitigation and potential reduction using the short and mid term technologies is about 38,000 $tCO_2-eq$, which should be compensated by the fundamental process innovation and the implementation of the most cutting-edge technologies including renewable energy.

• Journal of Preventive Medicine and Public Health
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• v.55 no.2
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• pp.134-143
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• 2022

Objectives: Many governments have imposed-and are still imposing-mobility restrictions to contain the coronavirus disease 2019 (COVID-19) pandemic. However, there is no consensus on whether policy-induced reductions of human mobility effectively reduce the effective reproduction number (Rt) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Several studies based on country-restricted data reported conflicting trends in the change of the SARS-CoV-2 Rt following mobility restrictions. The objective of this study was to examine, at the global scale, the existence of regional specificities in the correlations between Rt and human mobility. Methods: We computed the Rt of SARS-CoV-2 using data on worldwide infection cases reported by the Johns Hopkins University, and analyzed the correlation between Rt and mobility indicators from the Google COVID-19 Community Mobility Reports in 125 countries, as well as states/regions within the United States, using the Pearson correlation test, linear modeling, and quadratic modeling. Results: The correlation analysis identified countries where Rt negatively correlated with residential mobility, as expected by policymakers, but also countries where Rt positively correlated with residential mobility and countries with more complex correlation patterns. The correlations between Rt and residential mobility were non-linear in many countries, indicating an optimal level above which increasing residential mobility is counterproductive. Conclusions: Our results indicate that, in order to effectively reduce viral circulation, mobility restriction measures must be tailored by region, considering local cultural determinants and social behaviors. We believe that our results have the potential to guide differential refinement of mobility restriction policies at a country/regional resolution.

• Journal of the Earthquake Engineering Society of Korea
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• v.25 no.2
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• pp.71-81
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• 2021

This paper presents a real-time, false-pick filter based on deep learning to reduce false alarms of an onsite Earthquake Early Warning (EEW) system. Most onsite EEW systems use P-wave to predict S-wave. Therefore, it is essential to properly distinguish P-waves from noises or other seismic phases to avoid false alarms. To reduce false-picks causing false alarms, this study made the EEWNet Part 1 'False-Pick Filter' model based on Convolutional Neural Network (CNN). Specifically, it modified the Pick_FP (Lomax et al.) to generate input data such as the amplitude, velocity, and displacement of three components from 2 seconds ahead and 2 seconds after the P-wave arrival following one-second time steps. This model extracts log-mel power spectrum features from this input data, then classifies P-waves and others using these features. The dataset consisted of 3,189,583 samples: 81,394 samples from event data (727 events in the Korean Peninsula, 103 teleseismic events, and 1,734 events in Taiwan) and 3,108,189 samples from continuous data (recorded by seismic stations in South Korea for 27 months from 2018 to 2020). This model was trained with 1,826,357 samples through balancing, then tested on continuous data samples of the year 2019, filtering more than 99% of strong false-picks that could trigger false alarms. This model was developed as a module for USGS Earthworm and is written in C language to operate with minimal computing resources.

• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.1
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• pp.1-8
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• 2023

In this study, to reduce CO₂ emission in the cement manufacturing process, we evaluated the limestone that is used as a raw material for cement, substituted with steel slag by the various substituted levels. Based on the chemical composition of each raw materials including limestone, and blast furnace slow cooling slag, converter slag, and KR slag as an alternative raw material, we simulated the optimal cement raw mixture by the substitution levels of limestone. Test results indicated that the steel slags contain a certain level of CaO that can be used as alternative decarbonated raw materials, and it has enough to partially reduce the amount of limestonem. And we estimated the maximum usable levels of each raw material. In particular, it was confirmed that by using a mixture of these raw materials rather than using them one by one, the effect of reducing limestone was increased and CO₂ emission from the cement manufacturing process could be reduced.

• Journal of the Korean Society for Marine Environment & Energy
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• v.6 no.3
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• pp.16-25
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• 2003

In this paper, the reduction of green house effect gas CO₂ emission and NOx gas emission by using the RORO ship coastal transport of import-export container cargo was investigated. At first, the domestic CO₂ gas emission and the transportation of import-export container cargo were Investigated. Next, the characteristic of a RORO ship and CO₂ emission standard and NOx emission standard were investigated. And also, the reduction of CO₂ emission and NOx emission by the shift of coastal transport from land transport for the transportation of import-export container cargo between Kyongin area and Pusan Port were calculated. Finally, the change of CO2 and NOx gas emission due to the change of the share of coastal transportation and the load efficiency of RORO ship are investigated. The research results show that the shift of RORO ship coastal transport from land transport was very effective to reduce the CO₂ emission but it was no good to reduce the NOx emission.