• Journal of Ocean Engineering and Technology
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• v.37 no.6
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• pp.282-282
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• 2023

• KIEAE Journal
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• v.10 no.1
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• pp.33-44
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• 2010

These days, the use of alternative energy is recognized as one of countermeasures to rising oil prices and climate-change agreements. Especially, it is regarded as a main element to realize 'Low-Carbon Green Growth', one of the key policies of MB government. However, though alternative energy, renewable energy, is a main policy issue of the present administration, there are many problems to solve: the lack of recognition of its energy, the low level of its technology, its expert's shortage, and its limited application fields. Therefore, to stimulate the use of alternative energy in Korea and to change the recognition of this energy, it is needed to utilize it to urban street furniture that many people visit and use. In particular, if alternative energy is first applied to street furniture that needs energy for its management, the effect of publicity and energy saving will be so great. In this study, for the basic research to introduce and promote various alternative energy sources such as solar power, wind power, small hydro power, and human power, we analyzed the present condition of development of Korean and foreign street furniture items. Furthermore, we evaluated the level of development of these street furniture products and the design types of them and from these evaluations suggested the design direction that can solve problems in development and improve the possibility of application of these energy sources to these street furniture items. Through these analyses, this study aims to enhance the image of future environment-friendly city and make new index for the application of alternative energy.

• Journal of Korean Society on Water Environment
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• v.38 no.5
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• pp.240-246
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• 2022

Water and energy are inextricably linked and referred to as 'Water-Energy Nexus'. Recently, this topic has been drawing a lot of attention from various studies due to the exacerbated water availability. Korea's water and energy consumption has been increasing consistently, which calls for better management. This paper aims to identify changes in electricity consumption in relation to water intake and purification processes. Using Log Mean Divisia Index (LMDI) Decomposition Analysis method, this study attributes the changes to major factors such as; Total population (population effect), household/population (structure effect), GDP/household (economic effect), and water-related energy use/GDP (unit effect). The population effect, structure effect, and economic effect contributed to an increase in water-related electricity consumption, while the unit effect contributed to a decrease. As of 2019, the economic effect increased the water supply sector's electricity consumption by 534 GWh, the population effect increased by 73 GWh, and the structure effect increased by 243 GWh. In contrast, the unit effect decreased the electricity consumption by -461 GWh. We would like to make the following suggestions based on the findings of this study; first, the unit effect must be improved by increasing the energy efficiency of water intake and purification plants and installing renewable energy power generation facilities. Second, the structure effect is expected to increase over time, and to mitigate it, water consumption must be reduced through water conservation policies and the improvement of water facilities. Finally, the findings of this study are expected to be used as foundational data for integrated water and energy management.

• Journal of Energy Engineering
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• v.25 no.1
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• pp.100-107
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• 2016

In this study confirmed the reduction effect of pollutant by applying Fi-EGR and FPI-EGR to hybrid combustion system realizing premixed flame and non-premxied flame at once. The results showed that NOx emission index decreased significantly in case of adopting EGR. Additionally, the hybrid combustion system with EGR resulted in a better performance compared to usual non-premixed combustion system such that it can reduce $NO_x$ emission at equivalent EGR ratios. Especially, in the case of 25% of FI-EGR ratio at hybrid combustion system that the ratio of non-premixed and premixed is 50 : 50, NOx emission index reduction rate was about 59% compared to $NO_x$ emission of non-premixed combustion system without EGR and in the case of 15% of FPI-EGR ratio at hybrid combustion system that the ratio of non-premixed and premixed is 70 : 30, $NO_x$ emission index reduction rate was about 48% compared to $NO_x$ emission of hybrid combustion system without EGR.

• Progress in Medical Physics
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• v.23 no.2
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• pp.99-105
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• 2012

We investigated the influence of photon energy, couch and collimator angle differences between arcs on dose distribution of RapidArc treatment planning for prostate cancer. RapidArc plans were created for 6 MV and 10 MV photons using 2 arcs coplanar and noncoplanar fields. The collimator angle differences between two arcs were $0^{\circ}$, $15^{\circ}$, $30^{\circ}$, $45^{\circ}$, $60^{\circ}$, $75^{\circ}$ and $90^{\circ}$. The plans were optimized using same dose constrains for target and OAR (organ at risk). To evaluate the dose distribution, plans were analyzed using CI (conformity index), HI (homogeneity index), QOC (quality of coverage), etc. Photon energy, couch and collimator angle differences between arcs had a little influence on the target and OAR. The difference of dosimetric indices was less than 3.6% in the target and OAR. However, there was significant increase in the region exposed to low dose. The increase of V15% in the femur was 6.4% (left) and 5.5% (right) for the 6 MV treatment plan and 23.4% (left), 24.1% (right) for the noncoplanar plan. The increase of V10% in the Far Region distant from target was 54.2 cc for the 6 MV photon energy, 343.4 cc for the noncoplanar and 457.8 cc for the no collimator rotation between arcs.

• Nutrition Research and Practice
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• v.12 no.3
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• pp.258-264
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• 2018

BACKGROUND/OBJECTIVES: Diet quality scores or indices, based on dietary guidelines, are used to summarize dietary intake into a single numeric variable. The aim of this study was to examine the association between the modified diet quality index for Koreans (DQI-K) and mortality among Health Examinees-Gem (HEXA-G) study participants. SUBJECTS/METHODS: The DQI-K was modified from the original diet quality index. A total of 134,547 participants (45,207 men and 89,340 women) from the HEXA-G study (2004 and 2013) were included. The DQI-K is based on eight components: 1) daily protein intake, 2) percent of energy from fat, 3) percent of energy from saturated fat, 4) daily cholesterol intake, 5) daily whole-grain intake, 6) daily fruit intake, 7) daily vegetable intake, and 8) daily sodium intake. The association between all-cause mortality and the DQI-K was examined using Cox proportional hazard regression models. Hazard ratios and confidence intervals were estimated after adjusting for age, gender, income, smoking status, alcohol drinking, body mass index, and total energy intake. RESULTS: The total DQI-K score was calculated by summing the scores of the eight components (range 0-9). In the multivariable adjusted models, with good diet quality (score 0-4) as a reference, poor diet quality (score 5-9) was associated with an increased risk of all-cause mortality (hazard ratios = 1.23, 95% confidence intervals = 1.06-1.43). Moreover, a one-unit increase in DQI-K score resulted in a 6% higher mortality risk. CONCLUSIONS: A poor diet quality DQI-K score was associated with an increased risk of mortality. The DQI-K in the present study may be used to assess the diet quality of Korean adults.

• Economic and Environmental Geology
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• v.55 no.6
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• pp.717-726
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• 2022

This study was conducted to assess the geochemical contamination degree of As, Cd, Cu, Pb, Sb, and Zn in the soil and water samples from an abandoned gold mine. Enrichment Factor (EF), Geoaccumulation Index (Igeo), and Pollution Load Index (PLI) were carried out to assess the geochemical contamination degree of the soil samples. Variations of sulfate and heavy metals concentration in water samples were determined to identify the geochemical distribution with respect to the distance from the mine tailing dam. Geochemical pollution indices indicated significant contaminated with As, Cd, Pb, and Zn in the soil samples that areas close to the mine tailing dam, while, Sb showed similar indices in all soil samples. These results indicated that the As, Cd, Pb, and Zn dispersion has occurred via anthropogenic sources, such as mining activities. In terms of water samples, anomalies in the concentrations of As, Cd, Zn, and SO₄^2- was determined at specific area, in addition, the concentrations of the elements gradually decreased with distance. This result implies the heavy metals distribution in water has carried out by the weathering of sulfide minerals in the mine tailing and soil. The study area has been conducted the remediation of contaminated soil in the past, however, the geochemical dispersion of heavy metals was supposed to be occurred from the potential contamination source. Therefore, continuous monitoring of the soil and water is necessary after the completion of remediation.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.1
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• pp.39-58
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• 2024

Tunnel Boring Machines (TBM) use multiple disc cutters to excavate tunnels through rock. These cutters wear out due to continuous contact and friction with the rock, leading to decreased cutting efficiency and reduced excavation performance. The rock's abrasivity significantly affects cutter wear, with highly abrasive rocks causing more wear and reducing the cutter's lifespan. The Cerchar Abrasivity Index (CAI) is a key indicator for assessing rock abrasivity, essential for predicting disc cutter life and performance. This study aims to develop a new method for effectively estimating CAI using rock strength, petrological characteristics, linear regression, and machine learning. A database including CAI, uniaxial compressive strength, Brazilian tensile strength, and equivalent quartz content was created, with additional derived variables. Variables for multiple linear regression were selected considering statistical significance and multicollinearity, while machine learning model inputs were chosen based on variable importance. Among the machine learning prediction models, the Gradient Boosting model showed the highest predictive performance. Finally, the predictive performance of the multiple linear regression analysis and the Gradient Boosting model derived in this study were compared with the CAI prediction models of previous studies to validate the results of this research.

• Geomechanics and Engineering
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• v.22 no.6
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• pp.489-496
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• 2020

This study proposes a new empirical model to effectively predict the excavation performance of a shield tunnel boring machine (TBM). The TBM performance is affected by the geological and geotechnical characteristics as well as the machine parameters of TBM. Field penetration index (FPI) is correlated with rock mass parameters to analyze the effective geotechnical parameters influencing the TBM performance. The result shows that RMR has a more dominant impact on the TBM performance than UCS and RQD. RMR also shows a significant relationship with the specific energy, which is defined as the energy required for excavating the unit volume of rock. Therefore, the specific energy can be used as an indicator of the mechanical efficiency of TBM. Based on these relationships with RMR, this study suggests an empirical performance prediction model to predict FPI, which can be derived from the correlation between the specific energy and RMR.

• Journal of Ecology and Environment
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• v.35 no.3
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• pp.157-166
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• 2012

Many models intending to explain the latitudinal gradient of increasing species diversity from the poles to the equator are presented, which are a formalisation of the species-energy hypothesis. The model predictions are consistent with patterns of increasing species number with increasing mean air or water temperatures for plants and animals. An increase in species richness is also correlated with net primary production or the Normalised Difference Vegetation Index. This implies that increased availability of resources favours increased diversity capacity. The explanatory variables included in the biodiversity prediction models represent measures of water, energy, water-energy, habitat, history/evolution and biological responses. Water variables tend to be the best predictors when the geographic scope of the data is restricted to tropical and subtropical areas, whereas water-energy variables dominate when colder areas are included. In major models, about 20-35% of species in the various global regions (European, Africa, etc.) will disappear from each grid cell by 2050 and >50% could be vulnerable or threatened by 2080. This study provides good explanations for predictive models and future changes in biodiversity depending on various scenarios.