• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.439-451
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• 2020

This study focused on researching the factors affecting retail banking efficiency of Vietcombank branches in the Mekong-Delta region. By collecting data from financial statements from 15 branches of VCB in the Mekong-Delta Region between 2015 and 2018, the paper applies DEA estimation to measure the effectiveness of retail banking activities and uses the Tobit regression model to identify factors affecting retail banking efficiency. The results demonstrate that the retail banking efficiency of branches averaged 52.5% during the period. The rating result shows the branches in An Giang, Can Tho, Dong Thap, Kien Giang, Long An, Phu Quoc and Tra Noc rank at the top technical efficiency. In group of medium efficiency, there are branches in Soc Trang, Tien Giang and Vinh Long. In the category of the poor efficiency are the branches in Bac Lieu, Ben Tre, Ca Mau, Chau Doc and Tra Vinh. The results also show that bank scale-related factors, capital adequacy, credit quality, time specific and region impact significantly the retail banking efficiency. The research not, only contributes to enriching the empirical research method but also is significant for the management activities in business developing strategies, improving the operational efficiency of Vietcombank in the region.

• Nuclear Engineering and Technology
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• v.42 no.4
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• pp.434-441
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• 2010

The activation products of aluminum and argon are key radionuclides for operational and environmental radiological safety during the normal operation of open-tank-in-pool type research reactors using aluminum-clad fuels. Their activities measured in the primary coolant and pool surface water of HANARO have been consistent. We estimated their sources from the measured activities and then compared these values with their production rates obtained by a core calculation. For each aluminum activation product, an equivalent aluminum thickness (EAT) in which its production rate is identical to its release rate into the coolant is determined. For the argon activation calculation, the saturated argon concentration in the water at the temperature of the pool surface is assumed. The EATs are 5680, 266 and 1.2 nm, respectively, for Na-24, Mg-27 and Al-28, which are much larger than the flight lengths of the respective recoil nuclides. These values coincide with the water solubility levels and with the half-lives. The EAT for Na-24 is similar to the average oxide layer thickness (OLT) of fuel cladding as well; hence, the majority of them in the oxide layer may be released to the coolant. However, while the average OLT clearly increases with the fuel burn-up during an operation cycle, its effect on the pool-top radiation is not distinguishable. The source of Ar-41 is in good agreement with the calculated reaction rate of Ar-40 dissolved in the coolant.

• Journal of Integrative Natural Science
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• v.14 no.2
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• pp.41-49
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• 2021

The causes of climate change are natural and artificial. Natural causes include changes in temperature and sunspot activities caused by changes in solar radiation due to large-scale volcanic activities, while artificial causes include increased greenhouse gas concentrations and land use changes. Studies have shown that excessive carbon use among artificial causes has accelerated global warming. Climate change is rapidly under way because of this. Due to climate change, the frequency and cycle of infectious disease viruses are greater and faster than before. Currently, the world is suffering greatly from coronavirus infection-19 (COVID-19). Korea is no exception. The first confirmed case occurred on January 20, 2020, and the number of infected people has steadily increased due to several waves since then, and many confirmed cases are occurring in 2021. In this study, we conduct a study on climate change before and after COVID-19 using weather data from Korea to determine whether climate change affects infectious disease viruses through logistic regression analysis. Based on this, we want to classify before and after COVID-19 through a logistic regression model to see how much classification rate we have. In addition, we compare monthly classification rates to see if there are seasonal classification differences.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.467-479
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• 2022

Working memory (WM), which plays a vital role in daily activities, is a memory system that temporarily stores and processes information when people are engaged in complex cognitive activities. The influence of music on WM has been widely studied. In this work, we conducted a series of n-back memory experiments with different task difficulties and multiple trials on 14 subjects under the condition of no music and Alpha wave leading music. The analysis of behavioral data show that the change of music condition has significant effect on the accuracy and time of memory reaction (p<0.01), both of which are improved after the stimulation of Alpha wave music. Behavioral results also suggest that short-term training has no significant impact on working memory. In the further analysis of electrophysiology (EEG) data recorded in the experiment, auto-regressive (AR) model is employed to extract features, after which an average classification accuracy of 82.9% is achieved with support vector machine (SVM) classifier in distinguishing between before and after WM enhancement. The above findings indicate that Alpha wave leading music can improve WM, and the combination of AR model and SVM classifier is effective in detecting the brain activity changes resulting from music stimulation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.33-38
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• 2013

Smart phones that are equipped with various types of sensors can monitor human beings, and their social activities and environments. Smart phone sensing systems are inevitable to lose sensing data at a certain region. It is more severe effect on opportunistic sensing because this sensing scheme is designed to read values from sensors when the state of numberous users meets pre-defined conditions. In this paper, we suggested an estimation model of missing data considering features of smart phone sensing to solve lower quality of collected data. This proposed model does not only reflect a temporal and spatial correlation, but also give high priority to participants who provide high quality data to improve the accuracy of estimated values. The experimental results show that our scheme is more accurate than previous scheme.

• Journal of Korea Water Resources Association
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• v.30 no.6
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• pp.621-628
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• 1997

Excavation works on stream beds have been done for various reasons including aggregate collection, sediment dredging, bridge constructions, or laying pipes under the ground. These activities may cause significant loadings of SS (suspended solids) resulting in water pollution and other detrimental effects to the surrounding environment. This research investigates application potential of a fickian diffustion model, derived from two dimensional advection-diffusion equation through some simplifying assumptions, as a planning tool for the estimation of SS loadings from excavation works and evaluation fo pollution prevention measures in case that sophisticated numerical simulation models are not applicable due to various practical reasons. Through a case study of the Juncheon stream in the Donghae City on the Kangwondo Province, this study demonstrates applicability of the fickian diffustion model as a practical method for the preliminary estimation of Ss loadings from excavation works and evaluation of performance of fabrics made of synthetic fiber for the reduction of downstream SS concentration with deficient field data.

• Journal of the Korean Regional Science Association
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• v.35 no.4
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• pp.3-18
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• 2019

This study estimates the levels of the basic and nonbasic activities in five rural centers in Cheongwon County by using the direct survey method and indirect non-survey methods. The economic base multipliers obtained through direct survey method and indirect non-survey methods are compared to find out the advantages and disadvantages of the estimation methods. There are some limitations in applying non-survey methods for economic base estimation. It is found that, among three non-survey methods, multipliers obtained through minimum requirements method are better than other two methods in terms of the theoretical assumption. However, if we use direct survey data and in-commuter/out-commuter data, we can obtain more accurate multiplier estimates.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.1466-1483
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• 2008

This paper discusses the development of an up-to-date computerized CPT (Cone Penetration Test) based soil engineering classification system to provide geotechnical engineers with a handy tool for their daily design activities. Five CPT soil engineering classification systems are incorporated in this effort. They include the probabilistic region estimation and fuzzy classification methods, both developed by Zhang and Tumay, the Schmertmann, the Douglas and Olsen, and the Robertson et al. methods. In the probabilistic region estimation method, a conformal transformation is used to determine the soil classification index, U, from CPT cone tip resistance and friction ratio. A statistical correlation is established between U and the compositional soil type given by the Unified Soil Classification System (USCS). The soil classification index, U, provides a soil profile over depth with the probability of belonging to different soil types, which more realistically and continuously reflects the in-situ soil characterization, which includes the spatial variation of soil types. The CPT fuzzy classification on the other hand emphasizes the certainty of soil behavior. The advantage of combining these two classification methods is realized through implementing them into visual basic software with three other CPT soil classification methods for friendly use by geotechnical engineers. Three sites in Louisiana were selected for this study. For each site, CPT tests and the corresponding soil boring results were correlated. The soil classification results obtained using the probabilistic region estimation and fuzzy classification methods are cross-correlated with conventional soil classification from borings logs and three other established CPT soil classification methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.11C
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• pp.1077-1084
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• 2006

This paper proposed a fast algorithm to reduce the amount of calculation for inter prediction which takes a great deal of the operational time in H.264/AVC. This algorithm decides a search range according to the direction of predicted motion vector, and then performs an adaptive spiral search for the candidates with JM(Joint Model) FME(Fast Motion Estimation) which employs the rate-distortion optimization(RDO) method. Simultaneously, it decides a threshold cost value for each of the variable block sizes and performs the motion estimation for the variable search ranges with the threshold. These activities reduce the great amount of the complexity in inter prediction encoding. Experimental results by applying the proposed method .to various video sequences showed that the process time was decreased up to 80% comparing to the previous prediction methods. The degradation of video quality was only from 0.05dB to 0.19dB and the compression ratio decreased as small as 0.58% in average. Therefore, we are sure that the proposed method is an efficient method for the fast inter prediction.

• Journal of Environmental Science International
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• v.29 no.7
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• pp.729-737
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• 2020

This study estimates the greenhouse gas (GHG) emissions reduction resulting from photovoltaic and wind power technologies using a bottom-up approach for an indirect emission source (scope 2) in South Korea. To estimate GHG reductions from photovoltaic and wind power activities under standard operating conditions, methodologies are derived from the 2006 IPCC guidelines for national GHG inventories and the guidelines for local government greenhouse inventories of Korea published in 2016. Indirect emission factors for electricity are obtained from the 2011 Korea Power Exchange. The total annual GHG reduction from photovoltaic power (23,000 tons CO_2eq) and wind power (30,000 tons CO_2eq) was estimated to be 53,000 tons CO_2eq. The estimation of individual GHGs showed that the largest component is carbon dioxide, accounting for up to 99% of the total GHG. The results of estimation from photovoltaic and wind power were 63.60% and 80.22% of installed capacity, respectively. The annual average GHG reductions from photovoltaic and wind power per year per unit installed capacity (MW) were estimated as 549 tons CO_2eq/yr·MW and 647 tons CO_2eq/yr·MW, respectively. Finally, the results showed that the level of GHG reduction per year per installed capacity of photovoltaic and wind power is 62% and 42% compared to the CDM project, respectively.