• Journal of Industrial Convergence
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• v.20 no.10
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• pp.87-94
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• 2022

This paper seeks to raise inflection points of battery manufacturing bases in Korea in the V4 region through the reorganization of new industrial technologies in accordance with ESG. As a result, the global supply chain market is cut off. The Russian-Ukraine war and the U.S.-China hegemony are competing in the economic crisis caused by COVID-19. It is showing diversification of new suppliers in an environment where mineral, grain procurement, gas, and even wheat imports from China and Russia are not possible. As a protective glocal, this area is used as a buffer zone(Pro-Russia, Hungary). to an isolated zone(anti-Russia, Poland) by war. In this paper, economic growth is expected to slow further due to the EU tapering period and high inflation in world countries. Due to these changes, the conversion of new tech industry and the contraction of Germany's structure due to energy supply may lose the driving force for economic growth over the past 20 years. This is caused by market disconnection(chasm) in the nominal indicators in this area. On the other hand, Korea should actively develop into the V4 area as an energy generation export (nuclear and electric hydrogen generation) area as a bypass development supply area due to the imbalance in the supply chain of rare earth materials that combines AI. By linking this industry, the energy platform can be scaled up and reliable supply technology (next generation BT, recycling technology) in diversification can be formed in countries around the world. This paper proves that in order to overcome the market chasm caused by the industries connection, new energy development and platform size can be achieved and reliable supply technology (next-generation battery and recycling technology, Low-cost LFP) can be diversified in each country.

• The Journal of Engineering Geology
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• v.31 no.4
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• pp.701-718
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• 2021

Geological field surveys and a series of laboratory tests were conducted to obtain data related to landslides in Sancheok-myeon, Chungju-si, Chungcheongbuk-do, South Korea where many landslides occurred in the summer of 2020. The magnitudes of various factors' influence on landslide occurrence were evaluated using logistic regression analysis and an artificial neural network. Undisturbed specimens were sampled according to landslide occurrence, and dynamic cone penetration testing measured the depth of the soil layer during geological field surveys. Laboratory tests were performed following the standards of ASTM International. To solve the problem of multicollinearity, the variation inflation factor was calculated for all factors related to landslides, and then nine factors (shear strength, lithology, saturated water content, specific gravity, hydraulic conductivity, USCS, slope angle, and elevation) were determined as influential factors for consideration by machine learning techniques. Minimum-maximum normalization compared factors directly with each other. Logistic regression analysis identified soil depth, slope angle, saturated water content, and shear strength as having the greatest influence (in that order) on the occurrence of landslides. Artificial neural network analysis ranked factors by greatest influence in the order of slope angle, soil depth, saturated water content, and shear strength. Arithmetically averaging the effectiveness of both analyses found slope angle, soil depth, saturated water content, and shear strength as the top four factors. The sum of their effectiveness was ~70%.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.56 no.4
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• pp.411-418
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• 2023

Genome wide association studies (GWAS) identify genetic loci associated with quantitative traits in genomic selection. Although several studies have compared performance of various algorithms, no study compares them in olive flounder Paralichthys olivaceus. This study compared the GWAS results of four mixed linear model (MLM) algorithms and one Fixed and random model Circulating Probability Unification (FarmCPU) algorithm in olive flounder. Considering gender and genetic association matrices as fixed and random effects, the MLM had stable performance without inflation for λ_GC (genomic inflation factor) of -log₁₀P. The FarmCPU algorithm had some appropriate λ_GC of -log₁₀P, and an upward tail was identified in quantile-quantile plots. Therefore, the models were suitable for detecting genetic variants associated with olive flounder growth traits. Moreover, significant genotypes appeared several times at chromosome 22, around which quantitative trait loci are expected to exist. Finally, in both models, some of the most genetic variants were found in genes related to growth traits, confirming their reliability. These results will be helpful when applied to the genomic selection of olive flounder growth traits in the future.

• Economic Analysis
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• v.26 no.3
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• pp.71-133
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• 2020

The Bank of Korea began its operation on June 12, 1950, with the Bank of Korea Act established a month or so earlier. Thus was first introduced to Korea modern central banking in the real sense of the word. The Bloomfield Mission, consisting of A. Bloomfield and J. Jensen of the Federal Reserve Bank of New York, spent about six months drafting a bill, which finally became the Bank of Korea Act. Little has been known yet about the process leading to the creation of the Mission and the historical context surrounding it, except that F. Tamagna of the Federal Reserve Board made in his capacity of the ECA's representative the offer of technical assistance to the Korean government. This paper attempts to dig deeper into relevant historical records and literature to fill these gaps. As it happened, the confrontation between the US and the USSR was accelerating towards the end of 1940s. The paper's new findings include that the Bloomfield Mission was, together with the ECA Mission to Korea, a product of the then US foreign policy (Cold War policy) and that the former Mission's technical assistance was conceived and provided all along as part of the inflation stabilization program pursued by the latter Mission. The Bloomfield Mission was after all a historical necessity. Next, the paper examines the changes added to the bill during its journey to becoming the Bank of Korea Act enacted in May 1950, presenting a review of the Act. The paper further evaluates the Act in terms of legal persistence, finding that the revised Act currently in force still substantially resembles the Act enacted 70 years ago from now. Finally in order is a brief discussion on those factors which seem to have contributed much to such persistence and thus apparent excellence of the Act enacted.

• Journal of Navigation and Port Research
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• v.48 no.1
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• pp.62-77
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• 2024

In the maritime shipping industry, imbalance between supply and demand has persistently increased, leading to the utilization of blank sailings by major shipping companies worldwide as a key means of flexibly adjusting vessel capacity in response to shipping market conditions. Traditionally, blank sailings have been frequently implemented around the Chinese New Year period. However, due to unique circumstances such as the global pandemic starting in 2020 and trade tensions between the United States and China, shipping companies have recently conducted larger-scale blank sailings compared to the past. As blank sailings directly impact freight transport delays, they can have negative repercussions from perspectives of both businesses and consumers. Therefore, this study employed Poisson regression models and negative binomial regression models to analyze the influence of maritime freight rate determinants on shipping companies' decisions regarding blank sailings, aiming to proactively address potential consequences. Results of the analysis indicated that, in Poisson regression analysis for 2M, significant variables included global container shipping volume, container vessel capacity, container ship scrapping volume, container ship newbuilding index, and OECD inflation. In negative binomial regression analysis, ocean alliance showed significance with global container shipping volume and container ship order volume, the alliance with container ship capacity and interest rates, non-alliance with international oil prices, global supply chain pressure index, container ship capacity, OECD inflation, and total alliance with container ship capacity and interest rates.

• International Journal of Highway Engineering
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• v.16 no.2
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• pp.119-129
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• 2014

PURPOSES : The purpose of this study is to develop the U-turn accident model at 4-legged signalized intersections in urban areas. METHODS : In order to analyze the characteristics of the accidents which are associated with U-turn operation at 4-legged signalized intersections in urban areas and develop an U-turn accident model by regression analysis, the tests of overdispersion and zero-inflation are conducted about the dependent variables of number of accidents and EPDO (Equivalent Property Damage Only). RESULTS : As their results, the Poisson model fits best for number of accident and the ZIP (Zero Inflated Poisson) fits best for EPOD, the variables of conflict traffic, width of opposing road, traffic passing speed are adopted as independent variable for both models. The variables of number of bus berths and rate of U-turn signal time at which the U-turn is permitted are adopted as independent variable only for EPDO. CONCLUSIONS : These study results suggest that U-turn would be permitted at the intersection where the width of opposing road is wider than 11.9 meters, the passing vehicle speed is not high and U-turn operation is not hindered by the buses stopping at bus stops.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.123-129
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• 2020

This scholarly work is an effort to capture the effects of oil prices on the actual exchange rate between dollar and rupee. This is done with reference to the U.S. dollar as oil prices are marked in USD (U.S. Dollar) in the international market, and India is among the top five importers of oil. Using monthly data from January 2001 to May 2020. The study used the real GDP, money supply, short-term interest rate difference between two countries, and inflation apart from the crude oil prices per barrel as the factors that help define the exchange rate. The analysis, through cointegration and vector error correction method (VECM), suggests long and short-run causality amid prices of oil and the rate of exchange fluctuations. Oil prices are found to be negatively related to the exchange rate in the long term but positively related in the short term. The result of the Wald test also indicates the short-run causation from the short-term interest rate and the prices of crude oil towards the exchange rate. The present study shows that oil prices are evidence of the existence of short-term and long-term driving associations with short-term interest rates and exchange rates.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.109-114
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• 2020

The aim of this study is to develop basic artificial neural network models in forecasting the in-sample gross domestic product (GDP) of Malaysia. GDP is one of the main indicators in presenting the macro economic condition of a country as set by the world authority bodies such as the World Bank. Hence, this study uses an artificial neural network-based approach to make predictions concerning the economic growth of Malaysia. This method has been proposed due to its ability to overcome multicollinearity among variables, as well as the ability to cope with non-linear problems in Malaysia's growth data. The selected inputs and outputs are based on the previous literatures as well as the economic growth theory. Therefore, the selected inputs are exports, imports, private consumption, government expenditure, consumer price index (CPI), inflation rate, foreign direct investment (FDI) and money supply, which includes M1 and M2. Whilst, the output is real gross domestic product growth rate. The results of this study showed that the neural network method gives the smallest value of mean error which is 0.81 percent with a total difference of 0.70 percent. This implies that the neural network model is appropriate and is a relevant method in forecasting the economic growth of Malaysia.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.39-46
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• 2020

Playing an important role in developing the economy and overall developments of the country, commercial banks have to be aware of their crucial presence in order to perform well and contribute significantly. At the same time, as a place to receive deposits, banks are required to be in safe situations to avoid bankruptcy or deal with financial crises. This research seeks to identify the determinants of Capital Adequacy Ratio and Banks' performance as well as the relationship between these two dependent variables. The paper uses 128 observations of 16 Vietnamese commercial banks during the period from 2010 to 2017, with two simultaneous dependent variables CAR and ROE, and independent variables including Return on Assets, Tobin Q, Credit growth, GDP growth, Equity to Deposits, Loans to Deposits, Bank size, Cost to Income, Liquidity risk, Provision for Loan loss ratio, Non-performing loans and Inflation. The results reveal that Capital Adequacy Ratio and Banks' Performance have statistically significant relationship and Credit growth, GDP growth, Equity-to-Deposit ratio and Cost-to-Income ratio all have significant effects on two dependent variables. The findings of this study suggest that commercial banks should control the respective elements in order to maintain adequate level of capital and also create effective performance.

• Smart Structures and Systems
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• v.16 no.4
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• pp.743-758
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• 2015

This paper presents an advanced life cycle cost (LCC) analysis of a ground source heat pump (GSHP) system and suggests a smart operation mode with a thermal performance test (TPT) and an energy pile system constructed on the site of the Incheon International Airport (IIA). First, an economic analysis of the GSHP system was conducted for the second passenger terminal of the IIA considering actual influencing factors such as government support and the residual value of the equipment. The analysis results showed that the economic efficiency of the GSHP system could be increased owing to several influential factors. Second, a multiple regression analysis was conducted using different independent variables in order to analyze the influence indices with regard to the LCC results. Every independent index, in this case the initial construction cost, lifespan of the equipment, discount rate and the amount of price inflation can affect the LCC results. Third, a GSHP system using an energy pile was installed on the site of the construction laboratory institute of the IIA. TPTs of W-shape and spiral-coil-type GHEs were conducted in continuous and intermittent operation modes, respectively, prior to system operation of the energy pile. A cooling GSHP system in the energy pile was operated in both the continuous and intermittent modes, and the LCC was calculated. Furthermore, the smart operation mode and LCC were analyzed considering the application of a thermal storage tank.