• Human Ecology Research
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• v.53 no.1
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• pp.29-47
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• 2015

The purpose of this study is to conceptualize the definition of school readiness specific to the context of the Republic of Korea. The school readiness test can be used as basic data to enable early childhood educational institutes to determine the general readiness of preschoolers and provide support to fit individual characteristics. For this purpose, six stages of the school readiness development process were considered, that is, draft development, primary preliminary survey, primary expert verification, secondary expert verification, secondary preliminary survey, and main survey. In the main survey, tests were conducted using the school readiness final draft targeting 344 preschoolers living in Seoul and Gyeonggi-do. The item discrimination power analysis and factor analysis for the examination area and question area were also conducted. Consequently, a test tool was developed on the basic of the results obtained, consisting of 129 items in the five areas of knowledge, function, adaptation, tendency, and attitude. The knowledge area was divided into general, linguistic, and mathematical knowledge, and the function area into fine motor function, basic living ability, expressive function, and gross motor function. The adaptation area was classified into adaptation activity, separation anxiety, maladaptive behavior, and environment adaptation; the tendency area into learning tendency; others understanding, and individual tendency, and the attitude area into rule compliance and life habits.

• Corrosion Science and Technology
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• v.7 no.5
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• pp.259-264
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• 2008

A national consultative project entitled "corrosion cost survey in China and preventive strategies" was funded by the Chinese Academy of Engineering in 1998. Soon afterwards, an expert group was organized jointly by the Institute of Metal Research, CAS and Chinese Society of Corrosion and Protection. The report on corrosion cost survey in China was published in 2003. According to this report the overall annual corrosion cost in China estimated by the Uhlig Method and Hoar Method at 1997-2001 was found to be 200.7 billion Yuan RMB and 228.8 billion Yuan RMB respectively, which is equivalent to 2% of the gross national product of China. However the total cost of corrosion including the direct and indirect cost was estimated to be more than 500 billion Yuan RMB per year in China. Among them, corrosion cost of infrastructure ranked in first comparing with other sectors. Although corrosion costs in some sectors, such as electric power, petrochemical, oil pipeline and railway in China has reduced in the past years, significant losses are still being encountered in most sectors of industries and cost-effective methods have not always been implemented. Both successful and unsuccessful cases in corrosion control and corrosion management were collected. As the investment in capital construction continues increasing rapidly in China, the maintenance and life extension of the infrastructures will become a big issue. The preventive strategies have been suggested

• The KSFM Journal of Fluid Machinery
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• v.19 no.4
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• pp.54-62
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• 2016

This study presents an approach of tidal farming optimization using a numerical modelling method to simulate tidal energy extraction for 1MW scale tidal stream devices around Jangjuk-sudo, South Korea. The utility of the approach in this research is demonstrated by optimizing the tidal farm in an idealized scenario and a more realistic case with three scenarios of 28-turbine centered tidal array (named A, B and C layouts) inside the Jangjuk-sudo. In addition, the numerical method also provides a pre-processing calculation helps the researchers to quickly determine where the best resource site is located when considering the position of the tidal stream turbine farm. From the simulation results, it is clearly seen that the net energy (or wake energy yield which includes the impacts of wake effects on power generation) extracted from the layout A is virtually equal to the estimates of speed-up energy yield (or the gross energy which is the sum of energy yield of each turbine without wake effects), up to 30.3 GWh/year.

• Journal of the Economic Geographical Society of Korea
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• v.6 no.2
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• pp.293-306
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• 2003

This paper aims to clarify the change in industrial structure and industry itself, and makes suggestions for the industrial development direction at transitional periods in the Chungcheongbuk-do(province) region. Because profits of regional gross production in Chungcheongbuk-do region flow out of the region, basic industries must be brought up. For this phenomenon, main manufacturing must be developed for the industrial power of the next generation of high added values that combined with digital industry; the petrochemistry, semiconductor industry as major type of industry, and automobile industry as minor type of industry. Also for supporting industry, education service, health and welfare, research and development services that are knowledge-based service industries in Chungcheongbuk-do region, must be formated the network among corporations and constructed regional innovation system linked with educational institutions, precision chemistry industry and biology technology as major type of industry, and precision machinery and tools industry as minor type of industry.

• Nuclear Engineering and Technology
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• v.48 no.1
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• pp.236-245
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• 2016

In a reactor coolant system of a nuclear power plant (NPP), an overpressure protection system keeps pressure in the loop within 110% of design pressure. However if the system does not work properly, pressure in the loop could elevate hugely in a short time. It would be seriously disastrous if a weak point in the pressure boundary component bursts and releases radioactive material within the containment; and it may lead to a leak outside the containment. In this study, a gross deformation that leads to a burst of pressure boundary components was investigated. Major components in the primary pressure boundary that is structurally important were selected based on structural mechanics, then, they were used to study the burst pressure of components by finite element method (FEM) analysis and by number of closed forms of theoretical relations. The burst pressure was also used as a metric of design optimization. It revealed which component was the weakest and which component had the highest margin to bursting failure. This information is valuable in severe accident progression prediction. The burst pressures of APR-1400, AP1000 and VVER-1000 reactor coolant systems were evaluated and compared to give relative margins of safety.

• Journal of Aerospace System Engineering
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• v.15 no.4
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• pp.11-20
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• 2021

The estimation of hovering flight time of multicopters using the battery power propulsion system is important for the development and design of the aircraft and its operation. For a given operational weight, the maximum possible battery weight can be decided using both a conventional energy density method and a new Peukert law. In the present study, the hovering flight time is predicted using both methods. The specific data of multicopters in the published literatures were employed for the computation of the hovering flight time. The results were validated with the measured data. The effect of figure of merit of propeller, battery discharging process on the hovering flight time was evaluated, Finally, the effect of the battery cell and package connection types on the hovering time was investigated. It was found that the combination of serial battery cell connections and parallel package connection is the bast in the endurance maximization aspect. As the cell number increases in a package, the hovering flight time is increased. There exists the max. battery ratio for the given takeoff gross weight.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.2
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• pp.295-303
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• 2022

Information and communication technology (ICT) is one of the primary zones that stimulates economic development in today's globalized world. It promotes technological developments in worldwide communication and manufacturing systems, as well as economic growth and development. Many economic activities, such as international trade and foreign direct investment, rely heavily on contemporary information and communications technologies (FDI). The goal of this study is to look at the dynamic relationship between FDI, ICT, trade openness, and economic growth in the context of BRICS countries from 2000 to 2018, with Gross Domestic Product as the dependent variable and Telephone subscriptions, Mobile subscriptions, Broadband subscriptions, Internet subscribers, Secure internet servers, Trade, and Foreign direct investment as the independent variables.Two variables are used as proxies to manage the macroeconomic environment, while five variables are used as proxies for ICT infrastructures. The outcomes of this study are analyzed using Generalized Methods of Movements (GMM). According to this study, ICT has a positive impact on the economic growth of a few countries. Trade openness and foreign direct investment, on the other hand, have a negative impact on economic growth. As growing countries, the BRICS must participate in economic reform and liberalization measures. This report suggests policy proposals for improving ICT standards, focusing especially on economic growth, trade openness, and increasing foreign investment in the BRICS countries.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.17-28
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• 2023

Today Agriculture segment is a significant supporter of Indian economy as it represents 18% of India's Gross Domestic Product (GDP) and it gives work to half of the nation's work power. Farming segment are required to satisfy the expanding need of food because of increasing populace. Therefore, to cater the ever-increasing needs of people of nation yield prediction is done at prior. The farmers are also benefited from yield prediction as it will assist the farmers to predict the yield of crop prior to cultivating. There are various parameters that affect the yield of crop like rainfall, temperature, fertilizers, ph level and other atmospheric conditions. Thus, considering these factors the yield of crop is thus hard to predict and becomes a challenging task. Thus, motivated this work as in this work dataset of different states producing different crops in different seasons is prepared; which was further pre-processed and there after machine learning techniques Gradient Boosting Regressor, Random Forest Regressor, Decision Tree Regressor, Ridge Regression, Polynomial Regression, Linear Regression are applied and their results are compared using python programming.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.156-156
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• 2022

Explicitly spatially distributed and reliable data on industrial water demand is very much important for both policy makers and researchers in order to carry a region-specific analysis of water resources management. However, such type of data remains scarce particularly in underdeveloped and developing countries. Current research is limited in using different spatially available socio-economic, climate data and geographical data from different sources in accordance to predict industrial water demand at finer resolution. This study proposes a random forest regression (RFR) model to predict the industrial water demand at 0.50× 0.50 spatial resolution by combining various features extracted from multiple data sources. The dataset used here include National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) night-time light (NTL), Global Power Plant database, AQUASTAT country-wise industrial water use data, Elevation data, Gross Domestic Product (GDP), Road density, Crop land, Population, Precipitation, Temperature, and Aridity. Compared with traditional regression algorithms, RF shows the advantages of high prediction accuracy, not requiring assumptions of a prior probability distribution, and the capacity to analyses variable importance. The final RF model was fitted using the parameter settings of ntree = 300 and mtry = 2. As a result, determinate coefficients value of 0.547 is achieved. The variable importance of the independent variables e.g. night light data, elevation data, GDP and population data used in the training purpose of RF model plays the major role in predicting the industrial water demand.

• Journal of the Korea Convergence Society
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• v.8 no.1
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• pp.19-23
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• 2017

Energy is a vital resource for the economic growth and the social development for any country. As the industry becomes more sophisticated and the economy more grows, the electricity demand is increasing. So forecasting electricity demand is an important for electricity suppliers. Forecasting electricity demand makes it possible to distribute electricity demand. As the market for Negawatt market began to grow in Korea from 2014, the prediction of electricity consumption demand becomes more important. Moreover, power consumption forecasting provides a way for demand management to be directly or indirectly participated by consumers in the electricity market. We use Genetic Algorithms to predict the energy demand of the fishing industry in Jeju Island by using GDP, per capita gross national income, value add, and domestic electricity consumption from 1999 to 2011. Genetic Algorithm is useful for finding optimal solutions in various fields. In this paper, genetic algorithm finds optimal parameters. The objective is to find the optimal value of the coefficients used to predict the electricity demand and to minimize the error rate between the predicted value and the actual power consumption values.