• ETRI Journal
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• v.45 no.4
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• pp.724-724
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• 2023

• Explosives and Blasting
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• v.35 no.4
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• pp.1-9
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• 2017

This study undertakes an evaluation of blast effect through the analysis of the contribution rate and effect that different artificial joint number, artificial joint spacing and artificial joint angle have on blast velocity. Blast velocity according to the different state of the artificial joint was obtained using AUTODYN, a dynamic analysis program. The result of the numerical analysis was subjected to further normalization analysis. For the contribution rate of design factors was analyzed using the robust design method. The orthogonal array used in the analysis was $L_9(3^4)$ and each parameters were having 3 levels. The result of normalization analysis regarding the artificial joint angle was indicated a tendency in which blast velocity decreased. The result of analyzing blast velocity regarding artificial joint spacing and artificial joint angle was indicated a tendency in which blast velocity decreased as artificial joint spacing increased when the angle was perpendicular. In the case of blast velocity contribution rates they were ranked in the descending order of artificial joint angle, artificial joint number, artificial joint spacing.

• Progress in Superconductivity and Cryogenics
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• v.19 no.3
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• pp.27-32
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• 2017

The effects of artificial holes on the trapped magnetic fields and magnetic levitation forces of very large single-grain $Y_{1.5}Ba_2Cu_3O_{7-y}$ (Y1.5) bulk superconductors were studied. Artificial holes were made for Y1.5 powder compacts by die pressing using cylindrical dies with a diameter of 30 mm or 40 m, or rectangular dies with a side length of 50 mm. The single grain Y1.5 bulk superconductors (25 mm, 33 mm in diameter and 42 mm in side length) with artificial holes were fabricated using a top-seeded melt growth (TSMG) process for the die-pressed Y1.5 powder compacts. The magnetic levitation forces at 77 K of the 25 mm single grain Y1.5 samples with one (diameters of 4.2 mm) or six artificial holes (diameters of 2.5 mm) were 10-17% higher than that of the Y1.5 sample without artificial holes. The trapped magnetic fields at 77 K of the Y1.5 samples with artificial holes were also 9.6-18% higher than that of the Y1.5 sample without artificial holes. The 33 mm and 42 mm single grain Y1.5 samples with artificial holes (2.5 mm and 4.2 mm in diameter) also showed trapped magnetic fields 10-13% higher than that of the Y1.5 samples without artificial holes in spite of the reduced superconducting volume fraction due to the presence of artificial holes. The property enhancement in the large single grain Y1.5 bulk superconductors appears to be attributed to the formation of the pore-free regions near the artificial holes and the homogeneous oxygen distribution in the large Y123 grains.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.385-391
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• 2021

In this paper, a case of deep learning artificial neural network education was studied for artificial intelligence literacy education for preservice teachers and incumbent teachers. In addition, through the proposed educational case, we tried to explore the contents of artificial neural network principle education that elementary, middle and high school students can experience. To this end, first, an example of training on the principle of operation of an artificial neural network that recognizes two types of images is presented. And as an artificial neural network extension application education case, an artificial neural network education case for recognizing three types of images was presented. The number of output layers was changed according to the number of images to be recognized by the artificial neural network, and the cases implemented in a spreadsheet were divided and explained. In addition, in order to experience the operation results of the artificial neural network, we presented the educational contents to directly write the learning data necessary for the artificial neural network of the supervised learning method. In this paper, the implementation of the artificial neural network and the recognition test results are visually presented using a spreadsheet.

• Journal of Korean Society for Quality Management
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• v.46 no.3
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• pp.677-694
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• 2018

Purpose: The purpose of this study is to investigate various prior studies on artificial intelligence and to examine the concept and characteristics of various prior studies of existing service quality. And this paper is to study the concept and characteristics of artificial intelligence services and propose suitable quality measurement items. Methods: The research method of this paper is to examine previous research related to existing artificial intelligence and to analyze characteristics related to service quality. Results: This paper examines the concept and characteristics of artificial intelligence service in a new era by examining previous studies related to artificial intelligence and derives quality measurement items. Conclusion: In the future, it is necessary to verify the validity of the quality measurement items of artificial intelligence service. Therefore, it is necessary to elicit and verify the main quality measurement items through the investigation of the expert group.

• Asian Journal of Business Environment
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• v.8 no.4
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• pp.37-44
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• 2018

Purpose - The artificial intelligence industry plays an increasingly significant role in stimulating the development of United States of America's economy. On account of this background, this paper attempts to explore the impact of artificial intelligence industry on United States of America's macroeconomy. Research design, data, and methodology - This paper mainly focuses on the impact of artificial intelligence industry on GDP, employment, real income, import, export and foreign direct investment. Furthermore, the Phillips-Perron test and Canonical cointegrating regression will be employed to examine the impact of artificial intelligence industry on United States of America's macroeconomy with a sample form 2010-Q1 to 2017-Q4. Results - Via the empirical analysis, the results reveal that the artificial intelligence industry has a positive effect on United States of America's GDP, employment, real income, export and foreign direct investment. Conversely, the artificial intelligence industry has a negative effect on United States of America's import. Conclusions - In summary, the impact of artificial intelligence industry on United States of America's macroeconomy is positive and significant in statistics. Therefore, the government of United States of America should put more input into artificial intelligence industry.

• Korean Journal of Artificial Intelligence
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• v.6 no.2
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• pp.1-9
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• 2018

Recently, the rapid development of artificial intelligence industry has resulted in a great change in our modern society. Due to this background, this paper takes the United Kingdom as an example to explore the determinants of artificial intelligence industry in terms of United Kingdom's macroeconomics. The quarterly time series from the first quarter of 2010 to the fourth quarter of 2017 will be employed to conduct an empirical analysis under the vector error correction model. In this paper, the real GDP, the employment figure, the real income, the foreign direct investment, the government budget and the inflation will be regarded as independent variables. The input of artificial intelligence industry will be regarded as a dependent variable. These macroeconomic variables will be applied to perform an empirical analysis so as to explore how the macroeconomic variables affect the artificial intelligence industry. The findings show that the real GDP, the real income, the foreign direct investment and the government budget are the driving determinants to promote the development of artificial intelligence industry. Conversely, the employment figure and the inflation is the obstructive determinants to hamper the development of artificial intelligence industry.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.6
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• pp.478-487
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• 2002

This paper presents a hybrid method to compute the solutions of an optimization Problem. The present hybrid algorithm is the synthesis of an artificial life algorithm and the random tabu search method. The artificial life algorithm has the most important feature called emergence. The emergence is the result of dynamic interaction among the individuals consisting of the system and is not found in an individual. The conventional artificial life algorithm for optimization is a stochastic searching algorithm using the feature of artificial life. Emergent colonies appear at the optimum locations in an artificial ecology. And the locations are the optimum solutions. We combined the feature of random-tabu search method with the conventional algorithm. The feature of random-tabu search method is to divide any given region into sub-regions. The enhanced artificial life algorithm (EALA) not only converge faster than the conventional artificial life algorithm, but also gives a more accurate solution. In addition, this algorithm can find all global optimum solutions. The enhanced artificial life algorithm is applied to the optimum design of high-speed, short journal bearings and its usefulness is verified through an optimization problem.

• Communications of Mathematical Education
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• v.32 no.1
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• pp.23-36
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• 2018

Recently, we are working to utilize it in various fields with the expectation of the potential of artificial intelligence. There is also interest in applying to the field of education. In the field of education, machine learning and deep learning, which are used in artificial intelligence technology, are deeply interested in how to learn on their own. We are interested in how artificial intelligence and artificial intelligence technologies can be used in education and we have an interest in how artificial intelligence can be applied to mathematics education. The purpose of this study is to investigate the direction of mathematics education as the change of education paradigm and the development of artificial intelligence according to the development of information and communication technology. Furthermore, we examined how artificial intelligence can be applied to mathematics education.

• Journal of the Korean Institute of Landscape Architecture
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• v.29 no.6
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• pp.72-81
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• 2002

The purpose of this study is to determine the impact of the soil load for artificial ground on a building's structural expenses. Three types of soil - 100% soil, soil mixed with 50% perlite, and 100% artificial soil - were used for this study. A one story concrete steel building specific to each soil load was designed, and then, the cost of steel and concrete used for the design was estimated. As the result of this study, the structural expenses in the case of 5:5 mixed soil can be reduced about 17% compare with 100% soil. Using artificial soil, the structural expenses can be cut about 32% compare to 100% soil and about 12% less when 5:5 mixed soil is used. However, considering total expense which includes the structural expense and soil expense, the expense of 5:5 mixed soil have an increase 25% compared with 100% soil. In the artificial soil, the total expense is 45% more expensive than 100% soil and 17% higher when 5:5 mixed soil is used because of the high unit price of artificial soil. This study expected substantial savings in structural cost as the soil-load was lightened. But, savings were significantly reduced because the unit price of the artificial soil is much more expensive than the price of the natural one. Therefore, further research on methods of reducing the unit price of the artificial soil should be conducted in order to extend green space on to artificial ground.