• Journal of Welding and Joining
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• v.17 no.2
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• pp.44-52
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• 1999

This study deals with spot weld ability of dissimilar aluminum alloy sheets in order to take advantage of its lightweight and strength. The paper also shows the relationship between weld elements(i.e. current, welding time and tip force) and weld quality on the resistance spot weld part of the same and dissimilar Al alloy. The conclusions are: (1) Because of excessive tip force, deep indentation remained at the Al 5182 side which is lower stiffness at the dissimilar Al alloy. (2) Weld quality (i.e. tensile shear strength) of dissimilar Al alloy is superior to that of the same Al 6061 alloy. (3) As long cycles, fatigue life of spot weld specimen on dissimilar Al alloy sheets was better than that of the same Al alloy.

• Journal of Welding and Joining
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• v.25 no.4
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• pp.65-71
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• 2007

Laser weldability of the aluminized steel for the full penetration welding will be described in this paper. We focused on the effect of Al coating conditions on weld strength. For these objectives, aluminized steel sheets that have various thickness and coating weight were prepared for laser welding. And then, tensile-shear and hardness test were carried out. At the same time, Al contents in weld after laser welding were analyzed and their correlations with mechanical properties were investigated. Besides, as removing partially coating layer, weldability has been investigated according to the position of coating layer. As a result of this study, tensile-shear strength was decreased with increasing Al contents in weld, and Al of coating layer caused grain growth.

• Journal of the Korean Society for Heat Treatment
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• v.6 no.3
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• pp.159-165
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• 1993

Creep tests of the TiC particulate reinforced Al composite have been conducted in the temperature ranges from 200 to $500^{\circ}C$. The steady-state cree rate of the composite depended strongly on the temperature and ap' plied stress. The stress exponent for the steady state creep rate of the composites was approximately 17.5 and the activation anergy was calculated to be 390KJ/mol. The steady-state creep equation could be written as $\acute{\varepsilon}_{ss}$ $$(s^{-1})=1.5{\times}10^{-9}\;{\sigma}^{17.5}\exp(-390000/RT)$$. Fracture surface examination showed that the fracture mode of the particulate reinforced composite was ductile by plastic tearing of the aluminum matrix and TiC particle interfaces were offered as sites for crack.

• Journal of the Korea Society of Computer and Information
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• v.5 no.3
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• pp.132-141
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• 2000

Designing and implementing to support both technical and social interaction by group members, GDSS can effect positively on developing and sustaining knowledge-intensive organization. This study proposes usage types of GDSS as KMS. By understanding level of GDSS, knowledge transfer process, and group members' interaction modes, we suggest some additional characteristics of GDSS and possible technology to be able for ai)plying to GDSS.

• Journal of Engineering Education Research
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• v.24 no.6
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• pp.79-85
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• 2021

In a future society where cutting-edge science technology such as artificial intelligence becomes commonplace, the demand for talented people with basic knowledge of mathematics and science is expected to increase continuously, and the educational infrastructure suitable for the characteristics of future generations is still insufficient. In particular, in the case of students taking convergence courses including practical training, there was a problem in communication with the instructor. In this study, we looked at the current status of distance learning at domestic universities that came suddenly due to the global pandemic of COVID-19. In addition, a case study of the use of technology was conducted to facilitate the interaction between instructors and learners through case analysis of distance classes in convergence subjects. Therefore, this study aims to introduce the case of developing lecture contents for smooth convergence education in a non-face-to-face educational environment targeting the developed AI convergence courses and applying them to the education of enrolled students.

• Cross-Cultural Studies
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• v.26
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• pp.227-248
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• 2012

Orchid Dream Wonderful Biography(蘭花夢奇傳), whose author was Yimmeishanren(吟梅山人), is a Xia-Yi-Ai-Qing(俠義愛情) novel in the late Qing Dynasty. The work published in 1905 when Emperor Guangxu(光緖) governed China. The novel was reprinted for several times to its excellent art feature as well as its public praise. Orchid Dream Wonderful Biography narratives the life story of the heroin, Songbaozhu(松寶珠). Songbaozhu disguises herself as a man, takes the imperial examination, and takes part in the war. However, she is abused after marring Xuwenqing(許文卿), finally, she dies in misery. Songbaozhu's tragic fate show that although a woman may disguise as a man and makes great contributions in novel, it would never come true in reality. Songbaolin(松寶林) is also home to female hero. She has a younger brother and sister were strictly education. She is a female hero of the pitch. The writer creates her, had to satisfy a social reality male. Orchid Dream Wonderful Biography, this work has had a tragic or a reality. This work represents the limits of consciousness and the writers. Orchid Dream Wonderful Biography did not transcend male-oriented notions.

• Journal of Korea Multimedia Society
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• v.25 no.3
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• pp.468-475
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• 2022

Currently, fine dust forecast models are operated by dividing the country into 19 regions. Therefore, it is important to reduce the learning time and the number of models as well as accurate forecast performance to operate lots of forecast models. In this paper, we develop a categorical wide area model that outputs forecast results categorically and integrates the regions with similar regional characteristics. The proposed model improved the convergence rate by 223 times compared to the existing model, which outputs at a single concentration value, and reduced the number of forecast models by a third.

• Journal of Korea Multimedia Society
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• v.25 no.10
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• pp.1386-1394
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• 2022

As consumption of high-quality fruits increases and sales and packaging units become smaller, the demand for automatic fruit grading systems is increasing. Compared to other crops, the quality of fruit is determined by visual characteristics such as shape, color, and scratches, rather than just physical size and weight. Accordingly, this study presents a CNN model that can effectively extract and classify the visual features of fruits and a perceptron that classifies fruits using physical features, and proposes a stacking ensemble model that can effectively combine the classification results of these two neural networks. The experiments with AI Hub public data show that the stacking ensemble model is effective for grading fruits. However, the ensemble model does not always improve the performance of classifying all the fruit grading. So, it is necessary to adapt the model according to the kind of fruit.

• Journal of the Semiconductor & Display Technology
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• v.21 no.3
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• pp.92-97
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• 2022

Plastics are classified into 7 types such as PET (PETE), HDPE, PVC, LDPE, PP, PS, and Other for separation and recycling. Recently, large corporations advocating ESG management are replacing them with bioplastics. Incineration and landfill of disposal of plastic waste are responsible for air pollution and destruction of the ecosystem. Because it is not easy to accurately classify plastic materials with the naked eye, automated system-based screening studies using various sensor technologies and AI-based software technologies have been conducted. In this paper, NIR scanning devices considering the NIR wavelength characteristics that appear differently for each plastic material and a system that can identify the type of plastic by learning the NIR spectrum data collected through it. The accuracy of plastic material identification was evaluated through a decision tree-based SVM model for multiclass classification on NIR spectral datasets for 8 types of plastic samples including biodegradable plastic.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_2
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• pp.1083-1090
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• 2022

Since renal cell carcinoma(RCC) has various examination and treatment methods according to clinical stage and histopathological characteristics, it is required to determine accurate and efficient treatment methods in the clinical field. However, the process of collecting and processing RCC medical data is difficult and complex, so there is currently no AI-based clinical decision support system for RCC treatments worldwide. In this study, we propose a clinical decision support system that helps clinicians decide on a precision treatment to each patient. RCC standard big database is built by collecting structured and unstructured data from the standard common data model and electronic medical information system. Based on this, various machine learning classification algorithms are applied to support a better clinical decision making.