• Journal of The Korean Association of Information Education
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• v.23 no.6
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• pp.639-653
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• 2019

The purpose of this study is to design an instructional framework and cognitive learning environment for AI education based on computational thinking in order to ground the theoretical rationale for AI education. Based on the literature review, the learning model is proposed to select the algorithms and problem-solving models through the abstraction process at the stage of data collection and discovery. Meanwhile, the instructional model of AI education through computational thinking is suggested to enhance the problem-solving ability using the AI by performing the processes of problem-solving and prediction based on the stages of automating and evaluating the selected algorithms. By analyzing the research related to the cognitive learning environment for AI education, the instructional framework was composed mainly of abstraction which is the core thinking process of computational thinking through the transition from the stage of the agency to modeling. The instructional framework of AI education and the process of constructing the cognitive learning environment presented in this study are characterized in that they are based on computational thinking, and those are expected to be the basis of further research for the instructional design of AI education.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.405-413
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• 2021

The purpose of this study was to investigate empathic ability, Nunchi, learning flow and clinical competency, and to identify the influencing factors on clinical competency of nursing students. Method: There were 179 nursing students as participants in K city, who were surveyed between May 10 and May 14, 2021, using a self-report questionnaire. Data were analyzed by frequencies, t-test, ANOVA, Pearson's correlation, multiple regression using SPSS Win 21.0. Result: There was a positive correlation between empathic ability and Nunchi(r=.148, p=.048) and between learning flow and clinical competency(r=.605, p<.001). In the multiple regression, Academic achievement(𝛽=.129, p=.049), Age(𝛽=-.116, p=.014) and satisfaction of clinical practice(𝛽=-.242, p<.001) were associated with clinical competency. These factors accounted for 38.4% of the total variance in clinical competency. Therefore, to improve clinical competency of online nursing practice of nursing college students, it is necessary to develop a specific strategy to improve academic achievement and to develop various activities and programs to immerse students in satisfaction of online practice.

• Journal of Korean Tunnelling and Underground Space Association
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• v.18 no.2
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• pp.195-211
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• 2016

This paper concerns a study of a knowledge-based NATM tunnel lining design for subsea tunnels. Concept for tunnel automation designing system, the development of Artificial Neural Network based technology of the tunnel design system, the learning process and verification of the technology forecasting member forces were described. The design system is the series of process which can predict segmental lining member forces by ANN(artificial neural network system), analyze suitable section for the designated ground, construction and tunnel conditions using a FEM(finite element analysis). The lining member forces are predicted based on the ANN quickly and it helps designers determine its segmental lining dimension easily.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.175-192
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• 2022

Artificial intelligence-based natural language processing technology is playing an important role in helping users write English-language documents. For academic documents in particular, the English proofreading services should reflect the academic characteristics using formal style and technical terms. But the services usually does not because they are based on general English sentences. In addition, since existing studies are mainly for improving the grammatical completeness, there is a limit of fluency improvement. This study proposes an automatic academic English editing methodology to deliver the clear meaning of sentences based on the use of technical terms. The proposed methodology consists of two phases: misspell correction and fluency improvement. In the first phase, appropriate corrective words are provided according to the input typo and contexts. In the second phase, the fluency of the sentence is improved based on the automatic post-editing model of the bidirectional recurrent neural network that can learn from the pair of the original sentence and the edited sentence. Experiments were performed with actual English editing data, and the superiority of the proposed methodology was verified.

• The Journal of the Korea Contents Association
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• v.13 no.6
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• pp.212-226
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• 2013

In this paper, I tried to analyze objectively the structural relation among market directivity, study directivity, and achievement of organization which are intended to equip competitive power of social welfare organization on the social service market centrally formed by the voucher business. Data collection objectives is consist of 7 metropolitan cities social welfare organizations, performing voucher businesses of the Ministry of Health and Welfare, and data is secured from 203 institutions. Some basic technological statistics and regression analysis employing structural equation was used for analysing data. Analyzed result, the structural relation among market directivity and study directivity and organizational performance is appeared meaningfully according to the fact that goodness of fit coefficients is TLI = .86, CFI = .89, RMSEA = .02. With respect to achievement of organization, market directivity and study directivity are all confirmed as positively influenced. The results of analysis about whether market directivity and study directivity for achievement of organization is direct effect or indirect effect shows that market directivity and study directivity are all influenced both directly to organizational performance, and as parameter. By the results of this research, social welfare organizations performing voucher business are to have practical implication requiring organization learning needed collecting and sharing the relevant information and organizational response toward voucher social service market.

• Journal of Oriental Neuropsychiatry
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• v.20 no.1
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• pp.75-87
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• 2009

목적 : 이 연구는 알쯔하이머 병에 대한 육미지황가미방의 효과를 조사하였다. 육미지황가미방은 산약, 산수유, 복령, 목단피, 구기자, 택사, 숙지황을 포함한 여러 가지 한약재의 전탕액으로 치매의 한약 치료제로 널리 사용되어 왔다. 방법 : 이 약물의 신경보호 작용을 조사하기 위해, 수중미로를 사용하여 학습과 기억에 대한 육미지황가미방의 효과를 평가 했고, 트리메틸틴은 강력한 유독물질로 선택적으로 중추신경계와 면역계의 세포를 파괴시킨다. 트리메틸틴(6.0 mg/kg, i.p.)주입 후, 쥐에게 육미지황가미방(400mg/kg, p.o.)를 2주 동안 날마다 복용시켰으며, 수중미로를 수행시켰다. 결과 : 육미지황가미방을 트리메틸틴에 노출시킨 쥐에 투약했으며, 그들은 수중미로에서 학습과 기억의 향상을 보였고, 이는 육미지황가미방이 어떠한 환경에서는 트리메틸틴으로 유발된 신경퇴화 후 중추신경계의 결손을 감소시킬 수 있음을 보여준다. 결론 : 이러한 결론은 육미지황가미방이 인지능력을 증가시키고, 트리메틸틴으로 유발된 신경퇴화에서 콜린 아세틸전환효소의 정도를 변화시킬 수 있음을 보여준다.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.13 no.1
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• pp.85-92
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• 2002

Objectives：This study was conducted to compare the memory function among the attention deficit/hyperactivity disorder(ADHD), the learning disorder(LD) and the comorbidity disorder(ADHD+LD) groups. Methods：Thirty-four children(11 ADHD, 5 LD, 9 ADHD+LD, and 8 Psychiatric control) were individually assessed using the KEDI-WISC and Memoty Assessment Scale(MAS), and then the results of those test were analyzed. Results：In memory test, all of three group showed lower performances than control group. The comorbidity, the LD and the ADHD group showed lower scores in almost subtests of MAS respectively. The good performance in memory test was significantly correlated with the types of memory strategy and error response children used during testing. Discussion：The clinical utility of the memory test like MAS was discussed in terms of differential diagnosis for ADHD, LD and ADHD+LD children.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.299-306
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• 2022

In recent, sensors embedded in robots, equipment, and circuits have become common, and research for diagnosing device failures by learning measured sensor data is being actively conducted. This failure diagnosis study is divided into a classification model for predicting failure situations or types and a regression model for numerically predicting failure conditions. In the case of a classification model, it simply checks the presence or absence of a failure or defect (Class), whereas a regression model has a higher learning difficulty because it has to predict one value among countless numbers. So, the reason that regression modeling is more difficult is that there are many irregular situations in which it is difficult to determine one output from a similar input when predicting by matching input and output. Therefore, in this paper, we focus on input and output data with periodicity, analyze the input/output relationship, and secure regularity between input and output data by performing sliding window-based input data patterning. In order to apply the proposed method, in this study, current and temperature data with periodicity were collected from MMC(Modular Multilevel Converter) circuit system and learning was carried out using ANN. As a result of the experiment, it was confirmed that when a window of 2% or more of one cycle was applied, performance of 97% or more of fit could be secured.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.3
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• pp.144-154
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• 2003

In this paper we present Logical Evolution method which is a new teaming algorithm for the concepts expressed as binary logic function. We try to solve some problems of Inductive Learning algorithms through Logical Evolution. First, to be less affected from limited prior knowledge, it generates features using the gained informations during learning process and learns the concepts with these features. Second, the teaming is done using not the whole example set but the individual example, so even if new problem or new input-output variables are given, it can use the previously generated features. In some cases these old features can make the teaming process more efficient. Logical Evolution method consists of 5 operations which are selected and performed by the logical evaluation procedure for feature generation and learning process. To evaluate the performance of the present algorithm, we make experiments on MONK data set and a newly defined problem.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.11
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• pp.3390-3398
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• 2009

The knowledge management starts from the enhancement of learning capability in the members of the organization. The strategic change into the learning organization should be aligned with the change of organizational strategy, structure and processes. The study employed action learning methodology to transform the traditional organization into the learning one. The learning organization project has been successful thanks to the members' zeal and consensus to change the processes. However, not every learning team has been so successful. Some cases complained time consuming where others expect to be helpful for their incentives. The researchers concluded that the most important point for success of the learning organization project should be the support of top management.