• Korean Journal of Artificial Intelligence
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• v.5 no.1
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• pp.1-9
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• 2017

Recently, the Q-Learning algorithm, which is one kind of reinforcement learning, is mainly used to implement artificial intelligence system in combination with deep learning. Many research is going on to improve the performance of Q-Learning. Therefore, purpose of theory try to improve the performance of Q-Learning algorithm. This Theory apply Cross Entropy Error to the loss function of Q-Learning algorithm. Since the mean squared error used in Q-Learning is difficult to measure the exact error rate, the Cross Entropy Error, known to be highly accurate, is applied to the loss function. Experimental results show that the success rate of the Mean Squared Error used in the existing reinforcement learning was about 12% and the Cross Entropy Error used in the deep learning was about 36%. The success rate was shown.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.30 no.4
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• pp.104-130
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• 2017

Objectives : This study was designed to signpost the study of brain, intelligence and memory, while interpreting the concept of 'Chongmyeong(聰明)' neotrically and linking it to the clinic of Korean medicine. Methods : In this paper, the meaning of the word 'Chongmyeong(聰明)' is divided into two parts, intelligence and memory. We also explored the relationship between brain science and 'Chongmyeong(聰明)' based on complex system theory, cognitive science and embodied cognition. Results : Through the process of refining the concept of 'Chongmyeong(聰明)' neoterically, we proposed the new method to understand the concept of 'Chongmyeong(聰明)'. Conclusions : The concept of 'Chongmyeong(聰明)' should be interpreted not as a reductionistic viewpoint of brain science but as a viewpoint of brain science based on visual and auditory system and complex system. Human cognition is physically embodied in the environment, from the viewpoint of embodied cognition that it is constituted and formed in an interactive context with society and culture connected with the environment.

• Journal of Information Technology Services
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• v.20 no.1
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• pp.93-115
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• 2021

Various policy declarations and institutional experiments involving artificial intelligence are being made in most countries. Depending on how the artificial intelligence policy changes, the role of the government, the scope of the policy, and the policy means used may vary, which can lead to the success or failure of the policy. This study proposed a perspective on AI(Artificial Intelligence) in policy research, investigated the theory of path change, and derived the characteristics of path change in AI policy. Since AI policy is related to a wide range of policy areas and the policy making is at the start points, this study is based on the neo-institutional path theory about the types of institutional changes. As a result of this study, AI policy showed the characteristics of path creation, and in detail presented the conflict relationship between institutional design elements, the scalability of policy areas, policy stratification and policy mix, the top policy characteristics transcending the law, and the experiment for regulatory innovation. Since AI can also be used as a key tool for policy innovation in the future, research on the path and characteristics of AI policy will provide a new direction and approach to government policy or institutional innovation seeking digital transformation.

• Earthquakes and Structures
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• v.24 no.2
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• pp.127-140
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• 2023

The vibration of microtubule in human cells is the source of electrical field around it and inside cell structure. The induction of electrical field is a direct result of the existence of dipoles on the surface of the microtubules. Measuring the electrical fields could be performed using nano-scale sensors and the data could be transformed to other computers using internet of things (IoT) technology. Processing these data is feasible by artificial intelligence-based methods. However, the first step in analyzing the vibrational behavior is to study the mechanics of microtubules. In this regard, the vibrational behavior of the microtubules is investigated in the present study. A shell model is utilized to represent the microtubules' structure. The displacement field is assumed to obey first order shear deformation theory and classical theory of elasticity for anisotropic homogenous materials is utilized. The governing equations obtained by Hamilton's principle are further solved using analytical method engaging Navier's solution procedure. The results of the analytical solution are used to train, validate and test of the deep neural network. The results of the present study are validated by comparing to other results in the literature. The results indicate that several geometrical and material factors affect the vibrational behavior of microtubules.

• Journal of Gifted/Talented Education
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• v.5 no.2
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• pp.1-15
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• 1995

The latest researchs show that students have their own preconceptions about scientific phenomena or theory before they learn about it in school. The preconceptions exert a great influence on the teaching and learning science. The purpose of this study is to find out the effect of intelligence and attitude to science on elementary school students were sampled from 4th and 6th grade. Data were obtained by IQ test and the questionnaires on scientific conception and attitude toward science. The result was analyzed by t-test, Correlation and ANOVA in the statistical packages SPSS/PC+. The major findings of this study are as follows : 1. The mean score of scientific conception of elementary school students was 12.89. The mean score of attitude to science was 247.29. The mean score of intelligence was 109.93. 2. The correlation coefficient between scientific conception and intelligence (r=.5098)was relatively high(p<.001). The correlation coefficient between attitude to science and scientific conception(r=.2364) was low(p<.001). 3. Significant difference on science conception was found among grade levels(p<.001). Significant difference on science conception was not found between sex (p>.05). 4. The subjects were divided into 4 groups by intelligence and attitude toward science. These 4 groups show the significant difference (p<.01) in the scientific conception. The groups of high of high intelligence showed high scientific conception.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.497-507
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• 2021

The objective of the current research study is to examine those elements/factors that can reduce silence so that organizations can become more efficient, innovative, and adaptable by sharing knowledge and work-related problems. The purpose behind conducting this research was to explore the effects of emotional intelligence on silent behavior. The study also focuses on other individual negative aspects that can increase counterproductive behavior like silence and examines the effects of emotional intelligence on silence through moral disengagement. Data was collected from 400 employees using stratified sampling to ensure adequate representation of males and females. Data was collected from nurses and young doctors using the adopted measurement scale through a self-administered questionnaire. Since the sample included nursing staff and they usually are not well versed in English, the instrument was translated into Urdu. Data were analyzed using SEM to assess the direct and indirect effects of EI on employee silence. The result indicates that emotional intelligence has a positive impact on employee silence and moral disengagement. In contradiction to theory, the findings suggest that people with high emotional intelligence tend to get morally disengaged. As a result, they will remain silent and withhold information regarding work-related issues and problems.

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.261-266
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• 2018

This study aimed to provide an overview of artificial intelligence based music composition programs. The artificial intelligence-based composition program has shown remarkable growth as the development of deep neural network theory and the improvement of big data processing technology. Accordingly, artificial intelligence based composition programs for composing classical music and pop music have been proposed variously in academia and industry. But there are several limitations: devaluation in general populations, missing valuable materials, lack of relevant laws, technology-led industries exclusive to the arts, and so on. When effective measures are taken against these limitations, artificial intelligence based technology will play a significant role in fostering national competitiveness.

• The Mathematical Education
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• v.47 no.4
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• pp.405-419
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• 2008

The purpose of this study is to find oui the effects of teaching mathematical concepts by designing and applying teaching and learning programs that takes into consideration the students' strong intelligence, through the teaching and learning strategies based on the multiple intelligences theory. For this study, developmental and experimental research was conducted. In the developmental research part of the study, teaching and learning programs for teaching the concept of multiplication were designed and the activities based on the multiple intelligences were chosen. On the other hand, in the experimental research part, the data acquired from the application of nonequivalent control group pretest-posttest design in the actual classes was processed and analyzed. The results above indicate that the teaching and learning program based on the multiple intelligences theory improved the students' overall understanding of mathematical concepts by providing various types of activities. In addition, this program helped students to increase their confidence and generate a positive attitude towards learning math.

• Asia Marketing Journal
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• v.19 no.3
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• pp.75-98
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• 2017

Our study is trying to investigate the perceived training effectiveness by applying the theory of planned behavior (TPB) and Technological Acceptance Model (TAM) and intend to examine the effects of individual differences on perceived training effectiveness and performance of individuals. The main purpose is to evaluate the perceived training effectiveness, and role of individual differences in terms of learning. The results of this study supported all the hypothesis that participants with higher level of creative self-efficacy, intrinsic motivation, creativity and emotional intelligence (EI) will have greater inclinations to learn. Results showed that perceive training effectiveness is positively related to training transfer and training transfer increase the performance of individuals. Study results significantly agree with the theory of planned behavior (TPB) which was applied to measure the perceived training effectiveness and suggest trainee's perception of usefulness, ease and benefits enhance learning dimensions of participants that make any program effective. The study has highlighted a number of issues that influence the perceived training effectiveness.

• ETRI Journal
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• v.46 no.3
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• pp.367-378
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• 2024

We propose a number-theory-based quantized mathematical optimization scheme for various NP-hard and similar problems. Conventional global optimization schemes, such as simulated and quantum annealing, assume stochastic properties that require multiple attempts. Although our quantization-based optimization proposal also depends on stochastic features (i.e., the white-noise hypothesis), it provides a more reliable optimization performance. Our numerical analysis equates quantization-based optimization to quantum annealing, and its quantization property effectively provides global optimization by decreasing the measure of the level sets associated with the objective function. Consequently, the proposed combinatorial optimization method allows the removal of the acceptance probability used in conventional heuristic algorithms to provide a more effective optimization. Numerical experiments show that the proposed algorithm determines the global optimum in less operational time than conventional schemes.