• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.565-570
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• 2013

The mirror neuron regions which are distributed in cortical area handled a functionality of intention recognition on the basis of imitative learning of an observed action which is acquired from visual-information of a goal-directed action. In this paper an automated intention recognition system is proposed by applying computational model of mirror neuron system to the human-robot interaction system. The computational model of mirror neuron system is designed by using dynamic neural networks which have model input which includes sequential feature vector set from the behaviors from the target object and actor and produce results as a form of motor data which can be used to perform the corresponding intentional action through the imitative learning and estimation procedures of the proposed computational model. The intention recognition framework is designed by a system which has a model input from KINECT sensor and has a model output by calculating the corresponding motor data within a virtual robot simulation environment on the basis of intention-related scenario with the limited experimental space and specified target object.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.6
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• pp.606-611
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• 2014

The understanding of another's behavior is a fundamental cognitive ability for primates including humans. Recent neuro-physiological studies suggested that there is a direct matching algorithm from visual observation onto an individual's own motor repertories for interpreting cognitive ability. The mirror neurons are known as core regions and are handled as a functionality of intent recognition on the basis of imitative learning of an observed action which is acquired from visual-information of a goal-directed action. In this paper, we addressed previous works used to model the function and mechanisms of mirror neurons and proposed a computational model of a mirror neuron system which can be used in human-robot interaction environments. The major focus of the computation model is the reproduction of an individual's motor repertory with different embodiments. The model's aim is the design of a continuous process which combines sensory evidence, prior task knowledge and a goal-directed matching of action observation and execution. We also propose a biologically inspired plausible equation model.

• Journal of Christian Education in Korea
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• v.61
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• pp.81-107
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• 2020

This study reviews Bandura's vicarious reinforcement in observational learning process and implies this concept into Christian education in terms of spiritual role modeling. The first part of this study answers three questions: "what is vicarious reinforcement?" "how does vicarious reinforcement take place in observational learning?" and "how does vicarious reinforcement affect observer's behavior change?" Bandura conceptualizes the learning process with observational learning and imitative or non-imitative performance. Based on this concept, Bandura define the roles of vicarious reinforcement in the four steps of observational learning process: attention, retention, motor reproduction, and motivational process. Also, the three effects of vicarious reinforcements are explained in the following categories: the observational learning effect, inhibitory or disinhibitory effects, and eliciting effect. Adapting the structure of observational learning theory in terms of the effect of vicarious reinforcement and the function of role models, the second part of this study examines the biblical concept of imitation of Christ and the modeling strategy of discipleship. Especially Paul's spiritual role model serves as positive vicarious reinforcement for the Christian believers to perform the desired behaviors. Also, Paul's condemnation serves as explicit negative vicarious reinforcement. Then, the last part of this study covers the implication of these findings from observational learning and empirical studies in terms of spiritual role modeling to Christian education.

• The Mathematical Education
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• v.40 no.2
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• pp.161-177
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• 2001

This study is to investigate what students want to learn and what mathematics teachers should teach in their classrooms. 1314 students and 527 mathematics teachers were randomly selected to administer the questionnaire. The result shows that their is a considerable mismatch between students'learning desires and teachers'teaching practices in classrooms. What students want to learn is creative knowledge; however, what they learn in the classroom is ‘imitative’ knowledge. This study suggests that the overall educational goal of mathematics education in Korea should emphasize (1) learning to communicate mathematically, (2) loaming to reason mathematically, (3) becoming confident in pupils'own ability, (4) learning to$.$value mathematics, and (5) becoming mathematical problem solvers.

• Proceedings of the Technology Innovation Conference
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• 1999.06a
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• pp.176-202
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• 1999

Korea has exerted her efforts to assimilate nuclear power technology, and reportedly localized 95 percent of nuclear power technology by 1995. This paper investigates the evolution of nuclear power program in Korea to exploit the development process of the nuclear power industry and key factors for the technological localization of nuclear power plant. In developing countries, an imitative catching-up process can be shown as a course for developing the absorptive capacity of foreign technology, which depends on prior knowledge base and the intensity of effort. The process of technological learning consists of five stages including preparation, implementation of foreign technology, acquisition of peripheral technology, acquisition of core technology, and improvement f foreign technology. Moreover, this paper discusses six essential factors that have influenced the successful achievement of technological localization of nuclear power plants in Korea. They include the role and strategies of the government, the leading role of utility firm, the development and cooperation of the related organizations, the development of human resources and their efforts, market conditions and the assistance of foreign donors, and social conditions. Finally, this paper discusses about implications offered by the Korean experience for other developing countries.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.135-140
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• 2012

The mirror neuron system in the cerebrum, which are handled by visual information-based imitative learning. When we observe the observer's range of mirror neuron system, we can assume intention of performance through progress of neural activation as specific range, in include of partially hidden range. It is goal of our paper that imitative learning is applied to 3D vision-based intelligent system. We have experiment as stereo camera-based restoration about acquired 3D image our previous research Using Optical flow, unscented Kalman filter. At this point, 3D input image is sequential continuous image as including of partially hidden range. We used Hidden Markov Model to perform the intention recognition about performance as result of restoration-based hidden range. The dynamic inference function about sequential input data have compatible properties such as hand gesture recognition include of hidden range. In this paper, for proposed intention recognition, we already had a simulation about object outline and feature extraction in the previous research, we generated temporal continuous feature vector about feature extraction and when we apply to Hidden Markov Model, make a result of simulation about hand gesture classification according to intention pattern. We got the result of hand gesture classification as value of posterior probability, and proved the accuracy outstandingness through the result.

• Korean Journal of Artificial Intelligence
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• v.11 no.2
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• pp.7-17
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• 2023

Artificial Intelligence (AI) technology has already penetrated deeply into our daily lives, and we live with the convenience of it anytime, anywhere, and sometimes even without us noticing it. However, because AI is imitative intelligence based on human Intelligence, it inevitably has both good and evil sides of humans, which is why ethical principles are essential. The starting point of this study is the AI principles for companies or organizations to develop products. Since the late 2010s, studies on ethics and principles of AI have been actively published. This study focused on AI principles declared by global companies currently developing various products through AI technology. So, we surveyed the AI principles of the Global 500 companies by market capitalization at a given specific time and collected the AI principles explicitly declared by 46 of them. AI analysis technology primarily analyzed this text data, especially LDA (Latent Dirichlet Allocation) topic modeling, which belongs to Machine Learning (ML) analysis technology. Then, we conducted a Delphi technique to reach a meaningful consensus by presenting the primary analysis results. We expect to provide meaningful guidelines in AI-related government policy establishment, corporate ethics declarations, and academic research, where debates on AI ethics and principles often occur recently based on the results of our study.

• The Journal of Small Business Innovation
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• v.19 no.2
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• pp.53-68
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• 2016

Motivation and activities for technological learning, entrepreneurship, innovation, and creativity are driving forces of economic development in Asian countries. In the early stages of technological development, technological learning and entrepreneurship are efficient ways in which to catch up with advanced countries because firms can accumulate skills and knowledge quickly at relatively low risk. In the later stages of technological development, however, innovation and creativity become more important. This study aims to identify a) the factors (learning capabilities) that influence technological learning performance and b) barriers to enhancing innovation capabilities for the creative economy and organizations. The major part of this study is related to learning capabilities in the post-catch-up era. Based on a literature review and observations from Korean experiences, this study proposes a technological learning model composed of various influencing factors on technological learning. Three hypotheses are derived, and data are collected from Korean machine tool manufacturers. Intense interviews with CEOs and R&D directors are conducted using structured questionnaires. Statistical analysis, such as correlation and ANOVA are then carried out. Furthermore, this study addresses how to enhance innovation capabilities to move forward. Innovation enablers and barriers are identified by case studies and policy analysis. The results of the empirical study identify several levels of firms' learning capabilities and activities such as a) stock of technology, b) potential of technical labor, c) explicit technological efforts, d) readiness to learn, e) top management support, f) a formal technological learning system, g) high learning motivation, h) appropriate technology choice, and i) specific goal setting. These learning capabilities determine firms' learning performance, especially in the early stages of development. Furthermore, it is found that the critical factors for successful technological learning vary along the stages of technology development. Throughout the statistical and policy analyses, this study confirms that technological learning can be understood as an intrinsic principle of the technology development process. Firms perform proactive and creative learning in the late stages, while reactive and imitative learning prevails in the early stages. In addition, this study identifies the driving forces or facilitating factors enhancing innovation performance in the post catch-up era. The results of the preliminary case studies and policy analysis show some facilitating factors such as a) the strategic intent of the CEO and corporate culture, b) leadership and change agents, c) design principles and routines, d) ecosystem and collaboration with partners, and e) intensive R&D investment.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.4 no.1
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• pp.27-38
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• 1993

Pervasive developmental disorder is one of the most severe clinical disorder in child psychiatry and is associated with deviancies in multiple areas of development. Medication does not cure pervasive developmental disorder and its effectiveness is generally nonspecific. But psychopharmacological treatment can be important for some children with pervasive developmental disorder and can make many young autistics more amenable to behavior modification and education. Haloperidol, the most widely studied antipsychotics, was statistically and clinically superior to placebo, and furthermore, was known to facilitate the positive functioning such as, discrimination learning and imitative communication, without side effects. However, administration of haloperidol is associated with drug related dyskinesia, and it warrants the introduction and use of the other novel drugs. Several biochemical studies suggest that subgroups of children with pervasive developmental disorder show hyperserotonemia and increased endogenous opioid level as compared with controls. Psychopharmacological trials were conducted according to these findings(ex : fenfluramine, naltrexone), with mixed results till now. These and another drugs that have been used in children with pervasive developmental disorder and their effectiveness are reviewed.