• Archives of design research
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• v.18 no.2 s.60
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• pp.79-90
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• 2005

The aim of this study was to investigate how the psychological factors of human interrelation or human socialization are associated with the visual design based on sociological and psychological theories. To accomplish this goal, human socialization was examined on the basis of physiology, philosophy, and psychology. Then a case study was employed to assess how they function in the area of visual design. In literature, the sources of psychological factors of human socialization were categorized into 11 items including the sexual hedonic pursuit. These items were used for the evaluation of 40 printed media advertisements, all of which were the winners of the Korea Advertising Awards from 1994 to 2003. As a result, it was revealed that most advertisements responded to the items of adaptive value and cultural imprinting as biological bases. Also, it was discovered that the existential foundation of advertising has been based on mutual distrust and the payoff matrix as a mind of social unrest. In conclusions, it was illustrated that future advertising will remain based on adaptive value, cultural imprinting, social learning, and imitation learning, as long as advertising continue to hold its reason for existence.

• The Journal of Korea Robotics Society
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• v.8 no.1
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• pp.20-28
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• 2013

Large workspace and strong grasping force are required when a robot manipulates big and/or heavy objects. In that situation, bimanual manipulation is more useful than unimanual manipulation. However, the control of both hands to manipulate an object requires a more complex model compared to unimanual manipulation. Learning by human demonstration is a useful technique for a robot to learn a model. In this paper, we propose an imitation learning method of bimanual object manipulation by human demonstrations. For robust imitation of bimanual object manipulation, movement trajectories of two hands are encoded as a movement trajectory of the object and a force trajectory to grasp the object. The movement trajectory of the object is modeled by using the framework of dynamic movement primitives, which represent demonstrated movements with a set of goal-directed dynamic equations. The force trajectory to grasp an object is also modeled as a dynamic equation with an adjustable force term. These equations have an adjustable force term, where locally weighted regression and multiple linear regression methods are employed, to imitate complex non-linear movements of human demonstrations. In order to show the effectiveness our proposed method, a movement skill of pick-and-place in simulation environment is shown.

• 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.

• The Magazine of the IEIE
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• v.17 no.3
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• pp.28-36
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• 1990

제6세대 컴퓨터로 불리는 신경컴퓨터는 학습과 병렬처리에 의해 인간의 지능을 모방한다. 따라서 지능과 빠른 계산을 요하는 여러 분야에 응용되고 있으며 실제 로봇의 제어나 sensor에 의거한 제어에 응용하여 좋은 결과를 내고 있다. 신경회로의 로봇나 공정제어(process control)응용은 학술적인 측면에서는 복잡한 비선형 시스템의 지능제어(intelligent control)연구이며 산업적 측면에서 보면 산업 자동화라는 막대한 시장을 뒤로 하고 있어 우리나라도 활발한 연구를 절실히 필요로 하고 있다. 본 해설에서는 신경회로를 간단히 소개한 후 로봇 제어 응용을 다루기로 한다. 신경회로의 응용분야중 보고된 결과가 비교적 적은 제어분야를 소개함으로써 독자들에게 연구 자료들을 제공하고 또한 흩어져 있는 신경회로의 제어응용 논문들을 분류 통일함으로써 이 분야를 조감할 수 있게 한다. 또한 로봇을 하나의 복잡하고 비선형적 plant로 보았을 때 로봇의 신경제어는 곧 산업공정의 신경제어에도 그대로 응용되리라 믿는다. 신경제어는 plant의 모델없이도 학습에 의하여 고속 정확한 제어가 가능하고 또 plant 특성변화에 잘 적응하며 병렬성으로 인하여 실시간 제어도 가능하다는 점에서 무한한 잠재력이 있으나 전세계적인 연구는 아직도 크게 미흡한 편이다. 더욱 많은 연구가 절실히 필요하다고 본다.

• Journal of the Korea Computer Graphics Society
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• v.26 no.4
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• pp.1-8
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• 2020

Motion synthesis using physics-based controllers can generate a character animation that interacts naturally with the given environment and other characters. Recently, various methods using deep neural networks have improved the quality of motions generated by physics-based controllers. In this paper, we present a control policy learned by deep reinforcement learning (DRL) that enables Luxo, the mascot character of Pixar animation studio, to run towards a random goal location while imitating a reference motion and maintaining its balance. Instead of directly training our DRL network to make Luxo reach a goal location, we use a reference motion that is generated to keep Luxo animation's jumping style. The reference motion is generated by linearly interpolating predetermined poses, which are defined with Luxo character's each joint angle. By applying our method, we could confirm a better Luxo policy compared to the one without any reference motions.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.6
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• pp.117-128
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• 2014

This is the case study of SATREC INITIATIVE company which is the unique domestic production of commercial satellites. We examined the path and pattern for accumulation of technological capability and technology learning process. This case study show that the process of technological innovation and their influencing factors. First, the technological learning of the satellite industry follows the stage of technological acquisition, absorption, improvement and is embodied by the technological capability. Second, accumulated technological capability of the satellite industry influences the technology innovation. Third, the top management team(TMT) affects the technological learning and technological capability. Fourth, TMT has a moderating role between the technological capability and the performance of technological innovation. Finally, technological innovations in the small and venture business would be the source of technological capability and technological learning. The implications of this study are as follows. TMT has the very important role for the technological innovation and affect the technology development and the production. Also technology-based companies must gain a competitiveness advantage through technological learning and technological innovations for sustainable growth.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.258-260
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• 2022

In order to nurture talents who will lead the digital convergence era of the 4th industrial revolution that creates new knowledge and industries, research is being conducted on teaching methods that can improve the understanding of non-majors' SW concept, computational thinking ability, and convergence with majors is becoming Non-majors face difficulties in understanding and understanding the SW development environment, relevance to their major, and ability to converge. We used software education that is relatively easy to access for non-majors, and applied a demonstration-oriented model (DMM) that can be applied to beginners in SW education to understand the components and logical flow of ideas related to applications and majors used in real life. A convergence SW Learning method that combines repetitive implementation through instructor's demonstration and learner's modeling and learning motivational factors was proposed. In the experiment applying the teaching and learning method proposed in this paper, meaningful results were shown in terms of learning motivation and academic achievement in SW education.

• Journal of Korea Game Society
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• v.17 no.1
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• pp.27-40
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• 2017

This study explores the concept of Study Time Management Service(STMS) and the characteristics of gamification elements in STMS, in order to propose the meaning of psychic anti-entropy and the role of a meme as a new gamification element. The goal of gamification in education is to enhance study motivation and lead to flow by integrating similarities between game and study into the study environment. STMS also aims at such a goal. However, it differs in that the external anti-entropy environment, such as blocking apps, is connected with game mechanics or game thinking to give extrinsic motivation. It is also unique in that it uses a meme as a new gamification element to induce intrinsic motivation. In particular, a meme as a kind of guideline for performing study activities induces intrinsic motivation to imitate good study patterns and offers the driving force to sustain psychic anti-entropy state. Therefore, gamification in STMS is to strengthen the external anti-entropy environment by utilizing game mechanics or game thinking, and to maintain the psychic anti-entropy state by utilizing a meme of study patterns.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.3
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• pp.273-281
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• 2001

In this paper, we propose a CMAC(Cerebellar Model Articulation Controller) neural network for controlling a non-linear system. CMAC is a neural network that models the human cerebellum. CMAC uses a table look-up method to resolve the complex non-linear system instead of numerical calculation method. It is very fast learn compared with other neural networks. It does not need a calculation time to generate control signals. The simulation results show that the proposed CMAC controllers for a simple non-linear function and a DC Motor speed control reduce tracking errors and improve the stability of its learning controllers. The validity of the proposed CMAC controller is also proved by the real-time tension control.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.862-868
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• 2007

The planar motion of the index finger in general human hands is usually implemented by the actuation of three joints. This task requires a technique to determine the joint combination for each fingertip position which is well-known as the inverse kinematics problem in robotics. Especially, it is an essential work for grasping and manipulation tasks by robotic and humanoid fingers. In this paper, an intelligent neural learning scheme for solving such inverse kinematics is presented. Specifically, a multi-layered neural network is utilized for effective inverse kinematics, where a dynamic neural learning algorithm is employed for fast learning. Also, a bio-mimetic feature of general human fingers is incorporated to the learning scheme. The usefulness of the proposed approach is verified by simulations.