• Journal of Families and Better Life
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• v.24 no.3 s.81
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• pp.15-25
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• 2006

This study has been performed to identify intelligent ability, reward choice in assumed situation of delay of gratification, and delay of gratification ability. The subjects for this study were 100 preschoolers between the ages of 4 and 5, their mothers, and 15 teachers of three day-care centers in Seoul. T-test, F-test, Correlation analysis and multiple regression analysis were used for data analysis. The main results of this study were as follows: First, preschoolers' delay of gratification ability by mothers' educational background was significant and delay of gratification ability by sex was significant. This means that mothers who had a higher educational background were positively related to preschoolers' delay of gratification ability. Second, in an assumed situation of delay of gratification, preschoolers' delay of gratification ability by reward choice was not significant. Third, delay of gratification by intelligent ability was significant. Fourth, the correlation among intelligent ability, reward choice in assumed situation of delay of gratification and delay of gratification ability were significant. Finally, preschoolers' delay of gratification ability was significantly influenced by two factors: reward choice in assumed situation of delay of gratification and preschoolers' intelligent ability.

• Journal of the Korean School Mathematics Society
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• v.4 no.1
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• pp.69-80
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• 2001

A web-based intelligent education system(WEST) was designed and implemented to improve the self-directed study for students by providing them the study according to one's ability. WEST is composed of a tutor agent, an administrator module, a teacher module and a student module. The tutor agent analyzes students' ability and selects questions from a database according to their ability. The administrator module administrates subjects and students. The teacher module makes questions with three levels and administrates questions. The students module gives the questions students and the result of study. WEST was used in a mathematics subject for high-school students. Especially our system was better than the others in study according to students' ability.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1494-1507
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• 2018

Intelligent human identification using face information has been the research hotspot ranging from Internet of Things (IoT) application, intelligent self-service bank, intelligent surveillance to public safety and intelligent access control. Since 2D face images are usually captured from a long distance in an unconstrained environment, to fully exploit this advantage and make human recognition appropriate for wider intelligent applications with higher security and convenience, the key difficulties here include gray scale change caused by illumination variance, occlusion caused by glasses, hair or scarf, self-occlusion and deformation caused by pose or expression variation. To conquer these, many solutions have been proposed. However, most of them only improve recognition performance under one influence factor, which still cannot meet the real face recognition scenario. In this paper we propose a multi-scale parallel convolutional neural network architecture to extract deep robust facial features with high discriminative ability. Abundant experiments are conducted on CMU-PIE, extended FERET and AR database. And the experiment results show that the proposed algorithm exhibits excellent discriminative ability compared with other existing algorithms.

• Journal of the Korean Society of Earth Science Education
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• v.6 no.2
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• pp.152-158
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• 2013

The purpose of this work is to investigate pre-service elementary teachers' belief in science gifted education. To do that, from September to November 2012, this research had been conducted with 42 students who were in the third year of P University of Education. The conclusions of this work are presented as follows: First, the pre-service elementary teachers considered exploration ability to be the most important talent for the gifted students in science, and chose task commitment as the next most important. They regarded intelligent ability and leadership ability as the relatively less important. Secondly, regarding the most important tool in choosing scientifically gifted students, the pre-service elementary teachers preferred creativity test. It was found that they considered the intelligence test and academic achievements, which require intelligent ability, to be the less important. Thirdly, regarding the special knowledge related to science gifted education, the pre-service elementary teachers considered pedagogical knowledge about the gifted to be the most important. Fourthly, regarding a class type for gifted students in science, the pre-service elementary teachers most preferred project learning. Project learning is a learning method in which students choose an interesting problem and solve the problem in cooperation with group members. It is the most widely used exploration class in gifted education. It is in the same context as the result that exploration ability is the most important factor to elementary gifted students in science. This work revealed that, with regard to a talent for the gifted in science, judgment of the gifted in science and science gifted education, the potential ability and affective ability of gifted students are considered to be more important than their intelligent ability. Therefore, it was analyzed that pre-service elementary teachers' belief in the gifted students in science is almost consistent with the recent trend of gifted education.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.275-278
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• 2001

In this paper, We evaluate the learning ability of non-monotonic DBM(Deterministic Boltzmann Machine) network through numerical simulations. The simulation results show that the proposed system has higher performance than monotonic DBM network model. Non-monotonic DBM network also show an interesting result that network itself adjusts the number of hidden layer neurons. DBM network can be realized with fewer components than other neural network models. These results enhance the utilization of non-monotonic neurons in the large scale integration of neuro-chips.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2038-2057
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• 2017

Gaussian learning is a new technology in the computational intelligence area. However, this technology weakens the learning ability of a particle swarm and achieves a lack of diversity. Thus, this paper proposes a vector Gaussian learning strategy and presents an effective approach, named particle swarm optimization based on vector Gaussian learning. The experiments show that the algorithm is more close to the optimal solution and the better search efficiency after we use vector Gaussian learning strategy. The strategy adopts vector Gaussian learning to generate the Gaussian solution of a swarm's optimal location, increases the learning ability of the swarm's optimal location, and maintains the diversity of the swarm. The method divides the states into normal and premature states by analyzing the state threshold of the swarm. If the swarm is in the premature category, the algorithm adopts an inertia weight strategy that decreases linearly in addition to vector Gaussian learning; otherwise, it uses a fixed inertia weight strategy. Experiments are conducted on eight well-known benchmark functions to verify the performance of the new approach. The results demonstrate promising performance of the new method in terms of convergence velocity and precision, with an improved ability to escape from a local optimum.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.411-417
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• 2009

We proposed a robust body part tracking system for intelligent environment that will not limit freedom of users. Unlike any previous gesture recognizer, we upgraded the generality of the system by creating the ability the ability to recognize details, such as, the ability to detect the difference between long sleeves and short sleeves. For the precise each body part tracking, we obtained the image of hands, head, and feet separately from a single camera, and when detecting each body part, we separately chose the appropriate feature for certain parts. Using a calibrated camera, we transferred 2D detected body parts into the 3D posture. In the experimentation, this system showed advanced hand tracking performance in real time(50fps).

• The Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1323-1331
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• 1999

This paper suggests a multimedia educational system which has the ability to extract intelligent instruction on the distributed environment. The proposed system is designed for supporting individual instruction and real time user interaction. As the system based on CORBA, we put group managing module on it for multi user environment, so it has ability for distributed computing facilities. Using MHEG standard, we can provide multimedia courseware and real time user interaction. To diagnose students' responses and generate evaluations, we use several linguistic variables of fuzzy theory. There are two major advantages for using this system. This system can provide dynamic generation of problems and the ability to provide a dynamic instruction strategy. And it can increase reusability of courseware material for using standard of multimedia representation and communication. We use CORBA and MHEG to overcome the disadvantage of the Web, passive protocol and poor interactivity, HTTP.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.207-212
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• 2003

This paper proposed trajectory tracking control of Mobile Robot. Trajectory tracking control scheme are Real coding Genetic-Algorithm and Back-propergation Algorithm. Control scheme ability experience proposed simulation.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.181-186
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• 2004

This paper proposed trajectory tracking control of Mobile Robot. Trajectory tracking control scheme are Real coding Genetic-Algorithm and Back-propergation Algorithm. Control scheme ability experience proposed simulation.