• 가정과삶의질연구
• /
• 제24권3호
• /
• pp.15-25
• /
• 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.

• 한국학교수학회논문집
• /
• 제4권1호
• /
• pp.69-80
• /
• 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
• /
• 제14권6호
• /
• pp.1494-1507
• /
• 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.

• 대한지구과학교육학회지
• /
• 제6권2호
• /
• pp.152-158
• /
• 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.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
• /
• pp.275-278
• /
• 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)
• /
• 제11권4호
• /
• pp.2038-2057
• /
• 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
• /
• 한국HCI학회 2009년도 학술대회
• /
• pp.411-417
• /
• 2009

본 논문은 지능형 환경에 적합하도록 사용자의 자유를 제한하지 않는 실시간 신체 부위 추적 시스템의 구현에 관해 다룬다. 본 시스템은 기존의 신체 부위 추적 시스템과 달리 소매의 길이에 제약 없이 긴 소매, 반 소매 모두 인식할 수 있도록 함으로써 시스템의 generality를 높였다. 정확한 인식을 위하여, 한 대의 카메라에서 얻어진 이미지에서 손, 머리, 발의 신체 부위를 따로 검출하고 각 신체 부위를 검출할 때 해당 부위에 적합한 특징점을 따로 선택하여 검출하였다. 검출된 2차원의 신체 부위들을 calibrate된 카메라를 이용하여 3차원 자세로 변환하였다. 본 시스템은 실험을 통해 실시간(50fps) 성능으로 향상된 손 추적 성능을 보여주었다.

• 한국정보처리학회논문지
• /
• 제6권5호
• /
• pp.1323-1331
• /
• 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.

• 한국공작기계학회:학술대회논문집
• /
• 한국공작기계학회 2003년도 추계학술대회
• /
• pp.207-212
• /
• 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.

• 한국공작기계학회:학술대회논문집
• /
• 한국공작기계학회 2004년도 추계학술대회 논문집
• /
• pp.181-186
• /
• 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.