• Journal of Korean Elementary Science Education
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• v.25 no.3
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• pp.307-317
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• 2006

Those students with ability and interest in science should be supported to develop their potential and to reach high levels of achievement in science and technology. In order to ensure that gifted pupils are able to enhance their creativity as well as research abilities, appropriate learning programs and environments are essential. One of the various teaching and learning models for the gifted in science is the discovery learning model based on inductive science activities. There is a clear line of continuity between knowledge discovery at the forefront of research and student's learning activities. If students receive excellent training in organizing scientific concepts for themselves, they will be able to skillfully apply appropriate scientific concepts and solve problems when facing unfamiliar situations. It is very important to offer an appropriate learning environment to maximize the learning effect whilst, at the same time, understanding individual student's characteristics. In this study, the authors took great pains to research effective learning environments for gifted science students. Firstly, appropriate classroom learning environments thought by the teacher to offer the most potential were investigated. 3 different classes in which a revised teaching and learning environment was applied in sequence were examined. Inquiries were conducted into students' activities and achievement through observation, interviews, and examination of students' worksheets. A Science Education expert and 5 elementary school teachers specializing in gifted education also observed the class to examine the specific character of gifted science students. A number of suggestions in discovery learning classes for elementary students gifted in science are possible; 1) Readiness is essential in attitudes related to the inquiry. 2) The interaction between students should be developed. A permissive atmosphere is needed in small group activities. 3) Students require training in listening to others. In a whole class discussion, a permissive atmosphere needs to be restricted somewhat in order to promote full and inclusive discussion. 4) Students should have a chance to practice induction and abduction methods in solving problems.

• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1841-1848
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• 1999

DELVAUX is a genetics-based inductive learning system that learns a rule-set, which consists of Bayesian classification rules, from sets of examples for classification tasks. One problem that DELVAUX faces in the rule-set learning process is that, occasionally, the learning process ends with a local optimum without finding the best rule-set. Another problem is that, occasionally, the learning process ends with a rule-set that performs well for the training examples but not for the unknown testing examples. This paper describes efforts to alleviate these two problems centering on the N-version learning approach, in which multiple rule-sets are learning and a classification system is constructed with those learned rule-sets to improve the overall performance of a classification system. For the implementation of the N-version learning approach, we propose a decision-making scheme that can draw a decision using multiple rule-sets and a genetic algorithm approach to find a good combination of rule-sets from a set of learned rule-sets. We also present empirical results that evaluate the effect of the N-version learning approach in the DELVAUX learning environment.

• Journal of the Korean School Mathematics Society
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• v.11 no.2
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• pp.299-314
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• 2008

The purposes of this study were to investigate what attitudes students have toward learning proofs and what difficulties they have in learning proofs, and to examine how the use of dynamic geometry software, the Geometer's Sketchpad, helps students' proof learning. The study involved 117 9th graders in 2 high schools. According to questionnaire data, over 50 percent of the total respondents(116) indicated negative attitudes toward learning proofs, on the other hand, only 16 percent of the total respondents indicated positive attitudes toward the learning. Memorizing and remembering many kinds of theorems, definitions, and postulates to use in proving statements was the most difficult part in learning proofs, which the largest proportion of the total respondents indicated. The study found that the use of the Geometer's Sketchpad played positive roles in developing students' understanding of proofs and stimulating students' interests in learning proofs.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.10
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• pp.1861-1868
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• 2008

In this paper, Passive Telemerty RF Sensor System using Unscented Kalman Filter algorithm(UKF) is proposed. General Passive Telemerty RF Sensor System means that it should be "wireless", "implantable" and "batterless". Conventional Passive Telemerty RF Sensor System adopts Integrated Circuit type, but there are defects like complexity of structure and limit of large power consumption in some cases. In order to overcome these kinds of faults, Passive Telemetry RF Sensor System based on inductive coupling principle is proposed in this paper. Because passive components R, L, C have stray parameters in the range of high frequency such as about 200[KHz] used in this paper, Passive Telemetry RF Sensor System considering stray parameters has to be derived for accurate model identification. Proposed Passive Telemetry RF Sensor System is simple because it consists of R, L and C and measures the change of environment like pressure and humidity in the type of capacitive value. This system adopted UKF algorithm for estimation of this capacitive parameter included in nonlinear system like Passive Telemetry RF Sensor System. For the purpose of obtaining learning data pairs for UKF Algorithm, Phase Difference Detector and Amplitude Detector are proposed respectively which make it possible to get amplitude and phase between input and output voltage. Finally, it is verified that capacitive parameter of proposed Passive Telemetry RF Sensor System using UKF algorithm can be estimated in noisy environment efficiently.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2C
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• pp.162-171
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• 2003

It is difficult to reuse the captured motion data, because the data has a difficulty in editing it. In this paper, a uniform posture mar (UPM) algorithm, one of unsupervised learning neural network is proposed to edit the captured motion data. Because it needs much less computational cost than other motion editing algorithms, it is adequate to apply in teal-time applications. The UPM algorithm prevents from generating an unreal posture in learning phase. It not only makes more realistic motion curves, but also contributes to making more natural motions. Above of all, it complements the weakness of the existing algorithm where the calculation quantity increases in proportion to increase the number of restricted condition to solve the problems of high order articulated body. In this paper, it is shown two applications as a visible the application instance of UPM algorithm. One is a motion transition editing system, the other is a inductive inverse kinematics system. This method could be applied to produce 3D character animation based on key frame method, 3D game, and virtual reality, etc.

• Journal of IKEEE
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• v.23 no.3
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• pp.777-784
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• 2019

A pre-fire awareness and automatic notification system are required because it is possible to minimize the damage if the fire situation is precisely detected after a fire occurs in a place where people are unusual or in a mountainous area. In this study, we developed a RaspberryPi-based fire recognition system using Faster-recurrent convolutional neural network (F-RCNN) and single shot multibox detector (SSD) and demonstrated a fire alarm system that works with power line communication. Image recognition was performed with a pie camera of RaspberryPi, and the detected fire image was transmitted to a monitoring PC through an inductive power line communication network. The frame rate per second (fps) for each learning model was 0.05 fps for Faster-RCNN and 1.4 fps for SSD. SSD was 28 times faster than F-RCNN.

• The Mathematical Education
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• v.40 no.2
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• pp.253-263
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• 2001

Developing mathematical thinking skills is one of the most important goals of school mathematics. In particular, recent performance based on assessment has focused on the teaching and learning environment in school, emphasizing student's self construction of their learning and its process. Because of this reason, people related to mathematics education including math teachers are taught to recognize the fact that the degree of students'acquisition of mathematical thinking skills and strategies(for example, inductive and deductive thinking, critical thinking, creative thinking) should be estimated formally in math class. However, due to the lack of an evaluation tool for estimating the degree of their thinking skills, efforts at evaluating student's degree of mathematics thinking skills and strategy acquisition failed. Therefore, in this paper, mathematical thinking was studied, and using the results of study as the fundamental basis, mathematical thinking process model was developed according to three types of mathematical thinking - fundamental thinking skill, developing thinking skill, and advanced thinking strategies. Finally, based on the model, evaluation factors related to essential thinking skills such as analogy, deductive thinking, generalization, creative thinking requested in the situation of solving mathematical problems were developed.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.6
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• pp.319-327
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• 2022

Transformers are the most famous deep learning models that has achieved great success in natural language processing and also showed good performance on computer vision. In this survey, we categorized transformer-based models for computer vision, particularly object detection tasks and perform comprehensive comparative experiments to understand the characteristics of each model. Next, we evaluated the models subdivided into standard transformer, with key point attention, and adding attention with coordinates by performance comparison in terms of object detection accuracy and real-time performance. For performance comparison, we used two metrics: frame per second (FPS) and mean average precision (mAP). Finally, we confirmed the trends and relationships related to the detection and real-time performance of objects in several transformer models using various experiments.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.795-802
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• 2003

To live autonomously, intelligent agents such as robots or virtual characters need ability that recognizes given environment, and learns and chooses adaptive actions. So, we propose an action selection/learning mechanism in intelligent agents. The proposed mechanism employs a hybrid system which integrates a behavior-based method using the reinforcement learning and a cognitive-based method using the symbolic learning. The characteristics of our mechanism are as follows. First, because it learns adaptive actions about environment using reinforcement learning, our agents have flexibility about environmental changes. Second, because it learns environmental factors for the agent's goals using inductive machine learning and association rules, the agent learns and selects appropriate actions faster in given surrounding and more efficiently in extended surroundings. Third, in implementing the intelligent agents, we considers only the recognized states which are found by a state detector rather than by all states. Because this method consider only necessary states, we can reduce the space of memory. And because it represents and processes new states dynamically, we can cope with the change of environment spontaneously.

• Journal for History of Mathematics
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• v.33 no.1
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• pp.1-19
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• 2020

Under 2009 Revised Mathematics Curriculum and 2015 Revised Mathematics Curriculum, mathematics teachers can help students inductively express real life problems related to sequences but have difficulties in dealing with problems asking the general terms of the sequences defined inductively due to 'Guidelines for Teaching and Learning'. Because most of textbooks mainly deal with the simple calculation for the sums of sequences, students tend to follow them rather than developing their inductive and deductive reasoning through finding patterns in the sequences. In this study, we reconstruct 8 problems to find the sums of sequences in MukSaJipSanBup which is known as one of the oldest mathematics book of Chosun Dynasty, using the terminology and symbols of the current curriculum. Such kind of problems can be given in textbooks and used for teaching and learning. Using problems in mathematical books of Chosun Dynasty with suitable modifications for teaching and learning is a good method which not only help students feel the usefulness of mathematics but also learn the cultural value of our traditional mathematics and have the pride for it.