• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.118-130
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• 1996

Fuzzy inference is very useful in expressing ambiguous problems quantitatively and solving them. But like the most of the knowledge based inference systems. It has many difficulties in constructing rules and no learning capability is available. In this paper, we proposed a fuzzy inference system based on fuzy associative memory to solve such problems. The inference system proposed in this paper is mainly composed of learning phase and inference phase. In the learning phase, the system initializes it's basic structure by determining fuzzy membership functions, and constructs fuzzy rules in the form of weights using learning function of fuzzy associative memory. In the inference phase, the system conducts actual inference using the constructed fuzzy rules. We applied the fuzzy inference system proposed in this paper to a pattern classification problem and show the results in the experiment.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.491-494
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• 2004

Neural Oscillator can be applied to oscillatory systems such as the image recognition, the voice recognition, estimate of the weather fluctuation and analysis of geological fluctuation etc in nature and principally, it is used often to pattern recoglition of image information. Conventional BPL(Back-Propagation Learning) and MLNN(Multi Layer Neural Network) are not proper for oscillatory systems because these algorithm complicate Learning structure, have tedious procedures and sluggish convergence problem. However, these problems can be easily solved by using a synchrony characteristic of neural oscillator with PLL(phase-Locked Loop) function and by using a simple Hebbian learning rule. And also, Recognition velocity of Korean Character can be improved by using a Neural Oscillator's learning accelerator factor η$\_$ij/

• Research in Mathematical Education
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• v.14 no.1
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• pp.11-18
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• 2010

The basic idea of cooperative learning focuses on team reward, equal opportunities for success, cooperation within team and competition among teams, and emphasizes share of sense of achievement through joint efforts so as to realize specific learning objectives. The main strategies of engineering mathematics teaching based on cooperative learning are to establish favorable team and design reasonable team activity plan. During the period of team establishment, attention shall be given to team structure including such elements as team status, role, norm and authority. Team activity plan includes team activity series and team activity task. Team activity task shall be designed to be a chain of questions following a certain principle.

• The Journal of Korean Academic Society of Nursing Education
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• v.6 no.2
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• pp.359-375
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• 2000

PBL can be defined as an active, self-directed and student-centered learning, and an opposite way of classroom teacher-centered learning which has been traditional role learning. PBL enables students think more efficiently and effectively when puzzling through the patient problems. The purpose of this study is to find out the perception of student nurse about PBL, the characteristics and the structure of the type for PBL. The research process is as follow : First, the researcher selected 35 statements for PBL with the content analysis of in depth interview and the literature review. Second, the researcher asks 38 student nurse to classify the statement cards. The result of the research is that the type of student nurse's PBL perception is divided into 4 types(Affirmative type, Negative type, Suspicious type, and Preferable type), and the explanative total variance is 44 percent. In relation to this, if PBL well combined and adapted in our traditional curriculum will change our nursing education in better direction.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2005.05a
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• pp.281-282
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• 2005

The present design, which is the result of English Zone Project for 'I' Girls' High School in Yeonsu dong, Incheon, purposed to produce atmosphere like a cafe so that students can attempt more comfortable and diverse learning methods, breaking away from the structure and atmosphere of traditional language labs while providing functions such as experiential learning, teaching learning and native speaker conversation. In addition, it applied colors close to primary colors so that students throw away their fixed idea of language lab as a special class and access it easily at any time. Moreover, it was designed for the maximum changeability using foldable and portable furniture so that various types of group study can be performed. Ultimately the design project is expected to suggest methods of experiential learning distinguished from existing knowledge delivering education as it provides teaching learning methods beyond simple interior design.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.4
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• pp.427-438
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• 1991

An iterative learning control scheme for exact-tracking control and parameter estimation of uncertain robotic system is preented. In the learning control structure, the control input converges globally and asymtotically to the desired input as iteration increases. Since convergence of parameter errors depends only on the persistent exciting condition of system trajectories along the iteration independently of the time-duration of trajectories, it may be achieved with system trajectories with small duration. In addition, the proposd learning control schemes are applicable to time-varying parametric systems as well as time-invariant systems, because the parameter estimation is performed at each fixed time along the iteration. In the parameter estimator, the acceleration information as well as the inversion of estimated inertia matrix are not used at all, which makes the proposed learning control schemes more feasible.

• Journal of Engineering Education Research
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• v.23 no.5
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• pp.61-67
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• 2020

In the associate degree curriculum of the department of mechanical engineering, the results of the study are presented on the structure and content of a subject based on the case-based learning method. As an case, equipment called a laminator that is actually used in the manufacturing site was selected. Class deals with specific engineering issues at each stage of laminator manufacturing (design-machining-assembly-measurement-maintenance) in connection with general engineering topics in prerequisites in the curriculum. Topics include tolerance fit, length measurement, assembly practice, measurement design and statistics of machine maintenance, etc. Courses that apply the case-based learning method may be included in the curriculum as complementary roles to those that apply other student-centered learning method.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.1051-1059
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• 2014

In this paper, we propose an intelligent situation recognition model by collecting and analyzing multiple sensor signals. Multiple sensor signals are collected for fixed time window. A training set of collected sensor data for each situation is provided to K2-learning algorithm to generate Bayesian networks representing causal relationship between sensors for the situation. Statistical characteristics of sensor values and topological characteristics of generated graphs are learned for each situation. A neural network is designed to classify the current situation based on the extracted features from collected multiple sensor values. The proposed method is implemented and tested with UCI machine learning repository data.

• East Asian Economic Review
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• v.19 no.3
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• pp.243-273
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• 2015

The purpose of this paper is to identify learning in games in experimental economic settings, and apply their results to real multilateral trade negotiations, such as the Doha Development Agenda (DDA) in the World Trade Organizations (WTO). This paper argues that the structure of games including a veto player (Veto games) is similar to the WTO/DDA negotiations in that the players do not possess identical power. This paper's main contribution to the literature involves showing that learning about power is dominant over learning from simple repetition in Veto games. Additionally, this paper shows that players are concerned about how much they have gained in previous games in Veto games, although their memories generally do not last beyond the next game, and thus they tend to be selfish as they have less shares. Based on these results, there is a possibility to be more generous in the distribution of benefits by allowing players without veto power to retain special rights so that they would not be totally powerless. It also shows the necessity of having "respite" in the process of negotiations and policy options for choosing partners for winning coalitions.

• Journal of KIBIM
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• v.9 no.1
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• pp.22-31
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• 2019

In this paper, we construct a prototype model for city data prediction by using time series data of floating population, and use machine learning to analyze urban data of complex structure. A correlation prediction model was constructed using three of the 10 data (total flow population, male flow population, and Monday flow population), and the result was compared with the actual data. The results of the accuracy were evaluated. The results of this study show that the predicted model of the floating population predicts the correlation between the predicted floating population and the current state of commerce. It is expected that it will help efficient and objective design in the planning stages of architecture, landscape, and urban areas such as tree environment design and layout of trails. Also, it is expected that the dynamic population prediction using multivariate time series data and collected location data will be able to perform integrated simulation with time series data of various fields.