• Communications of Mathematical Education
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• v.30 no.4
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• pp.435-452
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• 2016

This study was designed to explore students' instrumentalization in relation to the van Hiele's teaching method within a technology environment using GeoGebra. To carry out the study, a total of 4 lesson units was developed based on van Hiele teaching method for two slow learners in Gyeonggi province, Korea. The results of study were as follows. Instrumentalization of students was actualized from preparation, to adaptation, and to application stages. In preparation, and adaptation stages, depending on visualization, students used a trial-and-error method a lot, however in application stage the role of GeoGebra was just to check the solution of what they conjectured. Therefore, a teacher should prepare geometric tasks according to the processes of instrumentalization based on geometric teaching method. During instrumentalization and instrumentation of users, usage scheme(US) and instrumented action scheme(IAS) should be concrete.

• Korean Journal of Organic Agriculture
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• v.5 no.1
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• pp.67-77
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• 1996

The Organic agricultural techinques were investigated through the observations made for 3 years of the actual conditions of a farmer who has been practicing organic agriculture over 21 years. The farmer was a member of the Ichijima-cho Organic Agriculture Association. The Farmer had not performed much of the organic agricultural techinques at the beginning of his farming history. However, he has gradually developed techniques upon the experiences with trial and error. The notable characteristic of his basic organic agriculture was the utilization of a suitable organic fertilizer to make the soil fertile. Crop damages by diseases and insect pests were prevented through a fertile soil, raising of good seedlings, adoption of tolerant varieties and planting at a wide spacing and consequently considering not to use chemical pesticides. Introduction of power weeder for weed control and paddy-upland crop rotation reduced the cost of production for farming. The crop pattern and method of land us such as mix cropping, crop rotation and conversion of paddy field-upland fieldd were appeared to be very important in organic agriculture. The organic agricultural techniques get systematized upon the adaptation the regional ecology and the development of skills of the farmer. The most important point to achieve the success in organic agriculture system is not only by the development of the technical matters but also by the building of healthy relation and understandings between producers and consumers.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.3
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• pp.316-322
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• 2009

This paper presents an analytical design method of a passive harmonic filter for a three-phase diode rectifier and uses a new transfer function approach in the analysis and design. The transfer function approach derives an analytical formulation of an utility system including passive filters with a basis of Laplace transform and provides a graphical formulation so that a visualized insight into an interaction between individual filter and system response can be attainted. Harmonic impedance, voltage division and current division transfer function are used as a design tool, which makes a calculated filter parameters to satisfy IEEE-519 distortion limits. A simple five-step design procedure is introduced in the filter design, which consists of system analysis, selection of PCC(Point of Common Coupling), filter specification calculation, appropriate filter design for system and filter implementation. Philosophy governing the design procedure is based on a numerical/graphical iterative solution, trial and error with visualization feed-back based on "algebra on the graph". Finally, performance of the designed passive harmonic filter is verified by experiment and shows that 5th, 7th, 9th, 11th and 13th harmonics are decreased within IEEE-519 distortion limits, respectively.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.3
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• pp.209-217
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• 2001

In this paper, we propose a linear quadratic regulator(LQR) controller design for the active suspension using evolution strategy(ES) and neural network. We can improve the inherent suspension problem, the trade-off between ride quality and suspension travel by selecting appropriate weight in the LQR-objective function. Since any definite rules for selecting weights do not exist, we replace the designers trial-and-error method with ES that is an optimization algorithm. Using the ES, we can find the proper control gains for selected frequencies, which have major effects on the vibrations of the vehicle. The relationship between the frequencies and proper control gains are generalized by use of the neural networks. When the vehicle is driven, the trained neural network is activated and provides the proper gains for operating frequencies. And we adopted double sky-hook control to protect car component when passing large bump. Effectiveness of our design has been shown compared to the conventional sky-hook controller through simulation studies.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.1
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• pp.90-97
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• 2004

DC motor requires a rotor speed sensor for accurate speed control. The speed sensors such as resolvers and encoders are used as speed detectors. but they increase cost and size of the motor and restrict the industrial drive applications. So in these days. many Papers have reported on the sensorless operation or DC motor(3)-(5). This paper Presents a new sensorless strategy using neural networks(6)-(8). Neural network structure has three layers which are input layer. hidden layer and output layer. The optimal neural network structure was tracked down by trial and error and it was found that 4-16-1 neural network has given suitable results for the instantaneous rotor speed. Also. learning method is very important in neural network. Supervised learning methods(8) are typically used to train the neural network for learning the input/output pattern presented. The back-propagation technique adjusts the neural network weights during training. The rotor speed is gained by weights and four inputs to the neural network. The experimental results were found satisfactory in both the independency on machine parameters and the insensitivity to the load condition.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.12
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• pp.935-942
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• 2002

When designing fluid mounts, design parameters can be varied in order to obtain a desired notch frequency and notch depth. The notch frequency is a function of the mount parameters and is typically selected by the designer to occur at the vibration disturbance frequency. Since the process of choosing these parameters can involve some trial and error, it seems to be a great application for obtaining optimal performance of the mount. Many combinations of parameters are possible to give us the desired notch frequency, but the question is which combination provides the lowest depth. Therefore. an automatic optimal technique is needed to optimize the performance of the fluid mount. In this study. the enhanced genetic algorithm (EGA) is applied to minimizing transmissibility of a fluid mount at the desired notch frequency, and at the notch and resonant frequencies. The EGA is modified genetic algorithm to search global and local optimal solutions of multi-modal function optimization. Furthermore. to reduce the searching time as compare to conventional genetic algorithm and Increase the precision of the solutions, the modified simplex method is combined with the algorithm. The results show that the performance of the optimized mount by using the hybrid algorithm is better than that of the conventional fluid mount.

• Earthquakes and Structures
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• v.25 no.6
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• pp.469-479
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• 2023

A probabilistic seismic damage analysis is an essential procedure to identify seismically vulnerable structures, prioritize the seismic retrofit, and ultimately minimize the overall seismic risk. To assess the seismic risk of multiple structures within a region, a large number of nonlinear time-history structural analyses must be conducted and studied. As a result, each assessment requires high computing resources. To overcome this limitation, we explore a deep learning-based metamodel to enable the prediction of the mean and the standard deviation of the seismic damage distribution of track-on steel-plate girder railway bridges in Korea considering the geometric variation. For machine learning training, nonlinear dynamic time-history analyses are performed to generate 800 high-fidelity datasets on the seismic response. Through intensive trial and error, the study is concentrated on developing an optimal machine learning architecture with the pre-identified variables of the physical configuration of the bridge. Additionally, the prediction performance of the proposed method is compared with a previous, well-defined, response surface model. Finally, the statistical testing results indicate that the overall performance of the deep-learning model is improved compared to the response surface model, as its errors are reduced by as much as 61%. In conclusion, the model proposed in this study can be effectively deployed for the seismic fragility and risk assessment of a region with a large number of structures.

• Korean Institute of Interior Design Journal
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• v.21 no.1
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• pp.248-257
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• 2012

The demand of elderly care facilities due to aging population has been increased and the trend of developed countries implies the necessity of innovate approach for elderly care in Korea. The purpose of this research is to evaluate the flexible elderly housing alternative which has been introduced showing adaptability and small scale. This elderly housing alternative was designed to fulfill the condition of residential facilities for various aging phases from the independent elderly to dependent elderly. The workshop method was used for pre-evaluation of the flexible elderly housing alternative from the viewpoint of administrators, care givers and the elderly. The pre-evaluation is to estimate the facility before finalizing the design so that it facilitates more effective and suitable plan by reducing the trial and error beforehand, unlike the post-evaluation. Major responses of plans were positive and the needs for improvement about some concerns were revealed. Thus, relevant aspects of architectural drawings were amended according to workshop participants' needs and features that require to be reflected during further planning procedures were also improved. The result of this research will develop the flexible elderly housing alternative and contribute to foster environment for the elderly as well.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.324-327
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• 1996

This paper describes the robust controller design methods applied to the problem of an automatic system for tow-vehicle/trailer combinations. This study followed an inverse Linear Quadratic Regulator(LQR) approach which combines pole assignment methods with conventional LOR methods. It overcomes two concerns associated with these separate methods. It overcomes the robustness problems associated with pole placement methods and trial and error required in the application of the LQR problem. Moreover, a Kalman filter is used as the observer, but is modified by using the loop transfer recovery (LTR) technique with modified transmission zero assignment. The proposed inverse LQG,/LTR controllers enhances the forward motion stability and maneuverability of the combination vehicles. At high speeds, where the inherent yaw damping of the vehicle system decreases, the controller operates to maintain an adequate level of yaw damping. At backward moton, both 4WS (2WS tow-vehicle, 2WS trailer) and 6WS (4WS tow-vehicle, 2WS trailer) control laws are proposed by using inverse LQG/LTR method. To evaluate the stability and robustness of the proposed controllers, simulations for both forward and backward motion were conducted using a detailed nonlinear model. The proposed controllers are significantly more robust than the previous controllers and continues to operate effectively in spite of parameter perturbations that would cause previous controllers to enters limit cycles or to loose stability.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.3
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• pp.280-285
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• 2004

This paper is concerned with the modeling and identification of sequencing batch reactor (SBR) via genetic algorithm based polynomial neural network (GA-based PNN). The model describes a biological SBR used in the wastewater treatment process fur nitrogen removal. A conventional polynomial neural network (PNN) is applied to construct a predictive model of SBR process fur nitrogen removal before. But the performances of PNN depend strongly on the number of input variables available to the model, the number of input variables and type (order) of the polynomials to each node. They must be fixed by the designer in advance before the architecture is constructed. So the trial and error method must go with heavy computation burden and low efficiency. To alleviate these problems, we propose GA-based PNN. The order of the polynomial, the number of input variables, and the optimum input variables are encoded as a chromosome and fitness of each chromosome is computed. Simulation results have shown that the complex SBR process can be modeled reasonably well by the present scheme with a much simpler structure compared with the conventional PNN model.