• Journal of the Korea Convergence Society
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• v.8 no.3
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• pp.123-131
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• 2017

This study is to find the weaknesses in drug dose calculations of nursing students by analyzing their general characteristics, confidence(C), performances in classes(PC) and exam sheets of drug dose calculations. The data were analyzed using SPSS 19.0. There was no significant difference between male and female students in simple calculation ability(SCA), but male students' mean scores were higher in applied calculation ability(ACA) and accuracy on calculation(AC). There were no significant differences in calculation abilities according to high school departments. And students were weak in questions which are needed ACA. The explanation rate of C on PC and PC on AC were 4.2% and 3.2% respectively, so there were weak positive effects from C to PC, and PC to AC. This study suggests that there is a need to develop and implement an intervention program according to students' abilities to increase AC, C, and PC by studying math on an ongoing basis. This study needs to be cautious in generalizing, because the data set was limited to nursing students from one university.

• Journal of Power Electronics
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• v.19 no.1
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• pp.119-133
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• 2019

Although the dual modulation wave method can solve the low-frequency neutral point potential (NPP) fluctuation problem for three-level neutral point clamped converters, it also increases the switching frequency and limits the zero-sequence voltage. That makes it harmful when dealing with the NPP drift problem if the converter suffers from a long dead time or asymmetric loads. By introducing two degrees of freedom (2-DOF), an NPP control based on a search optimization method can demonstrate its ability to cope with the above mentioned two types of NPP problems. However, the amount of calculations for obtaining an optimal 2-DOF is so large that the method cannot be applied to certain industrial applications with an inexpensive digital signal processor. In this paper, a novel optimal 2-DOF-based NPP control is proposed. The relationships between the NPP and the 2-DOF are analyzed and a method for directly determining the optimal 2-DOF is also discussed. Using a direct calculation method, the amount of calculations is significantly reduced. In addition, the proposed method is able to maintain the strongest control ability for the two types of NPP problems. Finally, some experimental results are given to confirm the validity and feasibility of the proposed method.

• Journal of the Korean School Mathematics Society
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• v.10 no.4
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• pp.471-485
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• 2007

In this study, a 27 class hour prescribed program for the fourth grade students is to be developed and applied by extracting the contents associated with basic operations studied prior to the fourth grade level of mixed calculations. After analyzing the results of the research, the following conclusions are obtained. First, the prescribed program for mixed calculations brought about the improvement in the mixed calculation problem solving ability of the students. Second, applying the prescribed program for mixed calculation resulted in an increase in students' interest and concentration on problem solving. In synthesis of the above conclusions, the development and application of the prescribed program for mixed calculation improved the students' concentration on the problem and the students' problem solving ability.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.734-736
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• 1996

This paper presents a method of calculating a selective number of eigenvalues in power systems, which are rightmost, or are largest modulus. The modified Arnoldi method in conjunction with implicit shift OR-algorithm is used to calculate the rightmost eigenvalues. Algorithm requires neither a prior knowledge of the specified shifts nor the calculation of inverse matrix. The key advantage of the algorithm is its ability to converge to the wanted eigenvalues at once. The method is compared with the modified Arnoldi method combined with S-matrix transformation, where the eigenvalues having the largest modulus are to be determined. The two methods are applied to the reduced Kansai system. Convergence characteristics and performances are compared. Results show that both methods are robust and has good convergence properties. However, the implicit shift OR method is seen to be faster than the S-matrix method under the same condition.

• Steel and Composite Structures
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• v.46 no.3
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• pp.435-449
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• 2023

Time domain method and frequency domain method are commonly used in the current fatigue life calculation theory. The time domain method has complicated procedures and needs a large amount of calculation, while the frequency domain method has poor applicability to different materials and different spectrum, and improper selection of spectrum model will lead to large errors. Considering that artificial neural network has strong ability of nonlinear mapping and generalization, this paper applied this technique to random fatigue life prediction, and the effect of average stress was taken into account, thereby achieving more accurate prediction result of random fatigue life.

• Journal of The Korean Association of Information Education
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• v.5 no.2
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• pp.185-196
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• 2001

Elementary school students feel more difficult the mathematical word problems than the numberical formula. I think that this reason isn't the ability of mathematical calculation but the problems representation. It is demanded exactly understanding about the requirements of problem for improving ability of the mathematical word problem representation. It is necessary that we take multimedia data and communication for this, because web advances multimedia materialization and promotes mutual communication, then it gives us with the most environment for word problem representation learning. According to, this thesis is designed web-based system to improve ability of the mathematical word problem representation, applied the sixth grade it experimentally.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.86-89
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• 2002

In NC machining, the ability to automatically generate an optimal process plan is an essential step toward achieving automation, higher productivity, and better accuracy. For this ability, a system that is capable of simulating the actual machining process has to be designed. In this paper, a milling process simulation system for the general NC machining was presented. The system needs first to accurately compute the cutting configuration. ME Z-map(Moving Edge node Z-map) was developed to reduce the entry/exit angle calculation error in cutting force prediction. It was shorn to drastically improve the conventional Z-map model. Experimental results applied to the pocket machining show the accuracy of the milling process simulation system.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.12
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• pp.1652-1662
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• 1995

In this paper, a hybrid neural network is proposed to improve the learning ability of a neural network. The union of the characteristics of a Self-Organizing Neural Network model and of multi-layer perceptron model using the backpropagation learning method gives us the advantage of reduction of the learning error and the learning time. In learning process, the proposed hybrid neural network reduces the number of nodes in hidden layers to reduce the calculation time. And this proposed neural network uses the fuzzy feedback values, when it updates the responding region of each node in the hidden layer. To show the effectiveness of this proposed hybrid neural network, the boolean function(XOR, 3Bit Parity) and the solution of inverse kinematics are used. Finally, this proposed hybrid neural network is applied to the visual tracking control of a PUMA560 robot, and the result data is presented.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.366-368
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• 2003

In this paper, a parametric evaluation method of protection ability is proposed. The adequacy of every parameter is evaluated for the setting rules. Then the results are combined to give protection level of a whole protective system. The setting rules are categorized into three groups for hierarchical calculation. The proposed scheme is applied to a location problem of a new protective device to show its effectiveness.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.164.1-164
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• 2001

Q-learning is a recent reinforcement learning algorithm that does not need a modeling of environment and it is a suitable approach to learn behaviors for autonomous agents. But when it is applied to multi-agent learning with many I/O states, it is usually too complex and slow. To overcome this problem in the multi-agent learning system, we propose the successive Q-learning algorithm. Successive Q-learning algorithm divides state-action pairs, which agents can have, into several Q-functions, so it can reduce complexity and calculation amounts. This algorithm is suitable for multi-agent learning in a dynamically changing environment. The proposed successive Q-learning algorithm is applied to the prey-predator problem with the one-prey and two-predators, and its effectiveness is verified from the efficient avoidance ability of the prey agent.