• Journal of the Korean Society for Precision Engineering
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• v.34 no.1
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• pp.23-27
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• 2017

This paper aims to develop a prediction model for the product quality of a casting process. Prediction of the product quality utilizes an artificial neural network (ANN) in order to renovate the manufacturing technology of the root industry. Various aspects of the research on the prediction algorithm for the casting process using an ANN have been investigated. First, the key process parameters have been selected by means of a statistics analysis of the process data. Then, the optimal number of the layers and neurons in the ANN structure is established. Next, feed-forward back propagation and the Levenberg-Marquardt algorithm are selected to be used for training. Simulation of the predicted product quality shows that the prediction is accurate. Finally, the proposed method shows that use of the ANN can be an effective tool for predicting the results of the casting process.

• Korean Journal of Organic Agriculture
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• v.24 no.2
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• pp.273-287
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• 2016

Accumulation of excessive salt in Reclaimed coastal tidelands can reduce crop yields, reduce the effectiveness of irrigation, degradation of soil structure, and affect other soil properties. These salts has shown to cause specific ions in the plant over a period of time leads to ion toxicity or ion imbalance and a continuous osmotic phase that prevents water uptake by plants due to osmotic pressure of saline soil solution. This review focuses on the characteristics of salt-affected soils, mechanisms of salt-tolerance plants, desalinization technology, and soil management to maintain sustainable agro-ecosystem in salt-affected soils.

• Carbon letters
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• v.15 no.2
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• pp.113-116
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• 2014

Due to their morphology, electrochemical stability, and function as a conducting carbon matrix, graphene nanosheets (GNS) have been studied for their potential roles in improving the performance of sulfur cathodes. In this study, a GNS/sulfur (GNS/S) composite was prepared using the infiltration method with organic solvent. The structure, morphology and crystallinity of the composites were examined using scanning electron microscopy, transmission electron microscopy, and X-ray diffraction. The electrochemical properties were also characterized using cyclic voltammetry (CV). The CV data revealed that the GNS/S composites exhibited enhanced specific-current density and ~10% higher capacity, in comparison with the S-containing, activated-carbon samples. The composite electrode also showed better cycling performance for multiple charge/discharge cycles. The improvement in the capacity and cycling stability of the GNS/S composite electrode is probably related to the fact that the graphene in the composite improves conductivity and that the graphene is well dispersed in the composites.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.129-131
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• 2006

The performances of neural network systems mainly depend on the kind and the number of input patterns for its training. Hence, the kind of input patterns as well as its number is very important for the character recognition system using back-propagation network. The more input patters are used, the better the system recognizes various characters. However, training is not always successful as the number of input patters increases. Moreover, there exists a limit to consider many input patterns of the recognition system for cursive script characters. In this paper we present a new character recognition system using the back-propagation neural networks. By using an additional neural network, an input pattern generation method is provided for increasing the recognition ratio and a successful training. We firstly introduce the structure of the proposed system. Then, the character recognition system is investigated through some experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.1
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• pp.187-192
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• 2009

This paper presents a method for designing a robust controller that alleviates disturbance effects and compensates performance degradation owing to the time-delay. Disturbance observer(DOB) approach as a tool of robust control has been widely employed in industry. However, since the Pade approximation of time-delay makes the plant non-minimum phase, the classical DOB cannot be applied directly to the system with time-delay. By using a new DOB structure for non-minimum phase systems together with the Smith Predictor, we propose a new controller for reducing the both effects of disturbance and time-delay. Moreover, the closed-loop system can be made robust against uncertain time-delay with the help of a Pill controller tuning method that is based on a second-order plus dead time modeling technique.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.2275-2276
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• 2008

Currently the quarter prediction giga it is used SE3208 from EISC ISA [1]] where it does in base. But the prediction which is perfect is difficult improved Pipeline structures and PC the structure which is not Delay to add it decided. Even PC and IF/ID blocks, the area and expense were added, but Bubble without it will be able to control Conditional Branch doors and the possibility of decreasing a help in processor performance improvements.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.850-851
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• 2008

This paper compares and investigates the vibration and noise characteristics through simulations of 12/8 and 6/4 switched reluctance motors (SRMs). The radial force which is the main source of vibration is computed from two-dimensional(2D) transient magnetic finite element analysis (FEA) and compared in both time and frequency domain. At the same output power, the radial force of 6/4 SRM is found to be more than two times as that one of 12/8 SRM. Three-dimensional structural finite-element analysis (3D FEA) is used to study the mechanical characteristics. It can be concluded from static structural analysis that the maximum total deformation could be reduced to 1/26 if the motor is designed with 12/8 structure instead of 6/4. The dominant vibration modes are verified by modal analysis.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.343-345
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• 2007

This paper proposes an inertial navigation system(INS) with which a biped robot can determine his position, velocity, posture, etc. The proposed system provides the information of robots independently without using any outer signals. The defect of the algorithm is the en'or accumulation as the robot increases the mobile range. However, in this application the problem is not so critical because the working space is small and operation period of the robots is relatively short. With the proposed INS system biped robots obtain enhanced intelligence to execute their tasks. The structure and theoretical backgrounds are utilized to design the INS system. The method for application of INS system to biped robots has been illustrated.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.86-87
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• 2000

Protein folding is a fundamental problem in structural bioinformatics and so numerous studies have been devoted to the subject. As the most common regular secondary conformation in proteins, helix has been an important ingredient of the protein folding problem. In particular, alanine based polypeptides are widely studied to identify the helix folding process in that the aianine amino acid is known to have one of the highest helix propensities. In principle, intrinsic helix propensities can be obtained from gas-phase measurements where solvent effect is absent. Hudgins et al. studied alanine-based peptides in vacuo using high-resolution ion mobility measurement technique. It was reported that introduction of a single Iysine at the C terminus resulted in the formation of very stable, monomeric polyalanine helices. We also have investigated helix formation in vacuo with different terminal charge conditions; we have found a new type of helix motif, To the best of our knowledge, this type of helix conformation has not been characterized before and we name it as I-helix.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.658-659
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• 2008

Numerical simulation is performed for a microdroplet deposition on the pre-patterned micro-structure. The liquid-air interface is tracked by level set method improved by incorporating the ghost fluid approach based on a sharp-interface representation. The method is further extended to treat the contact angle condition at an immersed solid surface. The present computation of a patterning process using microdroplet ejection demonstrates that the multiphase characteristics between the liquid-gas-solid phases can be used to overcome the patterning error.