• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.2
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• pp.242-248
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• 1996

The properties of TiN/TiSi$_{2}$ bilayer formed by a rapid thermal annealing is investigated when thin SiO$_{2}$ film exists at the Ti-Si interface. The competitive reaction for the TiN/TiSi_2 bilayer occurs above 600 .deg. C. The thickness of the TiSi$_{2}$ layer decreases with increasing SiO$_{2}$ film thickness and also decreases with increasing anneal temperture When the competitive reaction for the TiN/TiSi$_{2}$ bilayer is occured by rapid thermal annealing, the composition of TiN layer represents TiN$_{x}$O$_{y}$ due to the SiO$_{2}$ layer at the Ti-Si interface but the structures of the TiN and TiSi$_{2}$ layers were not changed.d.d.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1457-1464
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• 2011

In this paper, we go one step further in that the number of competitive layers is not determined by experience but can be determined by fuzzy control rules based on input pattern information. In our method, we design a set of membership functions and corresponding rules and used Max-Min reasoning proposed by Mamdani. Also, we use centroid method as a defuzzification. In experiment that has various patterns of English inputs, this new method works beautifully to determine the number of competitive layers and also efficient in overall accuracy as a result.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.8
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• pp.869-874
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• 1992

The physical and electrical properties of TiN/TiSiS12T bilayer were studied. The TiN/TiSiS12T bilayer was formed by rapid thermal anneal in NHS13T ambient after the Ti film was deposited on silicon substrate. The Ti film reacts with NHS13T gas to make a TiN layer at the surface and reacts with silicon to make a TiSiS12T layer at the interface respectively. It was found that the formation of TiN/TiSiS12T bilayer depends on RTA temperature. In this experiment, competitive reaction for TiN/TiSiS12T bilayer occured above $600^{\circ}C$. Ti-rich TiNS1xT layer and Ti-rich TiSiS1xT layer and Ti-rich TiSiS1xT layer were formed at $600^{\circ}C$. stable structure TiN layer TiSiS12T layer which has CS149T phase and CS154T phase were formed at $700^{\circ}C$. Both stable TiN layer and CS154T phase TiSiS12T layer were formed at 80$0^{\circ}C$. The thickness of TiN/TiSiS12T bilayer was increased as the thickness of deposited Ti film increased.

• Proceedings of the KIEE Conference
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• 1994.07b
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• pp.1223-1225
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• 1994

The properties of $TiN/TiSi_2$ bilayer formed by a rapid thermal anneal ing is investigated when thin $SiO_2$ film exists at the Ti-Si interface. The competitive reaction for the $TiN/TiSi_2$ bilayer occurs above $600^{\circ}C$. The thickness of the $TiSi_2$ layer decreases with increasing $SiO_2$ film thickness while the TiN layer increases at the competitive reaction. The composition of TiN layer is changed to the $TiN_xO_y$ film due to the thin $SiO_2$ layer at the Ti-Si interface while the structure of the TiN and $TiSi_2$ layers was not changed.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.159-167
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• 1996

In this paper, a new competitive learning algorithm called dynamic competitive learning (DCL) is presented. DCL is a supervised learning mehtod that dynamically generates output neuraons and nitializes weight vectors from training patterns. It introduces a new parameter called LOG (limit of garde) to decide whether or not an output neuron is created. In other words, if there exist some neurons in the province of LOG that classify the input vector correctly, then DCL adjusts the weight vector for the neuraon which has the minimum grade. Otherwise, it produces a new output neuron using the given input vector. It is largely learning is not limited only to the winner and the output neurons are dynamically generated int he trining process. In addition, the proposed algorithm has a small number of parameters. Which are easy to be determined and applied to the real problems. Experimental results for patterns recognition of remote sensing data and handwritten numeral data indicate the superiority of dCL in comparison to the conventional competitive learning methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.675-679
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• 2001

In this paper, we present a new competitive learning algorithm called Dynamic Competitive Learning (DCL). DCL is a supervised learning method that dynamically generates output neurons and initializes automatically the weight vectors from training patterns. It introduces a new parameter called LOG (Limit of Grade) to decide whether an output neuron is created or not. If the class of at least one among the LOG number of nearest output neurons is the same as the class of the present training pattern, then DCL adjusts the weight vector associated with the output neuron to learn the pattern. If the classes of all the nearest output neurons are different from the class of the training pattern, a new output neuron is created and the given training pattern is used to initialize the weight vector of the created neuron. The proposed method is significantly different from the previous competitive learning algorithms in the point that the selected neuron for learning is not limited only to the winner and the output neurons are dynamically generated during the learning process. In addition, the proposed algorithm has a small number of parameters, which are easy to be determined and applied to real-world problems. Experimental results for pattern recognition of remote sensing data and handwritten numeral data indicate the superiority of DCL in comparison to the conventional competitive learning methods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.3
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• pp.445-451
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• 2016

General fuse elements of solution for fast acting operation characteristics made using silver or silver alloy, those are not able to dominate cost competition to the advanced global leaders that have not only high technology but competitive price. In this study, the method that compose the fuse elements manufactured solution of fast acting operation characteristics by using precision multi-layer thin film plating and helical cutting process from low-priced copper metal. Furthermore, in order to move rated current line of fuse due to the heat loses, the manufacture construction method of fixed resistor is introduced, and then Ni-P plating layer and Sn plating layer are introduced multiply for controling fine opening time characteristics. So this study can establish the high productive and low-priced production method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.3
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• pp.135-144
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• 2004

In this paper, we propose competitive fuzzy polynomial neurons-based advanced Self-Organizing Neural Networks(SONN) architecture for optimal model identification and discuss a comprehensive design methodology supporting its development. The proposed SONN dwells on the ideas of fuzzy rule-based computing and neural networks. And it consists of layers with activation nodes based on fuzzy inference rules and regression polynomial. Each activation node is presented as Fuzzy Polynomial Neuron(FPN) which includes either the simplified or regression polynomial fuzzy inference rules. As the form of the conclusion part of the rules, especially the regression polynomial uses several types of high-order polynomials such as linear, quadratic, and modified quadratic. As the premise part of the rules, both triangular and Gaussian-like membership (unction are studied and the number of the premise input variables used in the rules depends on that of the inputs of its node in each layer. We introduce two kinds of SONN architectures, that is, the basic and modified one with both the generic and the advanced type. Here the basic and modified architecture depend on the number of input variables and the order of polynomial in each layer. The number of the layers and the nodes in each layer of the SONN are not predetermined, unlike in the case of the popular multi-layer perceptron structure, but these are generated in a dynamic way. The superiority and effectiveness of the Proposed SONN architecture is demonstrated through two representative numerical examples.

• Transactions on Electrical and Electronic Materials
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• v.17 no.1
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• pp.33-36
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• 2016

In the present work, a Ni-doped indium zinc oxide (NIZO) film and its multilayers with Ag layers were investigated as transparent conducting electrodes for liquid crystal display (LCD) applications, as a substitute for indium tin oxide (ITO) electrodes. By interposing the Ag layer between the NIZO layers, the loss of the optical transmittance occurred; however, the Ag layer brought enhancement of electrical sheet resistance to the NIZO/Ag/NIZO multilayer electrode. The twisted nematic cell based on the NIZO/Ag/NIZO multilayer electrode exhibited superior electro-optical characteristics than those based on single NIZO electrode and was competitive compared to those based on the conventional ITO electrode. An LCD-based NIZO/Ag/NIZO multilayer electrode may allow new approaches to conventional ITO electrodes in display technology.

• International Journal of Highway Engineering
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• v.19 no.2
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• pp.55-65
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• 2017

PURPOSES : This study aimed to analyze the experimental and numerical behavior of warm mix asphalt pavement prepared using steel slag and RAP and to conduct economic analysis of pavement construction. METHODS : For developing high performance asphalt pavement, we performed three evaluations: fundamental analysis, experimental testing, and 3D finite element analysis. In particular, 3D finite element analysis was conducted on several pavement structures by adopting the results of experimental tests. RESULTS : Through the various evaluations, it was established that steel slag was effective for use as asphalt mixture aggregate. Moreover, asphalt mixture constituting steel slag and RAP demonstrated higher performance behavior compared with conventionally used asphalt mixture. Furthermore, based on the 3D FE modeling, we established that the developed asphalt pavement constituting steel slag and RAP can be utilized for thin layer pavement with comparable performance behavior. CONCLUSIONS :Warm mix asphalt pavement prepared using steel slag and RAP is more competitive and economic compared to hot-mix asphalt pavement. Moreover, it can be applied for preparing thin layer asphalt pavements with reasonable performance. The developed warm mix asphalt pavement prepared using steel slag and RAP can be an alternative pavement type with competitive performance based on the reasonable economic benefit it provides.