• Journal of Electrochemical Science and Technology
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• v.2 no.2
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• pp.76-84
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• 2011

Potentiostatic oxidation of Pb-1.7%Sb alloy used in the manufacture of grids of lead-acid batteries over the potential range from -1.0V to 2.3V in 5M $H_2SO_4$ in the absence and the presence of 0.4M $H_3PO_4$ and the self-discharge characteristics of the oxide layer formed is studied by electrochemical impedance spectroscopy (EIS). Depending on the potential value, sharp variations in resistance and capacitance of the alloy are recorded during the oxidation and they can be used for identification of the various substances involved in passive layer. Addition of $H_3PO_4$ is found to deteriorate the insulating properties of the passive layer by the retardation of the formation of $PbSO_4$. $H_3PO_4$ completely inhibits the current and impedance fluctuations recorded in $H_3PO_4$-free solutions in the potential range 0.5 V-1.7 V. These fluctuations are attributed to the occurrence of competitive redox processes that involve the formation of $PbSO_4$, $PbOSO_4$, PbO and $PbO_2$ and the repeated formation and breakdown of the passive layer. Self-discharge experiments indicate that the amount of $PbO_2$ formed in the presence of $H_3PO_4$ is lesser than in the $H_3PO_4$-free solutions. The start of transformation of $PbSO_4$ into $PbO_2$ is greatly shortened. $H_3PO_4$ facilitates the diffusion process of soluble species through the passive layer ($PbSO_4$ and basic $PbSO_4$) but impedes the diffusion process through $PbO_2$.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.72-79
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• 2010

A EAARS(Electronic Attendance-Absence Recording System) is the important LSS(Learning Support System) for blending a on-line learning in the face-to-face classroom. However, the EAARS based on the smart card can not identify a real owner of the checked card. Therefore, we develop the CS(Client-Sever) system that manages the attendance-absence checking automatically, which is used the self-organizing neural network for the face recognition. A client system creates the ID file by extracting the face feature, a server system analyzes the ID file sent from client system, and performs a student identification by using the Recognized weight file saved in Database. As a result, The proposed CS EAARS shows the 92% efficiency in the CS environment that includes the various face image database of the real classroom.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.7
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• pp.1457-1467
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• 2015

Depending on the type of Tx-Rx pairs, VHF Data Exchange System (VDES) for maritime communication is expected to employ the different frequency channels. Load imbalance between the different channels turns out to be a critical problem for the multi-hop communication using Ad-hoc Self-Organizing TDMA (ASO-TDMA) MAC protocol, which has been proposed to provide the connectivity between land station and remote ship stations. In order to handle the inter-channel load imbalance problem, we consider a model of the stochastic geomety in this paper. After analyzing the spatial reuse efficiency in each hop region by the given model, we show that the resource utility can be maximized by balancing the inter-channel traffic load with optimal resource allocation in each hop region.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.2
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• pp.55-64
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• 1990

This paper concerned about a study on the direct pole placement PID self-tuning controller design for DC servo motor control system. The method of a direct pole placement self-tuning PID control for a DC servo motor of Robot manipulator tracks a reference velocity in spite of the parameters uncertainties in nonminimum phase system. In this scheme, the parameters of classical controller are estimated by the recursive least square (RLS)identification algorithm, the pole placement method and diophantine equation. A series of simulation in which minimum phase system and nonminimum phase system are subjected to a pattern of system parameter changes is presented to show some of the features of the proposed control algorithm. The proposed control algorithm which shown are effective for the practical application, and experiments of DC servo motor speed control for Robot manipulator by a microcomputer IBM-PC/AT are performed and the results are well suited.

• The Korean Nurse
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• v.37 no.1
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• pp.107-115
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• 1998

There is an important concern regarding the First-line nurse manager's leadership because of the recognition that effectiveness of Leadership in this position results in benefits for the whole health care organization. So knowledge and practice of effective leadership behavior are now more essential to nursing than ever before. First-line Nurse Managers must be effective leaders to meet today's challenge because staff nurse, patient are affected by them. So the purpose of this study was to identify and to analyse the need for Leadership program of First-Line nurse managers in university hospitals. There were three major purposes of this study. First, identify First-line nurse managers general characteristic, second, identify their experience of leadership training, third, identify and analysis their demands for leadership training program. The subjects for this study was 167 First-line nurse manager randomly from 18 university hospitals in Korea. The data were collected through questionnaires from Oct. 13th to Nov. 20th, 1997, data was analysed using frequencies and percentages. Especially the steps of analysis of descriptions were as follows: Initial analysis centered on the identification of the demands of first-line nurse managers. Later analysis collapsed the demands into broad categories. From the collect data, 283 demands of first-line nurse managers were identified. These demands were then sorted into 3 broad categories that included : Self development as first-line nurse managers, relationship with others, and practice. The result of the study were as follows ; 1) Most of nurse managers(79.6%) had leadership training course and had good experience to improve self leadership. 2) Their demands of leadership training course are as follows First, for self as first-line nurse managers, they want to learn leadership theory, identify their leadership style and then develop their leadership skill. Second, for others as first-line nurse managers, they want to improve their communication skill, empowering others, relationship with others. Third, for patients as first-line nurse managers, improve their knowledge of practice. From the above finding, this study can be suggested the following; 1. Develope a leadership training course to improve first- line nurse manager's leadership skill according to their demands, so they will be better able to lead staff nurses for organization purposes. 2. When develope leadership training program, it must be contained the factors which first-line nurse managers want to learn.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.2
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• pp.126-135
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• 2002

The study is concerned with an approach to the design of new architectures of fuzzy neural networks and the discussion of comprehensive design methodology supporting their development. We propose an Adaptive Fuzzy Polynomial Neural Networks(APFNN) based on Fuzzy Neural Networks(FNN) and Self-organizing Networks(SON) for model identification of complex and nonlinear systems. The proposed AFPNN is generated from the mutually combined structure of both FNN and SON. The one and the other are considered as the premise and the consequence part of AFPNN, respectively. As the premise structure of AFPNN, FNN uses both the simplified fuzzy inference and error back-propagation teaming rule. The parameters of FNN are refined(optimized) using genetic algorithms(GAs). As the consequence structure of AFPNN, SON is realized by a polynomial type of mapping(linear, quadratic and modified quadratic) between input and output variables. In this study, we introduce two kinds of AFPNN architectures, namely the basic and the modified one. The basic and the modified architectures depend on the number of input variables and the order of polynomial in each layer of consequence structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the AFPNN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed AFPNN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• Journal of Korean Academy of Nursing Administration
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• v.10 no.3
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• pp.291-298
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• 2004

Purpose: This study is to investigate if the effectiveness training program, suggested by Gordon(1970), could help these nursing students with the problems of interpersonal relationship and self-identification. Method: This study was designed using nonequivalent control group protest-posttest design. The subject for this study were thirty nursing students. Fifteen nursing students of the experimental group experienced the Effectiveness Training for 8 weeks (3 hours/week). The effect of Effectiveness Training was measured using Relationship Change Scale devised by Lee, H.D. & Moon, S.M.(1979) and Ego Identity Scale devised by Dignan(1965) which was translated by Seo, B.Y.(1975) Pretest data were collected by the researcher from both experimental and control group before training. After the end of eight weeks training, posttest data collected from both experimental and control group. Samples were analyzed using SPSS PC+. Result: 1. The first hypothesis, "level of interpersonal relationship of the experiment group after 8 weeks will be significantly higher than that of the control group"(z=-1.965, p=.049)was supported. 2. The second hypothesis, "level of ego-identity of the experimental group after 8 weeks will be significantly higher than that of the control group"(z=-2.191, p=.028)was supported. 3. The third hypothesis, "level of interpersonal relationship of the experiment group will be significantly higher than that of the control group after 4 months of training"(z=-.634, p=.238)was not supported. 4. The fourth hypothesis, "level of ego-identity of the experimental group will be significantly higher than that of the control group after 4 months of training"(z=-.292, p=.642)was not supported. Conclusion: The Effectiveness Training can be considered as an effective method of nursing students's interpersonal relationship & ego-identity, because it was proved to help nursing students increase level of their interpersonal relationship & ego-identity but it was needed to reinforce for continuing of the effect of the interpersonal relationship & ego-identity.

• 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.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.387-394
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• 2005

This paper describes an idea for determining self-localization using visual landmark. The critical geometric dimensions of a pentagon are used here to locate the relative position of the mobile robot with respect to the pattern. This method has the advantages of simplicity and flexibility. This pentagon is also provided nth a unique identification, using invariant features and colors that enable the system to find the absolute location of the patterns. This algorithm determines both the correspondence between observed landmarks and a stored sequence, computes the absolute location of the observer using those correspondences, and calculates relative position from a pentagon using its (ive vortices. The algorithm has been implemented and tested. In several trials it computes location accurate to within 5 centimeters in less than 0.3 second.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.311-320
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• 2003

The Optimal filter yielding optimal texture feature separation is a most effective technique for extracting the texture objects from multiple textures images. But, most optimal filter design approaches are restricted to the issue of supervised problems. No full-unsupervised method is based on the recognition of texture objects in image. We propose a novel approach that uses unsupervised learning schemes for efficient texture image analysis, and the band-pass feature of Gabor-filter is used for the optimal filter design. In our approach, the self-organizing neural network for multiple texture image identification is based on block-based clustering. The optimal frequency of Gabor-filter is turned to the optimal frequency of the distinct texture in frequency domain by analyzing the spatial frequency. In order to show the performance of the designed filters, after we have attempted to build a various texture images. The texture objects extraction is achieved by using the designed Gabor-filter. Our experimental results show that the performance of the system is very successful.