• 아동학회지
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• 제29권5호
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• pp.215-226
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• 2008

The purpose of this study was to identify dangerous routes by which the experience of victimization leads to bullying behavior and to clarify the intrapersonal moderating variables which control the routes. Subjects were 1,086 students of elementary and middle schools in Seoul and Gyeonggi Province. Data were analyzed by simple regression analysis and multiple moderating regression analysis. The major findings of this study were that (1) the experience of victimization was an important factor predicting bullying behavior; and (2) self esteem and internal locus of control were moderating variables between the experience of victimization and bullying behavior. This study provides effective information to protect students from bullying by finding some moderating variables.

• 품질경영학회지
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• 제32권3호
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• pp.109-125
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• 2004

This paper deals with an optimal process control problem in production of hull structural steel plate with high defective rate. The main quality characteristic(dependent variable) is the internal quality(defect) of plates and is dependent on process parameters(independent variables). The dependent variable(quality characteristics) has three categorical ordinal data and there are 35 independent variables(29 continuous variables and 6 categorical variables). In this paper, we determine the main factors and to develop the mathematical model between internal quality predicted probabilities and the main factors. Secondly, we find out the optimal process condition of main factors through analysis of variance(ANOVA) using simulation. We consider three models to obtain the main factors and the optimal process condition: linear, quadratic, error models.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.555-558
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• 1991

The IESF(Integral Error and State Feedback) controller, which incorporates state feedback as a modern control scheme and integral action as a classical control scheme, has better performance than that of the conventional PID controller in linear time-invariant systems. The IESF controller requires the measurement of all the state variables. But, unfortunately, it may be difficult or impossible to measure all state variables in many applications. And the IESF controller is applicable only to pole-assignable linear time-invariant system without time delay. In this paper, new IESF controller structure was proposed which performs feedback with only measurable state variables. In order to estimate the unmeasurable state variables. It was adopted the filter mode by full-order obserber. The good performance and effectiveness of the proposed controller was confirmed by computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1364-1367
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• 1996

Recently, direct rolling process, called as strip casting process, has been interested in to save production cost by reducing forming processes. In direct rolling process, since a steel strip of thickness 1-5(mm) can be produced directly from molten metal, it can eliminate secondary hot rolling process. On the other hand, since many process variables are existed in this process and relation of these variables is very complex, it is difficult to realize the process design and the quality control. In this paper, as first step to overcome above difficulties, the quantitative relationship of the process variables affected to quality of the strip has been carried out through the numerical analysis. Also, we determined the process variable to monitor the quality in the direct rolling process. As a result, we show that the solidification final point, called as Nip point, was related directly to quality of the strip.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.50.1-50
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• 2001

Dynamic optimization with partially structured model in a slurry-phase HDPE reactor is implemented by the modified hierarchical dynamic optimization. Optimal trajectories of MI and density of HDPE are calculated as controlled variables and optimal profiles of the concentrations of ethylene, hydrogen and comonomer are calculated as manipulated variables in dynamic optimization. MI, density, the concentrations of ethylene, hydrogen and comonomer are used as controlled variables and flow rates of ethylene, hydrogen and comonomer are sued as manipulated variables in control implementation. Two-level hierarchical method is applied in dynamic optimization to reduce computation time. In the upper level formulation ...

• Journal of Welding and Joining
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• 제15권3호
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• pp.118-127
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• 1997

With the trend towards welding automation and robotization, mathematical models for studying the influence of various variables on the weld bead geometry in gas metal arc (GMA) welding process are required. Partial penetration, single-pass bead-on-plate welds using the GMA welding process were fabricated in 12mm mild steel plates employed four different process variables. Experimental results has been designed to investigate the analytical and empirical formulae, and develop mathematical equations for understanding the relationship between process variables and weld bead geometry. The relationships can be usefully employed not only for open loop process control, but also for adaptive control provided that dynamic sensing of process output is performed.

• Journal of Welding and Joining
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• 제15권6호
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• pp.116-123
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• 1997

In GMA welding processes, bead contour and penetration patterns are criterion to estimate weld quality. Bead geometry is commonly defined with width, height and depth. When weaving is taken into account, selection of welding conditions is known to be difficult. Thus, empirical or trial-and-error method are usually introduced. This study examined the correlation of welding process variables including weaving parameters with bead geometry using srtificial neural networks(ANN). The main task of the Ann estimator is to realize the mapping characteristics from the sampled welding process variables to the actual bead geometry through training. After the neural network model is constructed, welding process variables for desired bead geometry is selected by inverse model. Experimental varification of the inverse model is conducted through actual welding.

• 대한가정학회지
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• 제47권5호
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• pp.107-121
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• 2009

The purpose of this study was to examine leadership-related variables of young children. Subjects were 467 fiveyear-olds from the region. Data were subjected to descriptive statistical analysis. Pearson’s correlation, and multiple regression analysis. Results showed that leadership in young children was related to their temperament, peer interaction, verbal control modes of mothers, and home environment. Positive peer interaction was the strongest predictor for leadership of young children.

• 전자공학회논문지B
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• 제32B권6호
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• pp.821-827
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• 1995

This paper presents a process control language for constructing multiloop control system. which include advanced control algorithms. In order to make controller, this language uses function blocks that do specific operations. Then, the total control algorithm is a set of function blocks, of which each block is represented as a function code. The function code is a line of simple ASCII codes denoting function, input, output, parameters. It is possible to use variables as input/output port of any block. Compared with other language using function block concept, the proposed one enables to use advanced control algorithms undefinitely, such as fuzzy, neural network, predictive controller, etc., because vector and matrix variables as input/output can be used freely in this language. To raise flexibility, we put an intermediate level, which is C-language code, between function code and target-dependent operation code.

• 품질경영학회지
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• 제29권4호
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• pp.38-53
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• 2001

In resolving industrial quality control problems, a vector of multiple quality characteristic variables is involved rather than a single variable. However, it is not guaranteed that a multivariate control chart based on statistical methods can monitor abnormal signal in case that small changes of relationship between each variables causes abnormal production process. Hence a quality control system for real-time monitoring of the multi-dimensional quality characteristic vector under a multivariate normal process is needed to enhance tile production system quality performance. A pattern analysis approach based on self-organizing map (SOM), an unsupervised learning technique of neural network, is applied to the design of such a quality control system. In this study we present a new material quality control system based on pattern analysis approach and illustrate the effectiveness of proposed system using actual electronic company material data.