• Journal of Electrical Engineering and Technology
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• v.2 no.1
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• pp.123-128
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• 2007

SPWPM traditional software development is surveyed and essential problems are investigated on the basis of system wireless link considerations. This paper presents the current state software planning tools for wireless LAN link optimization. The software directory is based on combination of MatLab and MapInfo software and measurement which gives the best grouping parameters to build up the software development. Among the requirements assumed, the WLAN site selections must be Line-of-sight (LOS) or near line of sight (NLOS) field strength prediction for either point to point or point to multi points. The results obtainable the out put of the program include two-dimensional (2D) and three dimensional (3D) plots for creating the link; design parameters through GUI representing the height and location for each antenna is depending on K-factor of the area and transmit antenna location.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.10
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• pp.1423-1427
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• 2014

Quantity of the solar power generation is heavily influenced by weather. In other words, due to difference in insolation, different quantity may be generated. However, it does not mean all areas with identical insolation produces same quantity because of various environmental aspects. Additionally, geographic factors such as altitude, height of plant may have an impact on the quantity. Hence, through this research, we designed a system to predict efficiency of the solar power generation system by applying insolation, weather factor such as duration of sunshine, cloudiness parameter and location. By applying insolation, weather data that are collected from various places, we established a system that fits with our nation. Apart from, we produced a geographic model equation through utilizing generated data installed nationwide. To design a prediction model that integrates two factors, we apply fuzzy algorithm, and validate the performance of system by establishing simulation system.

• Water for future
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• v.29 no.4
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• pp.187-198
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• 1996

A numerical model for unsteady dispersion of horizontal line source in turbulent shear flow is developed. A fractional step finite difference method is used which splits the unsteady two-dimensional advective diffusion equation into the longitudinal advection and the vertical diffusion equations, and solves them alternately for half time intervals by the Holly-Preissmann scheme and the Crank-Nicholson scheme, respectively. The developed numerical model is verified using a semi-analytic solution for steady dispersion in turbulent shear flow. Dispersion of an instantaneous plane source in turbulent shear flow is analyzed using the model. The degree of mixing at the same dimensionless time is almost the same regardless of the friction factor, and the travel distance required to reach a certain degree of mixing is inversely proportional to the square root of the friction factor.

• Journal of Korean Society of Water and Wastewater
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• v.16 no.6
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• pp.686-699
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• 2002

The purpose of this study is to estimate deterioration factors and weighting factors in pipe network which each local self-governments takes rehabilitation and replacement work present time. Deterioration factors in pipe network are able to effected of specific province or location related with water supply. Most of water supply pipes are laid under the ground, it is hard to quantify deterioration degree of water system. Moreover, the timing and economic limitation and insufficient information on the spot survey gives a difficulty to look over how old water supply system is. Accordingly, this study collects and analyses five data as the laying environment, visual analysis, analysis of soil contents, analysis of pipe material, and questionary survey data in water pipe of A city. The deterioration factor estimates 14 factors with excavation and experimental analysis and 9 factors without excavation and experimental analysis. Also, the weighting factors are estimated by using the multiple linear regressions and the linear programming. The estimated deterioration factor and weighting results are compared the analysis result of visual, pipe material, and soil contents with the Probabilistic Neural Network Model. Consequently, the model results of estimated 9 factors in this study and 14 factors show the 1-2% difference. The result show that the proposed model could be used to decide the deterioration condition of pipe line with real excavation and experimental analysis.

• Journal of Surface Science and Engineering
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• v.40 no.4
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• pp.185-189
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• 2007

A scanning electron microscope (SEM) is a complex system, consisting of many sophisticated components. For a systematic characterization, a $2^4$ full factorial experiment was conducted. The SEM components examined include condenser lens 1 and 2 (denoted as A and B, respectively), and Objective lens (coarse and fine-denoted as C and D respectively). A statistical analysis was conduced to investigate factor effects and variations In response surfaces. Among four factors, main effect analysis revealed that A and D were Identified as the dominant factor. Moreover, B showed conflicting effect against C. The $R^2$ of statistical regression model constructed was about 69.6%. The model generated 3D response surface plots facilitated understanding of complex tactor effects.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.11
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• pp.133-143
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• 2021

This study investigates the relationship between social capital and enterprise performance with knowledge sharing as the mediator. By employing the data of 677 respondents collected from delivering questionnaires to small and medium-size firms in Vietnam in 2020, this study suggests a two-step approach that combines exploration factor analysis (EFA), confirmatory factor analysis (CFA), and path analysis (SEM). The empirical findings significantly support our proposed model by demonstrating that knowledge sharing mediates the connection between all three elements of social capital and enterprise performance. At the same time, the results emphasize the importance of knowledge sharing as a major benefit of social capital and a substantial driving element of both operational and financial performance. The results show that all three social capital qualities (structural, relational, and cognitive) significantly impact both tacit and explicit knowledge sharing, while knowledge is one of the main routes connecting social capital to enterprise performance. Hence, our research model may be used in future studies to evaluate social capital, knowledge sharing, and firm performance as a new theoretical model. Our results offer a plausible explanation for how social capital improves knowledge sharing and enterprise performance.

• Geosystem Engineering
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• v.21 no.6
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• pp.318-325
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• 2018

Eight tight sandstone reservoir samples from $He_8$ and $Shan_1$ Formations of the Sulige Gas field were selected to perform gas-water micro-displacement experiment based on authentic sandstone micro-model. The gas pressure-relief experiment was proposed for the first time to simulate the pressure change and gas-water percolation characteristics in the process of gas exploitation. The experiment results show that: (1) In the process of gas accumulation, the gas preferentially flows into the well-connected pores and throats with large radius, but rarely flows into the area without pores and throats. (2) Under sufficient gas drive, the water in pores and throats usually exists in the forms of 'thin water film', 'thick water film', and 'water column', but under insufficient gas drive, gas fails to flow into new pathways in time, so that the reservoirs with large pores and throats are high in water cut. (3) Under the same water saturation, the reservoirs with better petrophysical properties has higher gas recovery factor within unit time. Under the same petrophysical conditions, the reservoirs with lower water saturation show higher gas recovery factor within unit time. The higher the permeability, the stronger the liquid carrying capacity of reservoirs.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.172-180
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• 2021

The purpose of this study is to analyze the structural relationship among perfectionism and dance achievement of middle and high school students majoring in dance. Specifically, this study aims to investigate the effects of perfectionism on dance achievement through the medium of dance commitment and career decision-making self-efficacy. For this purpose, a structural equation model based on the previous studies was constructed with perfectionism as an exogenous variable and dance commitment, career decision-making self-efficacy, and dance achievement as endogenous variables. The final subjects of this study were 279 middle and high school students majoring in dance. The data were processed by frequency analysis to find out personal characteristics using SPSS 23 and exploratory factor analysis and reliability analysis were conducted on the research tools. In addition, AMOS 21 was used for confirmatory factor analysis, correlation analysis and structural equation model analysis. As a result of data processing on the research model. First, the sub-dimensions of perfectionism tendency 'worry about mistakes', 'personal standard', and 'doubt about behavior' had a statistically significant effect on dance commitment. Second, the sub-dimensions of perfectionism 'worry about mistakes', 'personal standard', and 'doubt about behavior' had statistically significant effects on career decision-making self-efficacy. Third, dance commitment did not have a statistically significant effect on dance achievement, but career decision-making self-efficacy had a statistically significant effect on dance achievement. These results provide implications.

• Corrosion Science and Technology
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• v.20 no.2
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• pp.52-61
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• 2021

This study using experimental design and linear regression technique was implemented in order to predict the pitting potential of stainless steel in marine environments, with the target materials being AL-6XN and STS 316L. The various variables (inputs) which affect stainless steel's pitting potential included the pitting resistance equivalent number (PRNE), temperature, pH, Cl^- concentration, sulfate levels, and nitrate levels. Among them, significant factors affecting pitting potential were chosen through an experimental design method (screening design, full factor design, analysis of variance). The potentiodynamic polarization test was performed based on the experimental design, including significant factor levels. From these testing methods, a total 32 polarization curves were obtained, which were used as training data for the linear regression model. As a result of the model's validation, it showed an acceptable prediction performance, which was statistically significant within the 95% confidence level. The linear regression model based on the full factorial design and ANOVA also showed a high confidence level in the prediction of pitting potential. This study confirmed the possibility to predict the pitting potential of stainless steel according to various variables used with experimental linear regression design.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.59-66
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• 2020

In this study, we consider the problem of forecasting the number of inbound foreigners visiting Korea. Forecasting tourism demand is an essential decision to plan related facilities and staffs, thus many studies have been carried out, mainly focusing on the number of inbound or outbound tourists. In order to forecast tourism demand, we use a seasonal ARIMA (SARIMA) model, as well as a SARIMAX model which additionally comprises an exogenous variable affecting the dependent variable, i.e., tourism demand. For constructing the forecasting model, we use a search procedure that can be used to determine the values of the orders of the SARIMA and SARIMAX. For the exogenous variable, we introduce factors that could cause the tourism demand reduction, such as the 9/11 attack, the SARS and MERS epidemic, and the deployment of THAAD. In this study, we propose a procedure, called Measuring Impact on Demand (MID), where the impact of each factor on tourism demand is measured and the value of the exogenous variable corresponding to the factor is determined based on the measurement. To show the performance of the proposed forecasting method, an empirical analysis was conducted where the monthly number of foreign visitors in 2019 were forecasted. It was shown that the proposed method can find more accurate forecasts than other benchmarks in terms of the mean absolute percentage error (MAPE).