• International Journal of Fluid Machinery and Systems
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• v.3 no.4
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• pp.369-378
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• 2010

The creation of the hydraulic turbine flow factor map will undoubtedly benefit its design by decreasing both the design cycle time and product cost. In this paper, the geometry and flow variables, which effectively affect the flow factor, are proposed, analyzed and determined. These flow variables are further used to create the operating condition maps by using different model approaches categorized into Response Surface Method (RSM) and Artificial Neural Network (ANN). The accuracies of models created by different approaches are compared and the performances of model approaches are analyzed. The influences of chosen variables and the combination of Principle Component Analysis (PCA) and model approaches are also studied. The comparison results between predicted and actual flow factors suggest that two-hidden-layer Feed-forward Neural Network (FFNN), and one.hidden-layer FFNN with PCA has the best performance on forming this mapping, and are accurate sufficiently for hydraulic turbine design.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.1043-1052
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• 2009

To derive easily the coefficient of permeability from several other soil properties, the estimation model of coefficient of permeability was proposed using linear regression analysis. The coefficient of permeability is one of the major factors to evaluate the soil characteristics. The study area is located in Kangwon-do Pyeongchang-gun Jinbu-Myeon. Soil samples of 45 spots were taken from the study area and various soil tests were carried out in laboratory. After selecting the soil factor influenced by the coefficient of permeability through the correlation analysis, the estimation model of coefficient of permeability was developed using the linear regression analysis between the selected soil factor and the coefficient of permeability from permeability test. Also, the estimation model of coefficient of permeability was compared with the results from permeability test and empirical equation, and the suitability of proposed model was proved. As the result of correlation analysis between various soil factors and the coefficient of permeability using SPSS(statistical package for the social sciences), the largest influence factor of coefficient of permeability were the effective grain size, porosity and dry unit weight. The coefficient of permeability calculated from the proposed model was similar to that resulted from permeability test. Therefore, the proposed model can be used in case of estimating the coefficient of permeability at the same soil condition like study area.

• Fashion & Textile Research Journal
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• v.23 no.3
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• pp.323-336
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• 2021

This study investigated the cognitive process of fashion design images through eye activity tracking. Differences in the cognitive process and gaze activity according to image elements were confirmed. The results of the study are as follows. First, a difference was found between groups in the gaze time for each section according to the model and design. Although model diversity is an important factor leading the interest of observers, the simplicity of the model was deemed more effective for observing the design. Second, the examination of the differences by segments regarding the gaze weight of the image area showed differences for each group. When a similar type of model is repeated, the proportion of face recognition decreases, and the proportion of design recognition time increases. Conversely, when the model diversity is high, the same amount of time is devoted to recognizing the model's face in all the processes. Additionally, there was a difference in the gaze activity in recognizing the same design according to the type of model. These results enabled the confirmation of the importance of the model as an image recognition factor in fashion design. In the fashion industry, it is important to find a cognitive factor that attracts and retains consumers' attention. If the design recognition effect is further maximized by finding service points to be utilized, the brand's sustainability is expected to be enhanced even in the rapidly changing fashion industry.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.50-63
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• 2017

While transit is inconvenient, it is also inevitable for the efficient public transportation. Reducing the number of transfers as much as possible is most important in providing the convenience of public transportation and facilitating the public transportation. As for the public transportation card data, 61,986 items on weekdays and 69,100 items on weekends were collected. Pattern analysis and traffic influence factors were analyzed using traffic data card. Trip chain results revealed that people have more transit transfers for shopping and leasure than commuting purposes on weekends and that commuting distance and time increase by 10 km and 9.9 minutes, respectively. Besides, results of the structural equation model showed that factor 1(total travel time, total travel distance), factor 2(number of people getting on and off), factor 3(transit time), and factor 4(number of bus connections, number of operations) were found to have significant effects on the number of transfers.

• Survey Research
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• v.11 no.2
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• pp.123-140
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• 2010

The purpose of this study is to determine the unidimensionality of Grasmick's operationalization of Gottfredson and Hirschi's criminality inducing the concept of low self-control. By applying confirmatory factor analysis procedures that incorporate advances in the application, the proposed six factor model and two alternative models were examined suggesting that Grasmick's low self-control scale actually contains 6 distinguishable factors, not a single factor. The factors identified to be consistent with the six-factor model were impulsivity, simple tasks, risk seeking, physical activities, self-centered, and temper.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.12
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• pp.20-25
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• 2008

Codebook-based opportunistic beamforming (COBF) technique provides a beam selection diversity to the conventional opportunistic beamforming. In this paper, we design the random matrix and codebook for the COBF technique based on a kappa-factor channel model. Applying the proposed design to the COBF, nearly optimal beams are generated. Therefore, the COBF shows an outstanding performance without regard to the channel correlation related to the kappa-factor.

• Tunnel and Underground Space
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• v.30 no.1
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• pp.87-97
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• 2020

Fracture toughness of rock is a constant that can indicate the initiation and propagation of cracks due to blasting, excavation, etc. Scaled model tests have been applied to the behavior of tunnels and the stability of limestone mines. Through the scaled model, damaged zone evaluation due to blasting is also carried out, and the scale factor is not applied to the failure-related factors. In this study, DCT (diametral compression test) and finite element method ATENA2D numerical analysis results were compared to determine whether the scale factor could be applied to the fracture toughness of rock. The theoretical values of the scale factor applied to the fracture toughness of the rock and the DCT test results and the numerical results are 0.21~0.46, 0.40, and 0.99MPa ${\sqrt{m}}$ respectively, so these three values should be considered when determining scale factor. It is necessary to derive a suitable scale factor in consideration of the length, time, and mass to which the scale factor is applied, as well as the values of the scale factor of major design factors such as uniaxial compressive strength and density.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.617-631
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• 2019

In the four-step demand model, a gravity mode is used most commonly at the trip distribution stage. The purpose of this study was to develop a new friction factor that can express the accessibility property as a single friction factor to compensate for the variable limits of the gravity model parameters (travel time, travel cost). To derive a new friction factor, a new friction factor was derived using the space syntax that can quantify the characteristics of the urban space structure, deriving the link-unit integration degree and then using the travel time and travel distance relationship. Calibration of the derived friction factor resulted in a similar level to that of the existing friction factor. As a result of verifying the various indicators, the explanatory power was found to be excellent in the short - and long - distance range. Therefore, it is possible to derive and apply the new friction factor using the integration index, which can complement the accessibility beyond the limit of the existing shortest distance, and it is believed to be more advantageous in future utilization.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.393-406
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• 2015

We examine how to model mortality risk using the adaptation of the mean-reverting processes for the two factor model proposed by Cairns et al. (2006b). Mortality improvements have been recently observed in some countries such as United Kingdom; therefore, we assume long-run mortality converges towards a trend at some unknown time and the mean-reverting processes could therefore be an appropriate stochastic model. We estimate the parameters of the two-factor model incorporated with mean-reverting processes by a Metropolis-Hastings algorithm to fit United Kingdom mortality data from 1991 to 2015. We forecast the evolution of the mortality from 2014 to 2040 based on the estimation results in order to evaluate the issue price of a longevity bond of 25 years maturity. As an application, we propose a method to quantify the speed of mortality improvement by the average mean reverting times of the processes.

• Journal of the Ergonomics Society of Korea
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• v.26 no.2
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• pp.45-59
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• 2007

The operating tasks of overhead crane have caused undue stress to the operators from physical, mental, and environmental workload. Existing workload assessment models for musculoskeletal disorders such as OWAS, RULA, and QEC have limited applicability to the crane operating tasks because they focus mainly on physical factors and do not consider the relative importance of each factor. The present study was to develop a workload assessment model customized to overhead crane operation, following a systematic process: (1) analyzing task characteristics, (2) selecting workload factors, (3) developing assessment methods, (4) establishing action levels, and (5) computerizing the assessment model. Based on literature review, worksite survey, and focus group interview, 4 physical factors (awkward posture, static posture, repetitive motion, and excessive force), 6 mental factors (visual demand, auditory demand, task complexity and difficulty, time urgency, work schedule related stress, and safety related stress), and 4 environmental factors (noise, vibration, dust, and temperature) were selected and their rating scales and relative weights were determined. Then, based on the workload assessment results of 8 overhead cranes operated at different workplaces, the action levels of each factor category were established. Finally, the crane operation assessment model was computerized for effective analysis and report preparation. The present approach is applicable to develop a customized workload assessment model for an operating task under consideration.