• Korean Journal of Culture and Social Issue
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• v.30 no.2
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• pp.159-192
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• 2024

The purpose of this study is to validate the Reactive-Proactive Aggression Questionnaire (RPQ), a tool for measuring reactive-proactive aggression, in the context of South Korea. A thorough translation was conducted in collaboration with the original author. An exploratory factor analysis (EFA), exploratory structural equation modeling (ESEM), rating scale model (Rasch), differential item functioning (DIF), and convergent validity were performed on a sample of 510 South Korean individuals. The results revealed a two-factor structure of reactive and proactive aggression after removing one item showing dual loading. Rating scale analysis based on the Rasch model indicated the appropriateness of the 3-point Likert scale, with all items meeting fit criteria. Although the separation index and separation reliability of proactive aggression was marginally lower, the overall discrimination between participants and items was satisfactory. Examination of participant-item distribution indicated a suitable alignment between reactive aggression and participant ability levels, whereas proactive aggression exhibited slightly elevated item difficulty. Furthermore, three items were found to function differently based on gender. A moderate but statistically significant positive correlation was found between the Barratt Impulsiveness Scale-11-R (Korean version) and RPQ from the results of the convergent validity evaluation. Overall, this study employed rigorous statistical methods to validate the suitability of the RPQ for use in Korea, taking cultural nuances into account, and introduced the concepts of reactive and proactive aggression to the Korean general population.

• Journal of the Korean earth science society
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• v.44 no.4
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• pp.318-330
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• 2023

This study aimed to verify the validity of a measurement tool for Vietnamese high school students' systems thinking abilities. Two quantitative assessment tools, the Systems Thinking Measuring Instrument (Lee et al., 2013) and the Systems Thinking Scale (Dolansky et al., 2020), were used to measure students' systems thinking after translation into Vietnamese. As a result, it was revealed that Cronbach-α for each tool (i.e., STMI and STS) was .917 and .950, respectively, indicating high reliability for both. To validate the construct validity of the translated questionnaire, exploratory factor analysis was performed using SPSS 26.0, and confirmatory factor analysis was performed using AMOS 21.0. For concurrent validity, correlation analysis using structural equation modeling was performed to validate the translated questionnaire. Exploratory factor analysis revealed that 10 items from the STMI and 12 items from the STS loaded on the intended factors and appropriate factor loading values were obtained. For confirmatory factor analysis, a structural equation model organized with 10 items from the STMI and 12 items from the STS was used. The result of this showed that the convergent validity values of the model were all appropriate, and the model fit indices were analyzed to be χ²/df of 1.892, CFI of .928, TLI of .919, SRMR of .047, and RMSEA of .063, indicating that the model consisting of the 22 items of the two questionnaires was appropriate. Analysis of the concurrent validity of the two tools indicated a high correlation coefficient (.903) and high correlation (.571-.846) among the subfactors. In conclusion, both the STMI and STS are valid quantitative measures of systems thinking, and it can be inferred that the systems thinking of Vietnamese high-school students can be quantitatively measured using the 22 items identified in our analysis. Using the tool validated in this study with other tools (e.g., qualitative assessment) can help accurately measure Vietnamese high school students' systems thinking abilities. Furthermore, these tools can be used to collect evidence and support effective education in ODA projects and volunteer programs.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.17-17
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• 2017

In electric agricultural machine the gearhead is needed to convert the high speed low torque rotation motion generated by DC motor to lower speed high torque motion used by the vehicle. The gearhead consist of several spur gears works as reduction gears. Spur gear have straight tooth and are parallel to the axis of the wheel. Spur gears are the most easily visualized gears that transmit motion between two parallel shafts and easy to produce. The modeling and simulation of spur gears in DC motor gearhead is important to predict the actual motion behavior. A pair of spur gear tooth in action is generally subjected to two types of cyclic stress: contact stress and bending stress including bending fatigue. The stress may not attain their maximum values at the same point of contact fatigue. These types of failure can be minimized by analysis of the problem during the design stage and creating proper tooth surface profile with proper manufacturing methods. To improve its life expectation in this study modal and stress analysis of gearhead is simulated using ansys work bench software based on finite element method (FEM). The modal analysis was done to understand gearhead deformation behaviour when vibration occurs. FEM static stress analysis is also simulated on gearhead to simulate the gear teeth bending stress and contact stress behavior. This methodology serves as an approach for gearhead design evaluation, and the study of gear stress behavior in DC motor gearhead which is needed in the small workshop scale industries.

• Structural Engineering and Mechanics
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• v.58 no.2
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• pp.199-216
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• 2016

A large number of bridges were built several decades ago, and most of which have gradually suffered serious deteriorations or damage due to the increasing traffic loads, environmental effects, and inadequate maintenance. However, very few studies were conducted to investigate the vibration behaviors of a damaged bridge under moving vehicles. In this paper, the vibration behaviors of such vehicle-bridge system are investigated in details, in which the effects of the concrete cracks and bridge surface roughness are particularly considered. Specifically, two vehicle models are introduced, i.e., a simplified four degree-of-freedoms (DOFs) vehicle model and a more complex seven DOFs vehicle model, respectively. The bridges are modeled in two types, including a single-span uniform beam and a full scale reinforced concrete high-pier bridge, respectively. The crack zone in the reinforced concrete bridge is considered by a damage function. The bridge and vehicle coupled equations are established by combining the equations of motion of both the bridge and vehicles using the displacement relationship and interaction force relationship at the contact points between the tires and bridge. The numerical simulations and verifications show that the proposed modeling method can rationally simulate the vibration behaviors of the damaged bridge under moving vehicles; the effect of cracks on the impact factors is very small and can be neglected for the bridge with none roughness, however, the effect of cracks on the impact factors is very significant and cannot be neglected for the bridge with roughness.

• Journal of the Korean Geotechnical Society
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• v.28 no.2
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• pp.23-31
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• 2012

The purpose of this study is to analyze earth pressure acting on a circular shaft-tunnel considering arching effect by centrifuge modeling test on sands. The centrifuge testing method provides a way to model an in-situ stress state condition with a stress gradient within a laboratory specimen. A small-scale model of circular shaft-tunnel, which has a real diameter of 6.0 m and height of 15.0 m, was designed and tested twice under 75g-level. Additionally, an effect of excavation was presented by separating two segments of circular shaft wall to find behavioral properties and strength of earth pressure along with excavating ground. The test results were compared with those of the proposed earth pressure equation. The test results showed that earth pressure decreased by about 70% in comparison with existing two-dimensional earth pressure. This fact might be attributed to three-dimensional arching effects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3567-3582
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• 2020

Human activities are often affected by weather conditions. Automatic weather recognition is meaningful to traffic alerting, driving assistance, and intelligent traffic. With the boost of deep learning and AI, deep convolutional neural networks (CNN) are utilized to identify weather situations. In this paper, a three-channel convolutional neural network (3C-CNN) model is proposed on the basis of ResNet50.The model extracts global weather features from the whole image through the ResNet50 branch, and extracts the sky and ground features from the top and bottom regions by two CNN5 branches. Then the global features and the local features are merged by the Concat function. Finally, the weather image is classified by Softmax classifier and the identification result is output. In addition, a medium-scale dataset containing 6,185 outdoor weather images named WeatherDataset-6 is established. 3C-CNN is used to train and test both on the Two-class Weather Images and WeatherDataset-6. The experimental results show that 3C-CNN achieves best on both datasets, with the average recognition accuracy up to 94.35% and 95.81% respectively, which is superior to other classic convolutional neural networks such as AlexNet, VGG16, and ResNet50. It is prospected that our method can also work well for images taken at night with further improvement.

• Journal of the Korean Association of Geographic Information Studies
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• v.1 no.1
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• pp.3-7
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• 1998

The issue of data accuracy brings a different perspective to the issue of GIS modeling, calls into a question the usefulness of data models such as DEM. Accuracy can be determined by randomly checking positional and attribute accuracy within a GIS data layer. With the increasing availability of DEM and the software capable of processing them, it is worthwhile to call attention for data accuracy and error analysis as GIS application depends on the priori established spatial data. The purpose of this paper was to investigate methods for data accuracy measurement and error detection methodology with two types of DEM's: 1 to 24,000 and 1 to 250,000 DEM released by U.S. Geological Survey. Another emphasis was given to the development of methodology for processing DEM's to create Arc/Info and GRASS layers. Data accuracy analysis with DEM was applied to a 250 sq.km area and an error was detected at a scale of 1:24,000 DEM. There were two possible reasons for this error: gross errors and blunders.

• Journal of Soil and Groundwater Environment
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• v.17 no.5
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• pp.56-67
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• 2012

In the present study, an enhanced subsurface prediction algorithm based on a non-parametric geostatistical model and a history matching technique through Gibbs sampler is developed and the iterative prediction improvement procedure is proposed. The developed model is applied to a simple two-dimensional synthetic case where domain is composed of three different hydrogeologic media with $500m{\times}40m$ scale. In the application, it is assumed that there are 4 independent pumping tests performed at different vertical interval and the history curves are acquired through numerical modeling. With two hypothetical borehole information and pumping test data, the proposed prediction model is applied iteratively and continuous improvements of the predictions with reduced uncertainties of the media distribution are observed. From the results and the qualitative/quantitative analysis, it is concluded that the proposed model is good for the subsurface prediction improvements where the history data is available as a supportive information. Once the proposed model be a matured technique, it is believed that the model can be applied to many groundwater, geothermal, gas and oil problems with conventional fluid flow simulators. However, the overall development is still in its preliminary step and further considerations needs to be incorporated to be a viable and practical prediction technique including multi-dimensional verifications, global optimization, etc. which have not been resolved in the present study.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.323-330
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• 2018

The growth of the older population is expected to further increase social problems associated with population aging, such as isolation, poverty, and depression. The emerging issues associated with the older population are also expected to provide further momentum on studies about the dwelling environment as factors that ensure the health of older people as well as improve their quality of life. Therefore, approaches for explaining the issues of the older age group should be diversified using a variety of factors and appropriate analytic tools. Studies on measuring depression have principally focused on assessing an objective self-report questionnaire, usually in a highly structured, textual form which may not reflect the cognitive impairment of older adults. The aim of this study was to define and measure dwelling depression among older adults in Korea. There are two specific hypotheses in this study as follows: (a) there will be statistically significant relationships with dwelling dissatisfaction and depression, and (b) dwelling depression tools containing text and images will be, respectively, assessment tools that have a good construct with content validity and reliability. In the first experiment, to define and measure dwelling depression, 301 people over 65 years old living in single and two-person households were surveyed using a text-based dwelling depression questionnaires from September 1-30, 2017. In the second experiment, to examine whether the projective image questionnaire could serve as a suitable replacement for the text-based questionnaires, the same participants were surveyed from January 22 to February 2, 2018. The results show that depression has a close correlation with dwelling dissatisfaction. In addition, the geriatric dwelling depression index (GDDI) based on the projective image was refined. Additionally, the projective image questionnaire has a close correlation with the text-based questionnaire. Finally, through ROC curve analysis, it was found that the projective image questionnaire can accurately predict a depression group. To this end, this preliminary study examined the validity of the projective image questionnaire in older adults to make this instrument feasible for older populations and to contribute to a profound understanding of geriatric depression due to the living environment. We hope they will provide a basis for further research on psychological diagnoses using projective images.

• Journal of the Society of Naval Architects of Korea
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• v.56 no.4
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• pp.361-372
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• 2019

The flow pattern of air layers and skin-friction drag reduction by air injection are investigated to find the suitable multiphase flow model using unstructured finite-volume CFD solver for the Reynolds-averaged Navier-Stokes equations. In the present computations, two different multiphase flow modeling approaches, such as the Volume of Fluid (VOF) and the Eulerian Multi-Phase (EMP), are adopted to investigate their performances in resolving the two-phase flow pattern and in estimating the frictional drag reduction. First of all, the formation pattern of air layers generated by air injection through a circular opening on the bottom of a flat plate are investigated. These results are then compared with those of MMkiharju's experimental results. Subsequently, the quantitative ratios of skin-friction drag reduction including the behavior of air layers, within turbulent boundary layers in large scale and at high Reynolds number conditions, are investigated under the same conditions as the model test that has been conducted in the US Navy's William B. Morgan Large Cavitation Channel (LCC). From these results, it is found that both VOF and EMP models have similar capability and accuracy in capturing the topology of ventilated air cavities so called'air pockets and branches'. However, EMP model is more favorable in predicting quantitatively the percentage of frictional drag reduction by air injection.