• Journal of Environmental Impact Assessment
• /
• v.15 no.6
• /
• pp.357-372
• /
• 2006

The excessive land activities in farming can cause soil erosion, inundation by a flood, and fallow. So far land evaluation has been analyzed using the land use limitation derived from the excessive land activities. This study was done for evaluating the agricultural fields by using 3 land use limitations, inundation potential, soil erodibility potential, and fallow potential. The study area is Ibang-myeon, Changnyeong-gun, Gyeongnam-province, Korea. A logistic regression model was applied to recognize the inundation potential by a flood in the Nakdong river basin. And potential soil erodibility index (PSEI) was derived from USLE model to analyze the soil erodibility potential. And a probability model from a logistic regression model was applied to detect the fallow potential. Therefore, we found 220.7ha for the 4th grade and 86.1ha for the 5th grade was analyzed as water damage potential. Large area near Nakdong river have problem to grow the rice due to the damage by water inundation. And 213.6ha for the 3rd grade and 103.3ha for 4th grade was detected as a result of the analysis of soil erosion potential. The soil erosion potential was high when within-field integrity of soil was not stable, or the kinetic energy was high or the slope length was long due to a steep slope of a specific land. And 869.1ha for 3rd grade, 174.9ha for 4th grade, and 110.6ha for 5th grade was detected to be distributed having the fallow potential. Especially, a village, having a steep mountain, had 249.5ha for the 3rd grade, which was 28.7% of total area showing the 3rd grade. Finally, Three villages, including An-ri, Geonam-ri, Songgok-ri, showed they had largest area of the suitable land in the study area. These villages had similar topographic condition where they were far from Nakdong river, and they had relatively higher elevation and flat lands.

• Earthquakes and Structures
• /
• v.5 no.5
• /
• pp.499-526
• /
• 2013

Seismic isolation is an effective method for the protection of buildings and their contents during strong earthquakes. This research work aims to assess the appropriateness of the linear and nonlinear models that can be used in the analysis of typical low-rise base isolated steel buildings, taking into account the inherent nonlinearities of the isolation system as well as the potential nonlinearities of the superstructure in case of strong ground motions. The accuracy of the linearization of the isolator properties according to Eurocode 8 is evaluated comparatively with the corresponding response that can be obtained through the nonlinear hysteretic Bouc-Wen constitutive model. The suitability of the linearized model in the determination of the size of the required seismic gap is assessed, under various earthquake intensities, considering relevant methods that are provided by building codes. Furthermore, the validity of the common assumption of elastic behavior for the superstructure is explored and the alteration of the structural response due to the inelastic deformations of the superstructure as a consequence of potential collision to the restraining moat wall is studied. The usage of a nonlinear model for the isolation system is found to be necessary in order to achieve a sufficiently accurate assessment of the structural response and a reliable estimation of the required width of the provided seismic gap. Moreover, the simulations reveal that the superstructure's inelasticity should be taken into account, especially if the response of the structure under high magnitude earthquakes is investigated. The consideration of the inelasticity of the superstructure is also recommended in studies of structural collision of seismically isolated structures to the surrounding moat wall, since it affects the response.

• Informatization Policy
• /
• v.20 no.4
• /
• pp.23-50
• /
• 2013

The main purpose of this study is to empirically examine and to develop the optimal model about an influential relationship between the types of source-based trust and knowledge sharing of local government officials. Procedural and distributive justice-based calculative trust in organization, cognition-based trust in organization, cognition-based trust in supervisor, cognition-based trust in coworkers, and emotion-based trust in coworkers were set up as independent variables of this research model, and sharing of tacit knowledge and explicit knowledge based on the knowledge content as dependent variables. The research results shows that the suitability of each model has approximate value to the required level, and that emotion-based trust in coworkers significantly affects knowledge sharing for both the individual and integrated factors in hypothetical influential relationship. This study is expected to help to enable knowledge sharing in various situations by dividing the concepts of trust that affect knowledge sharing into a few types, and deriving the influential model of knowledge sharing by types.

• Journal of the Korean Geotechnical Society
• /
• v.34 no.4
• /
• pp.27-35
• /
• 2018

The objective of this study is to demonstrate the suitability of electromagnetic waves for evaluating necking defects in bored piles using electromagnetic waves. Experiments are conducted with small-scaled defective model pile with diameter of 150 mm and length of 270 mm. Two necking defects are generated at the upper and lower positions on two different sides of the model pile, respectively. The other two necking defects are generated at the upper and lower positions on the same side of the model pile. Electrical wires are installed alongside the stainless steel wire of a steel cage to configure a two-conductor transmission line. A time-domain reflectometer is used to generate and defect electromagnetic waves. The experimental results show that electromagnetic waves are reflected at the necking defects and the end of the model pile. In addition, calculated defect locations are almost the same as actual defect locations. This study demonstrates that electromagnetic waves can be effective tool for evaluating necking defects in bored piles.

• Journal of Korea Spatial Information System Society
• /
• v.9 no.1
• /
• pp.15-30
• /
• 2007

The purpose of this study is to explore essential factors of influencing user's usage intentions on telematics services and to find relationships among factors. This study derives several variables and hypotheses through literature reviews on the extended research model based on Davis's Technology Acceptance Model. With the objective of statistical verification, derived variables were sorted into meaningful categories through various statistical packages. These were included multiple regression analysis to improve the reliability of survey data. The demand analysis was conducted by targeting on users who have previously experienced telematics services. Indicated analyzed results which 'suitability', 'localization', and 'instant connectivity' variables were positively related to the user's usage intentions, especially accuracy of information variable. The factors of influencing the usage intention on telematics services can be useful empirical data in order to analyze the market trends and to suggest industrial or political guideline of telematics services.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.21 no.2
• /
• pp.39-51
• /
• 2018

Long-term unexecuted urban parks will be released from urban planning facilities after 2020, this may result in development of those parks. However, little research have been focused on how to develop those parks considering conservation, development, spatial pattern, and so on. Therefore, in this study, we suggested an optimization planning model that minimizes the fragmentation while maximizing the conservation and development profit using ACO (Ant Colony Optimization). Our study area is Suwon Yeongheung Park, which is long-term unexecuted urban parks and have actual plan for private development in 2019. Using our optimization planning model, we obtained four alternatives(A, B, C, D), all of which showed continuous land use patterns and satisfied the objectives related to conservation and development. Each alternative are optimized based on different weight combinations of conservation, development, and fragmentation, and we can also generated other alternatives immediately by adjusting the weights. This is possible because the planning process in our model is very fast and quantitative. Therefore, we expected our optimization planning model can support "spatial decision making" of various issue and sites.

• Journal of the Korea Society of Computer and Information
• /
• v.16 no.6
• /
• pp.99-109
• /
• 2011

Ubiquitous computing technology makes an impact on the appearance of u-learning and presents an advanced direction of futuristic school education. In ubiquitous learning environments, various embedded computational devices will be pervasive and interoperable across the network for supporting the learning, so users may utilize these devices anytime anywhere. An important next step for ubiquitous learning is the introduction of context-aware learning service that employing knowledge and reasoning to understand the local context and share this information in support of intelligent learning services. However, the existing studies on design and application of ontology context model to support context-aware service in actual school environments are incomplete state. This paper, therefore, suggests a scheme of constructing ubiquitous learning space for existing school network by introducing USN to support context-aware ubiquitous learning services. This paper, also, designs an ontology based context model for ubiquitous school environments which describes context information through OWL. To determine the suitability of proposed ubiquitous learning space and ontology context model, we implement some of context-aware learning services in the ubiquitous learning environments.

• Journal of the Korean Electrochemical Society
• /
• v.23 no.4
• /
• pp.81-89
• /
• 2020

To understand the performance of the electrochemical device, the analysis of the mechanism of ionic conduction is important. However, due to the ionic interaction in the electrolyte and the complexity of the electrolyte structure, a clear analysis method of the ion conduction mechanism has not been proposed. Instead, a variety of mathematical models have been devised to explain the mechanism of ion conduction, and this review introduces the Arrhenius and Vogel-Tammann-Fulcher (VTF) model. In general, the above two mathematical models are used to describe the temperature dependence of the transport properties of electrolytes such as ionic conductivity, diffusion coefficient, and viscosity, and a suitable model can be determined through the linearity of the graph consisting of the logarithm of the moving property and the reciprocal of the temperature. Currently, many electrolyte studies are evaluating the suitability of the above two models for electrolytes by varying the composition and temperature range, and the ion conduction mechanism analysis and activation energy calculation are in progress. However, since there are no models that can accurately describe the transport properties of electrolytes, new models and improvement of existing models are needed.

• Journal of Information Technology Services
• /
• v.18 no.2
• /
• pp.143-159
• /
• 2019

Machine learning (ML) is a method of fitting given data to a mathematical model to derive insights or to predict. In the age of big data, where the amount of available data increases exponentially due to the development of information technology and smart devices, ML shows high prediction performance due to pattern detection without bias. The feature engineering that generates the features that can explain the problem to be solved in the ML process has a great influence on the performance and its importance is continuously emphasized. Despite this importance, however, it is still considered a difficult task as it requires a thorough understanding of the domain characteristics as well as an understanding of source data and the iterative procedure. Therefore, we propose methods to apply deep learning for solving the complexity and difficulty of feature extraction and improving the performance of ML model. Unlike other techniques, the most common reason for the superior performance of deep learning techniques in complex unstructured data processing is that it is possible to extract features from the source data itself. In order to apply these advantages to the business problems, we propose deep learning based methods that can automatically extract features from transaction data or directly predict and classify target variables. In particular, we applied techniques that show high performance in existing text processing based on the structural similarity between transaction data and text data. And we also verified the suitability of each method according to the characteristics of transaction data. Through our study, it is possible not only to search for the possibility of automated feature extraction but also to obtain a benchmark model that shows a certain level of performance before performing the feature extraction task by a human. In addition, it is expected that it will be able to provide guidelines for choosing a suitable deep learning model based on the business problem and the data characteristics.

• Journal of Convergence for Information Technology
• /
• v.11 no.3
• /
• pp.107-124
• /
• 2021

This study is a study on the innovation resistance that may arise in connection with the introduction and use of smart factory-related technologies by SMEs. It is to study the effect of the leading factors of innovation resistance on innovation resistance and the effect of innovation resistance on use intention by using the extended innovation resistance model. A total of 176 survey data were used for the study, and the study was conducted using SPSS 25 and Smart PLS 2.0. Relative advantage, suitability, perceived risk, social impact, and organizational characteristics have a significant effect on innovation resistance, and innovation resistance was tested to have a significant effect on the intention to use. As an implication according to the research, a plan to improve the level of introduction and use of smart factories using the expanded innovative storage model was presented by dividing positive and negative factors, and factors that should be improved and factors that should be reduced are presented. It was specifically presented.