• Journal of the Korea Society for Simulation
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• v.15 no.2
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• pp.59-69
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• 2006

Component-based software development is introduced as a new development paradigm in software development method. This approach is different from existing software development approach because it is based on reusable and autonomous unit, component. Therefore, component-based development(CBD)is divided into two stages; component development process and component assembly process; application development process. Component development process is the core of CBD because component has a key for good software. Currently many methodologies or tools have been introduced by various academies or industries. However, those don't suggest systematic and flexible modeling techniques adaptable easily into component development project. Existing approaches have a unique orarbitrary modeling technique or provide heuristic guidelines for component modeling. As a result, many component developers are faced with a difficult problems; how to developcomponent models, when develop which diagrams, and so on. In order to address this problem, we suggest a meta-model driven approach for component development in this paper. We provide meta-models according to both layer and development phase. We expect that suggested meta-models allow component developers to develop appropriate models of the time.

• International Journal of Highway Engineering
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• v.11 no.1
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• pp.165-175
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• 2009

With the current move towards adopting mechanistic-empirical concepts in the design of pavement structures, state-of-the-art mechanistic analysis methodologies are needed to determine accurate pavement responses, such as stress, strain, and deformation. Previous laboratory studies of pavement foundation geomaterials, i.e., unbound granular materials used in base/subbase layers and fine-grained soils of a prepared subgrade, have shown that the resilient responses followed by nonlinear, stress-dependent behavior under repeated wheel loading. This nonlinear behavior is commonly characterized by stress-dependent resilient modulus material models that need to be incorporated into finite element (FE) based mechanistic pavement analysis methods to predict more realistically predict pavement responses for a mechanistic pavement analysis. Developed user material subroutine using aforementioned resilient model with nonlinear solution technique and convergence scheme with proven performance were successfully employed in general-purpose FE program, ABAQUS. This numerical analysis was investigated in predicted critical responses and domain selection with specific mesh generation was implemented to evaluate better prediction of pavement responses. Results obtained from both axisymmetric and three-dimensional (3D) nonlinear FE analyses were compared and remarkable findings were described for nonlinear FE analysis. The UMAT subroutine performance was also validated with the instrumented full scale pavement test section study results from the Federal Aviation Administration's National Airport Pavement Test Facility (FAA's NAPTF).

• Korean Journal of Soil Science and Fertilizer
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• v.39 no.1
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• pp.29-37
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• 2006

In remediation of the contaminated soil, it requires to select at least more than two remediation technologies depending on the fate and transport phenomena through complicated reactions in soil matrix. Therefore, methodologies related to develop the integrated remediation technology were reviewed for agricultural soils contaminated with heavy metals. Pneumatic fracturing is necessary to implement deficiency because soil washing is not effective to remove heavy metals in the subsurface soil. But it needs to evaluate the characteristics such as essential data and factors of designated technology in order to effectively apply them in the site. In the remediation site, the important soil physical and chemical factors to be considered are hydrology, porosity, soil texture and structure, types and concentrations of the contaminants, and fate and its transport properties. However, the integrated technology can be restrictive by advective flux in the area which remediation is highly effective although both soil washing and pneumatic fracturing were applied simultaneously in the site. Therefore, we need to understand flow pathways of the target contaminants in the subsurface soils, that includes kinetic desorption and flux, predictive simulation modeling, and complicated reaction in heterogenous soil.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.8
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• pp.547-565
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• 2009

Simulation is the imitation of some real thing, state of affairs, or process. The act of simulating something generally entails identifying certain key characteristics or behaviors of a selected physical or abstract system. And a simulator is the software or hardware tool that performs simulation tasks. When developing a simulator, the non-functional requirements such as modifiability, interoperability, and extendability should be required. However, existing studies about the simulator development focus not on such non-functional requirements but on the methodologies to build the simulation model. In this paper, we suggest the new architectural pattern for the software based simulator in consideration of such non-functional requirements. In order to define the architectural pattern, we identify the essential elements of the simulators, define relationships between them, and design the architectural structure with the elements to accommodate such non-functional requirements. According to the proposed pattern we can solve the simulation problems to combine the various simulation model components. The pattern guarantees modifiability by reconstructing the simulation model, also guarantees interoperability and extendability by adding various interfaces to the simulation model and by keeping the consistent interfacing mechanism between the simulation model components. The suggested architectural pattern can be used as the reference architecture of the simulator systems that will be developed in future.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.513-524
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• 2022

Recently, detecting damages of civil infrastructures from digital images using deep learning technology became a very popular research topic. In order to adapt those methodologies to the field, it is essential to explain robustness of deep learning models. Our research points out that the existing pixel-based deep learning model evaluation metrics are not sufficient for detecting cracks since cracks have linear appearance, and proposes a new evaluation methodology to explain crack segmentation deep learning model more rationally. Specifically, we design, implement and validate a methodology to generate tolerance buffer alongside skeletonized ground truth data and prediction results to consider overall similarity of topology of the ground truth and the prediction rather than pixel-wise accuracy. We could overcome over-estimation or under-estimation problem of crack segmentation model evaluation through using our methodology, and we expect that our methodology can explain crack segmentation deep learning models better.

• Journal of Korea Trade
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• v.23 no.6
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• pp.66-92
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• 2019

Purpose - Foreign Exchange Rates (FER) have been one of the most significant factors for both Korean exporters and the economy of Korea. The purpose of this study is to evaluate whether exporters with a high level of Exchange Rate Elasticity of Sales (ERES) make the use of earnings management for Income Smoothing (IS). Design/methodology - Income smoothing was obtained using the methodology suggested by Leuz, Nanda and Wysocki (2003). Accruals-based Earnings Management (AEM) was estimated using Discretionary Accruals (DA) calculated by the operant Jones Model developed by Dechow, Sloan and Sweeney (1995). Real Earnings Management (REM) was obtained using the methodologies suggested by Roychowdhury (2006) and Cohen and Zarowin (2010). Data were 2,402 firm years of public listed companies on the KRX, which were not in the financial industry and had a settlement of accounts in December for the period from 2013 to 2017. Findings - Results of the evaluation are as follows. First, companies with higher levels of ERES have relatively lower levels of smoothing of reported income. This might be because a fluctuation in sales caused by an exchange rate fluctuation has a direct impact on the volatility of the reported income. Second, companies with high levels of both ERES and IS have a positive correlation with both AEM and REM. This might be because companies with high levels of IS engage in earnings management to smooth reported income. Specifically, it is possible to assume that for smoothing the reported income, not only AEM but also REM is practiced. Third, companies with high levels of ERES but low levels of IS have a negative correlation with both AEM and REM. This could be interpreted as companies exhibiting low levels of IS due to higher levels of ERES tend to control IS. In addition, such results were supported by firms relying highly on exporting, and are consequently sensitive to exchange rate fluctuation. Therefore, it may conclude that companies with high levels of ERES make the use of earnings management as a means of IS. Originality/value - This study can find its significance from the fact that it is the first study, empirically verifying that companies of Korea, where exportation is a large part, use both AEM and REM as a means for smoothing reported income upon facing exchange rate fluctuations. In addition, it is highly expected that the results of this study could be useful for participants of financial markets when making IS-related decisions.

• Journal of the Korea Institute of Building Construction
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• v.19 no.1
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• pp.95-103
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• 2019

Introduction and use of Building Information Modeling(BIM) in construction projects have increased steadily over the past few years. However, the level of domestic BIM utilization is still tenuous compared to the international scene. Therefore, this study aims to present the possible directions for BIM research through an analysis of research literatures in Korea as well as in foreign countries. Papers on BIM were collected for this study from Korea and foreign countries for the field of architecture, and analyses and comparisons were performed by year and field. Further, the research patterns were analyzed using WordCloud, which is one of the popular big data techniques. From the analysis, it is found that the design field still constitutes the largest component of research, but the construction field is actively developing as well. In addition, it is realized that domestic BIM research continues to grow on collaboration and environment-friendly methodologies since 2012; it is also demonstrated that foreign BIM research has undergone changes in research trends every year including recently, and is progressing actively. Therefore, this study concludes that it is necessary to actively conduct research in the field of Industry Foundation Class(IFC) in the future. The results of this study can further be used as reference data for conducting BIM studies in Korea in the future.

• Journal of Korea Trade
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• v.24 no.7
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• pp.1-28
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• 2020

Purpose - This paper empirically investigates the predictors and main determinants of consumers' ratings of mobile applications in the Google Play Store. Using a linear and nonlinear model comparison to identify the function of users' review, in determining application rating across countries, this study estimates the direct effects of users' reviews on the application rating. In addition, extending our modelling into a sentimental analysis, this paper also aims to explore the effects of review polarity and subjectivity on the application rating, followed by an examination of the moderating effect of user reviews on the polarity-rating and subjectivity-rating relationships. Design/methodology - Our empirical model considers nonlinear association as well as linear causality between features and targets. This study employs competing theoretical frameworks - multiple regression, decision-tree and neural network models - to identify the predictors and main determinants of app ratings, using data from the Google Play Store. Using a cross-validation method, our analysis investigates the direct and moderating effects of predictors and main determinants of application ratings in a global app market. Findings - The main findings of this study can be summarized as follows: the number of user's review is positively associated with the ratings of a given app and it positively moderates the polarity-rating relationship. Applying the review polarity measured by a sentimental analysis to the modelling, it was found that the polarity is not significantly associated with the rating. This result best applies to the function of both positive and negative reviews in playing a word-of-mouth role, as well as serving as a channel for communication, leading to product innovation. Originality/value - Applying a proxy measured by binomial figures, previous studies have predominantly focused on positive and negative sentiment in examining the determinants of app ratings, assuming that they are significantly associated. Given the constraints to measurement of sentiment in current research, this paper employs sentimental analysis to measure the real integer for users' polarity and subjectivity. This paper also seeks to compare the suitability of three distinct models - linear regression, decision-tree and neural network models. Although a comparison between methodologies has long been considered important to the empirical approach, it has hitherto been underexplored in studies on the app market.

• Journal of the Korea Institute of Building Construction
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• v.23 no.4
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• pp.337-348
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• 2023

The central objective of this study is to curtail the leakage of mortar or cement paste, often resultant of ill-constructed formwork, by implementing thixotropy in the formulation of high-fluidity, standard-strength concrete. When such concrete is utilized in smaller scale construction projects, instances of formwork gaps due to suboptimal construction precision may lead to significant leakage of mortar and paste, a problem not typically encountered with traditional slump-flow concrete. In this investigation, Polyvinyl Alcohol(PVA) and borax are incorporated into the concrete mixture to induce thixotropy. The experimental design includes varying methodologies for integrating PVA and borax, while assessing alterations in diverse concrete performances, including thixotropy and leakage reduction potential that simulates formwork gap conditions. Under the experimental conditions defined within this study, it was found that replacing, rather than merely adding PVA and borax, aids in averting water addition via suspensions. This approach yielded promising results in terms of concrete properties and proved efficacious in stemming leakage in concrete possessing sufficient thixotropy. Notably, when a 6% PVA suspension was substituted, a significant reduction in leakage was observed. Consequently, it is projected that construction quality can be ensured, even with lower precision formwork, by applying thixotropy to concrete through the use of PVA and borax.

• Journal of Service Research and Studies
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• v.14 no.3
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• pp.1-18
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• 2024

Recent discussions regarding smart tourism have gained significant momentum in tourism policy and industry; however, knowledge production in this research area remains fragmented and sporadic. This study aims to analyze trends in smart tourism research published in domestic KCI journals up to the end of July 2024 through a systematic literature review, proposing future research tasks to foster academic development. The analysis addresses both the quantitative and qualitative dimensions of smart tourism research, particularly focusing on tourism journals where the terms and concepts are prominent in policy and industry contexts, while also diagnosing the related research paradigms. The findings indicate that the term "smart tourism" began to prominently appear in research titles, topics, keywords, and abstracts as early as 2014. Among the 126 studies analyzed, research related to tourism constituted the largest share, accounting for 30.2%. However, due to the interdisciplinary nature of smart tourism, research has also emerged from various academic fields, including business studies, design, information communication, and computer science. Research on smart tourism has appeared in tourism journals since 2015, predominantly adopting a positivist research paradigm with an emphasis on quantitative methodologies that often utilize surveys. Additionally, the study reveals a pre-paradigm stage within smart tourism research, characterized by insufficient comprehensive conceptual and theoretical development. This stage has also restricted discussions on various ontological, epistemological, methodological, and interpretive issues. The theories mainly employed draw from established behavioral models, such as the Technology Acceptance Model, the Extended Technology Acceptance Model, and the Technology Readiness Model. Based on these findings, the study suggests future research directions for tourism scholars to determine whether smart tourism will solidify as a sustainable research topic or merely be regarded as a transient trend within tourism studies over the next decade.