• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.3260-3269
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• 2014

The construction industry has strong ties with other industries, and so construction company insolvency also has a strong influence on other industries. Prediction models addressing the insolvency of construction company have been well studied. Although factors contributing to insolvency must precede those of predictions of insolvency, studies on these contributing factors are limited. The purpose of this study is to analyze the influence of changes in the housing market on construction company insolvency by using the Vector Error Correction Model. Construction companies were divided into two groups, and the expected default frequency(EDF), which indicates insolvency of each company was measured through the KMV model. The results verified that 10 largest construction companies were in a better financial condition compared to relatively smaller construction companies. As a result of conducting impulse response analysis, the EDF of large companies was found to be more sensitive to housing market change than that of small- and medium-sized construction companies.

• Journal of Korean Society of Transportation
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• v.32 no.4
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• pp.369-379
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• 2014

The Statistical regression model has been used to construct crash prediction models, despite its limitations in assuming data distribution and functional form. In response to the limitations associated with the statistical regression models, a few studies based on non-parametric methods such as neural networks have been proposed to develop crash prediction models. However, these models have a major limitation in that they work as black boxes, and therefore cannot be directly used to identify the relationships between crash frequency and crash factors. A genetic programming model can find a solution to a problem without any specified assumptions and remove the black box effect. Hence, this paper investigates the application of the genetic programming technique to develope the crash prediction model. The data collected from the Gyeongbu expressway during the past three years (2010-2012), were separated into straight and curve sections. The random forest technique was applied to select the important variables that affect crash occurrence. The genetic programming model was developed based on the variables that were selected by the random forest. To test the goodness of fit of the genetic programming model, the RMSE of each model was compared to that of the negative binomial regression model. The test results indicate that the goodness of fit of the genetic programming models is superior to that of the negative binomial models.

• Journal of Veterinary Clinics
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• v.36 no.1
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• pp.7-14
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• 2019

In South Korea, six large outbreaks of highly pathogenic avian influenza (HPAI) have occurred since the first confirmation in 2003 from chickens. For the past 15 years, HPAI outbreaks have become an annual phenomenon throughout the country and has extended to wider regions, across rural and urban environments. An understanding of the spatial epidemiology of HPAI occurrence is essential in assessing and managing the risk of the infection; however, local spatial variations of relationship between HPAI incidences in Korea and related risk factors have rarely been derived. This study examined whether spatial heterogeneity exists in this relationship, using a geographically weighted Poisson regression (GWPR) model. The outcome variable was the number of HPAI-positive farms at 252 Si-Gun-Gu (administrative boundaries in Korea) level notified to government authority during the period from January 2014 to April 2016. This response variable was regressed to a set of sociodemographic and topographic predictors, including the number of wild birds infected with HPAI virus, the number of wintering birds and their species migrated into Korea, the movement frequency of vehicles carrying animals, the volume of manure treated per day, the number of livestock farms, and mean elevation. Both global and local modeling techniques were employed to fit the model. From 2014 to 2016, a total of 403 HPAI-positive farms were reported with high incidence especially in western coastal regions, ranging from 0 to 74. The results of this study show that local model (adjusted R-square = 0.801, AIC = 954.5) has great advantages over corresponding global model (adjusted R-square = 0.408, AIC = 2323.1) in terms of model fitting and performance. The relationship between HPAI incidence in Korea and seven predictors under consideration were significantly spatially non-stationary, contrary to assumptions in the global model. The comparison between global Poisson and GWPR results indicated that a place-specific spatial analysis not only fit the data better, but also provided insights into understanding the non-stationarity of the associations between the HPAI and associated determinants. We demonstrated that an empirically derived GWPR model has the potential to serve as a useful tool for assessing spatially varying characteristics of HPAI incidences for a given local area and predicting the risk area of HPAI occurrence. Considering the prominent burden of HPAI this study provides more insights into spatial targeting of enhanced surveillance and control strategies in high-risk regions against HPAI outbreaks.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.5
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• pp.23-29
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• 2015

In this study, human is the subject of driving a car, the actual EEG is a biological information in a number of reactions that are displayed while driving the vehicle by using a measuring device, occurs during travel of the road EEG to be collected, number of experiments the collected material on the basis of changes associated with running time, extracts the factors such as changes due to road geometry, and analysis was performed. The required changes in the EEG occurring during traveling experiment analysis alpha (${\alpha}$) waves, beta (${\beta}$) wave, after the primary extraction in the form of gamma (${\gamma}$) faction, the brain wave frequency of the entire period of the experiment change rate extracts, to calculate the change in frequency in response to EEG characteristics by applying the regression model to observe a learning effect in response to an increase in the number of experiments, as a result, depending on the number of experiments, EEG changes due to individual differences. The show, by repeatedly driving a section like this, it was possible to verify that comfortably travels driver accustomed in accordance with the stored road geometry and signal, safety facilities.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.119-125
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• 2020

Research on high-attenuation concrete for the vibration reduction performance by mixing epoxy-based synthetic resins and aggregates is actively being conducted. The curing time of high-attenuation concrete is very short because water is not used, and the physical and dynamic properties are very excellent. therefore, it is expected to be widely used in building structures requiring reduction of interior-floor noise and vibration. Furthermore, A way to expand the applicability of the high-damping concrete mixed with polymer in the field of reinforcement material have been variously studied. In order to replace polymer concrete with ordirnary concrete and existing anti-vibration reinforcement material, it is necessary to review overall vibration reduction performance considering physical properties, dynamic properties, productivity and field applicability. In this study, the physical and dynamic properties of polymer concrete by epoxy mixing ratio compared with ordirnary concrete. As a result, the elastic modulus was similar. On the other hand, polymer concrete for the compressive, tensile, and flexural strengths was quite more excellent. In particular, the measured tensile strength of polymer concrete was 4-10 times higher than that of ordirnary concrete. it was a big difference, and the frequency response function and damping ratio was studied through modal test and finite element analysis model. The dynamic stiffness of polymer concrete was 20% greater than that of ordirnary concrete, and the damping ratio of polymer concrete was approximately 3 times more than that of ordirnary concrete.

• Korean Security Journal
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• no.62
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• pp.35-63
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• 2020

As the frequency and intensity of catastrophic disasters increase, there is widespread public sentiment that government capacity for disaster response and recovery is fundamentally limited, and that the involvement of civil society and the private sector is ever more vital. That is, in order to strengthen national disaster response capacity, governments need to build disaster systems that are more participatory and function through the channels of civil society, rather than continuing themselves to bear sole responsibility for these "wicked problems." With the advancement of smart mobile technology and social media, government and society as a whole have been called upon to apply these new information and communication technologies to address the current shortcomings of government-led disaster management. As illustrated in such catastrophic disasters as the 2011 Tohoku earthquake and tsunami in Japan, the 2010 Haitian earthquake, and Hurricane Katrina in the United States in 2005, the realization of participatory potential of smart technologies for better disaster response has enabled citizen participation via new smart technologies during disasters and resulted in positive impact on the management of such disasters. In this context, this study focuses on the South Korean context, and aims to analyze Korean government officials' readiness for public participation using smart technologies. On this basis, it aims to offer policy suggestions aimed at promoting smart technology-enabled citizen participation. For this purpose, it proposes a particular model, termed SMART (System, Motivation, Ability, Response, and Technology).

• Smart Structures and Systems
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• v.20 no.1
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• pp.61-74
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• 2017

One of the most reliable and simplest tools for structural vibration control in civil engineering is Tuned Mass Damper, TMD. Provided that the frequency and damping parameters of these dampers are tuned appropriately, they can reduce the vibrations of the structure through their generated inertia forces, as they vibrate continuously. To achieve the optimal parameters of TMD, many different methods have been provided so far. In old approaches, some formulas have been offered based on simplifying models and their applied loadings while novel procedures need to model structures completely in order to obtain TMD parameters. In this paper, with regard to the nonlinear decision-making of fuzzy systems and their enough ability to cope with different unreliability, a method is proposed. Furthermore, by taking advantage of both old and new methods a fuzzy system is designed to be operational and reduce uncertainties related to models and applied loads. To design fuzzy system, it is required to gain data on structures and optimum parameters of TMDs corresponding to these structures. This information is obtained through modeling MDOF systems with various numbers of stories subjected to far and near field earthquakes. The design of the fuzzy systems is performed by three methods: look-up table, the data space grid-partitioning, and clustering. After that, rule weights of Mamdani fuzzy system using the look-up table are optimized through genetic algorithm and rule weights of Sugeno fuzzy system designed based on grid-partitioning methods and clustering data are optimized through ANFIS (Adaptive Neuro-Fuzzy Inference System). By comparing these methods, it is observed that the fuzzy system technique based on data clustering has an efficient function to predict the optimal parameters of TMDs. In this method, average of errors in estimating frequency and damping ratio is close to zero. Also, standard deviation of frequency errors and damping ratio errors decrease by 78% and 4.1% respectively in comparison with the look-up table method. While, this reductions compared to the grid partitioning method are 2.2% and 1.8% respectively. In this research, TMD parameters are estimated for a 15-degree of freedom structure based on designed fuzzy system and are compared to parameters obtained from the genetic algorithm and empirical relations. The progress up to 1.9% and 2% under far-field earthquakes and 0.4% and 2.2% under near-field earthquakes is obtained in decreasing respectively roof maximum displacement and its RMS ratio through fuzzy system method compared to those obtained by empirical relations.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.680-689
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• 2011

A dynamic analysis procedure is developed to provide a comprehensive estimation of the dynamic response spectrum for locomotive's wheels running over a Pre-Stressed Concrete (PSC) box girder bridge on the Korea high speed railway. The wheel force spectrum with the bridge behavior are analyzed as the dynamic procedure for various running speeds (50~450km/h). The high-speed railway locomotive (KTX) is used as 38-degree of freedom system. Three displacements(vertical, lateral, and longitudinal) and three rotational components (pitching, rolling, and yawing). For one car-body and two bogies as well as five movements except pitching rotation components for four wheel axes forces are considered in the 38-degree of freedom model. Three dimensional frame element is used to model of the PSC box girder bridges, simply supported span length of 40m. The irregulation of rail-way is derived using the exponential spectrum density function under assumption of twelve level tracks conditions based on the normal probability procedure. The dynamic responses of bridge passing through the railway locomotive with high-speed analyzed by Newmark-${\beta}$ method and Runge-Kutta method are compared and contrasted considering the developed models of bridge, track and locomotive comprehensively. The dynamic analyses of wheel forces by Runge-Kutta method which are able to analyze the forces with high frequency running on the bridge and ground rail-way are conducted. Additionally, wheel forces spectrum and three rotational components of vehicle body for three typical running speeds is also presented.

• Journal of Digital Convergence
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• v.16 no.9
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• pp.405-412
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• 2018

When a film company decides whether to invest or not in a scenario is the appropriate time to predict box office success. In response to market demands, AI based scenario analysis service has been launched, yet the algorithm is by no means perfect. The purpose of this study is to present a prediction model of movie scenario's box office hit based on human brain processing mechanism. In order to derive patterns of visual, auditory, and cognitive stimuli on the time spectrum of box office animation hit, this study applied Weber's law and brain mechanism. The results are as follow. First, the frequency of brain stimulation in the biggest box office movies was 1.79 times greater than that in the failure movies. Second, in the box office success, the cognitive stimuli codes are spread evenly, whereas in the failure, concentrated among few intervals. Third, in the box office success movie, cognitive stimuli which have big cognition load appeared alone, whereas visual and auditory stimuli which have little cognitive load appeared simultaneously.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.3 s.147
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• pp.351-361
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• 2006

The fatigue strength analysis of VLFS is carried out by using a 3-dimensional plate finite element model with a zooming technology which performs the modeling of wide portions of the structure by a coarse mesh but the concerned parts by a very fine mesh of t by t level. And a stepwise substructure modeling technique for global loading conditions is applied which uses the motion response of the global structure from 2-D plate hydroelastic analysis as the enforcing nodal displacements of the concern 3-D structural zooming model. Seven incident wave angles and whole ranges of frequency domains of wave spectrum are considered. In order to consider the effect of breakwater, the modified JONSWAP wave spectrum is used. Applying the wave data of installation region, the longterm spectrum analysis is done based on stochastic process and the fatigue life of the structure is estimated. Finally some design considerations from the view point of fatigue strength analysis of VLFS are discussed.