• Journal of Animal Science and Technology
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• v.46 no.2
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• pp.137-144
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• 2004

Algorithms for estimating breeding values on several categorical data by using latent variables with threshold conception were developed and showed. Thresholds on each categorical trait were estimated by Newton’s method via gradients and Hessian matrix. This algorithm was developed by way of expansion of bivariate analysis provided by Quaas(2001). Breeding values on latent variables of categorical traits and observations on linear traits were estimated by preconditioned conjugate gradient(PCG) method, which was known having a property of fast convergence. Example was shown by simulated data with two linear traits and a categorical trait with four categories(CE=calving ease) and a dichotomous trait(SB=Still Birth) in threshold animal mixed model(TAMM). Breeding value estimates in TAMM were compared to those in linear animal mixed model (LAMM). As results, correlation estimates of breeding values to parameters were 0.91${\sim}$0.92 on CE and 0.87${\sim}$0.89 on SB in TAMM and 0.72~0.84 on CE and 0.59~0.70 on SB in LAMM. As conclusion, PCG method for estimating breeding values on several categorical traits with linear traits were feasible in TAMM.

• Restorative Dentistry and Endodontics
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• v.36 no.2
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• pp.98-107
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• 2011

Caries remains prevalent throughout modern society and is the main disease in the field of dentistry. Although studies of this disease have used diverse methodology, recently, X-ray microtomography has gained popularity as a non-destructive, 3-dimensional (3D) analytical technique, and has several advantages over the conventional methods. According to X-ray source, it is classified as monochromatic or polychromatic with the latter being more widely used due to the high cost of the monochromatic source despite some advantages. The determination of mineral density profiles based on changes in X-ray attenuation is the principle of this method and calibration and image processing procedures are needed for the better image and reproducible measurements. Using this tool, 3D reconstruction is also possible and it enables to visualize the internal structures of dental caries. With the advances in the computer technology, more diverse applications are being studied, such automated caries assessment algorithms.

• Journal of Korean Society of Steel Construction
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• v.19 no.5
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• pp.515-526
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• 2007

In this study, the models and methods for the safety assessment of Steel-Concrete Hybrid Cable-Stayed Bridge, which consists of steel composite girder and concrete girder erected by the FCM(Free Cantilever Method) and FSM(Full Staging Method) are proposed for the assurance of structural safety and the prevention against bridge collapse during construction. By the structural reliability approach that reasonably considers the uncertainties associated with the resistance and the load effect, the resistance and the load distribution characteristics of Steel-Concrete Hybrid Cable-Stayed Bridgeare defined and the strength limit state equations of permanent structures and temporary structures during construction are suggested. An AFOSM algorithm and MCS technique are used for the reliability analysis of cables, pylons, girders, steel-concrete conjunction part and temporary bents. Also, component reliability analyses are performed at the construction stages based on the structural system model. To demonstrate their rationality and practicality, the proposed models and approaches are applied to a real bridge. The sensitivity analyses of main parameters are performed in order to identify the critical factors that control the safety of similar bridges. As a result, it may be stated that the proposed models could be implemented as a rational and practical approach for the safety assessment of Steel-Concrete Hybrid Cable-stayed bridges erected by FCM and FSM during construction.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.67-80
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• 2005

In this paper, the primary objective of the research are to review the methods currently avaliable for estimating the delay incurred by vehicles at signalized intersections. The paper compares the delay estimates from a deterministic queueing model, a model based on shock wave theory , the steady-state Webster model, the queue-based models defined in the 1994 and 2001 version of the High way Capacity Manual, in addition to the delays estimated from the TRANSYT-7F macroscopic simulation and NETSIM microscopic simulation. More especially, this paper is to compare the delay estimates obtained using macroscopic and microscopic simulation tools against state-of-the practice analytical models that are derived from deterministic queueing and shock wave analysis theory. The results of the comparisons indicate that all delay models produce relatively similar results for signalized intersections with low traffic demand, but that increasing differences occur as the traffic demand approaches saturation. In particular, when the TRANSYT-7F and NETSIM are compared, it is highly differences as approach for traffic condition to over-saturation. Also, the NETSIM microscopic simulation is the lowest estimates among the various models.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.559-569
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• 2008

The Geostationary Ocean Color Imager (GOCI) on board the Communication Ocean Meteorological Satellite (COMS), the first geostationary ocean color sensor, requires accurate atmospheric correction since its eight bands are also affected by atmospheric constituents such as gases, molecules and atmospheric aerosols. Unlike gases and molecules in the atmosphere, aerosols can interact with sunlight by complex scattering and absorption properties. For the purpose of qualified ocean remote sensing, understanding of aerosol-radiation interactions is needed. In this study, we show micro-physical and optical properties of aerosols using the Optical Property of Aerosol and Cloud (OPAC) aerosol models. Aerosol optical properties, then, were used to analysis the relationship between theoretical satellite measured radiation from radiative transfer calculations and aerosol optical thickness (AOT) under various environments (aerosol type and loadings). It is found that the choice of aerosol type makes little different in AOT retrieval for AOT<0.2. Otherwise AOT differences between true and retrieved increase as AOT increases. Furthermore, the differences between the AOT and angstrom exponent from standard algorithms and this study, and the comparison with ground based sunphotometer observations are investigated. Over the northeast Asian region, these comparisons suggest that spatially averaged mean AOT retrieved from this study is much better than from standard ocean color algorithm. Finally, these results will be useful for aerosol retrieval or atmospheric correction of COMS/GOCI data processing.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.885-901
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• 2021

This paper illustratesthe impact of the temporal gap between satellite images and targetsize in mesoscale atmospheric motion vector (AMV) algorithm. A test has been performed using GEO-KOMPSAT-2A (GK2A) rapid-scan data sets with a temporal gap varying between 2 and 10 minutes and a targetsize between 8×8 and 40×40. Resultsshow the variation of the number of AMVs produced, mean AMV speed, and validation scores as a function of temporal gap and target size. As a results, it was confirmed that the change in the number of vectors and the normalized root-mean squared vector difference (NRMSVD) became more pronounced when smaller targets are used. In addition, it was advantageous to use shorter temporal gap and smaller target size for the AMV calculation in the lower layer, where the average speed is low and the spatio-temporal scale of atmospheric phenomena is small. The temporal gap and the targetsize are closely related to the spatial and temporalscale of the atmospheric circulation to be observed with AMVs. Thus, selecting the target size and temporal gap for an optimum calculation of AMVsrequires considering them. This paper recommendsthat the optimized configuration to be used operationally for the near-real time analysis of mesoscale meteorological phenomena is 4-min temporal gap and 16×16 pixel target size, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.594-600
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• 2021

Curved beam structures are generally used as components in structures such as railroad bridges and vehicles. The stability analysis of curved beams has been studied by a large number of researchers. Due to the complexities of structural components, it is difficult to obtain an analytical solution for any boundary conditions. In order to overcome these difficulties, the differential quadrature method (DQM) has been applied for a large number of cases. In this study, DQM was used to solve the complicated partial differential equations for buckling analysis of curved beams. The governing differential equation was deduced and solved for beams subjected to uniformly distributed radial loads. Critical loads were calculated with various opening angles, boundary conditions, and parameters. The results of the DQM were compared with exact solutions for available cases, and the DQM gave outstanding accuracy even when only a small number of grid points was used. Critical loads were also calculated for the in-plane inextensional buckling of the asymmetric curved beams, and two theories were compared. The study of a beam with extensibility of the arch axis shows that the effects on the critical loads are significant.

• Journal of IKEEE
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• v.23 no.2
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• pp.438-447
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• 2019

As the IoT-based hyper-connected society grows, public-key cryptosystem such as RSA is frequently used for encryption, authentication, and digital signature. Public-key cryptosystem use very large (safe) prime numbers to ensure security against malicious attacks. Even though the performance of the device has greatly improved, the generation of a large (safe)prime is time-consuming or memory-intensive. In this paper, we propose ET-MR and ET-MR-MR using Euler sieve so it runs faster while using less memory. We present a running time prediction model by probabilistic analysis and compare time and memory of our method with conventional methods. Experimental results show that the difference between the expected running time and the measured running time is less than 4%. In addition, the fastest running time of ET-MR is 36% faster than that of TD-MR, 8.5% faster than that of DT-MR and the fastest running time of ET-MR-MR is 65.3% faster than that of TD-MR-MR and similar to that of DT-MR-MR. When k=12,381, the memory usage of ET-MR is 2.7 times more than that of DT-MR but 98.5% less than that of TD-MR and when k=65,536, the memory usage of ET-MR-MR is 98.48% less than that of TD-MR-MR and 92.8% less than that of DT-MR-MR.

• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.229-250
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• 2022

Since the publication of Markowitz's (1952) mean-variance portfolio model, research on portfolio optimization has been conducted in many fields. The existing mean-variance portfolio model forms a nonlinear convex problem. Applying Dantzig's linear programming method, it was converted to a linear form, which can effectively reduce the algorithm computation time. In this paper, we proposed a Dantzig perturbation portfolio model that can reduce management costs and transaction costs by constructing a portfolio with stable and small (sparse) assets. The average return and risk were adjusted according to the purpose by applying a perturbation method in which a certain part is invested in the existing benchmark and the rest is invested in the assets proposed as a portfolio optimization model. For a covariance estimation, we proposed a Gaussian kernel weight covariance that considers time-dependent weights by reflecting time-series data characteristics. The performance of the proposed model was evaluated by comparing it with the benchmark portfolio with 5 real data sets. Empirical results show that the proposed portfolios provide higher expected returns or lower risks than the benchmark. Further, sparse and stable asset selection was obtained in the proposed portfolios.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.1
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• pp.56-61
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• 2022

In this paper, we classify and present AI algorithms and natural language processing methods used in chatbots. A framework that can be used to implement a chatbot is also described. A chatbot is a system with a structure that interprets the input string by constructing the user interface in a conversational manner and selects an appropriate answer to the input string from the learned data and outputs it. However, training is required to generate an appropriate set of answers to a question and hardware with considerable computational power is required. Therefore, there is a limit to the practice of not only developing companies but also students learning AI development. Currently, chatbots are replacing the existing traditional tasks, and a practice course to understand and implement the system is required. RNN and Char-CNN are used to increase the accuracy of answering questions by learning unstructured data by applying technologies such as deep learning beyond the level of responding only to standardized data. In order to implement a chatbot, it is necessary to understand such a theory. In addition, the students presented examples of implementation of the entire system by utilizing the methods that can be used for coding education and the platform where existing developers and students can implement chatbots.