• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.6
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• pp.445-452
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• 2014

This paper discusses the multifrontal direct solution method with out of core storage for large scale structural analysis in a limited computing resource. Large scale structural analysis requires huge amount of memory space and computation, so out of core solution method is needed in limited computing resource. In this research, out of core multifrontal solution algorithm which utilize the small size of physical memory and minimize the amount of access of low speed out of core storage is introduced. Three ideas, which are stack space in lower trianglar part of square factorization matrix, inverse stack data structure and selective data caching and recovery by data block size, are proposed.

• Journal of KIISE:Databases
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• v.29 no.6
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• pp.441-452
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• 2002

If continuous moving objects are managed by conventional database, it is not possible for them to store all position information changed over time in the database. Therefore, a time period of regular rate is determined and position information of moving objects are discretely stored in the system for every time period. However, if continuous moving objects are managed as discrete model, we will have problems which cannot properly answer to the query about uncertain past or future position information. To solve this problem, in this paper, we propose the method and algorithm which use the history information stored in the same database, to estimate the past or future location of moving objects. The cubic spline interpolation is used to estimate the past location and the mean movement value of the history information is used to predict the future location of moving objects. Finally, from the location estimation experimentation of using virtual trajectory and location sample, we proved that the proposed cubic spline function has less error than the linear function.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6B
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• pp.585-594
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• 2009

Efficient filtering is an important factor in RFID system performance. Because of huge volume of tag data in future ubiquitous environment, if RFID readers transmit tag data without filtering to upper-layer applications, which results in a significant system performance degradation. In this paper, we provide an efficient filtering technique which operates on RFID air protocol. RFID air protocol filtering between tags and a reader has some advantages over filtering in readers and middleware, because air protocol filtering reduces the volume of filtering work before readers and middleware start filtering. Exploiting the air protocol filtering advantage, we introduce a geometrical algorithm for generating air protocol filters and verify their performance through simulation with analytical time models. Results of dense RFID reader environment show that air protocol filtering algorithms reduce almost a half of the total filtering time when compared to the results of linear search.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.124-131
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• 2000

In this study, the NEURAL NETWORK (hereinafter referred to as NN) was applied to control of the nonlinear factors for turning movement of the crawler vehicle and experiment was carried out using a small model of crawler vehicle in order to inspect an application of NN. Furthermore, CHAOS NEURAL NETWORK (hereinafter referred to as CNN) was also applied to this control so as to compare with conventional NN. CNN is especially effective for plane in many variables with local minimum which conventional NN is apt to fall into, and it is relatively useful to nonlinear factors. Experiment of turning on the slope of crawler vehicle was performed in order to estimate an adaptability of nonlinear problems by NN and CNN. The inclination angles of the road surface which the vehicles travel on, were respectively 4deg, 8deg, 12deg. These field conditions were selected by the object for changing nonlinear magnitude in turning phenomenon of vehicle. Learning of NN and CNN was carried out by referring to positioning data obtained from measurement at every 15deg in turning. After learning, the sampling data at every 15deg were interpolated based on the constructed learning system of NN and CNN. Learning and simulation programs of NN and CNN were made by C language ("Association of research for algorithm of calculating machine (1992)"). As a result, conventional NN and CNN were available for interpolation of sampling data. Moreover, when nonlinear intensity is not so large under the field condition of small slope, interpolation performance of CNN was a little not so better than NN. However, when nonlinear intensity is large under the field condition of large slope, interpolation performance of CNN was relatively better than NN.

• The Journal of the Korea Contents Association
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• v.8 no.5
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• pp.276-286
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• 2008

In this paper, we introduce an adaptive e-Learning system for engineering mathematics which is based on computer algebra system (Mathematica) and on-line authoring environment. The system provides an assessment tool for individual diagnosis using Bayesian inference network. Using this system, an instructor can easily develop mathematical web contents via web interface. Examples of such content development are illustrated in the area of linear algebra, differential equation and discrete mathematics. The diagnostic module traces a student's knowledge level based on statistical inference using the conditional probability and Bayesian updating algorithm via Netica. As part of formative evaluation, we brought this system into real university settings and analyzed students' feedback using survey.

• Korea-Australia Rheology Journal
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• v.13 no.1
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• pp.29-35
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• 2001

The development of filament stretching extensional rheometers over the past decade has enabled the systematic measurement of the transient extensional stress growth in dilute and semi-dilute polymer solutions. The strain-hardening in the extensional viscosity of dilute solutions overwhelms the perturbative effects of capillarity, inertia & gravity and the kinematics of the extensional deformation become increasingly homogeneous at large strains. This permits the development of a robust open-loop control algorithm for rapidly realizing a deformation with constant stretch history that is desired for extensional rheometry. For entangled fluids such as concentrated solutions and melts the situation is less well defined since the material functions are governed by the molecular weight between entanglements, and the fluids therefore show much less pronounced strain-hardening in transient elongation. We use experiments with semi-dilute/entangled and concentrated/entangled monodisperse polystyrene solutions coupled with time-dependent numerical computations using nonlinear viscoelastic constitutive equations such as the Giesekus model in order to show that an open-loop control strategy is still viable for such fluids. Multiple iterations using a successive substitution may be necessary, however, in order to obtain the true transient extensional viscosity material function. At large strains and high extension rates the extension of fluid filaments in both dilute and concentrated polymer solutions is limited by the onset of purely elastic instabilities which result in necking or peeling of the elongating column. The mode of instability is demonstrated to be a sensitive function of the magnitude of the strain-hardening in the fluid sample. In entangled solutions of linear polymers the observed transition from necking instability to peeling instability observed at high strain rates (of order of the reciprocal of the Rouse time for the fluid) is directly connected to the cross-over from a reptative mechanism of tube orientation to one of chain extension.

• The Korean Journal of Applied Statistics
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• v.21 no.6
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• pp.923-932
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• 2008

We are likely to face complex multivariate data which can be characterized by having a non-trivial correlation structure. For instance, omitted covariates may simultaneously affect more than one count in clustered data; hence, the modeling of the correlation structure is important for the efficiency of the estimator and the computation of correct standard errors, i.e., valid inference. A standard way to insert dependence among counts is to assume that they share some common unobservable variables. For this assumption, we fitted correlated random effect models considering multilevel model. Estimation was carried out by adopting the semiparametric approach through a finite mixture EM algorithm without parametric assumptions upon the random coefficients distribution.

• The Korean Journal of Applied Statistics
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• v.26 no.3
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• pp.453-470
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• 2013

In this paper, we consider a Bayesian analysis of the dose-effect relationship of cadmium to evaluate a benchmark dose(BMD). For this purpose, two dose-response curves commonly used in the toxicity study are fitted based on Bayesian methods to the data collected from the scientific literature on cadmium toxicity. Specifically, Bayesian meta-analysis and hierarchical modeling build an overall dose-effect relationship that use a piecewise linear model and Hill model, where the inter-study heterogeneity and inter-individual variability of dose and effect such as gender, age and ethnicity are accounted. Estimation of the unknown parameters is made by using a Markov chain Monte Carlo algorithm based user-friendly software WinBUGS. Benchmark dose estimates are evaluated for various cut-offs and compared with different tested subpopulations with with gender, age and ethnicity based on these two Bayesian hierarchical models.

• Journal of Korean Society on Water Environment
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• v.36 no.5
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• pp.423-430
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• 2020

To improve the low treatment efficiency of sewage treatment plants, the separated sewer system must be maintained to provide an adequate flow rate and quality of the sewage under the effect of inflow. In this study, data from five locations of Namsuk, Dukgok1, Dukgok2, Kanggu, and Opo were used to conservatively calculate the inflow water volume. The sewer flow and rainfall data were collected in 2017. The factors in the standard method used to calculate the inflow of the combined sewer pipes including "rainy days", "rainfall impact period", and "period for basal sewer" were defined as 3 mm/day, continuous rain for two days, and two weeks prior to the inflow generation, respectively. "Rainy days", "rainfall impact period", and "period for basal sewer" were conservatively adjusted to 5 mm/day, continuous rain for five days, and three weeks prior to the inflow generation, respectively. As a results of the adjustment, the linearity (r²) was improved except for in Dukgok1. This implies that the conservative adjustment made in this study could improve the management quality of sewer pipes. Also, the linear correlation coefficient (a_i) between inflow and rainfall showed a large difference between the target locations, which can be another monitoring factor affecting the quality of sewer pipes. To improve the correlation based on the individual characteristics of the locations in Korea, the automatic algorithm for the inflow calculation should be developed by innovative intellectual technologies for application to the entire national area.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.31 no.3 s.258
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• pp.209-216
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• 2007

Bacterial chemotaxis is essential to the study of structure and function of bacteria. Although many studies have accumulated the knowledge about chemotaxis in the past, the motion of a single bacterium has not been studied much yet. In this study, we have developed a device microfabricated by soft lithography and consisting of microfluidic channels. The microfluidic assay generates a concentration gradient of chemoattractant linearly in the main channel by only diffusion of the chemicals. Bacteria are injected into the main channel in a single row by hydrodynamic focusing technique. We measured the velocity of bacteria in response to a given concentration gradient of chemoattractant using the microfludic assay, optical systems with CCD camera and simple PTV (Particle Tracking Velocimetry) algorithm. The advantage of this assay and experiment is to measure the velocity of a single bacterium and to quantify the degree of chemotaxis by statistically analyzing the velocity at the same time. Specifically, we measured and analyzed the motility of Escherichia coli strain RP437 in response to various concentration gradients of L-aspartate statistically and quantitatively by using this microfluidic assay. We obtained the probability density of the velocity while RP437 cells are swimming and tumbling in the presence of the linear concentration gradient of L-aspartate, and quantified the degree of chemotaxis by analyzing the probability density.