• Korean Management Science Review
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• v.30 no.1
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• pp.15-24
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• 2013

We consider the single machine scheduling problem with a rate-modifying activity and time-dependent deterioration after the activity. The class of scheduling problems with rate-modifying activities and the class of scheduling problems with time-dependent processing times have been studied independently. However, the integration of these classes is motivated by human operators of tasks who has fatigue while carrying out the operation of a series of tasks. This situation is also applicable to machines that experience performance degradation over time due to mal-position or mal-alignment of jobs, abrasion of tools, and scraps of operations, etc. In this study, the integration of the two classes of scheduling problems is considered. We present a mathematical model to determine job-sequence and a position of a rate-modifying activity for the integration problem. Since the model is difficult to solve as the size of real problem being very large, we propose genetic algorithms. The performance of the algorithms are compared with optimal solutions with various problems.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.399-413
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• 2021

The solution of the time-dependent neutron diffusion equation can be approximated using quasi-static methods that factorise the neutronic flux as the product of a time dependent function times a shape function that depends both on space and time. A generalization of this technique is the updated modal method. This strategy assumes that the neutron flux can be decomposed into a sum of amplitudes multiplied by some shape functions. These functions, known as modes, come from the solution of the eigenvalue problems associated with the static neutron diffusion equation that are being updated along the transient. In previous works, the time step used to update the modes is set to a fixed value and this implies the need of using small time-steps to obtain accurate results and, consequently, a high computational cost. In this work, we propose the use of an adaptive control time-step that reduces automatically the time-step when the algorithm detects large errors and increases this value when it is not necessary to use small steps. Several strategies to compute the modes updating time step are proposed and their performance is tested for different transients in benchmark reactors with rectangular and hexagonal geometry.

• Communications of the Korean Mathematical Society
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• v.22 no.3
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• pp.465-474
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• 2007

With the help of the coincidence degree and the related continuation theorem, we explore the existence of at least two periodic solutions of a discrete time non-autonomous ratio-dependent predator-prey system with control. Some easily verifiable sufficient criteria are established for the existence of at least two positive periodic solutions.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.524-532
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• 2005

This paper concerns delay-dependent guaranteed cost control (GCC) problem for a class of linear state-delayed systems with norm-bounded time-varying parametric uncertainties. By incorporating the free weighing matrix approach developed recently, new delay-dependent conditions for the existence of the guaranteed cost controller are presented in terms of matrix inequalities for both nominal state-delayed systems and uncertain state-delayed systems. An algorithm involving convex optimization is proposed to design a controller achieving a suboptimal guaranteed cost such that the system can be stabilized for all admissible uncertainties. Through numerical examples, it is shown that the proposed method can yield less guaranteed cost than the existing delay-dependent methods.

• Steel and Composite Structures
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• v.38 no.4
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• pp.447-462
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• 2021

In this work, we consider a problem in the context of thermoelectric materials with memory-dependent derivative for a half space which is assumed to have variable thermal conductivity depending on the temperature. The Lamé's modulii of the half space material is taken as a function of the vertical distance from the surface of the medium. The surface is traction free and subjected to a time dependent thermal shock. The problem was solved by using the Laplace transform method together with the perturbation technique. The obtained results are discussed and compared with the solution when Lamé's modulii are constants. Numerical results are computed and represented graphically for the temperature, displacement and stress distributions. Affectability investigation is performed to explore the thermal impacts of a kernel function and a time-delay parameter that are characteristic of memory dependent derivative heat transfer in the behavior of tissue temperature. The correlations are made with the results obtained in the case of the absence of memory-dependent derivative parameters.

• Science of Emotion and Sensibility
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• v.11 no.4
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• pp.637-644
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• 2008

Human emotion has been tried to be recognized by physiological measurements in developing emotion machine enabling to understand and react to user's emotion. This study is to find the time-dependent physiological measurements and their variation characteristics for discriminating emotions according to dimensional emotion model. Ten university students were asked to watch sixteen prepared images to evoke different emotions. Their subjective emotions and autonomic nervous responses such as ECG (electrocardiogram), PPG (photoplethysmogram), GSR (Galvanic skin response), RSP (respiration), and SKT(skin temperature) were measured during experiment. And these responses were analyzed into HR(Heart Rate), Respiration Rate, GSR amplitude average, SKT amplitude average, PPG amplitude, and PTT(Pulse Transition Time). TDPs(Time dependent parameters) defined as the delay, the activation, the half recovery and the full recovery of respective physiological signal in this study have been determined and statistically compared between variations from different emotions. The significant tendencies in TDP were shown between emotions. Therefore, TDP may provide useful measurements with emotion recognition.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.05
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• pp.27-33
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• 1995

A time-dependent large deformation fracture theory is developed for application to soft biological tissues. The theory uses the quasilinear viscoelastic theory of Fung, and particularizes it to constitutive assumptions on polyvinyl-chloride (PVC) (Part I) and cartilage (Part II). This constitutive theory is used in a general viscoelastic theory by Christensen and Naghdi and an energy balance to develop an expression for the fracture toughness of the materials. Experimental methods are developed for measuring the required constitutive parameters and fracture data for the materials. Elastic stress and reduced relaxation functions were determined using tensile and shear tests at high loading rates with rise times of 25-30 msec, and test times of 150 sec. The developed method was validated, using an engineering material, PVC to separate the error in the testing method from the inherent variation of the biological tissues. It was found that the the proposed constitutive modeling can predict the nonlinear stress-strain and the time-dependent behavior of the material. As an approximation method, a pseudo-elastic theory using the J-integral concept, assuming that the material is a time-independent large deformation elastic material, was also developed and compared with the time-dependent fracture theory. For PVC. the predicted fracture toughness is $1.2{\pm}0.41$ and $1.5{\pm}0.23\;kN/m$ for the time-dependent theory and the pseudo-elastic theory, respectively. The methods should be of value in quantifying fracture properties of soft biological tissues. In Part II, an application of the developed method to a biological soft tissue was made by using bovine humeral articular cartilage.

• The Journal of Korean Obstetrics and Gynecology
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• v.18 no.1
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• pp.181-191
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• 2005

Purpose : ${\beta}$-sitosterol is kind of phytosterols or plant which are structurally similar to cholesterol. This study was aimed to investigate the inhibitory effect of the ${\beta}$-sitosterol on the proliferation of human uterine leiomyoma cells and the expression of gene related the mechanism of cell apoptosis. Methods : We counted the number of death cells treated with indicated time of the ${\beta}$-sitosterol and investigated cell death rate by cell count assay. Furthermore, flow cytometry analysis and DNA fragmentation assay were used to dissect between necrosis and apoptosis. and then we observed the differential gene expression by western blot analysis. Results : 1) The inhibitory effect on the growth of uterine leiomyoma cell treated with the ${\beta}$-sitosterol $16{\mu}M$ was increased in a time dependent. 2) The result of flow cytometry analysis, subG1 phase arrest related cell apoptosis was investigated 16.97% in uterine leiomyoma cell treated with the ${\beta}$-sitosterol $16{\mu}M$ and showed the fashion of proportional time dependent. 3) The gene expression of p27, p21 related cell cycle was increased according to increasing time interval but cyclin E-CDK2 complex was decreased expression. 4) The character of apoptosis, DNA fragmentation was significantly observed on the time dependent. 5) The expression of pro-caspase 3 and PARP were decreased dependent on treatment with time dependent. Conclusion : This study showed that the ${\beta}$-sitosterol have the inhibitory effect on the proliferation of human uterine leiomyoma cell and the effect was related with apoptosis.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1275-1284
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• 2021

This paper presents a machine learning technique applied to prediction of time-dependent local scour around bridge piers in both non-cohesive and cohesive beds. The support vector machines (SVM), which is known to be free from overfitting, is used. The time-dependent scour depths are expressed by 7 and 9 variables for the non-cohesive and cohesive beds, respectively. The SVM models are trained and validated with time series data from different sources of experiments. Resulting Mean Absolute Percentage Error (MAPE) indicates that the models are trained and validated properly. Comparisons are made with the results from Choi and Choi's formula and Scour Rate in Cohesive Soils (SRICOS) method by Briaud et al., as well as measured data. This study reveals that the SVM is capable of predicting time-dependent local scour in both non-cohesive and cohesive beds under the condition that sufficient data of good quality are provided.

• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.69-81
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• 2019

We consider bivariate long range dependent (LRD) time series forecasting using a deep learning method. A long short-term memory (LSTM) network well-suited to time series data is applied to forecast bivariate time series; in addition, we compare the forecasting performance with bivariate fractional autoregressive integrated moving average (FARIMA) models. Out-of-sample forecasting errors are compared with various performance measures for functional MRI (fMRI) data and daily realized volatility data. The results show a subtle difference in the predicted values of the FIVARMA model and VARFIMA model. LSTM is computationally demanding due to hyper-parameter selection, but is more stable and the forecasting performance is competitively good to that of parametric long range dependent time series models.