• The KIPS Transactions:PartA
• /
• v.9A no.1
• /
• pp.61-74
• /
• 2002

This paper presents a method which synthesizes asynchronous circuits from free-choice Signal Transition Graphs (STGs) with timing constraints. The proposed method synthesizes asynchronous circuits by analyzing: the relations between signal transitions directly from the STGs without generating state graphs. The synthesis procedure decomposes a free-choice STG into deterministic STGs which do not have choice behavior. Then, a timing analysis extracts the timed concurrency and tamed causality relations between any two signal transitions for each deterministic STG. The synthesis procedure synthesizes circuits for each deterministic STG and synthesizes the final circuit by merging the circuits for each deterministic STG. The experimental results show that our method achieves significant reductions in synthesis time for the circuits which have a large state space, and generates circuits that have nearly the same area as compared to previous methods.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.8 no.1
• /
• pp.41-59
• /
• 1983

The purpose of this paper is to present a method of multi-objective, stochastic optimization in water resources system which investigates the development of potential non-normal deterministic equivalents for subsequent use in multiobjective stochastic programming methods, Given probability statement involving a function of several random variables, it is often possible to obtain a deterministic equivalent of it that does not include any orginal random variables. A Stochastic trade-off technique-MSTOT is suggested to help a decision maker achieve satisfactory levels for several objective functions. This makes use of deterministic equivalents to handle random variables in the objective functions. The emphasis is in the development of non-normal deterministic equivalents for use in multiobjective stochastic techniques.

• Convergence Security Journal
• /
• v.18 no.3
• /
• pp.3-9
• /
• 2018

The Deep Deterministic Policy Gradient (DDPG) algorithm is an algorithm that learns by using artificial neural network s and reinforcement learning. Among the studies related to reinforcement learning, which has been recently studied, the D DPG algorithm has an advantage of preventing the cases where the wrong actions are accumulated and affecting the learn ing because it is learned by the off-policy. In this study, we experimented to control the bicycle autonomously by applyin g the DDPG algorithm. Simulation was carried out by setting various environments and it was shown that the method us ed in the experiment works stably on the simulation.

• Geomechanics and Engineering
• /
• v.23 no.1
• /
• pp.15-30
• /
• 2020

The probabilistic bearing capacity of a strip footing placed on the edge of a purely cohesive reinforced soil slope is computed by combining lower bound finite element limit analysis technique with random field method and Monte Carlo simulation technique. To simulate actual field condition, anisotropic random field model of undrained soil shear strength is generated by using the Cholesky-Decomposition method. With the inclusion of a single layer of reinforcement, dimensionless bearing capacity factor, N always increases in both deterministic and probabilistic analysis. As the coefficient of variation of the undrained soil shear strength increases, the mean N value in both unreinforced and reinforced slopes reduces for particular values of correlation length in horizontal and vertical directions. For smaller correlation lengths, the mean N value of unreinforced and reinforced slopes is always lower than the deterministic solutions. However, with the increment in the correlation lengths, this difference reduces and at a higher correlation length, both the deterministic and probabilistic mean values become almost equal. Providing reinforcement under footing subjected to eccentric load is found to be an efficient solution. However, both the deterministic and probabilistic bearing capacity for unreinforced and reinforced slopes reduces with the consideration of loading eccentricity.

• Geomechanics and Engineering
• /
• v.10 no.6
• /
• pp.709-726
• /
• 2016

Corrugated-core sandwich panels are prevalent for many applications in industries. The researches performed with the aim of optimization of such structures in the literature have considered a deterministic approach. However, it is believed that deterministic optimum points may lead to high-risk designs instead of optimum ones. In this paper, an effort has been made to provide a reliable and robust design of corrugated-core sandwich structures through stochastic and probabilistic multi-objective optimization approach. The optimization is performed using a coupling between genetic algorithm (GA), Monte Carlo simulation (MCS) and finite element method (FEM). To this aim, Prob. Design module in ANSYS is employed and using a coupling between optimization codes in MATLAB and ANSYS, a connection has been made between numerical results and optimization process. Results in both cases of deterministic and probabilistic multi-objective optimizations are illustrated and compared together to gain a better understanding of the best sandwich panel design by taking into account reliability and robustness. Comparison of results with a similar deterministic optimization study demonstrated better reliability and robustness of optimum point of this study.

• JSTS:Journal of Semiconductor Technology and Science
• /
• v.17 no.2
• /
• pp.288-293
• /
• 2017

Transient simulation capability with an implicit time derivation method is a missing feature in deterministic Boltzmann equation solvers. The H-transformation, which is critical for the stable simulation of nanoscale devices, introduces difficulties for the transient simulation. In this work, the transient simulation of graphene sheets is reported. It is shown that simulation of homogeneous systems can be done without abandoning the H-transformation, as much as a specially designed discretization method is employed. The AC mobility and step response of the graphene sheet on the $SiO_2$ substrate are simulated.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.6
• /
• pp.2497-2517
• /
• 2020

For compressed sensing (CS) applications, it is significant to construct deterministic measurement matrices with good practical features, including good sensing performance, low memory cost, low computational complexity and easy hardware implementation. In this paper, a deterministic construction method of bipolar measurement matrices is presented based on binary sequence family (BSF). This method is of interest to be applied for sparse signal restore and image block CS. Coherence is an important tool to describe and compare the performance of various sensing matrices. Lower coherence implies higher reconstruction accuracy. The coherence of proposed measurement matrices is analyzed and derived to be smaller than the corresponding Gaussian and Bernoulli random matrices. Simulation experiments show that the proposed matrices outperform the corresponding Gaussian, Bernoulli, binary and chaotic bipolar matrices in reconstruction accuracy. Meanwhile, the proposed matrices can reduce the reconstruction time compared with their Gaussian counterpart. Moreover, the proposed matrices are very efficient for sensing performance, memory, complexity and hardware realization, which is beneficial to practical CS.

• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• v.21 no.3
• /
• pp.155-165
• /
• 2017

The Hansel-Spittel constitutive model requires a total of nine parameters for flow stress prediction. Typically, the parameters are estimated by least squares methods for given tensile test measurements from a deterministic perspective. In this research we took a different approach, a probabilistic viewpoint, to see through the development of the Hansel-Spittel constitutive model. This perspective change showed that deterministic least squares methods are closely related to statistical maximum likelihood methods via Gaussian noise assumption. More intriguingly, this perspective shift revealed that the Hansel-Spittel constitutive model may leave out deterministic trends in residuals despite nearly perfect agreement with measurements. With tensile test measurements of AA1070 aluminum alloy, we demonstrated this deficiency of the Hansel-Spittel constitutive model, suggesting room for improvement.

• Geomechanics and Engineering
• /
• v.22 no.1
• /
• pp.35-48
• /
• 2020

This paper provides methods for the deterministic and reliability-based design of the support pressures necessary to prevent tunnel face collapse. The deterministic method is developed by extending the use of the unique load multiplier, which is embedded within OptumG2/G3 with the intention of determining the maximum load that can be supported by a system. Both two-dimensional and three-dimensional examples are presented to illustrate the applications. The obtained solutions are validated according to those derived from the existing methods. The reliability-based method is developed by incorporating the Response Surface Method and the advanced first-order second-moment reliability method into the bisection algorithm, which continuously updates the support pressure within previously determined brackets until the difference between the computed reliability index and the user-defined value is less than a specified tolerance. Two-dimensional reliability-based support pressure is compared and validated via Monte Carlo simulations, whereas the three-dimensional solution is compared with the relationship between the support pressure and the resulting reliability index provided in the existing literature. Finally, a parametric study is carried out to investigate the influences of factors on the required support pressure.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2005.03a
• /
• pp.129-136
• /
• 2005

The deterministic analysis method has generally used to evaluate the slope stability and it evaluates the slope stability with decision value that is a representative value of design variables. However, one of disadvantages in the deterministic approach is there is not able to consider the uncertainty of soil strength properties, even though it is the biggest influential parameter of the slope stability. On the other hand, the limit state design(LSD) can take a consideration of uncertainties and computes both the reliability index and the probability of failure. LSD method is capable of overcoming the disadvantages of deterministic method and evaluating the slope stability more reliably. In this study, both the mean value and standard deviation of the internal land's representative soil strength properties applied to process the LSD method. The major purpose of this study is to gauge the general applicability of the limit state design in soil slope and to weigh the comparative validity of the proposed partial safety factor. In order to reach the aim of this study, the partial safety factor and resistance factor which totally satisfied the slope's overall safety factor were calculated by the load and resistance safety factor design (LRFD).