• Wind and Structures
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• v.1 no.2
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• pp.161-174
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• 1998

Wind forces on structures are usually schematized by the sum of their mean static part and a nil mean fluctuation generally treated as a stationary process randomly varying in space and time. The multi-variate and multi-dimensional nature of such a process requires a considerable quantity of numerical procedures to carry out the dynamic analysis of the structural response. With the aim of drastically reducing the above computational burden, this paper introduces a method by means of which the external fluctuating wind forces on slender structures and structural elements are schematized by an equivalent process identically coherent in space. This process is identified by a power spectral density function, called the Generalized Equivalent Spectrum, whose expression is given in closed form.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.8
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• pp.107-118
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• 1995

Three-dimensional simulator for thermal oxidation process is developed. The simulator is consisted by two individual module, one is analytic-model module and the other is numerical-model module. The analytic-model which uses simple complementary-error function guarantees fast calculation in prediction of multi-dimensional oxidation process. The numerical-model which is based on boundary element method (BEM), has a good accuracy and suitable for various process conditions. The results of this study show that oxide growth is retarded at the corner of hole structure and enhanced at the corner of island structure. These effects are reson of different distribution of oxidant diffusion and mask stress. The utility of models and simulator developed in this study is demonstrated by using it to predict not only traditional shape of LOCOS but also process effects in small geometry.

• Bulletin of the Korean Chemical Society
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• v.27 no.12
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• pp.1940-1960
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• 2006

Theoretical descriptions of two-dimensional (2D) vibrational and electronic spectroscopy are presented. By using a coupled multi-chromophore model, some examples of 2D spectroscopic studies of peptide solution structure determination and excitation transfer process in electronically coupled multi-chromophore system are discussed. A few remarks on perspectives of this research area are given.

• East Asian mathematical journal
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• v.29 no.1
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• pp.13-22
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• 2013

As a fuzzy counterpart of stochastic calculus, fuzzy calculus including Liu integral and Liu formula were introduced. In order to deal with the problems with several fuzzy dynamic factors, Liu process, Liu integral and Liu formula are extended to the case of multi-dimensional in this paper.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.9
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• pp.202-209
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• 2000

In recent years the concern of designing multi-stage gear drives increases with the more application of gear drives in high-speed and high-load. until now however research on the gear drive design has been focused on single gear pairs and the design has been depended on experiences and know-how of designers and carried out commonly by trial and error. We propose the automation of the dimensional design of gears and the configuration design for gear arrangement of two-and three-stage cylindrical gear drives. The dimensional design is divided into two types of design processes to determine the dimensions of gears. The first design process(Process I) uses the total volume of gears to determine gear ratio and uses K factor unit load and aspect ratio to determine gear dimensions. The second one(Process II) makes use of Niemann's formula and center distance to calculate gear ratio and dimensions. Process I and II employ material data from AGMA and ISO standards respectively. The configuration design determines the positions of gears to minimize the volume of gearbox by simulated annealing algorithm. Finally the availability of the design algorithm is validated by the design examples of two-and three-stage gear drives.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.142-148
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• 2003

Reinforcement learning is considered as an important tool for robotic learning in unknown/uncertain environments. In this paper, we propose an evaluation function expressed in a vector form to realize multi-dimensional reinforcement learning. The novel feature of the proposed method is that learning one behavior induces parallel learning of other behaviors though the objectives of each behavior are different. In brief, all behaviors watch other behaviors from a critical point of view. Therefore, in the proposed method, there is cross-criticism and parallel learning that make the multi-dimensional learning process more efficient. By ap-plying the proposed learning method, we carried out multi-dimensional evaluation (reward) and multi-dimensional learning simultaneously in one trial. A special neural network (Q-net), in which the weights and the output are represented by vectors, is proposed to realize a critic net-work for Q-learning. The proposed learning method is applied for behavior planning of mobile robots.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.32-41
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• 2006

In data-centric networks, various data items, such as temperature, humidity, etc. are sensed and stored in sensor nodes. As these attributes are mostly scalar values and inter-related, multi-dimensional range queries are useful. To process multi-dimensional range queries efficiently in data-centric storage, data addressing is essential. The Previous work focused on efficient query processing without considering overall network lifetime. To prolong network lifetime and support multi-dimensional range queries, we propose a dynamic data distribution method for multi-dimensional data, where data space is divided into equal-sized regions and linearized by using Hilbert space filling curve.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.2B
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• pp.123-130
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• 2012

MLP (Multi dimensional Limiting Process) is implemented to simulate shallow water flows, and its performance over conventional TVD limiters in multidimensional flows is verified through several numerical simulations. MLP was developed to control oscillations for multi-dimensional compressible flows and proved to improve accuracy, efficiency and robustness in compressible flows. In this study, we applies MLP to modeling shallow water equations(SWEs) given that the SWEs are amenable to be solved using the large range of numerical methods developed to deal with compressible flows and MLP has been yet used for SWEs. Simulation results through the benchmark tests show that MLP has favorable features such as numerical oscillation control and convergence behaviors comparable to the conventional limiters. Both numerical accuracy and stability are improved in multi-dimensional discontinuous flows.

• Smart Structures and Systems
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• v.15 no.3
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• pp.897-911
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• 2015

This study presents a novel approach based on advancements in Evolutionary Computation for data-driven modeling of complex multi-dimensional memory-dependent systems. The investigated example is a benchmark coupled three-dimensional system that incorporates 6 Bouc-Wen elements, and is subjected to external excitations at three points. The proposed technique of this research adapts Genetic Programming for discovering the optimum structure of the differential equation of an auxiliary variable associated with every specific degree-of-freedom of this system that integrates the imposed effect of vibrations at all other degrees-of-freedom. After the termination of the first phase of the optimization process, a system of differential equations is formed that represent the multi-dimensional hysteretic system. Then, the parameters of this system of differential equations are optimized in the second phase using Genetic Algorithms to yield accurate response estimates globally, because the separately obtained differential equations are coupled essentially, and their true performance can be assessed only when the entire system of coupled differential equations is solved. The resultant model after the second phase of optimization is a low-order low-complexity surrogate computational model that represents the investigated three-dimensional memory-dependent system. Hence, this research presents a promising data-driven modeling technique for obtaining optimized representative models for multi-dimensional hysteretic systems that yield reasonably accurate results, and can be generalized to many problems, in various fields, ranging from engineering to economics as well as biology.

• Journal of the Korean Mathematical Society
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• v.48 no.1
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• pp.147-158
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• 2011

In this paper, we consider a multi-dimensional diffusion process in a self-similar random environment and prove a limit theorem for the shape of the full trajectory of the diffusion by using the localization phenomenon.