• Structural Engineering and Mechanics
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• v.61 no.2
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• pp.193-207
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• 2017

In this study, the vibration of an electrostatically actuated micro cantilever beam is analyzed in which a viscoelastic layer covers a portion of the micro beam length. This proposed model is considered as the main element of mass and pollutant micro sensors. The nonlinear motion equation is extracted by means of Hamilton principle, considering nonlinear shortening effect for Euler-Bernoulli beam. The non-linear effects of electrostatic excitation, geometry and inertia have been taken into account. The viscoelastic model is assumed as Kelvin-Voigt model. The motion equation is discretized by Galerkin approach. The linear free vibration mode shapes of non-uniform micro beam i.e. the linear mode shape of the system by considering the geometric and inertia effects of viscoelastic layer, have been employed as comparison function in the process of the motion equation discretization. The discretized equation of motion is solved by the use of multiple scale method of perturbation theory and the results are compared with the results of numerical Runge-Kutta approach. The frequency response variations for different lengths and thicknesses of the viscoelastic layer have been founded. The results indicate that if a constant volume of viscoelastic layer is to be deposited on the micro beam for mass or gas sensor applications, then a modified configuration may be found by using the analysis of this paper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.7
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• pp.1452-1457
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• 2005

In the QR Decomposition-based (QRD) decoding class, the system performance is sensitive to the error propagation. Thus, it is critical to correctly decode the previous layers. One apprach to desensitize the error propagation is to propose the optimal decoding order of layers. In this wort we propose a new extended-list Soled QRD-based (SQRD) decoding approach. In the proposed decoding scheme, the solution of the few first layers is extended as the list of promising possible solutions. By doing so, the diversity of the lowest layer is increased. As a result, the system performance is less sensitive to the error propagation than its counterparts. The proposed approach is verified by the computer simulation results.

• ETRI Journal
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• v.41 no.2
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• pp.242-253
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• 2019

We devise a layer-wise hint training method to improve the existing hint-based knowledge distillation (KD) training approach, which is employed for knowledge transfer in a teacher-student framework using a residual network (ResNet). To achieve this objective, the proposed method first iteratively trains the student ResNet and incrementally employs hint-based information extracted from the pretrained teacher ResNet containing several hint and guided layers. Next, typical softening factor-based KD training is performed using the previously estimated hint-based information. We compare the recognition accuracy of the proposed approach with that of KD training without hints, hint-based KD training, and ResNet-based layer-wise pretraining using reliable datasets, including CIFAR-10, CIFAR-100, and MNIST. When using the selected multiple hint-based information items and their layer-wise transfer in the proposed method, the trained student ResNet more accurately reflects the pretrained teacher ResNet's rich information than the baseline training methods, for all the benchmark datasets we consider in this study.

• Earthquakes and Structures
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• v.16 no.1
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• pp.109-118
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• 2019

This study, analyses the seismic response for a rigid massless square foundation resting on a viscoelastic soil layer limited by rigid bedrock. The foundation is subjected either to externally applied forces or to obliquely incident seismic body or surface harmonic seismic waves P, SV and SH. A 3-D frequency domain BEM formulation in conjunction with the thin layer method (TLM) is adapted here for the solution of elastodynamic problems and used for obtained the seismic response. The mathematical approach is based on the method of integral equations in the frequency domain using the formalism of Green's functions (Kausel and Peck 1982) for layered soil, the impedance functions are calculated by the compatibility condition. In this study, The key step is the characterization of the soil-foundation interaction with the input motion matrix. For each frequency the impedance matrix connects the applied forces to the resulting displacement, and the input motion matrix connects the displacement vector of the foundation to amplitudes of the free field motion. This approach has been applied to analyze the effect of soil-structure interaction on the seismic response of the foundation resting on a viscoelastic soil layer limited by rigid bedrock.

• The KIPS Transactions:PartC
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• v.12C no.5 s.101
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• pp.733-740
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• 2005

In this paper, we propose an approach to transport layer mobility support leveraging the SCTP extension dubbed dynamic address reconfiguration in IPv6 networks. Timing issues related to the end-to-end address management, and a novel error recovery mechanism associated with a handover are discussed. The proposed error recovery mechanism is analyzed and compared to that of the plain SCTP to show that it reduces the handover latency and error recovery time.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.1
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• pp.23-35
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• 1998

This article presents a network flow analysis to form flexible machine cells with minimum intercellular part moves and a neural network model to form part families. The operational sequences and production quantity of the part, and the number of cells and the cell size are taken into considerations for a 0-1 quadratic programming formulation and a network flow based solution procedure is developed. After designing the machine cells, a neural network approach for the integration of part families and the automatic assignment of new parts to the existing cells is proposed. A multi-layer backpropagation network with one hidden layer is used. Experimental results with varying number of neurons in hidden layer to evaluate the role of hidden neurons in the network learning performance are also presented. The comprehensive methodology developed in this article is appropriate for solving large-scale industrial applications without building the knowledge-based expert rule for the cellular manufacturing environment.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.3
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• pp.130-138
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• 1995

In this paper, a Novel Approach is Proposed which Identifies linear system Parameters Using a multilayer feedforward neural network trained with backpropagation algorithm. The parameters of linear system can be represented by x9t)/x(t) and x(t)/u(t). Thud, its parameters can be represented in terms of the derivative of output with respect to input of parameters can be represented in terms of the derivative of output with respect to input of trained neural network which is a function of weights and output of neurons. Mathematical representation of the proposed approach is derived, and its validity is shown by simulation results on 2-layer and 3-layer neural network.

• Journal of the Korean Chemical Society
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• v.56 no.4
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• pp.478-483
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• 2012

We successfully synthesized $Fe_3O_4/SiO_2$ nanoparticles with ultrathin silica layer of $1.0{\pm}0.5$ nm that was fine controlled by changing concentration of $Fe_3O_4$. Among various reaction conditions for silica coating, increasing concentration of $Fe_3O_4$ was more effective approach to decrease silica thickness compared to water-to-surfactant ratio control. Moreover, we found that concentration of the 1-octanol is also important factor to produce the homogeneous $Fe_3O_4/SiO_2$ nanoparticles. The present approach could be available to apply on preparation of other core/shell nanoparticles with ultrathin silica layer.

• Geomechanics and Engineering
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• v.23 no.6
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• pp.547-560
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• 2020

This paper studies the dynamic foundation-soil-foundation interaction for two square rigid foundations embedded in a viscoelastic soil layer. The vibrations come from only one rigid foundation placed in the soil layer and subjected to harmonic loads of translation, rocking, and torsion. The required dynamic response of rigid surface foundations constitutes the solution of the wave equations obtained by taking account of the conditions of interaction. The solution is formulated using the frequency domain Boundary Element Method (BEM) in conjunction with the Kausel-Peek Green's function for a layered stratum, with the aid of the Thin Layer Method (TLM), to study the dynamic interaction between adjacent foundations. This approach allows the establishment of a mathematical model that enables us to determine the dynamic displacements amplitude of adjacent foundations according to their different separations, the depth of the substratum, foundations masss, foundations embedded, and the frequencies of excitation. This paper attempts to introduce an approach based on a polynomial mathematical tool conducted from several results of numerical methods (BEM-TLM) so that practicing civil engineers can evaluation the dynamic foundations displacements more easy.

• Industrial Engineering and Management Systems
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• v.11 no.4
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• pp.371-384
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• 2012

This study proposes a multi-level data analysis approach to identify both superficial and latent relationships among variables in the data set obtained from a vocational rehabilitation (VR) services program of people with significant disabilities. At the first layer, data mining and statistical predictive models are used to extract the superficial relationships between dependent and independent variables. To supplement the findings and relationships from the analysis at the first layer, association rule mining algorithms at the second layer are employed to extract additional sets of interesting associative relationships among variables. Finally, nonlinear nonparametric canonical correlation analysis (NLCCA) along with clustering algorithm is employed to identify latent nonlinear relationships. Experimental outputs validate the usefulness of the proposed approach. In particular, the identified latent relationship indicates that disability types (i.e., physical and mental) and severity (i.e., severe, most severe, not severe) have a significant impact on the levels of self-esteem and self-confidence of people with disabilities. The identified superficial and latent relationships can be used to train education program designers and policy developers to maximize the outcomes of VR training programs.