• Communications of the Korean Mathematical Society
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• v.20 no.2
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• pp.321-338
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• 2005

In this paper we investigate a generalization of the Hyers-Ulam-Rassias stability for a functional equation of the form $f(\varphi(X))\;=\;\phi(X)f(X)$, where X lie in n-variables. As a consequence, we obtain a stability result in the sense of Hyers, Ulam, Rassias, and Gavruta for many other equations such as the gamma, beta, Schroder, iterative, and G-function type's equations.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.2
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• pp.102-110
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• 2017

Current word sense disambiguation techniques employ various machine learning-based methods. Various approaches have been proposed to address this problem, including the knowledge base approach. This approach defines the sense of an ambiguous word in accordance with knowledge base information with no training corpus. In unsupervised learning techniques that use a knowledge base approach, graph-based and similarity-based methods have been the main research areas. The graph-based method has the advantage of constructing a semantic graph that delineates all paths between different senses that an ambiguous word may have. However, unnecessary semantic paths may be introduced, thereby increasing the risk of errors. To solve this problem and construct a fine-grained graph, in this paper, we propose a model that iteratively constructs the graph while eliminating unnecessary nodes and edges, i.e., senses and semantic paths. The hybrid similarity estimation model was applied to estimate a more accurate sense in the constructed semantic graph. Because the proposed model uses BabelNet, a multilingual lexical knowledge base, the model is not limited to a specific language.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.4
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• pp.36-44
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• 2012

Electrical impedance tomography is a relatively new imaging modality in which the internal conductivity (or resistivity) distribution of a object is reconstructed based on the injected currents and measured voltages through the electrodes placed on the surface of the object. In this paper, it is assumed that the relationship between the resistivity distribution and the resistance of electrodes is linear. From this linear relation, the weighting matrix can be obtained and modified iterative Landweber method is applied to estimate the internal resistivity distribution. Additionally, to accelerate the convergence rate and improve the spatial resolution of the reconstructed image, optimal step lengths for the iterative Landweber method are computed from the objective function in the least-square sense. The numerical experiments have been performed to illustrate the superior reconstruction performance of the proposed scheme.

• Korean Journal of Cognitive Science
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• v.27 no.1
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• pp.43-60
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• 2016

Recently, Unsupervised Word Sense Disambiguation research has focused on Graph based disambiguation. Graph-based disambiguation has built a semantic graph based on words collocated in context or sentence. However, building such a graph over all ambiguous word lead to unnecessary addition of edges and nodes (and hence increasing the error). In contrast, our work uses Word2Vec to consider the most similar words to an ambiguous word in the context or sentences, to rebuild a graph of the matched words. As a result, we show a higher F1-Measure value than the previous methods by using Word2Vec.

• Journal of the Chungcheong Mathematical Society
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• v.29 no.4
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• pp.663-676
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• 2016

In this paper we propose a new family of eighth order optimal methods for solving nonlinear equations by using weight function methods. The methods of the family require three function and one derivative evaluations per step and has order of convergence eight, and so they are optimal in the sense of Kung-Traub hypothesis. Precise analysis of convergence is given. Some members of the family are compared with several existing methods to show their performance and as a result to confirm that our methods are as competitive as compared to them.

• Structural Engineering and Mechanics
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• v.53 no.4
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• pp.661-679
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• 2015

In this article, nonlinear finite element solutions of bending responses of functionally graded spherical panels are presented. The material properties of functionally graded material are graded in thickness direction according to a power-law distribution of volume fractions. A general nonlinear mathematical shallow shell model has been developed based on higher order shear deformation theory by taking the geometric nonlinearity in Green-Lagrange sense. The model is discretised using finite element steps and the governing equations are obtained through variational principle. The nonlinear responses are evaluated through a direct iterative method. The model is validated by comparing the responses with the available published literatures. The efficacy of present model has also been established by demonstrating a simulation based nonlinear model developed in ANSYS environment. The effects of power-law indices, support conditions and different geometrical parameters on bending behaviour of functionally graded shells are obtained and discussed in detail.

• Journal of electromagnetic engineering and science
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• v.12 no.1
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• pp.1-7
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• 2012

In this paper, we investigated the throughput of a cognitive radio network where two primary frequency channels (PCs) are sensed and opportunistically accessed by N secondary users. The sharing sensing member (SSM) protocol is introduced to sense both PCs simultaneously. According to the SSM protocol, N SUs (Secondary User) are divided into two groups, which allows for the simultaneous sensing of two PCs. With a frame structure, after determining whether the PCs are idle or active during a sensing slot, the SUs may use the remaining time to transmit their own data. The throughput of the network is formulated as a convex optimization problem. We then evaluated an iterative algorithm to allocate the optimal sensing time, fusion rule and the number of members in each group. The computer simulation and numerical results show that the proposed optimal allocation improves the throughput of the SU under a misdetection constraint to protect the PCs. If not, its initial date of receipt shall be nullified.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.28-33
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• 1994

An optimal controller, e.g. LQG controller, may not be realistic in the sense that the required control power may not be achieved by existing actuators, and the measured output is not satisfactory. To be realistic, the controller should meet such constraints as sensor or actuator limitation, performance limit, etc. In this paper, the lnput/Output Variance Constrained (IOVC) control problem will be considered from the viewpoint of mathematical programming. A dual version shall be developed to solve the IOVC control problem, whose objective is to find a stabilizing control law attaining a minimum value of a quadratic cost function subject to the inequality constraint on each input and output variance for a stabilizable and detectable plant. One approach to the constrained optimization problem is to use the Kuhn-Tucker necessary conditions for the optimality and to seek an optimal point by an iterative algorithm. However, since the algorithm uses only the necessary conditions, the convergent point may not be optimal solution. Our algorithm will guarantee a sufficiency.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.1-6
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• 1992

A principle of "orthogonalization" is proposed as an extended notion of hybrid (force and position) control for robot manipulators under geometric endpoint constraints. The principle realizes the hybrid control in a strict sense by letting position and velocity feedback signals be orthogonal in joint space to the contact force vector whose components are exerted at corresponding joints. This orthogonalization is executed via a projection matrix computed in real-time from a gradient of the equation of the surface in joint coordinates and hence both projected position and velocity feedback signals become perpendicular to the force vector that is normal to the surface at the contact point in joint space. To show the important role of the principle in control of robot manipulators, three basic problems are analyzed, the first is a hybrid trajectory tracking problem by means of a "modified hybrid computed torque method", the second is a model-based adaptive control problem for robot manipulators under geometric endpoint constraints, and the third is an iterative learning control problem. It is shown that the passivity of residual error dynamics of robots follows from the orthogonalization principle and it plays a crucial role in convergence properties of both positional and force error signals.force error signals.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.298-301
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• 2000

We discuss the iterative methods for linear systems on a single processing node of the HITACHI SR8000. Each processing node of the SR8000 is a shared memory parallel computer which is composed of eight RISC processors with a pseudo-vector facility. We implement highly optimized codes for basic linear operations including a matrix-vector product and apply them to the conjugate gradient (CG) and the conjugate residual (CR) methods for linear systems. Our tuned codes for both method score nearly 50% of the theoretical peak performance, which is the best in the sense that it corresponds to an asymptotic performance of the inner product.