• Journal of Satellite, Information and Communications
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• v.8 no.4
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• pp.47-52
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• 2013

In this paper, The existing interference alignment algorithms were analyzed in Rayleigh fading channel environment. The interference alignment techniques are divided to two parts. First thing is Iterative-method, another is Linear-method. Iterative method needs local channel info, but it has the constraint of iteration. On the other hand Linear-method must have global channel info, but has free of iteration and better performance. This paper evaluates the performance of interference alignment algorithms in Rayleigh fading channel of outdoor environment and WLAN channel based on IEEE 802.11n of indoor environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1253-1272
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• 2010

In this paper, we propose a new affine shape adaptation scheme for the affine invariant feature detector, in which the convergence stability is still an opening problem. This paper examines the relation between the integration scale matrix of next iteration and the current second moment matrix and finds that the convergence stability of the method can be improved by adjusting the relation between the two matrices instead of keeping them always proportional as proposed by previous methods. By estimating and updating the shape of the integration kernel and differentiation kernel in each iteration based on the anisotropy of the current second moment matrix, we propose a coarse-to-fine affine shape adaptation scheme which is able to adjust the pace of convergence and enable the process to converge smoothly. The feature matching experiments demonstrate that the proposed approach obtains an improvement in convergence ratio and repeatability compared with the current schemes with relatively fixed integration kernel.

• Journal of the Korea Computer Industry Society
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• v.6 no.3
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• pp.447-456
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• 2005

This paper describes iterative restoration method of restoring blurred images using the LOG compansion function and Conjugate Gradient method. Conventional restoration methods results satisfy the requirement performance for restoring blurred images. but iteration number and convergence velocity increase. This paper proposed an opmtimised iteration restoration method for the images degraded by blurring effect, using the LOG compansion function and Conjugate Gradient method. Here, the LOG compansion function used to improve local properties of the image being restored, made the visual character and convergence velocity of the restored image improved. Throught the simulation results, the author showed that proposed algorithm produced superior performance results by conventional methods.

• Computers and Concrete
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• v.27 no.4
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• pp.385-393
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• 2021

Reinforcement corrosion is the main cause of the durability failure of reinforced concrete (RC) structure. In this paper, a three-dimensional (3D) numerical model of macro-cell corrosion is established to reveal the corrosion mechanisms of steel reinforcement in RC structure. Modified Direct Iteration Method (MDIM) is employed to solve the system of partial differential equations for reinforcement corrosion. Through the sensitivity analysis of electrochemical parameters, it is found that the average corrosion current density is more sensitive to the change of cathodic Tafel slope and anodic equilibrium potential, compared with the other electrochemical parameters. Furthermore, both the anode-to-cathode (A/C) ratio and the anodic length have significant influences on the average corrosion current density, especially when A/C ratio is less than 0.5 and anodic length is less than 35 mm. More importantly, it is demonstrated that the corrosion rate of semi-circumferential corrosion is much larger than that of circumferential corrosion for the same A/C ratio value. The simulation results can give a unique insight into understanding the detailed electrochemical corrosion processes of steel reinforcement in RC structure for application in service life prediction of RC structures in actual civil engineer.

• Computers and Concrete
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• v.7 no.4
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• pp.365-386
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• 2010

This paper presents the physical formulation of a 1D material model suitable for seismic applications. It is written within the framework of thermodynamics with internal variables that is, especially, very efficient for the phenomenological representation of material behaviors at macroscale: those of the representative elementary volume. The model can reproduce the main characteristics observed for concrete, that is nonsymetric loading rate-dependent (viscoelasticity) behavior with appearance of permanent deformations and local hysteresis (continuum plasticity), stiffness degradation (continuum damage), cracking due to displacement localization (discrete plasticity or damage). The parameters have a clear physical meaning and can thus be easily identified. Although this point is not detailed in the paper, this material model is developed to be implemented in a finite element computer program. Therefore, for the benefit of the robustness of the numerical implementation, (i) linear state equations (no local iteration required) are defined whenever possible and (ii) the conditions in which the presented model can enter the generalized standard materials class - whose elements benefit from good global and local stability properties - are clearly established. To illustrate the capabilities of this model - among them for Earthquake Engineering applications - results of some numerical applications are presented.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.3
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• pp.130-135
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• 2012

In this paper, we propose a technique to detect the size and location of the small target in images by using Gaussian kernel repeatedly. In order to detect the size and location of the small target, we find the local maximum value by applying the facet model and then use the $3{\times}3$ Gaussian kernel repeatedly. we determine the size of small target by comparing the local maximum value $D_2$ according to the number of iteration. To reduce the computational complexity, we use the Gaussian pyramid when using the kernel repeatedly. Through the experiment, we verified that the size and location of the small target is detected by the number of iterations and results show improvements from conventional methods.

• Transactions of the Korean Society of Mechanical Engineers
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• v.11 no.2
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• pp.234-242
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• 1987

The solution of shape design problems based on variational analysis has been approached by using the domain adaptive method. The objective of the structural shape design is to minimize the weight within a bound on local stress measure, or to minimize the maximum local stress measure within a bound on the weight. A derived optimality condition in both design problems requires that the unit mutual energy has constant value along the design boundary. However, the condition for constant stress on the design boundary was used in computation since the computed mutual energy oscillates severely on the boundary. A two step iteration scheme using domain adaptation was presented as a computational method to slove the example designs of elastic structures. It was also shown that remeshing by grid adaptation was effective to reduce oscillatory behavior on the design boundary.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.1-8
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• 2024

The traveling salesman problem(TSP) is one of the well known combinatorial optimization problems. Local search has been used as a method to solve TSP. Greedy Random Insertion(GRI) is known as an effective neighbor generation method for local search. GRI selects some cities from the current solution randomly and inserts them one by one into the best position of the current partial solution considering only one city at a time. We first propose another greedy neighbor generation method which is named Full Greedy Insertion(FGI). FGI determines insertion location one by one like GRI, but considers all remaining cities at once. And then we propose a method to combine GRI with FGI, in which GRI or FGI is randomly selected and executed at each iteration in simulated annealing. According to the experimental results, FGI alone does not necessarily perform very well. However, we confirmed that the combined method outperforms the existing local search methods including GRI.

• Smart Structures and Systems
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• v.20 no.1
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• pp.99-114
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• 2017

In cognitive science, it is illustrated how the collective opinions of a group of individuals answers to questions involving quantity estimation. One example of this approach is introduced in this article as Star Graph (SG) algorithm. This graph describes the details of communication among individuals to share their information and make a new decision. A new labyrinthine network of neighbors is defined in the decision-making process of the algorithm. In order to prevent getting trapped in local optima, the neighboring networks are regenerated in each iteration of the algorithm. In this algorithm, the normal distribution is utilized for a group of agents with the best results (guidance group) to replace the existing infeasible solutions. Here, some new functions are introduced to provide a high convergence for the method. These functions not only increase the local and global search capabilities but also require less computational effort. Various benchmark functions and engineering problems are examined and the results are compared with those of some other algorithms to show the capability and performance of the presented method.

• Journal of Broadcast Engineering
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• v.16 no.4
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• pp.669-679
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• 2011

In this paper, we propose a POCS based irregularly sampled image interpolation method exploiting non-local block-based wavelet shrinkage denoising algorithm. The method provides convex sets to improve the performance. The Delaunay triangulation interpolation is first applied to interpolate the missing pixels of the irregularly sampled image into the regular grids. Then, the non-local block-based wavelet shrinkage denoising algorithm is applied, and the originally observed pixels are enforced. After iteration is performed, the denoising algorithm for non-edge areas is applied to acquire the final result. The experimental results show that the proposed method outperforms the conventional methods.