• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4604-4622
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• 2015

It is not easy to reconstruct the geometrical characteristics of the distorted images captured by the devices. One of the most popular optimization methods is fast iterative shrinkage/ thresholding algorithm. In this paper, to deal with its approximation error and the turbulence of the decrease process, an adaptive proximal conjugate gradient (APCG) framework is proposed. It contains three stages. At first stage, a series of adaptive penalty matrices are generated iterate-to-iterate. Second, to trade off the reconstruction accuracy and the computational complexity of the resulting sub-problem, a practical solution is presented, which is characterized by solving the variable ellipsoidal-norm based sub-problem through exploiting the structure of the problem. Third, a correction step is introduced to improve the estimated accuracy. The numerical experiments of the proposed algorithm, in comparison to the favorable state-of-the-art methods, demonstrate the advantages of the proposed method and its potential.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.2
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• pp.270-275
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• 2008

The straight bevel gear for automobile part has been manufactured by the cold forging instead of the gear machining tool for the mass production. The application to CAD/CAM system has been necessary in order to develop the precision product quickly by forging through the minimization of trial and error and confirm the reproducibility. In the study, the straight bevel gear with the crown teeth has been modelled by the CAD/CAM system. The master gear after the gearing test has been machined after the modelling, NC data generation and verification. The die for forging and the jig for machining has been manufactured using the master gear.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.7 s.184
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• pp.152-158
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• 2006

The objective of this work is to develop the knee joint model for representing various pendulum motions and quantifying the spasticity. Knee joint model included the extension and flexion muscles. The joint moment consists of both the active moment from the stretch reflex and the passive moment from the viscoelastic joint properties. The stretch reflex was modeled as nonlinear feedback of muscle length and the muscle lengthening velocity, which is Physiologically-feasible. Moreover, we modeled the spastic reflex as having dynamic threshold to account far the various pendulum trajectories of spastic patients. We determined the model parameters of three patients who showed different pendulum trajectories through minimization of error between experimental and simulated trajectories. The simulated joint trajectories closely matched with the experimental ones, which show the proposed model can predict pendulum motions of patients with different spastic severities. The predicted muscle force from spastic reflex appeared more frequently in the severe spastic patient, which indicates the dynamic threshold relaxes slowly in this patient as is manifested by the variation coefficient of dynamic threshold. The proposed method provides prediction of muscle force and intuitive and objective evaluation of spasticity and it is expected to be useful in quantitative assessment of spasticity.

• Structural Engineering and Mechanics
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• v.22 no.4
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• pp.401-418
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• 2006

Solutions to the problems of structural parameter estimation from modal response using leastsquares minimization of force or displacement residuals are generally sensitive to noise in the response measurements. The sensitivity of the parameter estimates is governed by the physical characteristics of the structure and certain features of the noisy measurements. It has been shown that the regularization method can be used to reduce effects of the measurement noise on the estimation error through adding a regularization function to the parameter estimation objective function. In this paper, we adopt the regularization function as the Euclidean norm of the difference between the values of the currently estimated parameters and the a priori parameter estimates. The effect of the regularization function on the outcome of parameter estimation is determined by a regularization factor. Based on a singular value decomposition of the sensitivity matrix of the structural response, it is shown that the optimal regularization factor is obtained by using the maximum singular value of the sensitivity matrix. This selection exhibits the condition where the effect of the a priori estimates on the solutions to the parameter estimation problem is minimal. The performance of the proposed algorithm is investigated in comparison with certain algorithms selected from the literature by using a numerical example.

• International Journal of Contents
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• v.11 no.3
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• pp.47-53
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• 2015

Visual object tracking is a fundamental problem in the field of computer vision, as it needs a proper model to account for drastic appearance changes that are caused by shape, textural, and illumination variations. In this paper, we propose a feature-based visual-object-tracking method with a sparse representation. Generally, most appearance-based models use the gray-scale pixel values of the input image, but this might be insufficient for a description of the target object under a variety of conditions. To obtain the proper information regarding the target object, the following combination of features has been exploited as a corresponding representation: First, the features of the target templates are extracted by using the HOG (histogram of gradient) and LBPs (local binary patterns); secondly, a feature-based sparsity is attained by solving the minimization problems, whereby the target object is represented by the selection of the minimum reconstruction error. The strengths of both features are exploited to enhance the overall performance of the tracker; furthermore, the proposed method is integrated with the particle-filter framework and achieves a promising result in terms of challenging tracking videos.

• ETRI Journal
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• v.27 no.6
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• pp.747-758
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• 2005

The problem of selection among competing models has been a fundamental issue in statistical data analysis. Good fits to data can be misleading since they can result from properties of the model that have nothing to do with it being a close approximation to the source distribution of interest (for example, overfitting). In this study we focus on the preference among models from a family of polynomial regressors. Three decades of research has spawned a number of plausible techniques for the selection of models, namely, Akaike's Finite Prediction Error (FPE) and Information Criterion (AIC), Schwartz's criterion (SCH), Generalized Cross Validation (GCV), Wallace's Minimum Message Length (MML), Minimum Description Length (MDL), and Vapnik's Structural Risk Minimization (SRM). The fundamental similarity between all these principles is their attempt to define an appropriate balance between the complexity of models and their ability to explain the data. This paper presents an empirical study of the above principles in the context of model selection, where the models under consideration are univariate polynomials. The paper includes a detailed empirical evaluation of the model selection methods on six target functions, with varying sample sizes and added Gaussian noise. The results from the study appear to provide strong evidence in support of the MML- and SRM- based methods over the other standard approaches (FPE, AIC, SCH and GCV).

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.260-263
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• 2000

A technique that uses linear prediction to achieve noise reduction in a voice signal which has been mixed with an ambient noise (Signal to Noise (S-N) ratio = about 0dB) is proposed. This noise reduction method which is based on the linear prediction estimates the voice spectrum while ignoring the spectrum of the noise. The performance of the noise reduction method is first examined using the transversal linear predictor filter. However, with this method there is deterioration in the tone quality of the predicted voice due to the low level of the S-N ratio. An additional processing circuit is then proposed so as to adjust the noise reduction circuit with an aim of improving the problem of tone deterioration. Next, we consider a practical application where the effects of round on errors arising from fixed-point computation has to be minimized. This minimization is achieved by using the lattice predictor filter which in comparison to the transversal type, is Down to be less sensitive to the round-off error associated with finite word length operations. Finally, we consider a practical application where noise reduction is necessary. In this noise reduction method, both the voice spectrum and the actual noise spectrum are estimated. Noise reduction is achieved by using the linear predictor filter which includes the control of the predictor filter coefficient’s update.

• Journal of Families and Better Life
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• v.33 no.2
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• pp.35-51
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• 2015

The purpose of this study was to provide information for research about residents' opinion toward the physical environments of elderly facilities, through the analysis and investigation on the research methodology of foreign academic journal articles from 1990 to 2014. The study results were as follows: Firstly, purposive sampling was a large majority of both facilities and elderly residents. In quantitative studies, many researchers have conducted simple random, cluster, or stratified sampling. Diverse facilities in area, size, location, and etc. should be considered for participation. The qualifications for residents' participation should be considered as well, so that they all could have autonomy for study participation. Secondly, questionnaire and semi-structured guide were likely to be used in independent and resident care facilities. On the other hand in assisted living and long-term care facilities, open questions and visual material were used as well. A compatible scale should be developed so that elderly having variable functional level could participate independently in the study. Thirdly, in data collection process, compliance with research ethics and well trained interviewer's skill were important for residents' active responses and minimization of response errors. Enough research period of time and mixed study in data collection will decrease the response error.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1685-1695
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• 1996

The postprocessing of compressed images based on the projections onto convex sets and the constrained minimization imposes several constraints on the procesed data. The quantization constraint has been commonly used in various algorithms. Quantization is many-to-one mapping, by which all the dat in a quantization region are mapped to the corresponding representative level. The basic idea behind the projection onto the QCS(quantization constraint set) is to prevent the processed data from diverging from the original quantization region in order to redue the artifacts caused by filtering in postprocessing. However, there have been few efforts to analye the POQCS(projection onto the QCS). This paper analyzed mathematically the POQCS of filtered data from the viewpoint of minimizing the mean square error. Our analysis shows that a proper filtering technique followed by the POQCS can reduce the quantization distortion. In the conventional POQCS, the outside data of each quantization region are mapped into the corresponding boundary. Our analysis also shows that mappingthe outside data to the boundary of a subregion of the quantization region yields lower distortion than does the mapping to the boundary of the original region. In addition, several examples and discussions on the theory are introduced.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.2
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• pp.34-41
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• 2014

The purpose of this study is to present the improvement of connection system between traffic information centers for reliable traffic information service. We recognized traffic information error caused by too much time in conjunction between traffic information centers, lack of reliability of traffic information caused by absence of generation time and generation institution of traffic information. We presented minimization methods of connection time, improvement methods of reliability of traffic information and development methods of connection state management system.