• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.4
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• pp.114-119
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• 2011

Process capability indices (PCls) have been widely used in manufacturing industries to provide a quantitative measure of process potential and performance. The previous studies have measured only one location on each part in the case of single variate. To calculate the reliable process capability, a couple of measuring locations on each part are required. In this paper, we propose a new system process capability index $SC_{pm}$ (m) which is the minimum value of the location PCls.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3A
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• pp.193-200
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• 2010

Structural design requires simultaneously to ensure safety by considering quantitatively uncertainties in the applied loadings, material properties and fabrication error and to maximize economical efficiency. As a solution, system reliability-based design optimization (SRBDO), which takes into consideration both uncertainties and economical efficiency, has been extensively researched and numerous attempts have been done to apply it to structural design. Contrary to conventional deterministic optimization, SRBDO involves the evaluation of component and system probabilistic constraints. However, because of the complicated algorithm for calculating component reliability indices and system reliability, excessive computational time is required when the large-scale finite element analysis is involved in evaluating the probabilistic constraints. Accordingly, an algorithm for SRBDO exhibiting improved stability and efficiency needs to be developed for the large-scale problems. In this study, a more stable and efficient SRBDO based on the performance measure approach (PMA) is developed. PMA shows good performance when it is applied to reliability-based design optimization (RBDO) which has only component probabilistic constraints. However, PMA could not be applied to SRBDO because PMA only calculates the probabilistic performance measure for limit state functions and does not evaluate the reliability indices. In order to overcome these difficulties, the decoupled algorithm is proposed where RBDO based on PMA is sequentially performed with updated target component reliability indices until the calculated system reliability index approaches the target system reliability index. Through a mathematical problem and ten-bar truss problem, the proposed method shows better convergence and efficiency than other approaches.

• Journal of Korea Multimedia Society
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• v.18 no.9
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• pp.1008-1018
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• 2015

In this paper, we propose a method that constructs a saliency map in which important regions are accurately specified and the colors of the regions are less influenced by the similar surrounding colors. Our method utilizes LBP(Local Binary Pattern) histogram information to compare and analyze texture information of surrounding regions in order to reduce the effect of color information. We extract the saliency of stereoscopic images by integrating a 2D saliency map with depth information of stereoscopic images. We then measure the distance between two different sizes of the LBP histograms that are generated from pixels. The distance we measure is texture difference between the surrounding regions. We then assign a saliency value according to the distance in LBP histogram. To evaluate our experimental results, we measure the F-measure compared to ground-truth by thresholding a saliency map at 0.8. The average F-Measure is 0.65 and our experimental results show improved performance in comparison with existing other saliency map extraction methods.

• Journal of Broadcast Engineering
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• v.16 no.5
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• pp.883-893
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• 2011

In this paper, we propose a novel focus measure that determines in-focus and out-of-focus region in an image. In addition, we achieved extended depth of field by blending the acquired image and Wiener filtered image using a decision map based on the designed focus measure. Since conventional focus measures are based on the amount of high frequency components in an acquired image, the measures may not be accurate if there exist high frequency components in out-of-focused region. To overcome the problem, we designed the novel focus measure based on effective band pass filtering. In simulations and experiments, the proposed method showed better performance than existing methods.

• International Journal of Contents
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• v.11 no.2
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• pp.57-62
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• 2015

Relative entropy is a divergence measure between two probability density functions of a random variable. Assuming that the random variable has only two alphabets, the relative entropy becomes a cross-entropy error function that can accelerate training convergence of multi-layer perceptron neural networks. Also, the n-th order extension of cross-entropy (nCE) error function exhibits an improved performance in viewpoints of learning convergence and generalization capability. In this paper, we derive a new divergence measure between two probability density functions from the nCE error function. And the new divergence measure is compared with the relative entropy through the use of three-dimensional plots.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1824-1845
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• 2016

The GMM is a conventional approach which has been recently applied in many face recognition studies. However, the question about how to deal with illumination changes while ensuring high performance is still a challenge, especially with real-world databases. In this paper, we propose a Visual Observation Confidence (VOC) measure for robust face recognition for illumination changes. Our VOC value is a combined confidence value of three measurements: Flatness Measure (FM), Centrality Measure (CM), and Illumination Normality Measure (IM). While FM measures the discrimination ability of one face, IM represents the degree of illumination impact on that face. In addition, we introduce CM as a centrality measure to help FM to reduce some of the errors from unnecessary areas such as the hair, neck or background. The VOC then accompanies the feature vectors in the EM process to estimate the optimal models by modified-GMM training. In the experiments, we introduce a real-world database, called KoFace, besides applying some public databases such as the Yale and the ORL database. The KoFace database is composed of 106 face subjects under diverse illumination effects including shadows and highlights. The results show that our proposed approach gives a higher Face Recognition Rate (FRR) than the GMM baseline for indoor and outdoor datasets in the real-world KoFace database (94% and 85%, respectively) and in ORL, Yale databases (97% and 100% respectively).

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.1
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• pp.37-43
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• 2018

There has been the migration to a performance-based approach in many areas which include transition planning at global, regional and local levels, performance-based navigation and safety management. Achieving continuous success of Air Traffic Management (ATM) systems would require a performance-based approach to raise productivity and efficiency of it through performance measurements and reviews. This paper considers establishment planning of performance measurement and evaluation system for ATM. Related to key performance areas proposed by International Civil Aviation Organization, performance indicators and metrics which could be used to measure and evaluate ATM performance are presented. Also, organizational system and operational planning for efficient operation of ATM are presented.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.3
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• pp.297-304
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• 2021

The maintenance management system of domestic public facilities is shifting from the concept of diagnosis and repair for maintaining safety of facilities to performance evaluation method that improves and maintains the performance of facilities. However, in Korea, the performance evaluation method for the maintenance of facilities has not been established, so the performance evaluation has not been properly performed. In this study, we propose an asset management model that introduces the concept of performance evaluation to complement the simple maintenance strategy focused on safety management of current facilities. This model differentiated from the existing model by proposing a method for using WBS as a method for collecting facility maintenance information. This model proposed the most important level of service evaluation method and performance measure factors in the performance evaluation of facilities, and conducted a case analysis to assess the appropriateness of this model.

• International Journal of Automotive Technology
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• v.6 no.1
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• pp.71-77
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• 2005

This paper presents a systematic approach which determines the optimal period to minimize performance measure subject to the schedulability constraints of a real-time control system by formulating the scheduling problem as an optimal problem. The performance measure is derived from the summation of end-to-end response times of processed I/Os scheduled by the static cyclic method. The schedulability constraint is specified in terms of allowable resource utilization. At first, a uniprocessor case is considered and then it is extended to a distributed system connected through a communication link, local-inter network, UN. This approach is applied to the design of an automotive body control system in order to validate the feasibility through a real example. By using the approach, a set of optimal periods can easily be obtained without complex and advanced methods such as branch and bound (B&B) or simulated annealing.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.130-137
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• 1992

This paper presents the word recognition method using a neural-fuzzy pattern matching, in order to make a proper speech pattern for a spectrum sequence and to improve a recognition rate. In this method, a frequency variation is reduced by generating binary spectrum patterns through associative memory using a neural network, and a time variation is decreased by measuring the simillarity using a fuzzy pattern matching. For this method using binary spectrum patterns and logic algebraic operations to measure the simillarity, memory capacity and computation requirements are far less than those of DTW using a conventional distortion measure. To show the validity of the recognition performance for this method, word recognition experiments are carried out using 28 DDD city names and compared with DTW and a fuzzy pattern matching. The results show that our presented method is more excellent in the recognition performance than the other methods.