• Journal of Korean Society for Quality Management
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• v.44 no.2
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• pp.297-308
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• 2016

Purpose: This paper treats a defense-supply chain quality management model for analyzing the Korea defense industry. Methods: Various literature, the quality collaboration index for supply chain management model proposed by Korean Standards Association and shared growth index presented by Korea Commission for Corporate Partnership are reviewed to develop the defense supply chain quality management index and model based on the method presented by Hafeez et al.(2006). In addition, based on the proposed model, we survey the supply chain quality management efficiency including focused group interviews in the defense industry. Results: We propose a defense-supply chain quality management index and model for analyzing the quality level between the parent companies and its partners. In addition, the results of applying the model are proposed to improve the quality of military items. Conclusion: A model is developed for improving the quality of military items. This proposed model will be adopted to enhance the quality of military items.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.10
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• pp.25-32
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• 2011

We have analyzed adjacent cell dependency of threshold voltage shift caused by the cell to cell interference, and we proposed a 3-adjacent-cell model to model the pattern dependency of the threshold voltage shift. The proposed algorithm is verified by using MATLAB simulation and measurement results. In the experimental results, we found that accuracy of the proposed simple 3-adjacient-cell model is comparable to the widely used conventional 8-adjacient-cell model. The Bit Error Rate (BER) of LSB and of MSB is improved by 28.9% and 19.8%, respectively, by applying the proposed algorithm based on 3-adjacent-cell model to 20nm-class 2-bit MLC NAND flash memories.

• Geomechanics and Engineering
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• v.25 no.2
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• pp.75-87
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• 2021

Because the hydraulic/mechanical behaviour of unsaturated soil is more complicated than that of saturated soil, one of the most important issues in modelling unsaturated soil is to properly couple its stress-strain relationship with its water retention characteristics. Based on the results of a series of tests, the stress-strain relationship and the changes in suction and saturation of unsaturated completely decomposed granite (CDG, also called Masado) vary substantially under different loading/hydraulic conditions. To precisely model the hydraulic/mechanical behaviour of unsaturated Masado, in this study, the superloading concept was firstly introduced into an existing saturated/unsaturated constitutive model to consider the structural influences. Then a water retention curve (WRC) model considering the volumetric change in the soil, in which the skeleton and scanning curves of the water retention characteristics were assumed to shift in parallel in accordance with the change in the void ratio, was proposed. The proposed WRC model was incorporated into the constitutive model, and the validity of the newly proposed model was verified using the results of tests conducted on unsaturated Masado, including water retention, oedometer and triaxial tests. The accuracy of the proposed model in describing the stress-strain relationship and the variations in suction and saturation of unsaturated Masado is satisfactory.

• Journal of Korea Multimedia Society
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• v.22 no.8
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• pp.923-929
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• 2019

In this paper, biomimetic based physical ear model proposed for measuring the characteristics of a hybrid-acoustic sensor for fully implantable middle-ear hearing aid. The proposed physical ear model consists of the external ear, middle-ear, and cochlea. The physical ear model was implemented based on the anatomical structure and CT images of the human ear. To confirm the characteristics of the ear model, the vibrational characteristics of the stapes was measured after applying sound pressure to the tympanic membrane. The measured results were compared with the vibrational characteristics of the human temporal bone specified by ASTM F2504-05. Through the comparison results, the feasibility of the proposed ear model was confirmed. Then, after attaching the hybrid-acoustic sensor to the ear model, the output characteristics of the ECM and acceleration sensor were measured according to the sound pressure. The measured results were compared with previous studies using human temporal bone, and the usefulness of the proposed physical ear model was verified through the analysis results.

• Wind and Structures
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• v.22 no.4
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• pp.477-501
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• 2016

Though hilly topography influences both wind speeds and directions aloft, only the influence on wind speeds, i.e. the speed-up effect, has been thoroughly investigated. Due to the importance of a model showing the spatial variations of wind directions above hilly terrains, it is worthwhile to systematically assess the applicability and limitations of the model describing the influence of hilly topographies on wind directions. Based on wind-tunnel test results, a model, which describes the horizontal and vertical variations of the wind directions separately, has been proposed in a companion paper. CFD (Computational Fluid Dynamics) techniques were employed in the present paper to evaluate the applicability of the proposed model. From the investigation, it has been found that the model is acceptable for describing the vertical variation of wind directions by a shallow hill whose primary-to-secondary axis ratio (aspect ratio) is larger than 1. When the overall hill slope exceeds $20^{\circ}$, the proposed model should be used with caution. When the aspect ratio is less than 1, the proposed model is less accurate in predicting the spatial variation of wind directions in the wake zone in a separated flow. In addition, it has been found that local slope of a hill has significant impact on the applicability of the proposed model. Specifically, the proposed model is only applicable when local slope of a hill varies gradually from 0 (at the hill foot) to the maximum value (at the mid-slope point) and then to 0 (at the hill top).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.184-192
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• 2011

In this study, we introduce a identification methodology for FCM-based fuzzy model. The two underlying design mechanisms of such networks involve Fuzzy C-Means (FCM) clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on FCM clustering method for efficient processing of data and the optimization of model was carried out using PSO. The premise part of fuzzy rules does not construct as any fixed membership functions such as triangular, gaussian, ellipsoidal because we build up the premise part of fuzzy rules using FCM. As a result, the proposed model can lead to the compact architecture of network. In this study, as the consequence part of fuzzy rules, we are able to use four types of polynomials such as simplified, linear, quadratic, modified quadratic. In addition, a Weighted Least Square Estimation to estimate the coefficients of polynomials, which are the consequent parts of fuzzy model, can decouple each fuzzy rule from the other fuzzy rules. Therefore, a local learning capability and an interpretability of the proposed fuzzy model are improved. Also, the parameters of the proposed fuzzy model such as a fuzzification coefficient of FCM clustering, the number of clusters of FCM clustering, and the polynomial type of the consequent part of fuzzy rules are adjusted using PSO. The proposed model is illustrated with the use of Automobile Miles per Gallon(MPG) and Boston housing called Machine Learning dataset. A comparative analysis reveals that the proposed FCM-based fuzzy model exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.

• Journal of Intelligence and Information Systems
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• v.12 no.4
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• pp.1-14
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• 2006

This study proposed a customer preference estimation model for production recommendation and a method to enhance the performance of product recommendation using the estimated customer preference information. That is, we suggested customer preference estimation model to estimate exactly customer's product preference with his behavior. This model shows the relationship of customer's behaviors with his preferences. The proposed estimation model is optimized by learning the relative weights of customer's behavior variables to have an effect on his preference and enables to estimate exactly his preference. To validate our proposed models, we collected virtual book store data and then made a comparative analysis of our proposed models and a benchmark model in terms of performance results of collaborative filtering for product recommendation. The benchmark model means a prior preference weighting model. The results of our empirical analysis showed that our proposed model performed better results than the benchmark model.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.10
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• pp.831-841
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• 1991

A combined model of probabilistic and MLP(multi layer perceptron) model is proposed for the pattern classification of EMG( electromyogram) signals. The MLP model has a problem of not guaranteeing the global minima of error and different quality of approximations to Bayesian probabilities. The probabilistic model is, however, closely related to the estimation error of model parameters and the fidelity of assumptions. A proper combination of these will reduce the effects of the problems and be robust to input variations. Proposed model is able to get the MAP(maximum a posteriori probability) in the probabilistic model by estimating a priori probability distribution using the MLP model adaptively. This method minimize the error probability of the probabilistic model as long as the realization of the MLP model is optimal, and this is a good combination of the probabilistic model and the MLP model for the usage of MLP model reliability. Simulation results show the benefit of the proposed model compared to use the Mlp and the probabilistic model seperately and the average calculation time fro classification is about 50ms in the case of combined motion using an IBM PC 25 MHz 386model.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.369-382
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• 2014

This paper introduces a new multi-product multi-period multi-objective aggregate production planning problem. The proposed problem is modeled using multi-objective mixed-integer mathematical programming. Three objective functions, including minimizing total cost, maximizing customer services level, and maximizing the quality of end-product, are considered, simultaneously. Several constraints such as quantity of production, available time, work force levels, inventory levels, backordering levels, machine capacity, warehouse space and available budget are also considered. Some parameters of the proposed model are assumed to be qualitative and modeled using fuzzy sets. Then, a fuzzy goal programming approach is proposed to solve the model. The proposed approach is applied on a real-world industrial case study of a color and resin production company called Teiph-Saipa. The approach is coded using LINGO software. The efficacy and applicability of the proposed approach are illustrated in the case study. The results of proposed approach are compared with those of the existing experimental methods used in the company. The relative dominance of the proposed approach is revealed in comparison with the experimental method. Finally, a data dictionary, including the way of gathering data for running the model, is proposed in order to facilitate the re-implementation of the model for future development and case studies.

• ETRI Journal
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• v.38 no.1
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• pp.185-194
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• 2016

In this paper, a novel rate control scheme for low delay video coding of High Efficiency Video Coding (HEVC) is proposed. The proposed scheme is developed by considering a new temporal prediction structure of HEVC. In the proposed scheme, the relationship between bit rate and quantization step is exploited firstly to formulate an accurate quadratic rate-quantization (R-Q) model. Secondly, a method of determining the quantization parameters (QPs) for the first frames within a group of pictures is proposed. Thirdly, an accurate frame-level bit allocation method is proposed for HEVC. Finally, based on the proposed R-Q model and the target bit allocated for the frame, the QPs are predicted for coding tree units by using rate-distortion (R-D) optimization. We compare our scheme against that of three other state-of-the-art rate control schemes. Experimental results show that the proposed rate control scheme can increase the Bjøntegaard delta peak signal-to-noise ratio by 0.65 dB and 0.09 dB on average compared with the JCTVC-I0094 and JCTVC-M0036 schemes, respectively, both of which have been implemented in an HEVC test model encoder; furthermore, the proposed scheme achieves a similar R-D performance to Wang's scheme, as well as obtaining the smallest bit rate mismatch error of all the schemes.