• Resources Recycling
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• v.27 no.1
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• pp.84-91
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• 2018

In this study, a novel soft information based most probable classification scheme is proposed for sorting recyclable metal alloys with laser induced breakdown spectroscopy (LIBS). Regression analysis with LIBS captured spectrums for estimating concentrations of common elements can be efficient for classifying unknown arbitrary metal alloys, even when that particular alloy is not included for training. Therefore, partial least square regression (PLSR) is employed in the proposed scheme, where spectrums of the certified reference materials (CRMs) are used for training. With the PLSR model, the concentrations of the test spectrum are estimated independently and are compared to those of CRMs for finding out the most probable class. Then, joint soft information can be obtained by assuming multi-variate normal (MVN) distribution, which enables to account the probability measure or a prior information and improves classification performance. For evaluating the proposed schemes, MVN soft information is evaluated based on PLSR of LIBS captured spectrums of 9 metal CRMs, and tested for classifying unknown metal alloys. Furthermore, the likelihood is evaluated with the radar chart to effectively visualize and search the most probable class among the candidates. By the leave-one-out cross validation tests, the proposed scheme is not only showing improved classification accuracies but also helpful for adaptive post-processing to correct the mis-classifications.

• Journal of KIISE:Information Networking
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• v.28 no.2
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• pp.277-287
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• 2001

Test derivation methods suitable for interoperability testing of communication protocols were proposed in [1,2, 3] and applied to the TCP and the ATM protocols, The test cases that were generated by them deal with only the control part of the protocols. However, in real protocol testing, the test cases must manage the data part as well. For complete testing, in principle we must test all possible values of data part although it is impractical to do so. In this paper, we present a method generating the interoperability test suite for both the data part and the control part of protocols with the example of Tep connection establishment. In this process, we make use of experimental design techniques from industrial engineering to minimize the size of test suite while keeping testing capability. Experimental design techniques have been used for protocol confom1ance testing but not for intcruperability testing so far. We generate the test suite for data part by this method and show a possibility that we can test interoperability of protocols with the minimum number of test cases while maintaining the testing power.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.6
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• pp.1-10
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• 2007

This paper presents a direct nonlinear multivariable self-tuning PID controller using neural network which adapts to the changing parameters of the nonlinear multivariable system with noises and time delays. The nonlinear multivariable system is divided linear part and nonlinear part. The linear controller are used the self-tuning PID controller that can combine the simple structure of a PID controllers with the characteristics of a self-tuning controller, which can adapt to changes in the environment. The linear controller parameters are obtained by the recursive least square. And the nonlinear controller parameters are achieved the through the Back-propagation neural network. In order to demonstrate the effectiveness of the proposed algorithm, the computer simulation results are presented to adapt the nonlinear multivariable system with noises and time delays and with changed system parameter after a constant time. The proposed PID type nonlinear multivariable self-tuning method using neural network is effective compared with the conventional direct multivariable adaptive controller using neural network.

• Journal of Biomedical Engineering Research
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• v.22 no.1
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• pp.59-68
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• 2001

유체-고체 상호작용을 고려하여 다양한 복부대동맥류 모델에 대해서 맥동유동 및 구조를 동시에 해석하였다. 동맥류의 확장부 크기와 혈관벽 두께에 따라서 총 여덟 개의 축대칭 동맥류 모델을 선정하였다. 유한체적법 및 압력기반의 유한차분법을 이용하여 유동을 해석하였으며, 유한요소법을 이용하여 구조해석을 수행하였다. 동맥류의 확장부위가 클수록 최대응력은 최대확장부위와 변곡점에 해당하는 동맥류의 입구 및 출구 부분에 집중되었으며, Von Mises 응력은 최대확장부위 뿐만 아니라 동맥류의 근위부와 원위부($\pm$1D)에서도 현저하게 증가하였다. 또한 더욱 확장된 모델일수록 혈관벽은 직경방향의 변위보다 축방향의 변위가 지배적이었으며, 동맥류 원위부보다 근위부에서 큰 축방향 변위를 나타냈다. 동맥류 입구부의 미약한 와류는 한 주기동안 그 크기와 강도를 더해가며 동맥류 원외부로 이동하였고, 동맥류의 내부 유동은 압력차이가 감소하는 기간동안 더 큰 영향을 받았다. 확장정도가 심할수록 동맥류 내부에 더 크고 강한 와류가 관찰되었다. 압력차이가 최소가 된 직후 동맥류의 근위부와 원위부동맥 벽 근처에서의 역방향 유동이 관찰되었다. 대체로 혈관벽 두께가 감소한 모델과 더욱 확장된 모델일수록 벽전달률은 감소하였다. 혈관벽의 탄성에 의하여 압력차이와 벽전달률 사이에 위상차가 존재함이 확인되었다. 유체-고체의 상호작용을 고려한 연구는 다른 심혈관계를 이해하는데도 매우 유익할 것으로 생각된다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.349-355
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• 2017

Bending work using press dies involves bending a flat blank to a desired angle. The bending produces a flange (the bent part) and a web (the unbent part). The bending line will have a bending angle, and there is an inner and outer bending radius. The minimum inner radius size is determined by the material used. When the inner radius size is too small, there will be excess metal welding, which will cause a crack in the outer radius part. The outer bending radius size cannot be controlled by a bending punch and die block. Types of bending include V-bending, U-bending, O-bending, edge bending, twist bending, and crimping. Z-bending involves two bending lines, which are set on the upper side and under surface of the blank, respectively, and upward or downward bending is used. Z-bending is also called crank bending. Z-bending using this type of die structure will produce a standard inner bending radius. The standard size is the minimum bending radius that represents the angle radius of the bending punch. In industry, there is a need for a sharp edge shape with a very small size (R=0.2mm), but that is not possible when using bending punch and die block. The purpose of this research is to meet the need by development.

• Journal of the Korean GEO-environmental Society
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• v.20 no.11
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• pp.11-22
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• 2019

Limit state design (LSD) and allowable stress design (ASD) are two main types of soil nailing design methodologies. In the LSD method, stability is determined by applying individual coefficients to ground strength, working load and etc. The ASD method calculates the safety factor and compares it with the minimum safety factor to determine the stability. The global design trend of soil nailing system is changing from the ASD method to the LSD method. The design method in Korea still adopts the ASD philosophy while others mostly do the limit state design. In this study, four soil nail design methods, 'FHWA GEC 7' in U.S. (2015), 'Clouterre' in France (1991), 'Soil nailing - best practice guidance' in U.K. (2005), 'Geoguide 7' in Hongkong (2008), and 'Design guide for slope in construction work' in Korea (2016) were applied to the evaluation of the stability and the results were analyzed comparatively in brief. It is revealed that the design method of 'the overall stability of soil nail walls' in Korea is the most conservative and next those by FHWA, Clouterre and CIRIA become more conservative in order. However, the difference of results obtained from FHWA and Clouterre is negligible. Also, this study found out that efforts to improve domestic design criterion are needed.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.599-604
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• 2005

This paper presents fuzzy rules to predict diagnosis of Wisconsin breast cancer with minimized number of feature in put using the neural network with weighted fuzzy membership functions (NEWFM) and the non-overlap area distribution measurement method. NEWFM is capable of self-adapting weighted membership functions from the given the Wisconsin breast cancer clinical training data. n set of small, medium, and large weighted triangular membership functions in a hyperbox are used for representing n set of featured input. The membership functions are randomly distributed and weighted initially, and then their positions and weights are adjusted during learning. After learning, prediction rules are extracted directly from n set of enhanced bounded sums of n set of small, medium, and large weighted fuzzy membership functions. Then, the non-overlap area distribution measurement method is applied to select important features by deleting less important features. Two sets of prediction rules extracted from NEWFM using the selected 4 input features out of 9 features outperform to the current published results in number of set of rules, number of input features, and accuracy with 99.71%.

• Korean Journal of Optics and Photonics
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• v.31 no.3
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• pp.125-133
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• 2020

An innovative method for separating overlapping latent fingerprints, using laser-induced plasma spectroscopy (LIPS) combined with multivariate analysis, is reported in the current study. LIPS provides the capabilities of real-time analysis and high-speed scanning, as well as data regarding the chemical components of overlapping fingerprints. These spectra provide valuable chemical information for the forensic classification and reconstruction of overlapping latent fingerprints, by applying appropriate multivariate analysis. This study utilizes principal-component analysis (PCA) and partial-least-squares (PLS) techniques for the basis classification of four types of fingerprints from the LIPS spectra. The proposed method is successfully demonstrated through a classification example of four distinct latent fingerprints, using discrimination such as soft independent modeling of class analogy (SIMCA) and partial-least-squares discriminant analysis (PLS-DA). This demonstration develops an accuracy of more than 85% and is proven to be sufficiently robust. In addition, by laser-scanning analysis at a spatial interval of 125 ㎛, the overlapping fingerprints were separated as two-dimensional forms.

• Korean Chemical Engineering Research
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• v.45 no.1
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• pp.87-92
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• 2007

Recently, developments of process monitoring system in order to detect and diagnose process abnormalities has got the spotlight in process systems engineering. Normal data obtained from processes provide available information of process characteristics to be used for modeling, monitoring, and control. Since modern chemical and environmental processes have high dimensionality, strong correlation, severe dynamics and nonlinearity, it is not easy to analyze a process through model-based approach. To overcome limitations of model-based approach, lots of system engineers and academic researchers have focused on statistical approach combined with multivariable analysis such as principal component analysis (PCA), partial least squares (PLS), and so on. Several multivariate analysis methods have been modified to apply it to a chemical process with specific characteristics such as dynamics, nonlinearity, and so on.This paper discusses about missing value estimation and sensor fault identification based on process variable reconstruction using dynamic PCA and canonical variate analysis.

• The Journal of the Korea Contents Association
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• v.16 no.4
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• pp.426-433
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• 2016

This study investigates the effects of entrepreneurship and corporate social responsibility (CSR) on firm performance. I use the conditional quantile regression as well as the ordinary least square (OLS) with 300 samples, only medium and small size companies. I found firstly, entrepreneurship affected overall positively firm performance in the all quantile levels. Secondly, CSR also have a positive impact on firm performance in the overall all quantile levels. By these results, I recommend that entrepreneurship and CSR should a positive impact on the firm performance for the small and medium business companies.