• Tribology and Lubricants
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• 제30권1호
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• pp.59-63
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• 2014

Laser Surface Texturing(LST) is a surface engineering process used to improve tribological characteristics of materials by creating patterned microstructures on the mechanical contact surface. In LST technology, a pulsated laser beam is used to create arranged dimples on a surface by a material ablation process, which can improve such as load capacity, wear resistances, lubrication lifetime, and reduce friction coefficients. In the present study, the effect of multi-scale LST on lubricant regime was investigated. A pulsed Nd:YAG laser was applied on the bearing steel(AISI 52100) to create arranged dimples. To optimize the surface texturing effect on friction, multi-scale texture dimples with some specific formula arrays were fabricated by combining circles, ellipses and the laser ablation process. The tribological testing of multi-scale textured surface was performed by a flat-on-flat unidirectional tribometer under lubrication and the results compared with that of the non-textured surface. Through an increase in sliding speed, the beneficial effect of multi-scale LST performance was achieved. The multi-scale textured surface had lower friction coefficient performances than the non-textured surface due to the hydrodynamic lubrication effect.

• 한국항행학회논문지
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• 제23권5호
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• pp.400-407
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• 2019

본 논문에서는 다양한 조도의 영향에도 본질적인 특성이 변하지 않는 고유영상을 이용한 그림자 검출과 멀티 스케일 감마 보정 기반의 그림자 복원 방법을 제안하였다. 그림자 검출은 컬러 영상의 그레이스케일 영상과 고유영상 간의 화소 변화 정보를 이용하여 추정하였으며, 그림자 복원 과정에서는 감마 보정을 통해 영상의 밝기를 조절하는 방법을 적용하였다. 감마 보정은 개별적 화소값에 대한 비선형 조정으로 채도가 변경될 수 있으므로 컬러 영상의 채널별로 수행되는 멀티 스케일 감마 보정을 수행한다. 멀티 스케일 감마 값은 컬러 영상에서 그림자와 그림자가 아닌 영역의 교차 윤곽을 획득한 후 이 정보를 기반으로 추정되며, 결과적으로 서로 다른 유형의 영역 특징을 멀티 스케일 감마 값으로 보정하여 그림자를 복원하였다. 실험 결과, 제안하는 방법이 그림자가 포함된 단일 자연 영상에서 그림자를 효과적으로 복원함을 보였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.250-253
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• 1998

This paper presents a multi-modal neural network composed of a preprocessing module and a multi-layer neural network module in order to enhance the nonlinear characteristics of neural network. The former module is based on spectral method using Chebyschev polynomials and transforms input data into spectra. The latter module identifies the system using the spectra generated by the preprocessing module. The omnibus numerical experiments show that the method is applicable to many a nonlinear dynamic system in the real world, and that preprocessing using Chebyschev polynomials reduces the number of neurons required for the multi-layer neural network.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2005년도 추계 학술발표회 제17권2호
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• pp.177-180
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• 2005

The specified tensile strength provided by the manufacturer is determined on the basis of the reliable lower limit ($X-3{\sigma}$ : X=average tensile strength, $\sigma$=standard deviation) obtained from the material test results. Most of these data, however, are based on the test results of 1 layer of FRP sheet. Also, the partial strength reduction factor for strengthening RC members with FRP is based on the small-scale model tests. But, the failure mechanisms of small-scale model tests are reported to be different from those of the full-scale tests. This paper present the test results of full-scale RC beams strengthened with multi-layer GFRP sheets up to 3 layer as well as the material tests. From the material tests, it was observed that the average tensile strengths of GFRP sheets are decreased as the number of layer are increased. Also the premature debonding failure of RC beams strengthened with multi-layer GFRP sheets are observed in inverse proportion to the number of GFRP sheets

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권4호
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• pp.1846-1863
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• 2016

High dynamic range (HDR) images can present the perfect real scene and rich color information. A commonly encountered problem in practical applications is how to well visualize HDR images on standard display devices. In this paper, we propose a multi-scale decomposition method using guided filtering for HDR image tone mapping. In our algorithm, HDR images are directly decomposed into three layers：base layer, coarse scale detail layer and fine detail layer. We propose an effective function to compress the base layer and the coarse scale detail layer. An adaptive function is also proposed for detail adjustment. Experimental results show that the proposed algorithm effectively accomplishes dynamic range compression and maintains good global contrast as well as local contrast. It also presents more image details and keeps high color saturation.

• Coupled systems mechanics
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• 제8권2호
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• pp.99-109
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• 2019

This work investigates the accuracy and performance of a $FE^2$ multi-scale implementation used to predict the behavior of composite materials. The equations are formulated assuming the small deformations solid mechanics approach in non-linear material models with hardening plasticity. The uniform strain boundary conditions are applied for the macro-to-micro transitions. A parallel algorithm was implemented in order to solve large engineering problems. The scheme proposed takes advantage of the domain decomposition method at the macro-scale and the coupling between each subdomain with a micro-scale model. The precision of the method is validated with a composite material problem and scalability tests are performed for showing the efficiency.

• Nuclear Engineering and Technology
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• 제37권6호
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• pp.511-524
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• 2005

Thermalhydraulic reactor simulation of tomorrow will require a new generation of codes combining at least three scales, the CFD scale in open medium, the component scale and the system scale. DNS will be used as a support for modelling more macroscopic models. NEPTUNE is such a new generation multi-scale platform developed jointly by CEA-DEN and EDF-R&D and also supported by IRSN and FRAMATOME-ANP. The major steps towards the next generation lie in new physical models and improved numerical methods. This paper presents the advances obtained so far in physical modelling for each scale. Macroscopic models of system and component scales include multi-field modelling, transport of interfacial area, and turbulence modelling. Two-phase CFD or CMFD was first applied to boiling bubbly flow for departure from nucleate boiling investigations and to stratified flow for pressurised thermal shock investigations. The main challenges of the project are presented, some selected results are shown for each scale, and the perspectives for future are also drawn. Direct Numerical Simulation tools with Interface Tracking Techniques are also developed for even smaller scale investigations leading to a better understanding of basic physical processes and allowing the development of closure relations for macroscopic and CFD models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권10호
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• pp.5179-5196
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• 2019

To explore an effective non-invasion medical imaging diagnostics approach for hepatocellular carcinoma (HCC), we propose a method based on adopting the multiple technologies with the multi-parametric data fusion, transfer learning, and multi-scale deep feature extraction. Firstly, to make full use of complementary and enhancing the contribution of different modalities viz. multi-parametric MRI images in the lesion diagnosis, we propose a data-level fusion strategy. Secondly, based on the fusion data as the input, the multi-scale residual neural network with SPP (Spatial Pyramid Pooling) is utilized for the discriminative feature representation learning. Thirdly, to mitigate the impact of the lack of training samples, we do the pre-training of the proposed multi-scale residual neural network model on the natural image dataset and the fine-tuning with the chosen multi-parametric MRI images as complementary data. The comparative experiment results on the dataset from the clinical cases show that our proposed approach by employing the multiple strategies achieves the highest accuracy of 0.847±0.023 in the classification problem on the HCC differentiation. In the problem of discriminating the HCC lesion from the non-tumor area, we achieve a good performance with accuracy, sensitivity, specificity and AUC (area under the ROC curve) being 0.981±0.002, 0.981±0.002, 0.991±0.007 and 0.999±0.0008, respectively.

• 한국미생물·생명공학회지
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• 제20권3호
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• pp.324-328
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• 1992

보다 경제적인 공정개발을 위하여 pilot scale의 다단 연속발효공정(multi-stage CSTR)에서 전분질 원료의 에탄올 발효를 연구하였다. 에탄올 발효를 쌀보리는 30일, cassava는 60이 동안 성공적인 운전을 할 수 있었으며, 원료는 저온 증자를 위하여 20-mesh sieve를 통과한 가루를 사용하였다. 최적화된 운전조건하에서 cassava의 overall productivity는 에탄올 농도 9.51(v/v)에서 $1.27g/{\ell}{\cdot}h$로써 종래 산업적 규모의 회분식 공정에서 얻는 것보다 약 2배 증가되었다.

• 대한가정학회지
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• 제33권4호
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• pp.49-64
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• 1995

The purpose of this study was to develop the Daily Hassles Scale for children in Korea. The subject were 444 children of 184 fourth graders and 260 sixth graders selected form five elementary schools in Seoul(217 male and 227 female). A questionnaire consisting of 90-item daily hassles scale, demographic questions, and some additional questions was used as a methodological instrument. statistics used for data analysis were X2, cramer's V, factor analysis, multi-regression, Pearson's r, Cronbach's α. The major findings of this study were as follows. 1) 87 items of the 90-item scale were acceptible through item discriminant method. The discriminant coefficients of the items(Cramer's V) ranged form .28 to .73. 2) 6 factors(parents, home environment, friends, studies, teachers & school, the surroundings) were extracted from factor analysis. Multi-regression analysis conducted to reduce the length of scale have drawed 42 items for 'the Daily Hassles Scale for Children in Korea'. The correlation between this scale and the Quality of Life Scale(Olson & Barnes, 1982) was conducted to test the criterion-related validity, and the coefficient was significant(r=-.52, p<.001).3) Finally, reliability coefficients(Cronbach'α) of this scale was. 85.