• Tunnel and Underground Space
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• v.3 no.1
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• pp.63-79
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• 1993

The design of tunnels in rock masses often demands more informations on geologic features and rock mass properties than acquired by usual field survey and laboratory testings. In practice, the situation that a perfect set of geological and mechanical input data is given to geomechanics design engineer is rare, while the engineers are asked to achieve a high level of reliability in their design products. This study presents an artificial neural network which is developed to resolve the difficulties encountered in conventional design techniques, particulary the problem of deteriorating the confidence of existing numerical techniques such as the finite element, boundary element and distinct element methods due to the incomplete adn vague input data. The neural network has inferring capabilities to identify the possible failure modes, support requirements and its timing for underground openings, from previous case histories. Use of the neural network has resulted in a better estimate of the correlation between systems of rock mass classifications such as the RMR and Q systems. A back propagation learning algorithm together with a multi-layer network structure is adopted to enhance the inferential accuracy and efficiency of the neural network. A series of experiments comparing the results of the neural network with the actual field observations are performed to demonstrate the abilities of the artificial neural network as a new tunnel design assistance system.

• Journal of the Korea Fashion and Costume Design Association
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• v.7 no.2
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• pp.1-10
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• 2005

This study intends to examine extensively on the current situation where the full capacity of 3D CG is not being highlighted because of the lack of the information and the awareness and to look at how the virtual reality technology is being applied ranging from the design of the clothes to the marketing. A set of processes ranging from the development of the clothing design to the marketing will be performed on the web. Designers will design with 3D CG and make the patterns and will hand this over to the producer together with the virtual swatch. But there are important problems to work out. First, it is the problem of the virtual fitting room. Second, it is the absence of the 3D CG, which is easy and convenient for the clothing design. Third, it is to perfect the visual reconstruction. Fourth, it is the security of the distribution system. Fifth, it also calls for the strengthened internet network that can smooth the flow of the tremendous data. Consumer will be able to produce according to their needs and will become designer and producer at the same time, resulting in the achievement of the consumer-oriented marketing in real sense.

• Proceedings of the KIEE Conference
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• 2007.11c
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• pp.112-116
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• 2007

If any of the set parameters such as the environment temperature, mold temperature are not maintained at a consistent level, the fail rate of injection molding products is increased. The price of the injection molding machine is very high, so in order to maximize the utilization of the machine that is required the production of a number of different products with minimum fail rate using a single machine. To prevent the defect products by an inspection process with perfect quality is very important to minimizing production of defect products in the molding process. Vision inspection systems are widely utilized in various manufacturing industries for quality assurance purposes. The vision inspection system consists of CCD camera and lighting system to capture the image of the subject of inspection, an image comparison algorithm using to determine the pass/fail of the products, and mechanical devices for the operation of the whole system. This research focuses on the development of the vision inspection system to process the inspection of an automobile parts. We developed a mechanical devices for the inspection of the injection molding products and an image comparison algorithm to determine the pass/fail result of the inspection based on the molding image and the accepted product image.

• Wind and Structures
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• v.7 no.4
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• pp.251-264
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• 2004

The effects of a class of nonlinear Tuned Mass Dampers on the aeroelastic behavior of SDOF systems are investigated. Unlike classical linear TMDs, nonlinear constitutive laws of the internal damping acting between the primary oscillator and the TMD are considered, while the elastic properties are keept linear. The perturbative Multiple Scale Method is applied to derive a set of bifurcation equations in the amplitude and phase and a parametric analysis is performed to describe the postcritical scenario of the system. Both cubic- and van der Pol-type dampings are considered and the dependence of the limit-cycle amplitudes on the system parameters is studied. These new results, compared with the previously obtained bifurcation scenario of a SDOF aeroelastic oscillator equipped with a linear TMD, show a detrimental effect on the maximum limit-cycle amplitude reduction of the nonlinear TMD. However, the analyses evidence that in the parameter region away from the perfect tuning condition the nonlinear connection can be used to tune the system with an enhancement of the limit-cycle amplitude reduction.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.847-859
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• 2011

cDNA microarray-based comparative genomic hybridization(CGH) data includes low-intensity spots and thus a statistical strategy is needed to detect subtle differences between different cancer classes. In this study, genes displaying a high frequency of alteration in one of the different classes were selected among the pre-selected genes that show relatively large variations between genes compared to total variations. Utilizing copy-number changes of the selected genes, this study suggests a statistical approach to predict patients' classes with increased performance by pre-classifying patients with similar genetic alteration scores. Two-stage logistic regression model(TLRM) was suggested to pre-classify homogeneous patients and predict patients' classes for cancer prediction; a decision tree(DT) was combined with logistic regression on the set of informative genes. TLRM was constructed in cDNA microarray-based CGH data from the Cancer Metastasis Research Center(CMRC) at Yonsei University; it predicted the patients' clinical diagnoses with perfect matches (except for one patient among the high-risk and low-risk classified patients where the performance of predictions is critical due to the high sensitivity and specificity requirements for clinical treatments. Accuracy validated by leave-one-out cross-validation(LOOCV) was 83.3% while other classification methods of CART and DT performed as comparisons showed worse performances than TLRM.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.10b
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• pp.94-106
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• 2003

In recent years, the production value of Taiwanese mold and die industries have reached to a high peak in 1998, in amount of NT 604 hundred million dollars. But in recent years production value are going down year by year, till year of 2001 the production value have down to NT 394 hundred million dollars. Its main reason might be the major product were following in medium and low price category, the high accuracy and high cost mold and die still rely on import aboard. Therefore how to made the related technical database system on various field to provide the industry user to promote industries competition ability in mold and die is really urgent matter at this moment. In this research, we will offer how to apply the Visual Basic program language to edit a set of more perfect database system of mold and die material selection. At the present time, we have constructed complete Knowledge-Base-System of intelligence for forging mold and die material, the most related data from the existed data, the others are through our additional experimental results. By using this system by the user can got the related and need data easily, we hope it will reduce designing time and cost for mold and die.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.4
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• pp.98-104
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• 2006

In this paper, for the purpose of investigation the acoustic emission(AE) behaviors during resistance spot welding process and tension test of spec steels. As the results present the resistance spot welding method that can get suitable welding qualities or structural integrity estimating method. The resistance spot welding process consists of several stages: set-down of the electrodes; squeeze; current flow; forging; hold time; and lift-off. Various types of AE signals are produced during each of these stages. For tensile-shear test and cross tensile test in resistance spot welded specimens, fracture pa 야 ems are produced: tear fracture; shear fracture; and plug fracture. Tensile-shear specimens strength appeared higher than cross tensile specimens one. In case of tensile-shear specimen happened tear fracture that crack happens in most lower plate. Also, in case of cross tensile specimens, upper plate and lower plate are detached perfect fracture was exposed increases a little as acting force is lower than ordinary welding condition. Therefore, the structure which is combined by resistance spot welding confirmed that welding design must attain so that shear stress may can interact mainly.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.34D no.4
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• pp.1-7
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• 1997

This paper presents an analysis of the wave propagation in cross-type tunnels using the finite volume time domain (FVTD) method. Because the FVTD method is based on the volume intergrations of themaxwell's equations with respected to arbitrary shaped small polyhedron cells and the fields at every center point of the cells ar eassigned in a average fashion, the method can handle arbitrary boundary problems with inhomogeneous media. In this paper, the wave propagation in cross-type tunnels has been analyzed using the fVTD method with the PML (perfectly matched layer) absorbing bundary conditons, and the numerical results are verified with a set of experimental data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3594-3607
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• 2017

The traditional feature extraction methods such as principal component analysis (PCA) cannot obtain the local structure of the samples, and locally linear embedding (LLE) cannot obtain the global structure of the samples. However, a common drawback of existing PCA and LLE algorithm is that they cannot deal well with the sparse problem of the samples. Therefore, by integrating the globality of PCA and the locality of LLE with a sparse constraint, we developed an improved and unsupervised difference algorithm called Sparse Difference Embedding (SDE), for dimensionality reduction of high-dimensional data in small sample size problems. Significantly differing from the existing PCA and LLE algorithms, SDE seeks to find a set of perfect projections that can not only impact the locality of intraclass and maximize the globality of interclass, but can also simultaneously use the Lasso regression to obtain a sparse transformation matrix. This characteristic makes SDE more intuitive and more powerful than PCA and LLE. At last, the proposed algorithm was estimated through experiments using the Yale and AR face image databases and the USPS handwriting digital databases. The experimental results show that SDE outperforms PCA LLE and UDP attributed to its sparse discriminating characteristics, which also indicates that the SDE is an effective method for face recognition.

• Structural Engineering and Mechanics
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• v.75 no.1
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• pp.19-32
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• 2020

Due to repetitive traffic loadings and environmental attacks, reinforced concrete (RC) bridge deck slabs are suffering from severe degradation, which makes structural repairing an urgency. In this study, the fatigue performance of an RC bridge deck repairing technique using ultra-high performance fiber reinforcement concrete (UHPFRC) overlay is assessed experimentally with a wheel-type loading set-up as well as analytically based on finite element method (FEM) using a crack bridging degradation concept. In both approaches, an original RC slab is firstly preloaded to achieve a partly damaged RC slab which is then repaired with UHPFRC overlay and reloaded. The results indicate that the developed analytical method can predict the experimental fatigue behaviors including displacement evolutions and crack patterns reasonably well. In addition, as the shear stress in the concrete/UHPFRC interface stays relatively low over the calculations, this interface can be simply simulated as perfect. Moreover, superior to the experiments, the numerical method provides fatigue behaviors of not only the repaired but also the unrepaired RC slabs. Due to the high strengths and cracking resistance of UHPFRC, the repaired slab exhibited a decelerated deterioration rate and an extended fatigue life compared with the unrepaired slab. Therefore, the proposed repairing scheme can afford significant strengthen effects and act as a reference for future practices and engineering applications.