• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1792-1797
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• 2020

The shielding characteristics of two concrete blocks, widely used in the building industry in Mexico have been determined. These characteristics include the mass interaction coefficients, the linear attenuation coefficients and the half-value layers. The energy-dispersed X-ray fluorescence shows that the percentage mass content of each atom in the sample, and the atomic volume of the constituent elements of a material, plays an important role in its shielding capabilities. The total linear attenuation coefficients and the half-value layers were analyzed for a set of photon energies related to X-rays for diagnosis and cancer treatment with linear accelerators. Our results show that the concrete blocks have similar photon attenuation coefficients than the Portland concrete and better features than gypsum.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.557-561
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• 2008

Shape memory alloys (SMA) have interesting features which are the superelastic effect (SE), shape memory effect (SME), two-way SME (TWSME), and so on. These are utilized in actuation factor. The thermo-mechanical constitutive equations of SMA proposed by Lagoudas et al. were employed in the present study for simulating SMA truss structures. The constitutive equation includes the necessary internal variables to account for the material transformations and is utilized in the non-linear finite element procedure of three dimensional truss structures that composed SMA bar (wholly or partially). In this study, we observed which element should be actuated to get a desired shape (actuation shape) from computational analysis. To reach this goal, we apply SMA constitutive equation to non-linear finite element formulation. And then, we simulate two-way shape memory effect as well as superelastic effect of various three dimensional truss using SMA.

• The Korean Journal of Applied Statistics
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• v.24 no.4
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• pp.587-595
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• 2011

Credit scoring is an objective and automatic system to assess the credit risk of each customer. The logistic regression model is one of the popular methods of credit scoring to predict the default probability; however, it may not detect possible nonlinear features of predictors despite the advantages of interpretability and low computation cost. In this paper, we propose to use a generalized partially linear model as an alternative to logistic regression. We also introduce modern ensemble technologies such as bagging, boosting and random forests. We compare these methods via a simulation study and illustrate them through a German credit dataset.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.228-231
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• 1997

In this paper, we designed an ART(Adaptive Resonance Theory) network based on LPC(Linear Prediction Coefficient) for classification of PVB (Premature Ventricular Beat: PVC, LBBB, RBBB). The procedure of proposed system consists of the error calculation, feature generation and processing of the ART network. The error is calculated after processing by linear prediction algorithm and the features of ART network or classification are obtained from the binary ata determined by threshold method. In conclusion, ART network has good performance in classification of PVB.

• Wind and Structures
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• v.9 no.5
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• pp.357-367
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• 2006

Unsteady 3D Reynolds Averaged Navier-Stokes (URANS) solver is used to simulate the turbulent flow past an isolated prismatic cylinder at Re=37,400. The aspect ratio of height to base width of the body is 5. The turbulence closure is achieved through a non-linear $k-{\varepsilon}$ model. The applicability of this model to predict unsteady forces associated with this flow is examined. The study shows that the present URANS solver with standard wall functions predicts all the major unsteady phenomena showing closer agreement with experiment. This investigation concludes that URANS simulations with the non-linear $k-{\varepsilon}$ model as a turbulence closure provides a promising alternative to LES with view to study flows having complex features.

• Smart Structures and Systems
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• v.2 no.1
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• pp.47-60
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• 2006

Bi-spectrum is a tool in the signal processing for identification of non-linear dynamic behvaiour in systems, and well-known for stationary system where components are non-linearly interacting. Breathing of a crack during shaft rotation is also exhibits a non-linear behaviour. The crack is known to generate 2X (twice the machine RPM) and higher harmonics in addition to 1X component in the shaft response during its rotation. Misaligned shaft also shows similar such feature as a crack in a shaft. The bi-spectrum method has now been applied on a small rotating rig to observe its features. The bi-spectrum results are found to be encouraging to distinguish these faults based on few experiments conducted on a small rig. The results are presented here.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.22-33
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• 2019

This paper introduces an efficient fingerprint matching method based on multiple reference minutiae points. First, we attempt to effectively align two fingerprints by employing multiple reference minutiae points. However, the corresponding minutiae points between two fingerprints are ambiguous since a minutia of one fingerprint can be a match to any minutia of the other fingerprint. Therefore, we introduce a novel method based on linear classification concept to establish minutiae correspondences between two fingerprints. Each minutiae correspondence represents a possible alignment. For each possible alignment, a matching score is computed using minutiae and ridge orientation features and the maximum score is then selected to represent the similarity of the two fingerprints. The proposed method is evaluated using fingerprint databases, FVC2002 and FVC2004. In addition, we compare our approach with two existing methods and find that our approach outperforms them in term of matching accuracy, especially in the case of non-linear distorted fingerprints. Furthermore, the experiments show that our method provides additional advantages in low quality fingerprint images such as inaccurate position, missing minutiae, and spurious extracted minutiae.

• Journal of Veterinary Clinics
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• v.37 no.6
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• pp.367-370
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• 2020

Four dogs were incidentally diagnosed as plate-like atelectasis (PLA) by thoracic radiographs. The dogs underwent thoracic computed tomography (CT) examination with various causes. On the lateral radiographs, PLA lesions were observed as a single linear or curvilinear radiopaque area in all four dogs. Although PLA lesions were observed linear structures on dorsal and sagittal reformatted CT images as in the radiographs, it appeared pulmonary opacification or band shape on transverse images. Therefore, care should be taken to differentiate PLA from other pulmonary diseases.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.80-87
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• 2024

This paper focuses on improving accuracy in constrained computing settings by employing the ReLU (Rectified Linear Unit) activation function. The research conducted involves modifying parameters of the ReLU function and comparing performance in terms of accuracy and computational time. This paper specifically focuses on optimizing ReLU in the context of a Multilayer Perceptron (MLP) by determining the ideal values for features such as the dimensions of the linear layers and the learning rate (Ir). In order to optimize performance, the paper experiments with adjusting parameters like the size dimensions of linear layers and Ir values to induce the best performance outcomes. The experimental results show that using ReLU alone yielded the highest accuracy of 96.7% when the dimension sizes were 30 - 10 and the Ir value was 1. When combining ReLU with the Adam optimizer, the optimal model configuration had dimension sizes of 60 - 40 - 10, and an Ir value of 0.001, which resulted in the highest accuracy of 97.07%.

• Journal of Korea Multimedia Society
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• v.17 no.2
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• pp.232-239
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• 2014

As online texts have been rapidly growing, their automatic classification gains more interest with machine learning methods. Nevertheless, comparatively few research could be found, aiming for Korean texts. Evaluating them with statistical methods are also rare. This study took a sample of tweets and used machine learning methods to classify emotions with features of morphemes and n-grams. As a result, about 76% of emotions contained in tweets was correctly classified. Of the two methods compared in this study, Support Vector Machines were found more accurate than Na$\ddot{i}$ve Bayes. The linear model of SVM was not inferior to the non-linear one. Morphological features did not contribute to accuracy more than did the n-grams.