• Steel and Composite Structures
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• v.50 no.1
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• pp.63-75
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• 2024

In this paper, the modified couple stress theory (MCST) and first order shear deformation theory (FSDT) are employed to investigate the free vibration and bending analyses of a three-layered micro-shell sandwiched by piezoelectric layers subjected to an applied voltage and reinforced graphene nanoplatelets (GPLs) under external and internal pressure. The micro-shell is resting on an elastic foundation modeled as Pasternak model. The mixture's rule and Halpin-Tsai model are utilized to compute the effective mechanical properties. By applying Hamilton's principle, the motion equations and associated boundary conditions are derived. Static/ dynamic results are obtained using Navier's method. The results are validated with the previously published works. The numerical results are presented to study and discuss the influences of various parameters on the natural frequencies and deflection of the micro-shell, such as applied voltage, thickness of the piezoelectric layer to radius, length to radius ratio, volume fraction and various distribution pattern of the GPLs, thickness-to-length scale parameter, and foundation coefficients for the both external and internal pressure. The main novelty of this work is simultaneous effect of graphene nanoplatelets as reinforcement and piezoelectric layers on the bending and vibration characteristics of the sandwich micro shell.

• Journal of the Korean Society of Clothing and Textiles
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• v.17 no.2
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• pp.233-245
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• 1993

This study was undertaken to develop the artificially soiled cloth using clay and dyed oleic acid as model soil and to evaluating the detergency by determination of K/S value and chemical analysis. The results obtained were as follows : 1. Correlation were determined between the K/S value and chemical analysis data for the detergency of developed model soil at various conditions and it was found that model soil could be extensively used for the washing examination. 2. The surface reflectance of soiled cloth with clay-oleic acid mixture was measured two wave length band that was converted K/S values and the amount of two components was individually calculated. Positive correlation were found between detergency that obtained from chemical anlysis and K/S values. Therefore, proposed method of soiled cloth with clay-oleic acid mixed soiles could be extensively used for detergency experiment. 3. The attached state of soil of on the artificially soiled cloth which was observed under a scanning electronic microscope showed a different pattern by the sort of soil. And the difference of attached state of soil had great influence upon the detergency. 4. The composition of clay was changed and formated of noncrystalinity was vanished by calcined at $800^{\circ}C$. Because of a noncrystalline of clay, artificially soiled cloth could be prepared more uniformly but the detergency was decreased.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.125-137
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• 2009

Acoustic emission-based techniques are being used for the nondestructive inspection of mechanical systems used in service. For reliable fault monitoring related to the crack growth, it is important to identify the dynamical characteristics as well as transient crack-related signals. Widely used methods which are based on physical phenomena of the three damage stages for detecting the crack growth have a problem that crack-related acoustic emission activities overlap in time, therefore it is insufficient to estimate the exact crack growth time. The proposed pattern recognition method uses the dynamical characteristics of acoustic emission as inputs for minimizing false alarms and miss alarms and performs the temporal clustering to estimate the crack growth time accurately. Experimental results show that the proposed method is effective for practical use because of its robustness to changes of acoustic emission caused by changes of pressure levels.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.571-578
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• 2018

Recently, deep learning techniques have shown superior performance in various kinds of pattern recognition. However, there have been some arguments whether the DNN performs better than the conventional machine learning techniques when classification experiments are done using a small amount of training data. In this study, we compared the performance of the conventional GMM and SVM with DNN, a kind of deep learning techniques, in audio event detection. When tested on the same data, DNN has shown superior overall performance but SVM was better than DNN in segment-based F-score.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5427-5445
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• 2019

While deep neural networks have achieved remarkable performance in representation learning, a huge amount of labeled training data are usually required by supervised deep models such as convolutional neural networks. In this paper, we propose a new representation learning method, namely generative adversarial networks (GAN) based bagging deep convolutional autoencoders (GAN-BDCAE), which can map data to diverse hierarchical representations in an unsupervised fashion. To boost the size of training data, to train deep model and to aggregate diverse learning machines are the three principal avenues towards increasing the capabilities of representation learning of neural networks. We focus on combining those three techniques. To this aim, we adopt GAN for realistic unlabeled sample generation and bagging deep convolutional autoencoders (BDCAE) for robust feature learning. The proposed method improves the discriminative ability of learned feature embedding for solving subsequent pattern recognition problems. We evaluate our approach on three standard benchmarks and demonstrate the superiority of the proposed method compared to traditional unsupervised learning methods.

• Clean Technology
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• v.10 no.2
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• pp.89-100
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• 2004

The optimization for the water bath design and the skimmer installation are conducted to separate floated-sludge from the waste water in a water bath of a painting booth. VOF(volume of fluid) model is used to analyze the flow pattern of sludge-water-air mixture in a water bath. From the results of numerical analysis, the design criteria of the skimmer, the separation plate and the sludge inlet port of a water bath are obtained for effective sludge separation from water in bath. Furthermore, the installation condition of the skimmer immersed in water is optimized to minimize entrained air and pressure loss.

• Steel and Composite Structures
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• v.43 no.5
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• pp.603-623
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• 2022

This article is dedicated to predict the natural frequencies of joined conical shell structures made of Functionally Graded Material (FGM). The structure includes two conical segments. The equivalent material properties are found by using the rule of mixture based on Voigt model. In addition, three well-known patterns are employed for distribution of material properties throughout the thickness of the structure. The main objective of the present research is to propose a novel exponential pattern and obtain the related equivalent material properties. Furthermore, the Donnell type shell theory is used to obtain the governing equations of motion. Note that these equations are obtained by employing First-order Shear Deformation Theory (FSDT). In order to discretize the governing system of differential equations, well-known and efficient semi-analytical scheme, namely Generalized Differential Quadrature Method (GDQM), is utilized. Different boundary conditions are considered for various types of single and joined conical shell structures. Moreover, an applicable modification is considered for the continuity conditions at intersection position. In the first step, the proposed formulation is verified by solving some well-known benchmark problems. Besides, some new numerical examples are analyzed to show the accuracy and high capability of the suggested technique. Additionally, several geometric and material parameters are studied numerically.

• Steel and Composite Structures
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• v.43 no.5
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• pp.639-660
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• 2022

The bending and buckling behaviours of FG-GRNC laminated sandwich plates are investigated by using novel five-variables quasi 3D higher order shear deformation plate theory by considering the modified continuum nonlocal strain gradient theory. To calculate the effective Young's modulus of the GRNC sandwich plate along the thickness direction, and Poisson's ratio and mass density, the modified Halpin-Tsai model and the rule of the mixture are employed. Based on a new field of displacement, governing equilibrium equations of the GRNC sandwich plate are solved using a developed approach of Galerkin method. A detailed parametric analysis is carried out to highlight the influences of length scale and material scale parameters, GPLs distribution pattern, the weight fraction of GPLs, geometry and size of GPLs, the geometry of the sandwich plate and the total number of layers on the stresses, deformation and critical buckling loads. Some details are studied exclusively for the first time, such as stresses and the nonlocality effect.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1477-1484
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• 2015

With the growth of financial industry with smartphone, interest on user authentication using smartphone has been arisen in these days. There are various type of biometric user authentication techniques, but gait recognition using accelerometer sensor in smartphone does not seem to develop remarkably. This paper suggests the method of user authentication using accelerometer sensor embedded in smartphone. Specifically, calibrate the sensor data from smartphone with 3D-transformation, extract features from transformed data and do principle component analysis, and learn model with using gaussian mixture model. Next, authenticate user data with confidence interval of GMM model. As result, proposed method is capable of user authentication with accelerometer sensor on smartphone as a high degree of accuracy(about 96%) even in the situation that environment control and limitation are minimum on the research.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.22
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• pp.9673-9678
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• 2014

Background: Breast cancer is a fatal disease and the most frequently diagnosed cancer in women with an increasing pattern worldwide. The burden is mostly attributed to metastatic cancers that occur in one-third of patients and the treatments are palliative. It is of great interest to determine factors affecting time from cancer diagnosis to secondary metastasis. Materials and Methods: Cure rate models assume a Poisson distribution for the number of unobservable metastatic-component cells that are completely deleted from the non-metastasis patient body but some may remain and result in metastasis. Time to metastasis is defined as a function of the number of these cells and the time for each cell to develop a detectable sign of metastasis. Covariates are introduced to the model via the rate of metastatic-component cells. We used non-mixture cure rate models with Weibull and log-logistic distributions in a Bayesian setting to assess the relationship between metastasis free survival and covariates. Results: The median of metastasis free survival was 76.9 months. Various models showed that from covariates in the study, lymph node involvement ratio and being progesterone receptor positive were significant, with an adverse and a beneficial effect on metastasis free survival, respectively. The estimated fraction of patients cured from metastasis was almost 48%. The Weibull model had a slightly better performance than log-logistic. Conclusions: Cure rate models are popular in survival studies and outperform other models under certain conditions. We explored the prognostic factors of metastatic breast cancer from a different viewpoint. In this study, metastasis sites were analyzed all together. Conducting similar studies in a larger sample of cancer patients as well as evaluating the prognostic value of covariates in metastasis to each site separately are recommended.