• Geomechanics and Engineering
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• v.14 no.6
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• pp.519-532
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• 2018

In this work, two dimensional (2D) and quasi three-dimensional (quasi-3D) HSDTs are proposed for bending and free vibration investigation of functionally graded (FG) plates using hyperbolic shape function. Unlike the existing HSDT, the proposed theories have a novel displacement field which include undetermined integral terms and contains fewer unknowns. The material properties of the plate is inhomogeneous and are considered to vary continuously in the thickness direction by three different distributions; power-law, exponential and Mori-Tanaka model, in terms of the volume fractions of the constituents. The governing equations which consider the effects of both transverse shear and thickness stretching are determined through the Hamilton's principle. The closed form solutions are deduced by employing Navier method and then fundamental frequencies are obtained by solving the results of eigenvalue problems. In-plane stress components have been determined by the constitutive equations of composite plates. The transverse stress components have been determined by integrating the 3D stress equilibrium equations in the thickness direction of the FG plate. The accuracy of the present formulation is demonstrated by comparisons with the different 2D, 3D and quasi-3D solutions available in the literature.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.165-170
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• 2015

The unsharp mask technique emphasize the boundary of the image by adding the boundary of the original image. This technique improves quality by emphasize its boundaries but produce rough image from image noise. The multi channel unsharp mask is possible to enhance entire contrast of the image by applying at least two channels of unsharp mask. However, There is limitations to strengthen boundaries even if the scale strongly applies the multi channel unsharp mask technique. To solve this problem, linear scaling to nonlinear scaling by applying exponential function to existing multi channel unsharp mask technique. Experimental results show enhanced contrast for desired area because of control scaling in details compared with existing unsharp mask technique.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.5
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• pp.377-383
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• 2016

The effect of long-term aging degradation on magnetic properties of ferritic 11Cr low-carbon steel was investigated. Coercivity and hysteresis loss measured from the hysteresis loops decreased with long-term aging time and showed that the relation was well fitted by a second order exponential function. Vickers hardness also decreased with aging time and resulted in mechanical softening. In addition, the microstructural evolution was observed by the scanning electron microscopy, backscattered electron image and X-ray diffraction. The $Cr_{23}C_6$ precipitates along grain boundary grew fast and Laves ($Fe_2W$) phase on martensitic lath boundaries in interior grains was developed. The solid solution atoms depleted in matrix and lath subgrains recovered owing to precipitate coarsening with long-term aging degradation. There was a close relation with softening of magnetic and mechanical properties.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.7 s.262
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• pp.808-815
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• 2007

The optical performance of the mirror fur satellite camera is highly dependent on the adhesive properties between the mirror and its support. Therefore, in order to design a mirror with high optical performance, the mechanical properties of adhesives should be well defined. In this research, the mechanical properties of three kinds of space adhesives are studied. In case of the materials which show nearly incompressible behavior such as space adhesives, it is important to measure shear modulus which governs deviatoric stress components. Also the experiment should be performed in circumstances similar to real manufacturing process of mirror, because extra factors such as size effects, the adhesion effects of primer and reactions between adhesive and primer affect the properties of adhesive regions. In this research shear moduli of the adhesives are determined by using a single lap adhesively bonded joint. For the shear tests, several temperatures have been selected from $-20^{\circ}C$ to $55^{\circ}C$ which is operating temperature range of the adhesive. In the case of linear behavior materials, shear moduli are calculated through a linear curve fitting. Shear stress-strain relation is obtained by using an exponential curve fitting for material which shows non-linear behavior. The shear modulus of each adhesive is expressed as a function of temperature. Characteristics and adaptability of the adhesives are discussed regarding their temperature sensitivity.

• Applied Microscopy
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• v.33 no.3
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• pp.195-204
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• 2003

The Experimental calibration method has been investigated to correct d-spacing estimation and to identify phases in the electron diffraction data acquired by imaging plates. When the diffraction data from the imaging plate was corrected by the d-spacing calibration method with the radial intensity distribution plotting in this experiment, The accuracy of d-spacing estimation was significantly increased in errors of about 0.5%. The experimental calibration equation followed up the first order exponential decay function was derived from the trace of d-spacing deviation between the measured and the calculated values. It was applied to the analysis of d-spacing and the phase identification of the transitional phases formed from [001] gibbsite specimen by electron beam irradiation effect. In this case more accurate phase identification and d-spacing evaluation is possible for the transitional phases whose diffraction patterns are complicatedly superimposed. It is concluded that ${\chi}$-alumina, ${\gamma}$-alumina and ${\sigma}$-alumina are clearly identified as the major transitional phases formed from gibbsite by electron beam irradiation for 120 min.

• Journal of Internet Computing and Services
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• v.10 no.3
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• pp.35-49
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• 2009

In electronic warfare settings, battlefield helicopters identify various threats based upon threat data, which are acquired using their multi-sensors of aircraft survivability equipment (ASE). To continually function despite of potential threats and successfully execute their missions, the battlefield helicopters have to repeatedly report threats in simulated battlefield situations. Toward this ends, the paper presents threat unification using multi-sensor simulator and its implementation. The simulator consists of (1) threat attributes generator, which models threats against battlefield helicopters and defines their specific attributes, (2) threat data generator, which generates threats, being similar to real ones, using normal, uniform, and exponential distributions, and (3) graphic display for threat analysis and unification, which shows unified threat information, for example, threat angle and its level. We implement a multi-sensor threat simulator that can be repeatedly operable in various simulated battlefield settings. Further, we report experimental results that, in addition to tangibly modeling the threats to battlefield helicopters, test the capabilities of threat unification using our simulator.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.46 no.1
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• pp.56-69
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• 2010

This study was intended to determine the maneuverability of the vessel CHARMBADA. When the rudder angle was at $10^{\circ}$, $20^{\circ}$ and $30^{\circ}$, the maximum advance by slow, half and full ahead were varied in the range of 523.6-131.3m, 528.8-177.2m and 530.6-219.7m, respectively. The maximum transfer was 799.9-181.3m, 792.1-232.8m and 807.7-316.9m, respectively. The turning circle ability was better during starboard turning. When the rudder angle was $10^{\circ}$, $20^{\circ}$ and $30^{\circ}$, variation in the maximum advances was 392.0m, 245.0m and 153.0m. The maximum transfer was 528.0m, 339.0m and 218.0m, respectively based on the regression equations. As the rudder angle became bigger, the maximum advance or maximum transfer became smaller by the exponential function. The advance inertia took 127sec, 145sec, 181sec each until the vessel speed was 7.0konts, 12.0konts, 17.0konts. The static inertia took 245sec, 269sec, 300sec each until the vessel speed was under 2.0konts and the advance distance was 114.4m, 181.2m, 197.0m each. Accordingly, the static inertia was inclined to increase to scale according to the increase in vessel speed. For the CHARMBADA, the smaller the rudder angle was, the much bigger the turning circle became due to adhesion to the skeg, thereby lowering the vessel's turning ability.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.47 no.5
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• pp.390-394
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• 2002

Spikelet number per unit area(SPN) is a major determinant of rice yield. Nitrogen nutrition status and biomass during reproductive stage determine the SPN. To formulate a model for estimating SPN, the 93 field experiment data collected from widely different regions with different japonica varieties in Korea and Japan were analyzed for the upper boundary lines of SPN responses to nitrogen nutrition index(NNI), shoot dry weight and shoot nitrogen content at panicle initiation and heading stage. The boundary lines of SPN showed asymptotic responses to all the above parameters(X) and were well fitted to the exponential function of $f(X)=alphacdot{1-etacdotexp(gamma;cdot;X)}$. Excluding the constant, from the boundary line equation, the values of the equation range from 0 to 1 and represent the indices of parameters expressing the degree of influence on SPN. In addition to those indices, the index of shoot dry weight increase during reproductive stage was calculated by directly dividing the shoot dry weight increase by the maximum value ($800 extrm{g/m}^{-2}$) of dry weight increase as it showed linear relationship with SPN. Four indices selected by forward stepwise regression at the stay level of 0.05 were those for NNI ($I_{NNI}_P$) at panicle initiation, NNI($I_{NNI}_h$) and shoot dry weight($I_{DW}_h$) at heading stage, and dry weight increase($I_{DW}$) between those two stages. The following model was obtained: SPN=48683ㆍ $I_{DWH}$$^{0.482}$ㆍ $I_{NNIp}$$^{0.387}$ㆍ $I_{NNIH}$$^{0.318}$ㆍ $I_{DW}$ $^{0.35}$). This model accounted for about 89% of the variation of spikelet number. In conclusion this model could be used for estimating the spikelet number of japonica rice with some confidence in widely different regions and thus, integrated into a rice growth model as a component model for spikelet number estimation.n.n.

• The Korean Journal of Applied Statistics
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• v.8 no.1
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• pp.89-104
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• 1995

This paper is concerned with the method of estimating lifetime distributin from field data for products with multiple modes of failure. When product failures occur within warranty period, a manufacturer can obtain failure-record data; failure times, causes of failure, and covariates. Since these data are seriously incomplete for satisfactory inference, that is, only failures occured during warrantly period may be recorded, it is usually necessary to incoporate the failure-record data by taking a supplementary sample of items obtained following up a portion of products that survive warranty time. The log linear function is considered as a model for describing the relation between failure time of a product and covariates. General methods for obtaining pseudo maximum likelihood estimators(PMLEs) for the parameters are outlined and their asymptotic properties are studied, and specific formulas for exponential or Weibull distribution are obtained. Effects of follow-up percentage on the PMLEs are investigated. Extensions to calendar time warranty or calendar and obtaining time warranty are also considered.

• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.423-436
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• 2017

This paper presents a deep learning-based road segmentation framework from very high-resolution orthophotos. The proposed method uses Deep Convolutional Autoencoders for end-to-end mapping of orthophotos to road segmentations. In addition, a set of post-processing steps were applied to make the model outputs GIS-ready data that could be useful for various applications. The optimization of the model's parameters is explained which was conducted via grid search method. The model was trained and implemented in Keras, a high-level deep learning framework run on top of Tensorflow. The results show that the proposed model with the best-obtained hyperparameters could segment road objects from orthophotos at an average accuracy of 88.5%. The results of optimization revealed that the best optimization algorithm and activation function for the studied task are Stochastic Gradient Descent (SGD) and Exponential Linear Unit (ELU), respectively. In addition, the best numbers of convolutional filters were found to be 8 for the first and second layers and 128 for the third and fourth layers of the proposed network architecture. Moreover, the analysis on the time complexity of the model showed that the model could be trained in 4 hours and 50 minutes on 1024 high-resolution images of size $106{\times}106pixels$, and segment road objects from similar size and resolution images in around 14 minutes. The results show that the deep learning models such as Convolutional Autoencoders could be a best alternative to traditional machine learning models for road segmentation from aerial photographs.