• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.472-484
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• 2004

We proposed 3D mesh watermarking algorithm using CEGI distribution. In the proposed algorithm, we divide a 3D mesh of VRML data into 6 patches using distance measure and embed the same watermark bits into the normal vector direction of meshes that mapped into the cells of each patch that have the large magnitude of complex weight of CEGI. The watermark can be extracted based on the known center point of each patch and order information of cell. In an attacked model by affine transformation, we accomplish the realignment process before the extraction of the watermark. Experiment results exhibited the proposed algorithm is robust by extracting watermark bit for geometrical and topological deformed models.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.3
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• pp.5-15
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• 2007

A welding structures is generally composed of dissimilar steel materials in order to reduce weight cost, and has a gap to fill the welding agent. Also, heat flow analysis should be fulfilled for structure existing of gap to figure out residual stress which is generated after welding. Since mechanical properties of welding structure composed of dissimilar steel is more fragile than mechanical properties of welding structure consisted of same material, heat flow analysis verifying this should be fulfilled as well. Therefore, on this research, heat flow analysis about dissimilar steel weldment consisted of gap existing AISI304 and AISI630 is practiced so that it could be a basic data of research about mechanical properties of gap existing dissimilar steel welding part which is going to be studied later on. During heat flow analysis, heat input model which based on Gaussian profile and using volume heat flux was newly consisted and applied. In addition, for verifying of analysis on this research, gap existing dissimilar steel weldment which had gap of 0.25mm and was welded using Nd-YAG. The welding profile and temperature distribution for weldment during welding was compared to the result which was gotten through heat flow analysis. Both of those results corresponded each other.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.365-371
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• 2011

Most recently issued paper money includes security patterns that can be only identified by ultra violet (UV) illuminations. We propose an automatic extraction method of UV patterns for paper money inspection systems. The image acquired by camera and UV illumination is transformed to input data through preprocessing. And then, the Gaussian mixture model (GMM) and split-and-merge expectation maximization (SMEM) algorithm are applied to segment the image represented by input data. In order to extract the UV pattern from the segmented image, we develop a criterion using the area of covariance vector and the weight value. The experimental results on various paper money are presented to verify the usefulness of the proposed method.

• Steel and Composite Structures
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• v.39 no.3
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• pp.275-290
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• 2021

The main purpose of this research work is to investigate the critical buckling load of functionally graded (FG) porous plates with graphene platelets (GPLs) reinforcement using generalized differential quadrature (GDQ) method at thermal condition. It is supposed that the GPL nanofillers and the porosity coefficient vary continuously along the plate thickness direction. Generally, the thermal distribution is considered to be nonlinear and the temperature changing continuously through the thickness of the nanocomposite plates according to the power-law distribution. To model closed cell FG porous material reinforced with GPLs, Halpin-Tsai micromechanical modeling in conjunction with Gaussian-Random field scheme are used, through which mechanical properties of the structures can be extracted. Based on the third order shear deformation theory (TSDT) and the Hamilton's principle, the equations of motion are established and solved for various boundary conditions (B.Cs). The fast rate of convergence and accuracy of the method are investigated through the different solved examples and validity of the present study is evaluated by comparing its numerical results with those available in the literature. A special attention is drawn to the role of GPLs weight fraction, GPLs patterns through the thickness, porosity coefficient and distribution of porosity on critical buckling load. Results reveal that the importance of thermal condition on of the critical load of FGP-GPL reinforced nanocomposite plates.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.4
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• pp.186-191
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• 2018

As influence of the 4th industry is growing with development of information society more electronic devices and sensor are used in the field. As this is the case, importance of signal processing during data transfer is rising Furthermore, the need for technology to remove noise caused by various reasons and to stabilize sensor output is growing as well. This research suggests digital filter algorithm that efficiently remove noise by stabilizing output of accelerating sensor. The standard value of this algorithm is calculated by applying Gaussian coefficient. To maintain its feature, final output is obtained by subtracting weight depending on variance from standard value For its evaluation, it is compared with other protocols and its function is checked through output features.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.908-928
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• 2022

Multiple target tracking mainly focuses on tracking unknown number of targets in the complex environment of clutter and missed detection. The generalized labeled multi-Bernoulli (GLMB) filter has been shown to be an effective approach and attracted extensive attention. However, in the scenarios where the clutter rate is high or measurement-outliers often occur, the performance of the GLMB filter will significantly decline due to the Gaussian-based likelihood function is sensitive to clutter. To solve this problem, this paper presents a robust GLMB filter and smoother to improve the tracking performance in the scenarios with high clutter rate, low detection probability, and measurement-outliers. Firstly, a Student-T distribution variational Bayesian (TDVB) filtering technology is employed to update targets' states. Then, The likelihood weight in the tracking process is deduced again. Finally, a trajectory smoothing method is proposed to improve the integrative tracking performance. The proposed method are compared with recent multiple target tracking filters, and the simulation results show that the proposed method can effectively improve tracking accuracy in the scenarios with high clutter rate, low detection rate and measurement-outliers. Code is published on GitHub.

• Journal of Bio-Environment Control
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• v.27 no.4
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• pp.424-430
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• 2018

This study was carried out to estimate growth characteristics of hot pepper and to develop predicted models for the production yield based on the growth parameters and climatic elements. Sigmoid regressions for the prediction of growth parameters in terms of fresh and dry weight, plant height, and leaf area were designed with growing degree days (GDD). The biomass and leaf expansion of hot pepper plants were rapidly increased when 1,000 and 941 GDD. The relative growth rate (RGR) of hot pepper based on dry weight was formulated by Gaussian's equation RGR $(dry\;weight)=0.0562+0.0004{\times}DAT-0.00000557{\times}DAT^2$ and the yields of fresh and dry hot pepper at the 112 days after transplanting were estimated 1,387 and 291 kg/10a, respectively. Results indicated that the growth and yield of hot pepper were predicted by potential growth model under plastic tunnel cultivation. Thus, those models need to calibration and validation to estimate the efficacy of prediction yield in hot pepper using supplement a predicting model, which was based on the parameters and climatic elements.

• Clinical and Experimental Pediatrics
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• v.48 no.11
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• pp.1179-1186
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• 2005

Purpose : A universal standard of the birth weight for gestational age cannot be made since girth weight distribution varies with race and other sociodemographic factors. This report aims to establish the birth weight distribution curve by gestational age, specific for Korean live births. Methods : We used the national birth certificate data of all live births in Korea from January 2001 to December 2003; for live births with gestational ages 24 weeks to 44 weeks(n=1,509,763), we obtained mean birth weigh, standard deviation and 10th, 25th, 50th, 75th and 90th percentile values for each gestational age group by one week increment. Then, we investigated the birth weight distribution of each gestational age group by the normal Gaussian model. To establish final standard values of Korean birth weight distribution by gestational age, we used the finite mixture model to eliminate erroneous birth slights for respective gestational ages. Results : For gestational ages 28 weeks 32 weeks, birth weight distribution showed a biologically implausible skewed tail or bimodal distribution. Following correction of the erroneous distribution by using the finite mixture model, the constructed curve of birth weight distribution was compared to those of other studies. The Korean birth weight percentile values were generally lower than those for Norwegians and North Americans, particularly after 37 weeks of gestation. The Korean curve was similar to that of Lubchenco both 50th and 90th percentiles, but generally the Korean curve had higher 10th percentile values. Conclusion : This birth weight distribution curve by gestational age is based on the most recent and the national population data compared to previous studies in Korea. We hope that for Korean infants, this curve will help clinicians in defining and managing the large for gestational age infants and also for infants with intrauterine growth retardation.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.6
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• pp.267-274
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• 2023

In this paper, a method for estimating the illuminant chromaticity of a scene for an input image is proposed. The illuminant chromaticity is estimated using the illuminant reference region. The conventional method uses a certain number of reference lighting information. By comparing the chromaticity distribution of pixels from the input image with the chromaticity set prepared in advance for the reference illuminant, the reference illuminant with the largest overlapping area is regarded as the scene illuminant for the corresponding input image. In the process of calculating the overlapping area, the weights for each reference light were applied in the form of a Gaussian distribution, but a clear standard for the variance value could not be presented. The proposed method extracts an independent reference chromaticity region from a given reference illuminant, calculates the characteristic values in the r-g chromaticity plane of the RGB color coordinate system for all pixels of the input image, and then calculates the independent chromaticity region and features from the input image. The similarity is evaluated and the illuminant with the highest similarity was estimated as the illuminant chromaticity component of the image. The performance of the proposed method was evaluated using the database image and showed an average of about 60% improvement compared to the conventional basic method and showed an improvement performance of around 53% compared to the conventional Gaussian weight of 0.1.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.3
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• pp.149-154
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• 2014

The cross-correntropy concept can be expressed with inner products of two different probability density functions constructed by Gaussian-kernel density estimation methods. Blind algorithms based on the maximization of the cross-correntropy (MCC) and a symbol set of randomly generated N samples yield superior learning performance, but have a huge computational complexity in the update process at the aim of weight adjustment based on the MCC. In this paper, a method of reducing the computational complexity of the MCC algorithm that calculates recursively the gradient of the cross-correntropy is proposed. The proposed method has only O(N) operations per iteration while the conventional MCC algorithms that calculate its gradients by a block processing method has $O(N^2)$. In the simulation results, the proposed method shows the same learning performance while reducing its heavy calculation burden significantly.