• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권12호
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• pp.6190-6213
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• 2019

For small-scale vector data, restrictions on watermark scheme capacity and robustness limit the use of copyright protection. A watermarking scheme based on robust geometric features and capacity maximization strategy that simultaneously improves capacity and robustness is presented in this paper. The distance ratio and angle of adjacent vertices are chosen as the watermark domain due to their resistance to vertex and geometric attacks. Regarding watermark embedding and extraction, a capacity-improved strategy based on quantization index modulation, which divides more intervals to carry sufficient watermark bits, is proposed. By considering the error tolerance of the vector map and the numerical accuracy, the optimization of the capacity-improved strategy is studied to maximize the embedded watermark bits for each vertex. The experimental results demonstrated that the map distortion caused by watermarks is small and much lower than the map tolerance. Additionally, the proposed scheme can embed a copyright image of 1024 bits into vector data of 150 vertices, which reaches capacity at approximately 14 bits/vertex, and shows prominent robustness against vertex and geometric attacks for small-scale vector data.

• 호남수학학술지
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• 제26권2호
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• pp.219-236
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• 2004

In this paper, the problem of estimating a p-variate ($p{\geq}4$) normal mean vector is considered in a decision-theoretic setup. Using a simple property of the noncentral chi-square distribution, a sequence of smooth estimators dominating the Lindley type estimator has been produced and each improved estimator is better than previous one.

• Communications for Statistical Applications and Methods
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• 제12권2호
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• pp.463-472
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• 2005

In this paper, the problem of estimating a p-variate (p $\ge$4) normal mean vector is considered in decision-theoretic set up. Using a simple property of the noncentral chi-square distribution, a sequence of estimators dominating the Lindley type estimator with the cases of unknown covariance matrices has been produced and each improved estimator is better than previous one.

• Journal of Astronomy and Space Sciences
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• 제15권1호
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• pp.111-118
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• 1998

A method to determine normal vectors for boundaries of plasmas with a series of data acquired from a single spacecraft is investigated. The determination of the normal vector is possible through a set of Rankine-Hugoniot(R-H) relations that are conser-vation relations of plasmas across a boundary. It is assumed that the boundary is planar and that the structure of the boundary is not varing in the rest frame of plasmas. The present method utilizes a complete set of R-H relations and provieds self-consistent predictions of the plasma densities, bulk velocities, and temperatures a s well as mag-netic fields. It is expected that the present method provides a more accurate normal vector than the previous methods which employ only subsets of the available R-H relations.

• 대한수학회지
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• 제32권3호
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• pp.509-518
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• 1995

Let $M^n$ be a hypersurface in the Euclidean space $R^{n+1}$ with position vector field x and unit normal vector field G.

• Nuclear Engineering and Technology
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• 제39권1호
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• pp.63-74
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• 2007

In this paper, a reconfigurable controller consisting of a normal controller and a standby controller is designed to control the thermoelectric (TE) power in the SP-100 space reactor. The normal controller uses a model predictive control (MPC) method where the future TE power is predicted by using support vector regression. A genetic algorithm that can effectively accomplish multiple objectives is used to optimize the normal controller. The performance of the normal controller depends on the capability of predicting the future TE power. Therefore, if the prediction performance is degraded, the proportional-integral (PI) controller of the standby controller begins to work instead of the normal controller. Performance deterioration is detected by a sequential probability ratio test (SPRT). A lumped parameter simulation model of the SP-100 nuclear space reactor is used to verify the proposed reconfigurable controller. The results of numerical simulations to assess the performance of the proposed controller show that the TE generator power level controlled by the proposed reconfigurable controller could track the target power level effectively, satisfying all control constraints. Furthermore, the normal controller is automatically switched to the standby controller when the performance of the normal controller degrades.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권4호
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• pp.1562-1578
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• 2020

Vector data compression algorithm can meet requirements of different levels and scales by reducing the data amount of vector graphics, so as to reduce the transmission, processing time and storage overhead of data. In view of the fact that large threshold leading to comparatively large error in Douglas-Peucker vector data compression algorithm, which has difficulty in maintaining the uncertainty of shape features and threshold selection, a segmented Douglas-Peucker algorithm based on node importance is proposed. Firstly, the algorithm uses the vertical chord ratio as the main feature to detect and extract the critical points with large contribution to the shape of the curve, so as to ensure its basic shape. Then, combined with the radial distance constraint, it selects the maximum point as the critical point, and introduces the threshold related to the scale to merge and adjust the critical points, so as to realize local feature extraction between two critical points to meet the requirements in accuracy. Finally, through a large number of different vector data sets, the improved algorithm is analyzed and evaluated from qualitative and quantitative aspects. Experimental results indicate that the improved vector data compression algorithm is better than Douglas-Peucker algorithm in shape retention, compression error, results simplification and time efficiency.

• Journal of Computational Design and Engineering
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• 제2권2호
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• pp.79-87
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• 2015

Surface segmentation and edge feature lines extraction from fractured fragments of relics are essential steps for computer assisted restoration of fragmented relics. As these fragments were heavily eroded, it is a challenging work to segment surface and extract edge feature lines. This paper presents a novel method to segment surface and extract edge feature lines from triangular meshes of irregular fractured fragments. Firstly, a rough surface segmentation is accomplished by using a clustering algorithm based on the vertex normal vector. Secondly, in order to differentiate between original and fracture faces, a novel integral invariant is introduced to compute the surface roughness. Thirdly, an accurate surface segmentation is implemented by merging faces based on face normal vector and roughness. Finally, edge feature lines are extracted based on the surface segmentation. Some experiments are made and analyzed, and the results show that our method can achieve surface segmentation and edge extraction effectively.

• 대한의용생체공학회:의공학회지
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• 제17권4호
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• pp.433-442
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• 1996

Since one texture property(i.e coarseness, orientation, regularity, granularity) for ultrasound liver ages was not sufficient enough to classify the characteristics of livers, we used multi texture vectors tracted from ultrasound liver images and a statistical classifier. Multi texture vectors are selected among the feature vectors of the normal liver, fat liver and cirrhosis images which have a good separability in those ultrasound liver images. The statistical classifier uses multi texture vectors as input vectors and classifies ultrasound liver images for each multi texture vector by the Bayes decision rule. Then the decision of the liver disease is made by choosing the maximum value from the averages of a posteriori probability for each multi texture vector In our simulation, we obtained higtler correct ratio than that of other methods using single feature vector, for the test set the correct ratio is 94% in the normal liver, 84% in the fat liver and 86% in the cirrhosis liver.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -2
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• pp.983-986
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• 2002

Support Vector Machine (SVM) is one of the methods of pattern recognition that separate input data using hyperplane. This method has high capability of pattern recognition by using the technique, which says kernel trick, and the Radial basis function (RBF) kernel is usually used as a kernel function in kernel trick. In this paper we propose using the q-normal distribution to the kernel function, instead of conventional RBF, and compare two types of the kernel function.