• Journal of the Optical Society of Korea
• /
• v.18 no.6
• /
• pp.650-656
• /
• 2014

We propose a novel active fiber design for selectively generating cylindrical vector beams (CVBs) or cylindrical vector modes (CVMs) which can be applied to conventional fiber lasers. A fiber is designed to have a ring-shaped core refractive index profile which can lead to the best overlap between the active dopant distribution profile and the lowest-order CVM (LCVM) field profile. Therefore, the overlap factor (OVF) of the LCVM becomes even higher than that of the fundamental mode. We emphasize that this condition cannot be satisfied by a conventional step-index core fiber (SICF) but by the ring-doped core fiber (RDCF). Because the lasing threshold is inversely proportional to the OVF, the LCVM can predominantly be stimulated even without going through special procedures to impose extra loss mechanisms to the fundamental mode. We numerically verify that the OVF of the LCVM with the doped ions can significantly exceed that of the fundamental mode if the proposed fiber design is applied. In addition, an RDCF of the proposed fiber design can also operate in a regime containing no higher-order modes besides the LCVM, so that it can selectively and efficiently generate the LCVM without being disrupted by the parasitic lasing of the higher-order modes. We highlight that an optimized RDCF can lead to a >30 % higher OVF ratio than a SICF having the same doped area. The proposed model is expected to be useful for enhancing the efficiency of generating CVBs in an all-fiber format.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.6
• /
• pp.89-101
• /
• 2014

In this paper, we proposed a new local micro pattern, Signed Local Directional Pattern(SLDP). SLDP uses information of edges to represent the face's texture. This can produce a more discriminating and efficient code than other state-of-the-art methods. Each micro pattern of SLDP is encoded by sign and its major directions in which maximum edge responses exist-which allows it to distinguish among similar edge patterns that have different intensity transitions. In this paper, we divide the face image into several regions, each of which is used to calculate the distributions of the SLDP codes. Each distribution represents features of the region and these features are concatenated into a feature vector. We carried out facial expression recognition with feature vectors and SVM(Support Vector Machine) on Cohn-Kanade and JAFFE databases. SLDP shows better classification accuracy than other existing methods.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.54 no.12
• /
• pp.723-731
• /
• 2005

The $4{\times}4$ homogeneous transformation matrix is a compact representation of orientation and position of an object in robotics and computer graphics. A coordinate transformation is accomplished through the successive multiplications of homogeneous matrices, each of which represents the orientation and position of each corresponding link. Thus, for real time control applications in robotics or animation in computer graphics, the fast multiplication of homogeneous matrices is quite demanding. In this paper, a parallel-architecture vector processor is designed for this purpose. The processor has several key features. For the accuracy of computation for real application, the operands of the processors are floating point numbers based on the IEEE Standard 754. For the parallelism and reduction of hardware redundancy, the processor takes column vectors of homogeneous matrices as multiplication unit. To further improve the throughput, the processor structure and its control is based on a pipe-lined structure. Since the designed processor can be used as a special purpose coprocessor in robotics and computer graphics, additionally to special matrix/matrix or matrix/vector multiplication, several other useful instructions for various transformation algorithms are included for wide application of the new design. The suggested instruction set will serve as standard in future processor design for Robotics and Computer Graphics. The design is verified using FPGA implementation. Also a comparative performance improvement of the proposed design is studied compared to a uni-processor approach for possibilities of its real time application.

• Journal of information and communication convergence engineering
• /
• v.6 no.3
• /
• pp.289-293
• /
• 2008

In this paper, we propose the hardware architecture to accelerate 2D Vector graphics process for mobile devices. we propose the Transformation Unit Architecture that considerates the operation dependency. It has 3 cycles excution time and uses 2 multipliers and 2 adders. Proposed paint generation unit uses a LUT method, so it does not execute color interpolation which needs to be calculated every time. The proposed OpenVG 1.0 Accelerator achieved a 2.85 times faster performance in a tiger model.

• Proceedings of the IEEK Conference
• /
• 2008.06a
• /
• pp.191-192
• /
• 2008

We give new definition of the effective-leakage and the signal to effective-leakage plus noise ratio (SELNR) to consider receiver combining motivated by the leakage. We propose a method to find jointly beamforming vector and combining vector for the two linear receivers (maximal ratio combining (MRC) receiver and minimum mean square error (MMSE) receiver) based on the SELNR.

• Proceedings of the IEEK Conference
• /
• 2002.07b
• /
• pp.983-986
• /
• 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.

• Advances in Computational Design
• /
• v.5 no.3
• /
• pp.291-304
• /
• 2020

In this paper, we develop models to design the airfoil using Multilayer Feed-forward Artificial Neural Network (MFANN) and Support Vector Regression model (SVR). The aerodynamic coefficients corresponding to series of airfoil are stored in a database along with the airfoil coordinates. A neural network is created with aerodynamic coefficient as input to produce the airfoil coordinates as output. The performance of the models have been evaluated. The results show that the SVR model yields the lowest prediction error.

• Proceedings of the IEEK Conference
• /
• 2006.06a
• /
• pp.989-990
• /
• 2006

This paper presents a design of 3D Graphics Geometry processor. A geometry processor needs to cope with a large amount of computation and consists of transformation processor and lighting processor. To deal with the huge computation, a vector processing structure based on pipeline chaining is proposed. The proposed geometry processor performs 4.3M vertices/sec at 100MHz using 11 floating-point units.

• Proceedings of the KSR Conference
• /
• 2000.05a
• /
• pp.78-85
• /
• 2000

Computer algorithms for the loadflow of the DC traction power supply system are examined. Algorithms to solve the nodal equation are reviewed and the two iterative methods to solve the nonlinear nature of the loadflow are analyzed and tested, which are so called conductance matrix method and current vector iterative mettled. The result of the analysis tells that the current vector iterative method makes faster convergency and needs less computing time, and it is verified by the test running of the programs based on each of the iterative methods.

• Journal of the Chungcheong Mathematical Society
• /
• v.34 no.1
• /
• pp.37-53
• /
• 2021

In this paper we define scaled visual curvature and visual Frenet frame that can be visually accepted for discrete space curves. Scaled visual curvature is relatively simple compared to multi-scale visual curvature and easy to control the influence of noise. We adopt scaled minimizing directions of height functions on each neighborhood. Minimizing direction at a point of a curve is a direction that makes the point a local minimum. Minimizing direction can be given by a small noise around the point. To reduce this kind of influence of noise we exmine the direction whether it makes the point minimum in a neighborhood of some size. If this happens we call the direction scaled minimizing direction of C at p ∈ C in a neighborhood Br(p). Normal vector of a space curve is a second derivative of the curve but we characterize the normal vector of a curve by an integration of minimizing directions. Since integration is more robust to noise, we can find more robust definition of discrete normal vector, visual normal vector. On the other hand, the set of minimizing directions span the normal plane in the case of smooth curve. So we can find the tangent vector from minimizing directions. This lead to the definition of visual tangent vector which is orthogonal to the visual normal vector. By the cross product of visual tangent vector and visual normal vector, we can define visual binormal vector and form a Frenet frame. We examine these concepts to some discrete curve with noise and can see that the scaled visual curvature and visual Frenet frame approximate the original geometric invariants.