• Proceedings of the Acoustical Society of Korea Conference
• /
• 1994.06a
• /
• pp.836-841
• /
• 1994

This paper describes the global vibro-acoustic troubleshooting approach, used to identify and separate different sources of noise and vibrations on a boilerfeed pump testrig. The pump serves for rotor dynamic research of a EC-funded BRITE-Euram profect. This approach resulted in the identification of local structural flexibilities in the connections between the machinery and the base plate. The relative importance of the modes during normal operation is revealed by comparison with operational deformation shapes. The use of sound intensity mapping allowed to calculate the total sound power and to rank the equipment according to its sound power contribution. High acoustic levels were found and related to the fluid drive and to the piping system. Modification of the piping section resulted in a reduction of noise and vibration levels along the test loop and smooth operation in a wide suction pressure range.

• Korean Journal of Remote Sensing
• /
• v.23 no.3
• /
• pp.189-198
• /
• 2007

Introduction of lidar technology have contributed to a wide range of applications in generating quality surface models. Accordingly, because of the importance of terrain surface models in mapping applications, rigorous studies have been performed to extract ground points from a lidar data point cloud. Although most filters have been shown abilities to extract ground points with their parameters tuned, however, most experiments revealed that there are certain limitations in optimizing filter parameters and the correction of remaining misclassified points is not straightforward. In this study, therefore, a method to improve the quality of filtered lidar data is proposed, which exploits neighboring surface properties arising between immediate neighbors. The method comprises a sequence of procedures which can reduce commission and omission errors. Commission errors occurring in low-rise objects are reduced by utilizing morphological operations. On the other hand, omission errors are reduced by adding missing ground points around step edges. Experimental results show that the qualities of filtered data can be improved considerably by the proposed method.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.6
• /
• pp.73-80
• /
• 2019

In this paper, we propose an effective dynamic range compression (DRC) method of infrared images. A histogram of infrared images has narrow dynamic range compared to visible images. Hence, it is important to apply the effective DRC algorithm for high performance of an infrared image analysis. The proposed algorithm for high dynamic range divides an infrared image into the overlapped blocks and calculates Shannon's entropy of overlapped blocks. After that, we classify each block according to the value of entropy and apply adaptive histogram modification method each overlapped block. We make an intensity mapping function through result of the adaptive histogram modification method which is using standard-deviation and maximum value of histogram of classified blocks. Lastly, in order to reduce block artifact, we apply hanning window to the overlapped blocks. In experimental result, the proposed method showed better performance of dynamic range compression compared to previous algorithms.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2019.06a
• /
• pp.98-101
• /
• 2019

At present, deep convolutional neural networks have made a very important contribution in single-image super-resolution. Through the learning of the neural networks, the features of input images are transformed and combined to establish a nonlinear mapping of low-resolution images to high-resolution images. Some previous methods are difficult to train and take up a lot of memory. In this paper, we proposed a simple and compact deep recursive residual network learning the features for single image super resolution. Global residual learning and local residual learning are used to reduce the problems of training deep neural networks. And the recursive structure controls the number of parameters to save memory. Experimental results show that the proposed method improved image qualities that occur in previous methods.

• Journal of the Semiconductor & Display Technology
• /
• v.18 no.1
• /
• pp.102-104
• /
• 2019

Registering different kinds of clinical images widely used in diagnostic and surgery planning. However, cause of tumor growth or effected by gravity, human tissue has plenty of non-rigid deformation with clinically. Non-rigid registration allows the mapping of straight lines to curves. Therefore, such local deformation makes registration more complicated. In this work, we mainly introduce intra-subject, inter-modality registration. This paper mainly studies the nonlinear registration method of 2D medical image registration. The general medical image registration algorithm requires manual intervention, and cost long registration time. In our work to reduce the registration time in rough registration step, the barycenter and the direction of main axis of the image is calculated, which reduces the calculation amount compared with the method of using mutual information.

• Nonlinear Functional Analysis and Applications
• /
• v.27 no.1
• /
• pp.1-22
• /
• 2022

The purpose of this research is to formulate a new proximal-type algorithm to solve the equilibrium problem in a real Hilbert space. A new algorithm is analogous to the famous two-step extragradient algorithm that was used to solve variational inequalities in the Hilbert spaces previously. The proposed iterative scheme uses a new step size rule based on local bifunction details instead of Lipschitz constants or any line search scheme. The strong convergence theorem for the proposed algorithm is well-proven by letting mild assumptions about the bifunction. Applications of these results are presented to solve the fixed point problems and the variational inequality problems. Finally, we discuss two test problems and computational performance is explicating to show the efficiency and effectiveness of the proposed algorithm.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.37 no.5
• /
• pp.476-485
• /
• 2024

Understanding the structure-property relationship in functional materials is crucial as microstructural features such as nano-precipitates, phase boundary, grain boundary segregation, and grain boundary phases play a key role in their functional properties. Atom probe tomography (APT) is an advanced analytical technique that allows for the three-dimensional (3D) mapping of atomic distributions and the precise determination of local chemical compositions in materials. Moreover, it offers sub-nanometer spatial resolution and chemical sensitivity at the tens of parts per million (ppm) level. Owing to its unique capabilities, this technique has been employed to uncover the 3D elemental distributions in a wide range of materials, including alloys, semiconductors, nanomaterials, and even biomaterials. In this paper, various kinds of examples are introduced for elucidating structure-property relationships on functional materials by utilizing the atom probe tomography.

• International Journal of Control, Automation, and Systems
• /
• v.2 no.1
• /
• pp.107-117
• /
• 2004

A new algorithm for planning a collision-free path based on an algebraic curve as well as the concept of path space is developed. Robot path planning has so far been concerned with generating a single collision-free path connecting two specified points in a given robot workspace with appropriate constraints. In this paper, a novel concept of path space (PS) is introduced. A PS is a set of points that represent a connection between two points in Euclidean metric space. A geometry mapping (GM) for the systematic construction of path space is also developed. A GM based on the 2$^{nd}$ order base curve, specifically Bezier curve of order two is investigated for the construction of PS and for collision-free path planning. The Bezier curve of order two consists of three vertices that are the start, S, the goal, G, and the middle vertex. The middle vertex is used to control the shape of the curve, and the origin of the local coordinate (p, $\theta$) is set at the centre of S and G. The extreme locus of the base curve should cover the entire area of actual workspace (AWS). The area defined by the extreme locus of the path is defined as quadratic workspace (QWS). The interference of the path with obstacles creates images in the PS. The clear areas of the PS that are not mapped by obstacle images identify collision-free paths. Hence, the PS approach converts path planning in Euclidean space into a point selection problem in path space. This also makes it possible to impose additional constraints such as determining the shortest path or the safest path in the search of the collision-free path. The QWS GM algorithm is implemented on various computer systems. Simulations are carried out to measure performance of the algorithm and show the execution time in the range of 0.0008 ~ 0.0014 sec.

• Journal of KIISE:Computer Systems and Theory
• /
• v.32 no.2
• /
• pp.55-67
• /
• 2005

Separation between computation and communication in system design allows the system designer to explore the communication architecture independently of component selection and mapping. In this paper we present an iterative two-step exploration methodology for bus-based on-chip communication architecture and memory allocation, assuming that memory traces from the processing elements are given from the mapping stage. The proposed method uses a static performance estimation technique to reduce the large design space drastically and quickly, and applies a trace-driven simulation technique to the reduced set of design candidates for accurate Performance estimation. Since local memory traffics as well as shared memory traffics are involved in bus contention, memory allocation is considered as an important axis of the design space in our technique. The viability and efficiency of the proposed methodology arc validated by two real -life examples, 4-channel digital video recorder (DVR) and an equalizer for OFDM DVB-T receiver.

• Journal of Ocean Engineering and Technology
• /
• v.23 no.2
• /
• pp.58-68
• /
• 2009

The increased use of unmanned underwater vehicles (UUV) has led to the development of alternative navigational methods that do not employ acoustic beacons and dead reckoning sensors. This paper describes a simultaneous localization and mapping (SLAM) scheme that uses range sonars mounted on a small UUV. A SLAM scheme is an alternative navigation method for measuring the environment through which the vehicle is passing and providing the relative position of the UUV. A technique for a SLAM algorithm that uses several ranging sonars is presented. This technique utilizes an unscented Kalman filter to estimate the locations of the UUV and surrounding objects. In order to work efficiently, the nearest neighbor standard filter is introduced as the data association algorithm in the SLAM for associating the stored targets returned by the sonar at each time step. The proposed SLAM algorithm was tested by experiments under various three degrees of freedom motion conditions. The results of these experiments showed that the proposed SLAM algorithm was capable of estimating the position of the UUV and the surrounding objects and demonstrated that the algorithm will perform well in various environments.