• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.1
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• pp.21-31
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• 2002

This study applied each Neural Networks theory and Fuzzy Set theory to improve accuracy in remotely sensed images. Remotely sensed data have been used to map land cover. The accuracy is dependent on a range of factors related to the data set and methods used. Thus, the accuracy of maps derived from conventional supervised image classification techniques is a function of factors related to the training, allocation, and testing stages of the classification. Conventional image classification techniques assume that all the pixels within the image are pure. That is, that they represent an area of homogeneous cover of a single land-cover class. But, this assumption is often untenable with pixels of mixed land-cover composition abundant in an image. Mixed pixels are a major problem in land-cover mapping applications. For each pixel, the strengths of class membership derived in the classification may be related to its land-cover composition. Fuzzy classification techniques are the concept of a pixel having a degree of membership to all classes is fundamental to fuzzy-sets-based techniques. A major problem with the fuzzy-sets and probabilistic methods is that they are slow and computational demanding. For analyzing large data sets and rapid processing, alterative techniques are required. One particularly attractive approach is the use of artificial neural networks. These are non-parametric techniques which have been shown to generally be capable of classifying data as or more accurately than conventional classifiers. An artificial neural networks, once trained, may classify data extremely rapidly as the classification process may be reduced to the solution of a large number of extremely simple calculations which may be performed in parallel.

• Journal of Broadcast Engineering
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• v.19 no.5
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• pp.616-626
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• 2014

In this paper, we introduce a real-time stereo-to-multiview conversion system using FPGA and GPU. The system is based on two different devices so that it consists of two major blocks. The first block is a disparity estimation block that is implemented on FPGA. In this block, each disparity map of stereoscopic video is estimated by DP(dynamic programming)-based stereo matching. And then the estimated disparity maps are refined by post-processing. The refined disparity map is transferred to the GPU device through USB 3.0 and PCI-express interfaces. Stereoscopic video is also transferred to the GPU device. These data are used to render arbitrary number of virtual views in next block. In the second block, disparity-based view interpolation is performed to generate virtual multi-view video. As a final step, all generated views have to be re-arranged into a single image at full resolution for presenting on the target autostereoscopic 3D display. All these steps of the second block are performed in parallel on the GPU device.

• Tribology and Lubricants
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• v.36 no.4
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• pp.193-198
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• 2020

Fluid film bearings are among the best devices used for overcoming friction and reducing wear. Surface texturing is a new surface treatment technique used for processing grooves and dimples on the lubricated surface, and it helps to minimize friction further and improve the wear resistance. In several studies, parallel surfaces, such as thrust bearings and mechanical face seals, have been investigated, but most sliding bearings have a convergent film shape. This paper presents the third part of a recent study and focuses on the effect of the groove shape on the lubrication performance of inclined slider bearings, following the two previous papers on the effects of the groove position and depth. We adopted the continuity and Navier - Stokes equations to conduct numerical analyses using FLUENT, which is a commercial computational fluid dynamics code. The groove shape adopted in the numerical analysis is rectangular and triangular, and its depth is varied. The results show that the streamlines, pressure distributions, and groove shape significantly influence the lubrication performance of the inclined slider bearing. For both shapes, the load-carrying capacity (LCC) is maximum near the groove depth, where vortices occur. In the shallow grooves, the LCC of the rectangular shape is higher, but in deeper grooves, that of the triangular shape is higher. The deeper the rectangular groove, the higher the decrease in the frictional force. The results of this study can be used as design data for various sliding bearings.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.3_4
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• pp.149-159
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• 2003

The need for information security increases interests on cipher algorithms recently. Especially, a large volume of data transmission over high-band communication network requires faster encryption and decryption techniques for real-time processing. It would be a good solution for this problem that we implement the cipher algorithm in forms of hardware circuits. Though some previous researches use this approach, they focus only on repeatedly executing the core part of the algorithm to minimize the hardware chip size, while most cipher algorithms are inherently parallel. In this paper, we propose a new design for the SEED block cipher algorithm developed by KISA (Korea Information Security Agency) in 1998 as Korean standard cipher algorithm. It exploits the parallelism of the algorithm basically and implements it in a pipelined fashion. We described the design in VHDL program and performed functional simulations on the program, and then found that it worked correctly. In addition, we synthesized it and verified that it could be implemented in a single FPGA chip, implying that the new design can be Practically used for the actual hardware implementation of a high-speed and high-performance cipher system.

• The KIPS Transactions:PartD
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• v.19D no.2
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• pp.151-160
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• 2012

Most of the distributed high-dimensional indexing structures provide a reasonable search performance especially when the dataset is uniformly distributed. However, in case when the dataset is clustered or skewed, the search performances gradually degrade as compared with the uniformly distributed dataset. We propose a method of improving the k-nearest neighbor search performance for the distributed vector approximation-tree based on the strongly clustered or skewed dataset. The basic idea is to compute volumes of the leaf nodes on the top-tree of a distributed vector approximation-tree and to assign different number of bits to them in order to assure an identification performance of vector approximation. In other words, it can be done by assigning more bits to the high-density clusters. We conducted experiments to compare the search performance with the distributed hybrid spill-tree and distributed vector approximation-tree by using the synthetic and real data sets. The experimental results show that our proposed scheme provides consistent results with significant performance improvements of the distributed vector approximation-tree for strongly clustered or skewed datasets.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.154-162
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• 2003

In this paper, Associative Memory with Cellular Neural Networks classifies and recognizes image patterns as an operator applied to image process. CNN processes nonlinear data in real-time like neural networks, and made by cell which communicates with each other directly through its neighbor cells as the Cellular Automata does. It is applied to the optimization problem, associative memory, pattern recognition, and computer vision. Image processing with CNN is appropriate to 2-D images, because each cell which corresponds to each pixel in the image is simultaneously processed in parallel. This paper shows the method for designing the structure of associative memory based on CNN and getting output image by choosing the most appropriate weight pattern among the whole learned weight pattern memories. Each template represents weight values between cells and updates them by learning. Hebbian rule is used for learning template weights and LMS algorithm is used for classification.

• The KIPS Transactions:PartB
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• v.12B no.5 s.101
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• pp.561-566
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• 2005

This paper presents a visual tracking algorithm for the golf swing motion analysis by using the information of the pixels of video frames and movement of the golf club to solve the problem fixed center point in model based tracking method. The model based tracking method use the polynomial function for trajectory displaying of upswing and downswing. Therefore it is under the hypothesis of the no movement of the center of gravity so this method is not for the amateurs. we proposed method using the information of pixel and movement, we first detected the motion by using the information of pixel in the frames in golf swing motion. Then we extracted the club head and hand by a properties of club shaft that consist of the parallel line and the moved location of club in up-swing and down-swing. In addition, we can extract the center point of user by tracking center point of the line between center of head and both foots. And we made an experiment with data that movement of center point is big. Finally, we can track the real trajectory of club head, hand and center point by using proposed tracking algorithm.

• The KIPS Transactions:PartA
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• v.19A no.2
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• pp.73-76
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• 2012

In this paper, we propose an efficient method to extract surface atoms from a protein molecule. Surface atoms are defined as a set of atoms who can contact given probe solvent $P$, where $P$ does not collide with the molecule. The atoms contained in the molecule are represented as a set of spheres with van der Waals radii. The probe solvent also is represented as a sphere. We propose a method to extract the surface atoms by computing the offset surface of the molecule with respect to the radius of $P$. For efficient computation of the offset surface of a molecule, a voxel map is constructed for the offset surfaces of the spheres. Based on GPU (graphic processor unit) acceleration, a data parallel algorithm is used to extract the surface atoms in 42.87 milliseconds for the molecule containing up to 6,412 atoms.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.2
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• pp.53-60
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• 2020

Sentiment analysis is the automated process of understanding attitudes and opinions about a given topic from written or spoken text. One of the sentiment analysis approaches is a dictionary-based approach, in which a sentiment dictionary plays an much important role. In this paper, we propose a method to automatically generate Korean sentiment lexicon from the well-known English sentiment lexicon called VADER (Valence Aware Dictionary and sEntiment Reasoner). The proposed method consists of three steps. The first step is to build a Korean-English bilingual lexicon using a Korean-English parallel corpus. The bilingual lexicon is a set of pairs between VADER sentiment words and Korean morphemes as candidates of Korean sentiment words. The second step is to construct a bilingual words graph using the bilingual lexicon. The third step is to run the label propagation algorithm throughout the bilingual graph. Finally a new Korean sentiment lexicon is generated by repeatedly applying the propagation algorithm until the values of all vertices converge. Empirically, the dictionary-based sentiment classifier using the Korean sentiment lexicon outperforms machine learning-based approaches on the KMU sentiment corpus and the Naver sentiment corpus. In the future, we will apply the proposed approach to generate multilingual sentiment lexica.

• Journal of Astronomy and Space Sciences
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• v.19 no.3
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• pp.215-224
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• 2002

This paper describes EGSE design for the small satellite such like KOMPSAT-2 satellite. Recent design trend of small satellite and EGSE is to take short development time and less cost. For this purpose, the design for KOMPSAT-2 satellite and EGSE are not much modified from KOMPSAT-1 heritage. It means that it is able to be accommodated the verified hardware and software modules used in KOMPSAT-1 satellite program if possible. The objective of EGSE is to provide hardware and software for efficient electrical testing of integrated KOMPSAT-2 satellite in three general categories. (1) Simulators for ground testing (e.g. solar-simulation power, earth scenes, horizons and sun sensor). (2) Ground station type satellite data acquisition and processing test sets. (3) Overall control of satellite using hardline datum. In KOMPSAT (KOrea Multi-Purpose SATellite) program, KOMPSAT-2 EGSE was developed to support satellite integration and test activities. The KOMPSAT-2 EGSE was designed in parallel with satellite design. Consequently, the KOMPSAT-2 EGSE was based on the KOMPSAT-1 heritage since the spacecraft design followed the heritage. The KOMPSAT-2 baseline was elaborated by taking advantage of experience from KOMPSAT-1 program. The EGSE of KOMPSAT-2 design concept is generic modular design with preference in part selection with commercial off-the-shelf which were proven from KOMPSAT-1 programs, flexible/user friendly operational environment (graphical interface preferred), minimized new design and self test capability.