• The Journal of the Korea Contents Association
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• v.11 no.11
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• pp.19-27
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• 2011

In this paper, we present an emulation library for the essential features and their API function calls provided by Direct3D, the most actively used API for computer game-related application programs on the MS-Windows-based desktop's, with OpenGL library in the Linux environment. In typical Linux-based systems, only the X window system and OpenGL graphics library are available. There are lots of needs for this kind of emulation library to convert the Direct3D-based game applications and user interfaces on these systems. Through carefully selecting the essential API functions from the DirectX version 9.0, we obtained the prototype implementation of that emulation library, to finally get the final full-scale DirectX implementation. Our implementation currently covers 3D coordinate transformations, light and material processing, texture mapping, simple animation features and more. We showed its feasibility through successfully executing a set of Direct3D demonstration programs including a real-world game character animation on our implementation.

• Journal of Korean Society on Water Environment
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• v.31 no.3
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• pp.241-252
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• 2015

Runoff behaviors by five bias correction methods were analyzed, which were Change Factor methods using past observed and estimated data by the estimation scenario with average annual calibration factor (CF_Y) or with average monthly calibration factor (CF_M), Quantile Mapping methods using past observed and estimated data considering cumulative distribution function for entire estimated data period (QM_E) or for dry and rainy season (QM_P), and Integrated method of CF_M+QM_E(CQ). The peak flow by CF_M and QM_P were twice as large as the measured peak flow, it was concluded that QM_P method has large uncertainty in monthly runoff estimation since the maximum precipitation by QM_P provided much difference to the other methods. The CQ method provided the precipitation amount, distribution, and frequency of the smallest differences to the observed data, compared to the other four methods. And the CQ method provided the rainfall-runoff behavior corresponding to the carbon dioxide emission scenario of SRES A1B. Climate change scenario with bias correction still contained uncertainty in accurate climate data generation. Therefore it is required to consider the trend of observed precipitation and the characteristics of bias correction methods so that the generated precipitation can be used properly in water resource management plan establishment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.125-130
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• 2018

Linear discriminant analysis is a statistical analysis method that is generally used for dimensionality reduction of the feature vectors or for class classification. However, in the case of a data set that cannot be linearly separated, it is possible to make a linear separation by mapping a feature vector into a higher dimensional space using a nonlinear function. This method is called generalized discriminant analysis or kernel discriminant analysis. In this paper, we carried out target classification experiments with active sonar target signals available on the Internet using both liner discriminant and generalized discriminant analysis methods. Experimental results are analyzed and compared with discussions. For 104 test data, LDA method has shown correct recognition rate of 73.08%, however, GDA method achieved 95.19% that is also better than the conventional MLP or kernel-based SVM.

• The Transactions of the Korea Information Processing Society
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• v.2 no.5
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• pp.777-786
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• 1995

This paper describes several algorithms for technology mapping of logic functions into interesting and popular FPGAs that use look-up table memories. In order to improve the technology mapping for FPGA, some existing multi-level logic synthesis, decomposition reduction and packing techniques are analyzed and compared. And then new algorithms such as node-pair decomposition, merging fanin, unified reduction and multiple output decomposition which are used for combinational logic design, are proposed. The cost function is used to minimize the number of CLBs and edges of the network. The cost is a linear combination of each weight that is given by user. Finally we compare our new algorithm with previous logic design technique［8］. In an experimental comparison our algorithm requires 10% fewer CLB and nets than SIS-pga.

• The Journal of the Acoustical Society of Korea
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• v.15 no.4
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• pp.58-64
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• 1996

This paper was proposed the recognition method by using parameters which was estimated from the data on the estimated plane and a neural network. After the LPC estimated in each frame algorithm was mapped to the estimated plane by the optimum feature mapping function, we estimated the C-LPC and the maximum and minimum value and 3 divided power from the mapping data on the estimated plane. As a result of the experiment of the speech recognition that those parameters were applied to the input of a neural network, it was found that those parameters estimated from the estimated plane have the features of the original speech for a change in the time scale and that the recongnition rate by the proposed methods was 96.3 percent.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.503-508
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• 2001

Conformal mapping is useful to solve problems in heat conduction, electrostatic potential and fluid flow involving Laplace's equation in two independent variables. Determinations of conformal maps from the unit disk onto a Jordan region eventually requires solving the Theodorsen equation which is in general nonlinear with respect to the boundary correspondence function. H bner's method which has been well known for the efficient method among the many suggestions for the Theodorsen equation, was improved in early study[1, 2]. In this paper Wegmann's method is treated that is more efficient in computation cost rather than H bner's. But we found that a question which is divergent in some difficult problems by numerical experiment of Wegmann's iteration. We analyze theoretically the cause of divergence and propose an improved method by applying a low frequency filter to the Wegmann's method. Numerical experiments by our improved method show convergence for all divergent problems by Wegmann's method.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.40-44
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• 2002

Precision correction is the process of geometrically aligning images to a reference coordinate system using GCPs(Ground Control Points). Many applications of remote sensing data, such as change detection, mapping and environmental monitoring, rely on the accuracy of precision correction. However it is a very time consuming and laborious process. It requires GCP collection, the identification of image points and their corresponding reference coordinates. At typical satellite ground stations, GCP collection requires most of man-powers in processing satellite images. A method of automatic registration of satellite images is demanding. In this paper, we propose a new algorithm for automatic precision correction by GCP chips and RANSAC(Random Sample Consensus). The algorithm is divided into two major steps. The first one is the automated generation of ground control points. An automated stereo matching based on normalized cross correlation will be used. We have improved the accuracy of stereo matching by determining the size and shape of match windows according to incidence angle and scene orientation from ancillary data. The second one is the robust estimation of mapping function from control points. We used the RANSAC algorithm for this step and effectively removed the outliers of matching results. We carried out experiments with SPOT images over three test sites which were taken at different time and look-angle with each other. Left image was used to select UP chipsets and right image to match against GCP chipsets and perform automatic registration. In result, we could show that our approach of automated matching and robust estimation worked well for automated registration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.3984-4005
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• 2017

Image recognition has become an increasingly important topic for its wide application. It is highly challenging when facing to large-scale database with large variance. The recognition systems rely on a key component, i.e. the low-level feature or the learned mid-level feature. The recognition performance can be potentially improved if the data distribution information is exploited using a more sophisticated way, which usually a function over hidden variable, model parameter and observed data. These methods are called generative score space. In this paper, we propose a discriminative extension for the existing generative score space methods, which exploits class label when deriving score functions for image recognition task. Specifically, we first extend the regular generative models to class conditional models over both observed variable and class label. Then, we derive the mid-level feature mapping from the extended models. At last, the derived feature mapping is embedded into a discriminative classifier for image recognition. The advantages of our proposed approach are two folds. First, the resulted methods take simple and intuitive forms which are weighted versions of existing methods, benefitting from the Bayesian inference of class label. Second, the probabilistic generative modeling allows us to exploit hidden information and is well adapt to data distribution. To validate the effectiveness of the proposed method, we cooperate our discriminative extension with three generative models for image recognition task. The experimental results validate the effectiveness of our proposed approach.

• Korean Journal of Remote Sensing
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• v.17 no.1
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• pp.45-56
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• 2001

To acquire seabed information, the mosaic images of the seabed were generated using Side Scan Sonar. Short time energy function which is needed for slant range correction is proposed to get the height of Tow-Fish to the reflected acoustic amplitudes of each ping, and that leads to a mosaic image without water column. While generating mosaic image, maximum value, last value and average value are used for the measure of a pixel in the mosaic image and 3-D information was kept by using acoustic amplitudes which were heading for specific direction. As a generating method of mosaic image, low resolution mosaic image which is over 1m/pixel resolution was generated for whole survey area first, and then high resolution mosaic image which is generated under 0.1m/pixel resolution was generated for the selected area. Rocks, ripple mark, sand wave, tidal flat and artificial fish reef are found in the mosaic image.

• The Plant Pathology Journal
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• v.38 no.6
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• pp.572-582
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• 2022

Sheath blight disease caused by the necrotrophic, soilborne pathogen Rhizoctonia solani Kuhn, is the global threat to rice production. Lack of reliable stable resistance sources in rice germplasm pool for sheath blight has made resistance breeding a very difficult task. In the current study, 101 rice landraces were screened against R. solani under artificial epiphytotics and identified six moderately resistant landraces, Jigguvaratiga, Honasu, Jeer Sali, Jeeraga-2, BiliKagga, and Medini Sannabatta with relative lesion height (RLH) range of 21-30%. Landrace Jigguvaratiga with consistent and better level of resistance (21% RLH) than resistant check Tetep (RLH 28%) was used to develop mapping population. DNA markers associated with ShB resistance were identified in F₂ mapping population developed from Jigguvaratiga × BPT5204 (susceptible variety) using bulk segregant analysis. Among 56 parental polymorphic markers, RM5556, RM6208, and RM7 were polymorphic between the bulks. Single marker analysis indicated the significant association of ShB with RM5556 and RM6208 with phenotypic variance (R²) of 28.29 and 20.06%, respectively. Co-segregation analysis confirmed the strong association of RM5556 and RM6208 located on chromosome 8 for ShB trait. This is the first report on association of RM6208 marker for ShB resistance. In silico analysis revealed that RM6208 loci resides the stearoyl ACP desaturases protein, which is involved in defense mechanism against plant pathogens. RM5556 loci resides a protein, with unknown function. The putative candidate genes or quantitative trait locus harbouring at the marker interval of RM5556 and RM6208 can be further used to develop ShB resistant varieties using molecular breeding approaches.