• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.645-651
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• 2002

we propose a k-nearest neighbors(k-NN) based pattern selection method. The method tries to select the patterns that are near the decision boundary and that are correctly labeled. The simulations over synthetic data sets showed promising results: (1) By converting a non-separable problem to a separable one, the search for an optimal error tolerance parameter became unnecessary. (2) SVM training time decreased by two orders of magnitude without any loss of accuracy. (3) The redundant SVM were substantially reduced.

• Bulletin of the Korean Chemical Society
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• v.7 no.5
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• pp.347-353
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• 1986

Fisher's discriminant method has been applied to the problem of the classification of Korean potsherds, using their elemental composition as analyzed by neutron activation analysis. A combination of analytical data by means of statistical linear discriminant analysis has resulted in removal of redundant variables, optimal linear combination of meaningful variables and formulation of classification rules.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.65-65
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• 2002

In remote sensing, images are acquired over the same area by sensors of different spectral ranges (from the visible to the microwave) and/or with different number, position, and width of spectral bands. These images are generally partially redundant, as they represent the same scene, and partially complementary. For many applications of image classification, the information provided by a single sensor is often incomplete or imprecise resulting in misclassification. Fusion with redundant data can draw more consistent inferences for the interpretation of the scene, and can then improve classification accuracy. The common approach to the classification of multisensor data as a data fusion scheme at pixel level is to concatenate the data into one vector as if they were measurements from a single sensor. The multiband data acquired by a single multispectral sensor or by two or more different sensors are not completely independent, and a certain degree of informative overlap may exist between the observation spaces of the different bands. This dependence may make the data less informative and should be properly modeled in the analysis so that its effect can be eliminated. For modeling and eliminating the effect of such dependence, this study employs a strategy using self and conditional information variation measures. The self information variation reflects the self certainty of the individual bands, while the conditional information variation reflects the degree of dependence of the different bands. One data set might be very less reliable than others in the analysis and even exacerbate the classification results. The unreliable data set should be excluded in the analysis. To account for this, the self information variation is utilized to measure the degrees of reliability. The team of positively dependent bands can gather more information jointly than the team of independent ones. But, when bands are negatively dependent, the combined analysis of these bands may give worse information. Using the conditional information variation measure, the multiband data are split into two or more subsets according the dependence between the bands. Each subsets are classified separately, and a data fusion scheme at decision level is applied to integrate the individual classification results. In this study. a two-level algorithm using hierarchical clustering procedure is used for unsupervised image classification. Hierarchical clustering algorithm is based on similarity measures between all pairs of candidates being considered for merging. In the first level, the image is partitioned as any number of regions which are sets of spatially contiguous pixels so that no union of adjacent regions is statistically uniform. The regions resulted from the low level are clustered into a parsimonious number of groups according to their statistical characteristics. The algorithm has been applied to satellite multispectral data and airbone SAR data.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.43-47
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• 1999

In this paper, we describe the configuration of the KITSAT-3 image data receiving, archiving, processing and distribution system in operation. Following the low-cost and software-based design concept, the whole system is composed of three PCs : two for data receiving, archiving and processing which provide a full dual-redundant configuration and one for image catalog browsing which can be accessed by public users. Except that receiving and archiving PCs have serial data ingest boards plugged in, they are configured by general peripherals. This basic and simple hardware configuration made it possible to show that a very low cost system can support a full ground operation for the utilization of high-resolution satellite image data.

• IE interfaces
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• v.11 no.2
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• pp.149-157
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• 1998

In this paper, various techniques considering the characteristics of computer memory management are suggested, which can be used in the implementation of simplex method. First, reduction technique of indirect addressing, redundant references of memory, and scatter/gather technique are implemented, and the effectiveness of the techniques is shown. Loop-unrolling technique, which exploits the arithmetic operation mechanism of computer, is also implemented. Second, a subroutine frequently called is written in low-level language, and the effectiveness is proved by experimental results. Third, row-column linked list and Gustavson's data structure are compared as the data structure for the large sparse matrix in LU form. Last, buffering technique and memory-mapped file which can be used in reading large data file are implemented and the effectiveness is shown.

• Journal of KIISE:Software and Applications
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• v.34 no.9
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• pp.804-816
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• 2007

Sample training data for machine learning often contain irrelevant information or redundant concept. It is also the case that the original data may include noise. If the information collected for constructing learning model is not reliable, it is difficult to obtain accurate information. So the system attempts to find relations or regulations between features and categories in the teaming phase. The feature selection is to remove irrelevant or redundant information before constructing teaming model. for improving its performance. Existing feature selection methods assume that the distribution of documents is balanced in terms of the number of documents for each class and the length of each document. In practice, however, it is difficult not only to prepare a set of documents with almost equal length, but also to define a number of classes with fixed number of document elements. In this paper, we propose a new feature selection method that considers the impurities among the words and unbalanced distribution of documents in categories. We could obtain feature candidates using the word impurity and eventually select the features through unbalanced distribution of documents. We demonstrate that our method performs better than other existing methods via some experiments.

• ETRI Journal
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• v.38 no.6
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• pp.1064-1073
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• 2016

An adaptive speech streaming method to improve the perceived speech quality of a software-based multipoint control unit (SW-based MCU) over IP networks is proposed. First, the proposed method predicts whether the speech packet to be transmitted is lost. To this end, the proposed method learns the pattern of packet losses in the IP network, and then predicts the loss of the packet to be transmitted over that IP network. The proposed method classifies the speech signal into different classes of silence, unvoiced, speech onset, or voiced frame. Based on the results of packet loss prediction and speech classification, the proposed method determines the proper amount and bitrate of redundant speech data (RSD) that are sent with primary speech data (PSD) in order to assist the speech decoder to restore the speech signals of lost packets. Specifically, when a packet is predicted to be lost, the amount and bitrate of the RSD must be increased through a reduction in the bitrate of the PSD. The effectiveness of the proposed method for learning the packet loss pattern and assigning a different speech coding rate is then demonstrated using a support vector machine and adaptive multirate-narrowband, respectively. The results show that as compared with conventional methods that restore lost speech signals, the proposed method remarkably improves the perceived speech quality of an SW-based MCU under various packet loss conditions in an IP network.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.10
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• pp.413-420
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• 2013

Redundant arrays of independent disks (RAID) without a power-fail-safe component in small and mid-sized business suffers from intolerably long resynchronization time after a unclean power-failure. Data blocks and a parity block in a stripe must be updated in a consistent manner, however a data block may be updated but the corresponding parity block may not be updated when a power goes off. Such a partially modified stripe must be updated with a correct parity block. However, it is difficult to find which stripe is partially updated (inconsistent). The widely-used traditional parity resynchronization manner is a intolerably long process that scans the entire volume to find and fix inconsistent stripes. This paper presents a fast resynchronization scheme with a negligible overhead for small and mid-sized RAIDs. The proposed scheme is integrated into a software RAID driver in a Linux system. According to the performance evaluation, the proposed scheme shortens the resynchronization process from 200 minutes to 5 seconds with 2% overhead for normal I/Os.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.10
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• pp.859-869
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• 2012

In this paper, a new method to efficiently generate the 3-D(three-dimensional) video holograms for 3-D moving scenes, which is called here the TSR-N-LUT method, is proposed by the combined use of temporal-spatial redundancy(TSR) of 3-D video images and novel look-up table(N-LUT) technique. That is, in the proposed scheme, with the differential pulse code modulation (DPCM) algorithm, temporally redundancy redundant data in the inter-frame of a 3-D video images are removed between the frames, and then inter-line redundant data in the inter-frame of 3-D video images are also removed by using the DPCM method between the lines. Experimental results show that the proposed method could reduced the number of calculated object points and the calculation time of one object point by 23.72% and 19.55%, respectively on the average compared to the conventional method. Good experimental results with 3-D test moving pictures finally confirmed the feasibility of the proposed method to the fast generation of CGH patterns of the 3-D video images.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.2
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• pp.206-212
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• 2006

Many image and video compression algorithms work by splitting the input image into blocks and producing variable-length coded bits for each block data. If variable-length coded data are transmitted consecutively, then the resulting coder is highly sensitive to channel errors. Therefore, most image and video techniques for providing some protection to the stream against channel errors usually involve adding a controlled amount of redundancy back into the stream. Such redundancy might take the form of resynchronization markers, which enable the decoder to restart the decoding process from the known state, in the event of transmission errors. The Error Resilient Entropy Code (EREC) is a well known method which can regain synchronization without any redundant information to convert from variable-length code to fixed-length code. This paper proposes an enhancement to EREC, which greatly improves its transmission ability for the compressed image quality without any redundant bits in the event of errors. The simulation result shows that the both objective and subjective quality of transmitted image is enhanced compared with the existing EREC at the same BER(Bit Error Rate).