• Asian-Australasian Journal of Animal Sciences
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• v.19 no.4
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• pp.507-513
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• 2006

Changes of in vitro true digestibility (IVTD) of Napiergrass (Pennisetum purpureum) were determined by a filter bag system, and their relationships to chemical composition, leaf to stem ratio, plant height, geographic location, climatic factors and harvest interval were studied and used to develop prediction models for the crude protein (CP), acid-detergent fiber (ADF), and neutral-detergent fiber (NDF) contents and IVTD. Partitioning the total variance of IVTD of Napiergrass showed that 80% was attributable to the effect of harvest interval. Days of growth, plant height, leaf/stem ratio, CP, ADF and NDF of Napiergrass had highly significant relationships (p<0.01) with IVTD. The highest coefficient of correlation between the ADF, NDF, and IVTD of Napiergrass and growth degree days was obtained when the base temperature was set at $0^{\circ}C$. Growth degree days could predict ADF, NDF, and IVTD of Napiergrass more accurately than plant height, and plant height is not suitable to predict IVTD.

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.46-56
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• 2016

Dynamic textures are videos that exhibit a stationary property with respect to time (i.e., they have patterns that repeat themselves over a large number of frames). These patterns can easily be tracked by a linear dynamic system. In this paper, a model that identifies the underlying linear dynamic system using wavelet coefficients, rather than a raw sequence, is proposed. Content based threshold filtering based on Set Partitioning in a Hierarchical Tree (SPIHT) helps to get another representation of the same frames that only have low frequency components. The main idea of this paper is to apply SPIHT based threshold filtering on different bands of wavelet transform so as to have more significant information in fewer parameters for singular value decomposition (SVD). In this case, more flexibility is given for the component selection, as SVD is independently applied to the different bands of frames of a dynamic texture. To minimize the time complexity, the proposed model is implemented on a graphics processing unit (GPU). Test results show that the proposed dynamic system, along with a discrete wavelet and SPIHT, achieve a highly compact model with better visual quality, than the available LDS, Fourier descriptor model, and higher-order SVD (HOSVD).

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.5 no.3 s.11
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• pp.29-39
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• 2006

In this paper, we propose an efficient method to detect the signal and evaluate performance of the system in frequency selective fading channel. We combine proposed system with OFDM (Orthogonal Frequency Division Multiplexing) to improve performance of the system. First, we study the SOSTTC-OFDM system using two transmit antenna and one receive antenna, and compare performance of the proposed space-time coded OFDM with that of previous system. We expand this system to the system using four transmit antennas with the proposed decoding method. Simulation results show that the proposed decoding method can detect the signal efficiently, and we identify that the performance of the proposed system is shown with varying doppler frequency in frequency selective fading channel.

• ETRI Journal
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• v.30 no.3
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• pp.412-420
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• 2008

A new scan partition architecture to reduce both the average and peak power dissipation during scan testing is proposed for low-power embedded systems. In scan-based testing, due to the extremely high switching activity during the scan shift operation, the power consumption increases considerably. In addition, the reduced correlation between consecutive test patterns may increase the power consumed during the capture cycle. In the proposed architecture, only a subset of scan cells is loaded with test stimulus and captured with test responses by freezing the remaining scan cells according to the spectrum of unspecified bits in the test cubes. To optimize the proposed process, a novel graph-based heuristic to partition the scan chain into several segments and a technique to increase the number of don't cares in the given test set have been developed. Experimental results on large ISCAS89 benchmark circuits show that the proposed technique, compared to the traditional full scan scheme, can reduce both the average switching activities and the average peak switching activities by 92.37% and 41.21%, respectively.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.415-417
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• 2005

In order to retrieve the latent and sensible heat fluxes, high-resolution airborne imageries with visible, near infrared, and thermal infrared bands and ground-base meteorology measurements are utilized in this paper. The retrieval scheme is based on the balance of surface energy budget and momentum equations. There are three basic surface parameters including surface albedo $(\alpha)$, normalized difference vegetation index (NOVI) and surface kinetic temperature (TO). Lowtran 7 code is used to correct the atmosphere effect. The imageries were taken on 28 April and 5 May 2003. From the scattering plot of data set, we observed the extreme dry and wet pixels to derive the fitting of dry and wet controlled lines, respectively. Then the sensible heat and latent heat fluxes are derived from through a partitioning factor A. The retrieved latent and sensible heat fluxes are compared with in situ measurements, including eddy correlation and porometer measurements. It is shown that the retrieved fluxes from our scheme match with the measurements better than those derived from the S-SEBI model.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.31-45
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• 2007

Large data handling is one of critical issues that the data mining community faces. This is particularly true for computationally intense tasks such as data clustering. Random sampling of instances is one possible means of achieving large data handling, but a pervasive problem with this approach is how to deal with the noise in the evaluation of the learning algorithm. This paper develops a new optimization based clustering approach using an algorithm specifically designed for noisy performance. Numerical results show this algorithm better than the other algorithms such as PAM and CLARA. Also with this algorithm substantial benefits can be achieved in terms of computational time without sacrificing solution quality using partial data.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.687-695
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• 2003

In this paper, we present a document image compression system based on segmentation, Quincunx downsampling, (5/3) wavelet lifting and subband-oriented SPIHT coding. We reduced the coding time by the adaptation of subband-oriented SPIHT coding and Quincunx downsampling. And to increase compression rate further, we applied arithmetic coding to the bitstream of SPIHT coding output. Finally, we present the reconstructed images for visual comparison and also present the compression rates and PSNR values under various scalar quantization methods.

• Journal of Broadcast Engineering
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• v.4 no.1
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• pp.1-11
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• 1999

This paper introduces orthogonally multiplexed modulation and demodulation methods based on Wavelet Packet Bases and particularly describes Wavelet Packet Modulation (WPM) techniques that provide the designer of transmission signal set in time-frequency domain with tree structural information which can be adapted to given channel characterristics. Multi-dimensional signaling methods are also contrasted to common and different characteristics of conventional QAM. multi-tone modulation methods. The paper addresses the mothod how to find a best tree structure that has more adaptivity to impulse and narrowband tone pulse noises using a tunning algorithm which arbitrarily partitions the time-frequency space and makes a suitable orthogonal signaling waveforms. Simulation results exhibits a favorable performance over existing mod/demod methods specially for narrowband tone pulse and impulse interferences.

• Korean Journal of Computational Design and Engineering
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• v.4 no.3
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• pp.173-179
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• 1999

In reverse engineering, when a shape containing multi-patched surfaces is digitized, the boundaries of these surfaces should be detected. The objective of this paper is to introduce a computationally efficient segmentation technique for extracting edges, ad partitioning the 3D measuring point data based on the location of the boundaries. The procedure begins with the identification of the edge points. An automatic edge-based approach is developed on the basis of local geometry. A parametric quadric surface approximation method is used to estimate the local surface curvature properties. the least-square approximation scheme minimizes the sum of the squares of the actual euclidean distance between the neighborhood data points and the parametric quadric surface. The surface curvatures and the principal directions are computed from the locally approximated surfaces. Edge points are identified as the curvature extremes, and zero-crossing, which are found from the estimated surface curvatures. After edge points are identified, edge-neighborhood chain-coding algorithm is used for forming boundary curves. The original point set is then broke down into subsets, which meet along the boundaries, by scan line algorithm. All point data are applied to each boundary loops to partition the points to different regions. Experimental results are presented to verify the developed method.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.4
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• pp.206-216
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• 2010

Wireless sensor networks (WSNs) are used to collect various data in environment monitoring applications. A spatial clustering may reduce energy consumption of data collection by partitioning the WSN into a set of spatial clusters with similar sensing data. For each cluster, only a few sensor nodes (samplers) report their sensing data to a base station (BS). The BS may predict the missed data of non-samplers using the spatial correlations between sensor nodes. ASAP is a representative data collection algorithm using the spatial clustering. It periodically reconstructs the entire network into new clusters to accommodate to the change of spatial correlations, which results in high message overhead. In this paper, we propose a new data collection algorithm, name EPDC (Energy-efficient Periodic Data Collection). Unlike ASAP, EPDC identifies a specific cluster consisting of many dissimilar sensor nodes. Then it reconstructs only the cluster into subclusters each of which includes strongly correlated sensor nodes. EPDC also tries to reduce the message overhead by incorporating a judicious probabilistic model transfer method. We evaluate the performance of EPDC and ASAP using a simulation model. The experiment results show that the performance improvement of EPDC is up to 84% compared to ASAP.