• Journal of Broadcast Engineering
• /
• v.25 no.3
• /
• pp.338-345
• /
• 2020

Versatile Video Coding (VVC), which has been developing as a next generation video coding standard, has adopted various techniques to achieve more than twice the compression performance of HEVC (High Efficiency Video Coding). The recently released VVC Test Model (VTM) shows 38% Bjontegaard Delta bitrate (BD-rate) improvement and 9x/1.6x encoding/decoding complexity over HEVC. In order to reduce such increased complexity, various fast algorithms have been proposed. In this paper, gradient-based methods of fast intra mode decision and block splitting are presented. Experimental results show that, compared to VTM6.0, the proposed method gives up to 65% encoding time reduction with 3.54% BD-rate loss in All-Intra (AI) configuration.

• Journal of Educational Research in Mathematics
• /
• v.19 no.1
• /
• pp.25-43
• /
• 2009

The fraction concept consists of various meanings and is one of the abstract and difficult in elementary school mathematics. This study intends to find out the implication for introducing the fraction concept by comparing mathematics textbooks of Korea and Singapore. Both countries' students peformed well in recent TIMMSs. Some implications are as follows; The term 'equal' is not defined and the results of various 'equal partitioning' activities can not easily examined in Korea's mathematics textbook. And contexts of introducing fractions as a quotient and a ratio are unnatural in Korea's mathematics textbook in comparison with Singapore's mathematics textbook. So these ideas should be reconsidered in order to seek the direction for improvement of it. And Korea's textbooks need the emphasis on the fraction as a measure and on constructing fraction concept by unit fraction.

• KIISE Transactions on Computing Practices
• /
• v.21 no.1
• /
• pp.70-75
• /
• 2015

In this paper, we explore the efficient processing of continuous range queries over a huge number of moving objects, each of which retrieves the moving objects that are currently located within a geographic query region of interest. The moving objects should continually communicate with the server to report their current locations, so as to keep the results of the continuous range queries up-to-date. However, this increases the server workload and involves a enormous amount of communication as the number of continuous range queries and the moving objects becomes enormous. In this paper, we adopt an approach where we leverage available memory and computational resources of the moving objects in order to resolve these problems. To this end, we propose a query indexing structure, referred to as the Space Partitioning Query Index(SPQI), which enables the server to efficiently cooperate with the moving objects for processing continuous range queries. SPQI improves system performance in terms of server workload and communication cost. Through simulations, we show the superiority of SPQI.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.4C
• /
• pp.533-540
• /
• 2004

This paper proposes a new multispectral image data compression algorithm that can efficiently reduce spatial and spectral redundancies by applying classified prediction, a Karhunen-Loeve transform (KLT), and the three-dimensional set partitioning in hierarchical trees (3-D SPIHT) algorithm in the wavelet transform (WT) domain. The classification is performed in the WT domain to exploit the interband classified dependency, while the resulting class information is used for the interband prediction. The residual image data on the prediction errors between the original image data and the predicted image data is decorrelated by a KLT. Finally, the 3-D SPIHT algorithm is used to encode the transformed coefficients listed in a descending order spatially and spectrally as a result of the WT and KLT. Simulation results showed that the reconstructed images after using the proposed algorithm exhibited a better quality and higher compression ratio than those using conventional algorithms.

• Journal of KIISE:Software and Applications
• /
• v.31 no.4
• /
• pp.478-487
• /
• 2004

We had proposed the RPA(Recursive Partition Averaging) method in order to improve the storage requirement and classification rate of the Memory Based Reasoning. That algorithm worked not bad in many area, however, the major drawbacks of RPA are it's partitioning condition and the way of extracting major patterns. We propose an adaptive RPA algorithm which uses the FPD(feature-based population densimeter) to stop the ARPA partitioning process and produce, instead of RPA's averaged major pattern, optimizing resulting hyperrectangles. The proposed algorithm required only approximately 40% of memory space that is needed in k-NN classifier, and showed a superior classification performance to the RPA. Also, by reducing the number of stored patterns, it showed an excellent results in terms of classification when we compare it to the k-NN.

• Korean Journal of Remote Sensing
• /
• v.18 no.6
• /
• pp.359-367
• /
• 2002

In this paper, a new embedded wavelet packet image coder algorithm is proposed for an effective image coder using correlation between partitioned coefficients. This new algorithm presents parent-child relationship for reducing image reconstruction error using relations between individual frequency sub-bands. By parent-child relationship, every coefficient is partitioned and encoded for the zerotree data structure. It is shown that the proposed wavelet packet image coder algorithm achieves low bit rates and rate-distortion. It also demonstrates higher PSNR under the same bit rate and an improvement in image compression time. The perfect rate control is compared with the conventional method. These results show that the encoding and decoding processes of the proposed coder are simpler and more accurate than the conventional ones for texture images that include many mid and high-frequency elements such as aerial and satellite photograph images. The experimental results imply the possibility that the proposed method can be applied to real-time vision system, on-line image processing and image fusion which require smaller file size and better resolution.

• Journal of Ecology and Environment
• /
• v.43 no.1
• /
• pp.73-83
• /
• 2019

Background: Habitat selectivity and ecology of freshwater fishes were studied in two selected streams and their junction point which consist a total of 39 microhabitats. The aims of this study were to describe the habitat preference and its availability to fish assemblage, as well as ecology, habitat use, and habitat characteristics. Methods: We collected fish with backpack electrofishing three times during August 2013, December 2013, and March 2014. Using a variation partitioning approach of R software, we studied the relationship of fish abundances with stream type, habitat type, and abundance of key macroinvertebrate taxa. Results: A total of 6554 fishes representing four species belonging to the family Cyprinidae were caught. A higher total fish abundance was recorded from Gereb Tsedo (4870; 74.3%) than from Elala stream (1684; 25.7%). Taking both streams together, the overall total relative fish abundance was significantly higher in pools (53%) than in runs (35%) and in riffles (12%) at P < 0.05. Species-wise comparisons showed that 71%, 15%, 13%, and 1% of the pool fish community were occupied by Garra blanfordii, Garra ignestii, Garra dembecha, and Garra aethiopica, respectively. Stream type, habitat type, and key macroinvertebrate taxa each explained a significant proportion of the variation in fish abundance. Based on the variation partitioning approach, fish abundance was higher in Gereb Tsedo stream (P < 0.01). Moreover, fish abundance increased with pool habitat type (P < 0.01) and with availability of key macroinvertebrate taxa (P < 0.01). Conclusion: Fish abundance differed between stream types, among habitats and among key macroinvertebrate taxa availability. Among the factors, habitat type was the most important driving factor behind variation among fish abundances, and pool supports the highest fish abundance.

• Smart Structures and Systems
• /
• v.20 no.1
• /
• pp.61-74
• /
• 2017

One of the most reliable and simplest tools for structural vibration control in civil engineering is Tuned Mass Damper, TMD. Provided that the frequency and damping parameters of these dampers are tuned appropriately, they can reduce the vibrations of the structure through their generated inertia forces, as they vibrate continuously. To achieve the optimal parameters of TMD, many different methods have been provided so far. In old approaches, some formulas have been offered based on simplifying models and their applied loadings while novel procedures need to model structures completely in order to obtain TMD parameters. In this paper, with regard to the nonlinear decision-making of fuzzy systems and their enough ability to cope with different unreliability, a method is proposed. Furthermore, by taking advantage of both old and new methods a fuzzy system is designed to be operational and reduce uncertainties related to models and applied loads. To design fuzzy system, it is required to gain data on structures and optimum parameters of TMDs corresponding to these structures. This information is obtained through modeling MDOF systems with various numbers of stories subjected to far and near field earthquakes. The design of the fuzzy systems is performed by three methods: look-up table, the data space grid-partitioning, and clustering. After that, rule weights of Mamdani fuzzy system using the look-up table are optimized through genetic algorithm and rule weights of Sugeno fuzzy system designed based on grid-partitioning methods and clustering data are optimized through ANFIS (Adaptive Neuro-Fuzzy Inference System). By comparing these methods, it is observed that the fuzzy system technique based on data clustering has an efficient function to predict the optimal parameters of TMDs. In this method, average of errors in estimating frequency and damping ratio is close to zero. Also, standard deviation of frequency errors and damping ratio errors decrease by 78% and 4.1% respectively in comparison with the look-up table method. While, this reductions compared to the grid partitioning method are 2.2% and 1.8% respectively. In this research, TMD parameters are estimated for a 15-degree of freedom structure based on designed fuzzy system and are compared to parameters obtained from the genetic algorithm and empirical relations. The progress up to 1.9% and 2% under far-field earthquakes and 0.4% and 2.2% under near-field earthquakes is obtained in decreasing respectively roof maximum displacement and its RMS ratio through fuzzy system method compared to those obtained by empirical relations.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.49 no.8
• /
• pp.1-11
• /
• 2012

The multi-code spread spectrum communication system, which spreads data bit stream by multiplexing orthogonal codes, can transmit data in high rate. However it needs the high-cost good linear amplifier because of the multi-level output signal. In order to overcome this drawback several systems making the amplitude of output signal constant with Walsh codes have been proposed. Recently constant amplitude pre-coded multi-code spread spectrum systems using extended m-sequence have been proposed. In this paper we consider an extended m-sequence based constant amplitude multi-code spread spectrum system with code set partitioning. By grouping the orthogonal codes into 4 subsets, not only is the computational complexity of the transceiver reduced but BER performance also improves. It has been shown that parity checking on four detected codes at the receiver can correct code detection error and result in BER performance enhancement. In this paper we propose a improved parity check receiver. We carried out computer simulation to verify feasibility of the proposed algorithm.

• Korean Journal of Remote Sensing
• /
• v.32 no.5
• /
• pp.471-482
• /
• 2016

This paper presents an extraction method for water body which uses block-based image partitioning and extension of water body boundaries to improve the performance of supervised classification for water body extraction. The Mahalanobis distance image is created by computing the spectral information of Normalized Difference Water Index (NDWI) and Near Infrared (NIR) band images over a training site within the water body in order to extract an initial water body area. To reduce the effect of noise contained in the Mahalanobis distance image, we apply mean curvature diffusion to the image, which controls diffusion coefficients based on connectivity strength between adjacent pixels and then extract the initial water body area. After partitioning the extracted water body image into the non-overlapping blocks of same size, we update the water body area using the information of water body belonging to water body boundaries. The update is performed repeatedly under the condition that the statistical distance between water body area belonging to water body boundaries and the training site is not greater than a threshold value. The accuracy assessment of the proposed algorithm was tested using KOMPSAT-2 images for the various block sizes between $11{\times}11$ and $19{\times}19$. The overall accuracy and Kappa coefficient of the algorithm varied from 99.47% to 99.53% and from 95.07% to 95.80%, respectively.