• Journal of Educational Research in Mathematics
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• v.16 no.4
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• pp.273-295
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• 2006

It is the purpose of this study to help computational estimation study to settle down in effective teaching method through analysis how students are understanding computational estimation and what occurs using computational estimation in actual life problem situations. I set 3 cases to accomplish these purposes. (1) How students are understanding computational estimation? (2) How students' computational estimation ability is in applying actual life problem situation? (3) What is students' different attitudes in an actual life problem situation before studying computational estimation and after? To accomplish tile purpose, I chose 6 third grade students and taught 'Computational estimation using actual life problem situation' and analyzed students computational estimation processing. Then I arranged the computational estimation processing in an actual life problem situation and differences between the before and tile after. As a result, I obtained the followings. (1) Need of estimation: Every students could recognize the need of estimation with experiencing an actual life problem situation. (2) Choosing the order of decimals: Students could choose appropriate order of decimals according to an actual life problem situations. (3) Using strategy: They usually use rounding strategy and quite often use special number and compatible number strategy.

• Journal of Elementary Mathematics Education in Korea
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• v.24 no.1
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• pp.53-87
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• 2020

The purpose of this study was to find a future direction for improving computational estimation instruction through examining the contents of computational estimation included in the 2015 revised elementary school mathematics curriculum and elementary school mathematics textbook and teacher's guide. Through this, several suggestions was made as follow. Firs, it is necessary to emphasize the computational estimation across all grade groups. Second, it is necessary to teach the computational estimation strategies systematically. It was found that it is necessary to reinforce the activities related to computational estimation in the computation related units.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.2
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• pp.91-98
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• 2022

In the next generation wireless communication system, the beamforming technique based on a massive antenna is one of core technologies for transmitting and receiving huge amounts of data, efficiently and accurately. For highly performed and highly reliable beamforming, it is required to accurately estimate the Angle of Arrival (AOA) for the desired signal incident to an antenna. Employing the massive antenna with a large number of elements, although the accuracy of the AOA estimation is enhanced, its computational complexity is dramatically increased so much that real-time communication is difficult. In order to improve this problem, AOA estimation algorithms based on the massive antenna with the low computational complexity have been actively studied. In this paper, we compute and analyze the computational complexity of the cascade AOA estimation algorithm based on the Flexible Massive Concentric Circular Array (FMCCA). In addition, its computational complexity is compared to conventional AOA estimation techniques such as the Multiple Signal Classification (MUSIC) algorithm with the high resolution and the Only Beamspace MUSIC (OBM) algorithm.

• The Mathematical Education
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• v.59 no.3
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• pp.255-269
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• 2020

In this study, how to instruct the computational estimation of addition and subtraction was considered from the perspective of a 'intended-written-implemented' multi-dimensional curriculum. To this end, the 2015 revised elementary school mathematics curriculum as a intended curriculum and the 2015 revised first~sixth grade textbook as a written curriculum were analyzed with respect to how to instruct the computational estimation of addition and subtraction. As an implemented curriculum, a research study was conducted in relation to the method of instructing teachers about the computational estimation of addition and subtraction. As a result, first, it is necessary to discuss how to develop the ability to estimate and set it as a teaching goal and achievement standard in a separate curriculum to instruct it with learning content. Second, it is necessary to provide an opportunity to learn about various estimation methods by presenting specific activities so that students can learn the estimation itself in a separate operation method. Third, in order to improve the computational estimating ability of addition and subtraction, contents related to the computational estimation need to be included in the achievement criteria, and discussions on the expansion of the areas, and the diversification of the instructing time will be needed.

• Communications for Statistical Applications and Methods
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• v.25 no.4
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• pp.431-442
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• 2018

This paper highlights the computational explosion issues in the autoregressive moving average approach of frequency estimation of sinusoidal data with a large sample size. A new algorithm is proposed to circumvent the computational explosion difficulty in the conditional least-square estimation method. Notice that sinusoidal pattern can be generated by a non-invertible non-stationary autoregressive moving average (ARMA) model. The computational explosion is shown to be closely related to the non-invertibility of the equivalent ARMA model. Simulation studies illustrate the computational explosion phenomenon and show that the proposed algorithm can efficiently overcome computational explosion difficulty. Real data example of sunspot number is provided to illustrate the application of the proposed algorithm to the time series data exhibiting sinusoidal pattern.

• Journal of the Korean Statistical Society
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• v.10
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• pp.91-96
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• 1981

The development of Minimum Norm Quadratic Unbiased Estimation (MINQUE) has introduced a unified approach for the estimation of variance components in general linear models. The computational problem has been studied by Liu and Senturia (1977) and Goodnight (1978, setting a-priori values to 0). This paper further simplifies the computation and gives efficient and compact computational algorithm for the MINQUE and dispersion matrix in general linear random model.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1055-1062
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• 2022

In order to use the Massive MIMO (Multi Input Multi Output) technology using the massive array antenna, it is essential to know the angle of arrival (AOA) of the signal. When using a massive array antenna, the existing AOA estimation algorithm has excellent estimation performance, but also has a disadvantage in that computational complexity increases in proportion to the number of antenna elements. To solve this problem, a cascade AOA estimation algorithm has been proposed and the performance of a single-shaped (non)massive array antenna has been proven through a number of papers. However, the computational complexity of the cascade AOA estimation algorithm to which single and double rim array antennas are applied has not been compared. In this paper, we compare and analyze the computational complexity for AOA estimation when single and double rim array antennas are applied to the cascade AOA estimation algorithm.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.6
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• pp.382-387
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• 2014

A computational approach to depth estimations using a color over lapped integral imaging system is presented. The proposed imaging system acquires multiple color images simultaneously through a single lens with an array of multiple pinholes that are distributed around the optical axis. This paper proposes a computational model of the relationship between the real distance of an object and the disparity among different color images. The proposed model can serve as a computational basis of a single camera-based depth estimation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1109-1122
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• 1996

Generally, moving images contain the various components in motions, which reange from a static object and background to a fast moving object. To extract the accurate motion parameters, we must consider the various motions. That requires a wide search egion in motion estimation. The wide search, however, causes a high computational complexity. If we have a few knowledge about the motion direction and magnitude before motion estimation, we can determine the search location and search window size using the already-known information about the motion. In this paper, we present a local adaptive motion estimation approach that predicts a block motion based on spatio-temporal neighborhood blocks and adaptively defines the search location and search window size. This paper presents a technique for reducing computational complexity, while having high accuracy in motion estimation. The proposed algorithm is introduced the forward and backward projection techniques. The search windeo size for a block is adaptively determined by previous motion vectors and prediction errors. Simulations show significant improvements in the qualities of the motion compensated images and in the reduction of the computational complexity.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.976-983
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• 2002

We presents a modified variable dimension filter with input estimation for maneuvering target tracking. The conventional variable dimension filter with input estimation(VDIE) consists of the input estimation(IE) technique and the variable dimension(VD) filter. In the VDIE, the IE technique is used for estimation of a maneuver onset time and its magnitude in the least square sense. The detection of the maneuver is declared according to the estimated magnitude of the maneuver. The VD filter structure is applied for the adaptation to the maneuver of the target after compensating the filter parameter with respect to the estimated maneuver when the detection of the maneuver is declared. The VDIE is known as one of the best maneuvering target tracking filter based on a single filter. However, it requires too much computational burden since the IE technique is performed at every sampling instance and thus it is computationally inefficient. We propose another variable dimension filter with input estimation named 'Modified VDIE' which combines VD filter with If technique. Modified VDIE has less computational load than the original one by separating maneuver detection and input estimation. Simulation results show that the proposed VDIE is more efficient and outperforms in terms of computational load.