• Journal of applied mathematics & informatics
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• v.32 no.1_2
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• pp.211-225
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• 2014

A new class of smoothing functions is introduced in this paper, which includes some important smoothing complementarity functions as its special cases. Based on this new smoothing function, we proposed a smoothing Newton method. Our algorithm needs only to solve one linear system of equations. Without requiring the nonemptyness and boundedness of the solution set, the proposed algorithm is proved to be globally convergent. Numerical results indicate that the smoothing Newton method based on the new proposed class of smoothing functions with ${\theta}{\in}(0,1)$ seems to have better numerical performance than those based on some other important smoothing functions, which also demonstrate that our algorithm is promising.

• International Journal of Contents
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• v.5 no.4
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• pp.1-6
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• 2009

In this paper, we propose a mesh smoothing method for mesh models with noise. The proposed method enables not only the removal of noise from the vertexes but the preservation and smoothing of shape recognized as edges and comers. The magnitude ratio of 2D area and 3D volume in mesh data is adopted for the smoothing of noise. Comparing with previous smoothing methods, this method does not need many iteration of the smoothing process and could preserve the shape of original model. Experimental results demonstrate improved performance of the proposed approach in 3D mesh smoothing.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.1015-1023
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• 2001

error behaviour can be considered as a linear combination of low amplitude random noise and abrupt jumps. The reason of jump appearance can be explained by the semi-shading effects(buildings, trees), jamming, high dynamic of vehicle and so on. This study describes the stand-alone GPS error jump smoothing algorithm which is developed based on the scalar adaptive filter. The algorithm consists of the coarse jump smoothing and the fine jump smoothing. On the coarse smoothing step, GPS velocities or position differences are used as the measurement for the scalar adaptive filter. The purpose of adaptive filter is to smooth the jump errors. The coarse positions are detennined by the integration of smoothed velocities. On the fine smoothing step, the differences between GPS positions and the coarse positions are smoothed by another scalar adaptive filter. The reason of fine smoothing is based on the facts that smoothing accuracy depends on the variance ofusefuJ signa\. The coarse smoothing which deal with the difference of positions provides the rough error removing. So the coarse smoothed velocities can have much more low amplitude than the raw ones. The fine smoothing procedure provides high quality of filtering process. Simulation results show the efficiency of proposed scheme.

• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.277-285
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• 1998

The smoothing parameter $\lambda$ in smoothing spline regression is usually selected by minimizing cross-validation (CV) or generalized cross-validation (GCV). But, simple CV or GCV is poor candidate for estimating prediction error. We defined MGCV (Multifold Generalized Cross-validation) as a criterion for selecting smoothing parameter in smoothing spline regression. This is a version of cross-validation using $leave-\kappa-out$ method. Some numerical results comparing MGCV and GCV are done.

• Journal for History of Mathematics
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• v.17 no.2
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• pp.15-20
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• 2004

We investigate the unbiasedness and consistency as the statistical properties of density estimators. We show histogram, kernel density estimation, and local adaptive smoothing as density smoothing in this paper. Also, the early and recent research on nonparametric density estimation is described and discussed.

• The KIPS Transactions:PartB
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• v.11B no.2
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• pp.241-246
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• 2004

In this paper, we propose VCCV units as a processing unit of language model and compare them with clauses and morphemes of existing processing units. Clauses and morphemes have many vocabulary and high perplexity. But VCCV units have low perplexity because of the small lexicon and the limited vocabulary. The construction of language models needs an issue of the smoothing. The smoothing technique used to better estimate probabilities when there is an insufficient data to estimate probabilities accurately. This paper made a language model of morphemes, clauses and VCCV units and calculated their perplexity. The perplexity of VCCV units is lower than morphemes and clauses units. We constructed the N-grams of VCCV units with low perplexity and tested the language model using Katz, absolute, modified Kneser-Ney smoothing and so on. In the experiment results, the modified Kneser-Ney smoothing is tested proper smoothing technique for VCCV units.

• International Area Studies Review
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• v.15 no.3
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• pp.191-213
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• 2011

This study empirically examines whether income smoothing effectively contributes to consumption smoothing. Since international factor movement plays an important role for income smoothing across countries, net factor income across countries deserves more attention in considering income smoothing than attention having been paid by previous studies in the literature. Most of previous studies assume that net factor income has the same degree of effects on consumption as GDP. For the case of 12 EU countries during the period from 1999 to 2010, our empirical investigation observes that the response of consumption with respect to net factor income is severely lower than the response of consumption with respect to GDP, and further net factor income has ignorable effects on the consumption. This evidence implies that the income smoothing via international factor movement is less significant in contributing to the consumption smoothing. In the sequel, our finding suggests that legal and institutional process for transferring net factor income across countries should be eased further to improve contribution of income smoothing to consumption smoothing.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.821-832
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• 2021

Earnings management is very important for companies that aim for decision-making. The research was conducted to analyze the quality of earnings and income smoothing motives in manufacturing companies in Indonesia. The research approach is carried out with a quantitative approach. The sampling method using purposive sampling was associated with several criteria so that a sample of 130 was determined, which was analyzed during the 4 years of the study. The partial least square method was used for data analysis. The results of the study state that institutional ownership has no effect on earnings quality, institutional ownership has a negative effect on income smoothing, leverage has a negative effect on income smoothing, independent commissioners have a positive effect on earnings quality as well as independent commissioners have a positive effect on income smoothing. We assume that the tendency of income smoothing can affect the quality of efficient earnings. Meanwhile, income smoothing affects the quality of company earnings. Management that performs income smoothing is more aimed at conveying the company's prospects for generating profits rather than opportunistic motives.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.481-487
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• 2013

This paper presents an FIR (Finite Impulse Response) fixed-interval smoothing filter for fast and exact estimating state variables of a discrete nonlinear system with modeling uncertainty. Conventional IIR (Infinite Impulse Response) filter and smoothing filter can estimate state variables of a system with an exact model when the system is observable. When there is an uncertainty in the system model, however, conventional IIR filter and smoothing filter may cause large errors because the filters cannot estimate the state variables corresponding to the uncertain model exactly. To solve this problem, FIR filters that have fast estimation properties and have robustness to the modeling uncertainty have been developed. However, there is time-delay estimation phenomenon in the FIR filter. The FIR smoothing filter proposed in this paper makes up for the drawbacks of the IIR filter, IIR smoothing filter, and FIR filter. Therefore, the FIR smoothing filter has good estimation performance irrespective of modeling uncertainty. The proposed FIR smoothing filter is applied to the integrated navigation system composed of a magnetic compass based DR (Dead Reckoning) and a GPS (Global Positioning System) receiver. Even when the magnetic compass error that changes largely as the surrounding magnetic field is modeled as a random constant, it is shown that the FIR smoothing filter can estimate the varying magnetic compass error fast and exactly with simulation results.

• Journal of the Korean Geographical Society
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• v.49 no.3
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• pp.339-356
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• 2014

Easy access to DEMs and the development of technology treating DEMs make it easier to extract stream longitudinal profiles from DEMs than previously done. Since such profiles possess many problems such as artificial flats and steps, it should be required for them to be smoothed like natural profiles to estimate gradient values along those sections. However smoothing itself comes with much distortion of raw profile from original DEMs. There has been no research evaluating quantitatively the effects due to smoothing process. Here we attempt to quantify the effects of major smoothing methods on raw and real profiles, suggest a new method to overcome the limitations of them, and evaluate it. This study not only suggests a new smoothing method, but also provides a guideline for choosing a proper smoothing method.