• Journal of applied mathematics & informatics
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• v.17 no.1_2_3
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• pp.615-622
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• 2005

In this paper, we discuss the average case errors of some numerical quadratures, namely Trapezoidal and Simpson's, in the numerical integration problem. Our integrands are r-fold Wiener functions from the interval [0,1] and only at finite number of points the function values are evaluated. We study average case errors of these quadratures theoretically and then compare it with our practical (a posteriori) researches. Monte-Carlo simulation is used to perform these empirical researches. Finally we empirically compute the error bounds of studied quadratures for the higher degrees of Wiener functions.

• Journal of Animal Environmental Science
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• v.17 no.2
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• pp.93-100
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• 2011

This study was conducted to verify the applicability of robot milking system through acquisition and analysis of model teat's position information using scanning range finder (SRF). Model teats, same size and shape as real teats, were designed to analyze the properties according to the material, distance error and angle error of the sensor. In addition, 2-dimensional distance information of each teats was obtained at same time with 4 teat models and the result were as follows. 1. In the case of the fingers on the experiment for selection of materials for teat model, the distance error was from 4.3 mm to 1.3 mm, average was 2.8 mm as a minimum record. In the case of rubber material, average distance error was 4.3 mm. So, this material was considered to be a most suitable model. 2. The distance error was maximum at 100 mm distance. The more distance increased, the less error increased up to 300 mm. Then the error increased after 300 mm and decreased again. 3. The maximum angle error of 10.1 mm was measured at $170^{\circ}$, in case of $70^{\circ}$ the error was 0.2 mm as a minimum value. There was no specific tendency to error of angle. 4. In the 2-dimensional location error for 4 teat models, distance error was 3.8 mm as minimum and 7.2 mm as maximum. The angle error was $1.2^{\circ}$ as maximum. All of errors were included within the accuracy of sensor, the robot milking system was considered to be applicable to measure the distance of teats due to the measuring velocity of SRF and the hole size of teat-cup.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.30-31
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• 2021

This study aims to build a deep learning model that can predict the value of concrete mixing properties according to a given concrete strength value. A model was created for a total of 1,291 concrete data, including 8 characteristics related to concrete mixing elements and environment, and the compressive strength of concrete. As the deep learning model, DNN-3L-256N, which showed the best performance on the prior study, was used. The average value for each characteristic of the data set was used as the initial input value. In results, in the case of 'curing temperature', which had a narrow range of values in the existing data set, showed the lowest error rate with less than 1% error based on MAE. The highest error rate with an error of 12 to 14% for fly and bfs.

• Journal of the Korean Data and Information Science Society
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• v.9 no.1
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• pp.77-88
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• 1998

Smoothing spline estimators are modified to remove boundary bias effects using the technique proposed in Eubank and Speckman (1991). An O(n) algorithm is developed for the computation of the resulting estimator as well as associated generalized cross-validation criteria, etc. The asymptotic properties of the estimator are studied for the case of a linear smoothing spline and the upper bound for the average mean squared error of the estimator given in Eubank and Speckman (1991) is shown to be asymptotically sharp in this case.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1416-1426
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• 2021

In the case of a scanning type multi-channel LiDAR sensor, the distance error called a walk error may occur due to a difference in received signal power. This work error causes different distance values to be output for the same object when scanning the surrounding environment based on multiple LiDAR sensors. For minimizing walk error in overlapping regions when scanning all directions using multiple sensors, to calibrate distance for each channels using convolution on external system. Four sensors were placed in the center of 6×6 m environment and scanned around. As a result of applying the proposed filtering method, the distance error could be improved by about 68% from average of 0.5125 m to 0.16 m, and the standard deviation could be improved by about 48% from average of 0.0591 to 0.030675.

• Journal of Communications and Networks
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• v.18 no.2
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• pp.182-189
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• 2016

The focus in this paper is on obtaining tight, simple algebraic-form bounds and invertible expressions for the average symbol error probability (ASEP) of M-ary phase shift keying (MPSK) in a class of composite fading channels. We employ the mixture gamma (MG) distribution to approximate the signal-to-noise ratio (SNR) distributions of fading models, which include Nakagami-m, Generalized-K ($K_G$), and Nakagami-lognormal fading as specific examples. Our approach involves using the tight upper and lower bounds that we recently derived on the Gaussian Q-function, which can easily be averaged over the general MG distribution. First, algebraic-form upper bounds are derived on the ASEP of MPSK for M > 2, based on the union upper bound on the symbol error probability (SEP) of MPSK in additive white Gaussian noise (AWGN) given by a single Gaussian Q-function. By comparison with the exact ASEP results obtained by numerical integration, we show that these upper bounds are extremely tight for all SNR values of practical interest. These bounds can be employed as accurate approximations that are invertible for high SNR. For the special case of binary phase shift keying (BPSK) (M = 2), where the exact SEP in the AWGN channel is given as one Gaussian Q-function, upper and lower bounds on the exact ASEP are obtained. The bounds can be made arbitrarily tight by adjusting the parameters in our Gaussian bounds. The average of the upper and lower bounds gives a very accurate approximation of the exact ASEP. Moreover, the arbitrarily accurate approximations for all three of the fading models we consider become invertible for reasonably high SNR.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.280-286
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• 2022

In order to efficiently collect data, it is essential to locate the facilities and analyze the movement data. The current technology for location collection can collect data using a GPS sensor, but GPS has a strong straightness and low diffraction and reflectance, making it difficult for indoor positioning. In the case of indoor positioning, the location is determined by using wireless network technologies such as Wifi, but there is a problem with low accuracy as the error range reaches 20 to 30 m. In this paper, using BLE 4.2 built in Raspberry Pi, we implement Bluetooth Smart Ready. In detail, a beacon was produced for Advertise, and an experiment was conducted to support the serial port for data transmission/reception. In addition, advertise mode and connection mode were implemented at the same time, and a 3-count gradual algorithm and a quadrangular positioning algorithm were implemented for Bluetooth RSSI error correction. As a result of the experiment, the average error was improved compared to the first correction, and the error rate was also improved compared to before the correction, confirming that the error rate for position measurement was significantly improved.

• Journal of the Korea Society of Computer and Information
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• v.18 no.3
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• pp.91-96
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• 2013

Because the r-fold Wiener process is truly infinitely dimensional and a computer can only handle finitely dimensional subspaces, we study in this paper the basic properties of the m-dimensional approximation function of the r-fold Wiener process.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.2
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• pp.1-11
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• 2021

Salt and pepper is a type of impulse noise. It may appear due to an error in the image transmission process and image storage memory. This noise changes the pixel value at any position in the image to 0 (in case of pepper noise) or 255 (in case of salt noise). In this paper, we present an algorithm for SAP noise reduction. The proposed method consists of three steps. In the first step, the location of the SAP noise is detected, and in the second step, the pixel value of the detected location is restored using a weighted average of the surrounding pixel values. In the last step, a reliability matrix around the reconstructed pixels is constructed, and additional correction is performed with a weighted average using this. As a result of the experiment, the proposed method appears to have similar or higher objective and subjective image quality than previous methods for almost all SAP noise ratios.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.5
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• pp.235-242
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• 2020

This paper analyzes the effect of reduced output width of the truncated logarithmic multiplication and application to inferences using convolutional neural networks (CNNs). For small hardware overhead, output width is reduced in the truncated Mitchell multiplier, so that fractional bits in multiplication output are minimized in error-resilient applications. This analysis shows that when reducing output width in the truncated Mitchell multiplier, even though worst-case relative error increases, average relative error can be kept small. When adopting 8 fractional bits in multiplication output in the evaluations, there is no significant performance degradation in target CNNs compared to existing exact and original Mitchell multipliers.