• Journal of Internet Computing and Services
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• v.11 no.4
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• pp.59-72
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• 2010

WIM(Weigh-In-Motion) is the system measuring the weight of the vehicle with a high-speed. In the existing WIM system, vehicle weight is measured based on the constant speed and the error ratio has 10%. However, because of measuring the driving pattern, that is abnormal driving pattern which is like the acceleration and down-shift of the drivers, it has the error ratio which is bigger than the real. In order to it reduces the error ratio of WIM system, the improved WIM system needs to find the abnormal driving pattern. In order to reducing the error ratio of these WIM systems, the improved WIM system can find abnormal driving patterns. In this paper, the improved WIM system which analyzes the abnormality driving pattern influencing on the error ratio of WIM system of an existing and minimizes the error span is designed. The improved WIM system has the multi step loop structure of adding the loop sensor to an existing system. In addition, the measure function defined as an intrinsic is improved and the weight measured by the abnormal driving pattern is amended. The analysis of experiment result improved WIM system can know the fact that the error span reduces by 8% less than in the existing the maximum average sampling error 22.98%.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.4
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• pp.365-375
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• 2014

This paper proposes an abnormal V-shaped-error-free non-blind deconvolution technique featuring an adaptively segmented forward-problem based iterative deconvolution (ASDCN) process. Unlike the algebraic based inverse operations, this eliminates any operations of differential and division by zero to successfully circumvent the issue on the abnormal V-shaped error. This effectiveness has been demonstrated for the first time with applying to a real analysis for the effects of the Random Telegraph Noise (RTN) and/or Random Dopant Fluctuation (RDF) on the overall SRAM margin variations. It has been shown that the proposed ASDCN technique can reduce its relative errors of RTN deconvolution by $10^{13}$ to $10^{15}$ fold, which are good enough for avoiding the abnormal ringing errors in the RTN deconvolution process. This enables to suppress the cdf error of the convolution of the RTN with the RDF (i.e., fail-bit-count error) to $1/10^{10}$ error for the conventional algorithm.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.6
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• pp.582-590
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• 2020

This paper presents the results of new error analysis on the veering of marine target with the concept of frequency of occurrence, and shows how to apply the midcourse guidance errors of anti-ship missile. The veering error would be a dominant factor in the midcourse guidance errors with flight time increase. This study suggests the reasonable application method of the veering error based on the characteristics of abnormal error, and describes the tailoring method including trade-off between the midcourse guidance range of veering target and the value of frequency of occurrence on veering error.

• Elastomers and Composites
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• v.51 no.3
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• pp.206-211
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• 2016

Experimental error sources for thermogravimetric analysis (TGA) of poly(ethylene-co-vinyl acetate) (EVA) were investigated and sample preparation method to reduce the experimental error was suggested. Maximum dissociation temperatures of EVA for the first and second dissociation reactions ($T_{m1}$ and $T_{m2}$, respectively) were measured. By decreasing the weight of raw EVA, the $T_{m1}$ increased but the the $T_{m2}$ decreased. When weight of the raw EVA was over 10 mg, the TGA curve showed abnormal behaviors. The abnormal TG behaviors were explained by gathering and instantaneous evaporation of acetic acid formed by deacetylation of the VA unit. When TGA analysis of EVA was performed using untreated (raw) EVA, the experimental errors were about 1%. In order to eliminate the abnormal TG behaviors and to reduce the experimental errors, EVA film made by solvent casting was used. For the treated EVA (EVA film), the abnormal TG behaviors did not appear, the $T_{m1}$ decreased by about $2^{\circ}C$ but the $T_{m2}$ increased by about $6^{\circ}C$, and the experimental errors were reduced by 0.5%.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.1
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• pp.37-42
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• 2011

An extended scalar adaptive filter for guided missiles using a global positioning system receiver is presented. A conventional scalar adaptive filter is adequate filter for eliminating sudden abnormal jumping measurements. However, if missile or vehicle velocities have variation, the conventional filter cannot eliminate abnormal measurements. The proposed filter utilizes an acceleration term, which is an improvement not used in previous conventional scalar adaptive filters. The proposed filter continuously estimates noise measurement variance, velocity error variance and acceleration error variance. For estimating the three variances, an innovation method was used in combination with the least square method for the three variances. Results from the simulations indicated that the proposed filter exhibited better position accuracy than the conventional scalar adaptive filter.

• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.75-86
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• 2019

Purpose: It is essential for the steel industry to produce steel products without unexpected downtime to reduce costs and produce high quality products. A hot strip rolling mill consists of many mechanical and electrical units. In condition monitoring and diagnosis, various units could fail for unknown reasons. Methods: In this study, we propose an effective method to detect units with abnormal status early to minimize system downtime. The early warning problem with various units was first defined. An autoencoder was modeled to detect abnormal states. An application of the proposed method was also implemented in a simulated field-data analysis. Results: We can compare images of original data and reconstructed images, as well as visually identify differences between original and reconstruction images. We confirmed that normal and abnormal states can be distinguished by reconstruction error of autoencoder. Experimental results show the possibility of prediction due to the increase of reconstruction error from just before equipment failure. Conclusion: In this paper, hot strip roughing mill monitoring method using autoencoder is proposed and experiments are performed to study the benefit of the autoencoder.

• Journal of the Korean Institute of Gas
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• v.25 no.5
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• pp.63-69
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• 2021

In this study, we established an algorithm to determine whether the work in the gas facility is a normal work or an abnormal work using the threshold of the reconstruction error of the autoencoder. This algorithm do deep learning the autoencoder only with time-series data of a normal work, and derives the optimized threshold of the reconstruction error of the normal work. We applied this algorithm to the time series data of the new work to get the reconstruction error, and then compare it with the reconstruction error threshold of the normal work to determine whether the work is normal work or abnormal work. In order to train and validate this algorithm, we defined the work in a virtual gas facility, and constructed the training data set consisting only of normal work data and the validation data set including both normal work and abnormal work data.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.377-384
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• 2023

The existence of abnormal breakpoint data leads to poor channel balance in wireless sensor networks (WSN). To enhance the communication quality of WSNs, a method for positioning abnormal breakpoint data in WSNs on the basis of signal reconstruction is studied. The WSN signal is collected using compressed sensing theory; the common part of the associated data set is mined by exchanging common information among the cluster head nodes, and the independent parts are updated within each cluster head node. To solve the non-convergence problem in the distributed computing, the approximate term is introduced into the optimization objective function to make the sub-optimization problem strictly convex. And the decompressed sensing signal reconstruction problem is addressed by the alternating direction multiplier method to realize the distributed signal reconstruction of WSNs. Based on the reconstructed WSN signal, the abnormal breakpoint data is located according to the characteristic information of the cross-power spectrum. The proposed method can accurately acquire and reconstruct the signal, reduce the bit error rate during signal transmission, and enhance the communication quality of the experimental object.

• Journal of Advanced Navigation Technology
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• v.14 no.5
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• pp.610-617
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• 2010

This paper analyzes the characteristics of abnormal broadcast GPS ephemeris by comparing distances between the receiver and the satellites. Effects of abnormal ephemeris on receiver's position estimate are closely related with range errors caused by variations of satellite positions. In more detail each range error depends on the satellite position error and the line of sight vector. Based on the fact, the ephemeris parameters are classified into three types depending on the size, the shape, and the shape of the satellite orbit to analyze the fault characteristics. The effects of satellite position errors caused by the three type s of parameters on the receiver's position estimate are analyze d in detail.

• Journal of Korean Society for Quality Management
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• v.30 no.2
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• pp.130-151
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• 2002

This paper investigates the relation between the Process capability index(PCI) and the quality assurance level under various conditions. The effect of the off-targetness of the process mean, deviation from the nomality, the estimation error, and tile measurement error on the quality assurance level is evaluated. Various distributions such as the Student-t, the chi-square, the gamma, the Weibull, and the log-normal distributions are considered to evaluate the deviation from the nomality. The quality levels under abnormal conditions turn out to be severely different from that under the standard condition. We provide tables and graphs of the quality assurance level on various abnormal conditions. In order for the industry users to use the PCI properly, they should refer to the tables and graphs, especially when they are not certain about the standard assumptions on which the PCI depends.