• Journal of Institute of Control, Robotics and Systems
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• v.6 no.11
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• pp.968-973
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• 2000

Fault diagnosis plays an important role in the performance and safe operation of many modern engineering plants. This paper investigates the problem of fault detection using neural networks in dynamic systems. A general framework for constructing a nonlinear fault detection scheme for nonlinear dynamic systems containing modeling uncertaintly is proposed. The main idea behind the proposed approach is to monitor the physical system with an off -line learning neural network and then to approximate the upper and lower thresholds of acceleration of the nominal system with the model-based threshold(ThMB) method, The performance of the proposed fault detection scheme is investigated through simulations of a pendulum with uncertainty.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.229-232
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• 2009

Shot change detection is an important technique for effective management of video data, so detection scheme requires adaptive detection techniques to be used actually in various video. In this paper, we propose an adaptive shot change detection algorithm using the mean of feature value on variable reference blocks. Our algorithm determines shot change detection by defining adaptive threshold values with the feature value extracted from video frames and comparing the feature value and the threshold value. We obtained better detection ratio than the conventional methods maximally by 15% in the experiment with the same test sequence. We also had good detection ratio for other several methods of feature extraction and could see real-time operation of shot change detection in the hardware platform with low performance was possible by implementing it in TVUS model of HOMECAST Company. Thus, our algorithm in the paper can be useful in PMP or other portable players.

• International Journal of Automotive Technology
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• v.8 no.1
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• pp.33-38
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• 2007

Since it is difficult to analytically express the Melnikov function when a dynamic system possesses multiple saddle fixed points with homoclinic and/or heteroclinic orbits, this paper investigates a vehicle model with nonlinear suspension spring and hysteretic damping element, which exhibits multiple heteroclinic orbits in the unperturbed system. First, an algorithm for Melnikov integrals is developed based on the Melnikov method. And then the amplitude threshold of road excitation at the onset of chaos is determined. By numerical simulation, the existence of chaos in the present system is verified via time history curves, phase portrait plots and $Poincar{\acute{e}}$ maps. Finally, in order to further identify the chaotic motion of the nonlinear system, the maximal Lyapunov exponent is also adopted. The results indicate that the numerical method of estimating chaotic threshold is an effective one to complicated vehicle systems.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.8
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• pp.72-79
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• 1994

In this paper semi empirical models are presented for the hot electron induced threshold voltage shift(${\Delta}V_{t}$) and effective channel shortening length (${\Delta}L_{H}$) in degraded PMOSFET. Trapped electron charges in gate oxide are calculated from the well known gate current model and ΔLS1HT is calculated by using trapped electron charges. (${\Delta}L_{H}$) is a function of gate stress voltage such as threshold voltage shift and degradation of drain current. From the correlation between (${\Delta}L_{H}$) has a logarithmic function of stress time. From the measured results, (${\Delta}V_{t}$) and (${\Delta}L_{H}$) are function of initial gate current and device channel length.

• Journal of information and communication convergence engineering
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• v.13 no.2
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• pp.113-122
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• 2015

Feature subset selection is as a pre-processing step in learning algorithms. In this paper, we propose an efficient algorithm, ModifiedFAST, for feature subset selection. This algorithm is suitable for text datasets, and uses the concept of information gain to remove irrelevant and redundant features. A new optimal value of the threshold for symmetric uncertainty, used to identify relevant features, is found. The thresholds used by previous feature selection algorithms such as FAST, Relief, and CFS were not optimal. It has been proven that the threshold value greatly affects the percentage of selected features and the classification accuracy. A new performance unified metric that combines accuracy and the number of features selected has been proposed and applied in the proposed algorithm. It was experimentally shown that the percentage of selected features obtained by the proposed algorithm was lower than that obtained using existing algorithms in most of the datasets. The effectiveness of our algorithm on the optimal threshold was statistically validated with other algorithms.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.402-404
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• 2003

We present two methods for the automatic selection of the threshold values in unsupervised change detection. Both methods consist of the same two procedures: 1) to determine the parameters of Gaussian mixtures from a difference image or ratio image, 2) to determine threshold values using the Bayesian rule for minimum error. In the first method, the Expectation-Maximization algorithm is applied for estimating the parameters of the Gaussian mixtures. The second method is based on the iterative thresholding that successively employs thresholding and estimation of the model parameters. The effectiveness and applicability of the methods proposed here are illustrated by an experiment on the multi-temporal KOMPAT-1 EOC images.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.33-40
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• 2023

Machine-learning techniques are discovering effective performance on data analytics. Classification and regression are supported for prediction on different kinds of data. There are various breeds of classification techniques are using based on nature of data. Threshold determination is essential to making better model for unlabelled data. In this paper, threshold value applied as range, based on min-max normalization technique for creating labels and multiclass classification performed on rainfall data. Binary classification is applied on autism data and classification techniques applied on child abuse data. Performance of each technique analysed with the evaluation metrics.

• Journal of Oral Medicine and Pain
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• v.41 no.3
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• pp.85-90
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• 2016

Purpose: The aim of this study was to develop an automated software to extract tooth and pulpal area from sectional cone-beam computed tomography (CBCT) images, which can guarantee more reproducible, objective and time-saving way to measure pulp/tooth volume ratio. Methods: The software program was developed using MATLAB (MathWorks). To determine the optimal threshold for the region of interest (ROI) extraction, user interface to adjust the threshold for extraction algorithm was added. Default threshold was determined after several trials to make the outline of extracted ROI fitting to the tooth and pulpal outlines. To test the effect of starting point location selected initially in the pulpal area on the final result, pulp/tooth volume ratio was calculated 5 times with different 5 starting points. Results: Navigation interface is composed of image loading, zoom-in, zoom-out, and move tool. ROI extraction process can be shown by check in the option box. Default threshold is adjusted for the extracted tooth area to cover whole tooth including dentin, cementum, and enamel. Of course, the result can be corrected, if necessary, by the examiner as well as by changing the threshold of density of hard tissue. Extracted tooth and pulp area are reconstructed three-dimensional (3D) and pulp/tooth volume ratio is calculated by voxel counting on reconstructed model. The difference between the pulp/tooth volume ratio results from the 5 different extraction starting points was not significant. Conclusions: In further studies based on a large-scale sample, the most proper threshold to present the most significant relationship between age and pulp/tooth volume ratio and the tooth correlated with age the most will be explored. If the software can be improved to use whole CBCT data set rather than just sectional images and to detect pulp canal in the original 3D images generated by CBCT software itself, it will be more promising in practical uses.

• Journal of Korea Water Resources Association
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• v.46 no.3
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• pp.287-299
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• 2013

The objective of this study is to derive and evaluate the drought threshold level based on hydro-meteorological data using historical drought events. After collecting the drought events during 1991 to 2009 year, the observed meteorological data and estimated hydrological component from LSM are used as input for the percentile analysis that is drought analysis data. The drought threshold level that precipitation and runoff of 3 month duration are less than 35%, soil moisture of 2 month duration is less than 35% and evapotranspiration of 3 month duration is more than 65% is derived using ROC analysis that are objective test method. ROC analysis with SPI (3) is performed to evaluate the applicability of threshold level in the domestic. As a result, it can be concluded that the derived drought threshold level show better performance to reflect the historical drought events than SPI (3) and it reasonably explain the spatial drought situation through the spatial analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.2
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• pp.330-336
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• 2007

A single pixel photon counting type image sensor which is applicable for medical diagnosis with digitally obtained image and industrial purpose has tern designed with $0.18{\mu}m$ triple-well CMOS process. The designed single pixel for readout chip is able to be operated by single supply voltage to simplify digital X-ray image sensor module and a preamplifier which is consist of folded cascode CMOS operational amplifier has been designed to enlarge signal voltage(${\Delta}Vs$), the output voltage of preamplifier. And an externally tunable threshold voltage generator circuit which generates threshold voltage in the readout chip has been newly proposed against the conventional external threshold voltage supply. In addition, A dark current compensation circuit for reducing dark current noise from photo diode is proposed and 15bit LFSR(Linear Feedback Shift Resister) Counter which is able to have high counting frequency and small layout area is designed.