• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.54-58
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• 2023

In this study, we compared the detection accuracy of the parameters of the scaffold failure detection model. A detection algorithm based on convolutional neural network was used to construct a failure detection model for scaffold. The parameter properties of the model were changed and the results were quantitatively verified. The detection accuracy of the model for each parameter was compared and the parameter with the highest accuracy was identified. We found that the activation function has a significant impact on the detection accuracy, which is 98% for softmax.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.549-551
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• 1999

Recently, Several type of motors are used more widely in Fan system because of their low cost and high reliability. Therefore, the importance of fault detection and isolation of fan system significantly increases. The motor is a important factor bring out the fan system fault. So the problem of a fault detection for motor based on a parameter identification will be considered in this paper. After an introduction into fault detection with parameter estimation, a mathematical model for motor with special emphasis on motor itself. In the fault detection system, current and motor speed are used as parameter. Finally, simulation results are used to demonstrate the efficiency of the fault detection system.

• Speech Sciences
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• v.10 no.1
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• pp.95-105
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• 2003

This paper describes a new parameter for voice activity detection which serves as a front-end part for automatic speech recognition systems. The new parameter called run-ratio is derived from the runs test statistic which is used in the statistical test for randomness of a given sequence. The run-ratio parameter has the property that the values of the parameter for the random sequence are about 1. To apply the run-ratio parameter into the voice activity detection method, it is assumed that the samples of an inputted audio signal should be converted to binary sequences of positive and negative values. Then, the silence region in the audio signal can be regarded as random sequences so that their values of the run-ratio would be about 1. The run-ratio for the voiced region has far lower values than 1 and for fricative sounds higher values than 1. Therefore, the parameter can discriminate speech signals from the background sounds by using the newly derived run-ratio parameter. The proposed voice activity detector outperformed the conventional energy-based detector in the sense of error mean and variance, small deviation from true speech boundaries, and low chance of missing real utterances

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.378-383
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• 2020

Viola & Jones' object detection algorithm is a very good algorithm for the face component(FC) detection, but there are still problems such as duplicate detection, false detection and non-detection due to parameter setting. This paper proposes an improved FC detection algorithm that applies the variable parameter to reduce non-detection and the verification to reduce duplicate detection and false detection to the Viola & Jones' algorithm. The proposed algorithm reduces the non-detection by changing the parameter value of the Viola & Jones' algorithm until the potential valid FCs are detected, and eliminates the duplicate detection and the false detection by using the verification that evaluates size, position, and uniqueness of the detected FCs. Simulation results show that the proposed algorithm includes valid FCs in the detected objects and then detects only the valid FCs by removing invalid FCs from them.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.1
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• pp.22-30
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• 2011

Plane detection is very important information for mission-critical of robot in 3D environment. A representative method of plane detection is Hough-transformation. Hough-transformation is robust to noise and makes the accurate plane detection possible. But it demands excessive memory and takes too much processing time. Iterative randomized Hough-transformation has been proposed to overcome these shortcomings. This method doesn't vote all data. It votes only one value of the randomly selected data into the Hough parameter space. This value calculated the value of the parameter of the shape that we want to extract. In Hough parameters space, it is possible to detect accurate plane through detection of repetitive maximum value. A common problem in these methods is that it requires too much computational cost and large number of memory space to find the distribution of mixed multiple planes in parameter space. In this paper, we detect multiple planes only via data sampling using Self Organizing Map method. It does not use conventional methods that include transforming to Hough parameter space, voting and repetitive plane extraction. And it improves the reliability of plane detection through division area searching and planarity evaluation. The proposed method is more accurate and faster than the conventional methods which is demonstrated the experiments in various conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1927-1943
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• 2016

Jitterbug is a passive network covert timing channel supplying reliable stealthy transmission. It is also the basic manner of some improved covert timing channels designed for higher undetectability. The existing entropy-based detection scheme based on training sample binning may suffer from model mismatching, which results in detection performance deterioration. In this paper, a new detection method based on the feature of Jitterbug covert channel traffic is proposed. A fixed binning strategy without training samples is used to obtain bins distribution feature. Coefficient of variation (CV) is calculated for several sets of selected bins and the weighted mean is used to calculate the final CV value to distinguish Jitterbug from normal traffic. Furthermore, the timing window parameter of Jitterbug is estimated based on the detected traffic. Experimental results show that the proposed detection method can achieve high detection performance even with interference of network jitter, and the parameter estimation method can provide accurate values after accumulating plenty of detected samples.

• Journal of IKEEE
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• v.25 no.4
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• pp.689-696
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• 2021

In this paper, in order to apply Prognostics and Health Management(PHM) to an electronic system or circuit, a circuit capable of detecting and predicting defect characteristics inside the system or circuit is implemented, and the results are described. In the previous study, we demonstrated that the frequency of the amplitude of S-parameter changed as the circuit defect progressed. These characteristics were measured by network analyser. but in this study, even if the same defect detection method is used, a circuit is proposed to check the progress of the defect, the remaining time, and the occurrence of the defect without large measurement devices. The circuit is designed to detect the change in impedance that generates changes of S-parameter, and it is verified through simulation using the measurement results of Bond-wires.

• Journal of information and communication convergence engineering
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• v.1 no.4
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• pp.205-208
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• 2003

Voice activity detection is a important problem in the speech recognition and speech communication. This paper introduces new feature parameter which are reconstructed by spectral entropy of information theory for robust voice activity detection in the noise environment, then analyzes and compares it with energy method of voice activity detection and performance. In experiments, we confirmed that spectral entropy and its reconstructed parameter are superior than the energy method for robust voice activity detection in the various noise environment.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1432-1435
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• 1997

This paper proposes a fault detection and isolation metho by combining the parameter estimation method[4] with the observer method[2] to use merits of both methods. To verify the performance of the method proposed some simulations applied to remotely piloted vehicle are performed.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.748-750
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• 1995

An early detection of cancer is very important for the complete cure of cancer. Therefore, it is considered a diagnosis of cancer via the detection of an abrupt change from the healthy state to the cancerous state. It includes the development of algorithm for the detection of parameter change for conditionally-linear stochastic systems for the cancer diagnosis. The statistical testing is proposed to implement a parameter change algorithm. The detection algorithm studied in this research is based on sequential hypotheses testing in a so-called local asymptotic framework. Here a simple numerical example is provided to highlight some of the concepts and to provide a basis for further investigation. Despite its simplicity this research may have practical application in clinical oncology.