• Korean Journal of Food Science and Technology
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• v.35 no.2
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• pp.173-181
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• 2003

Physicochemical changes in corn starch caused by irradiation were investigated, and irradiated samples were identified. Viscosity, TBA value, Hunter color, and total viable count were measured after irradiation of corn starch. Corn starches from Korea and China were irradiated at 0, 2.5, 5, 7.5, 10, and 15 kGy using a $Co^{60}$ irradiator and stored for 9 months at $0^{\circ}C$ and $20^{\circ}C$. Viscosity and specific parameter values decreased in all samples with increasing irradiation dosage at 50 rpm, showing a dose-dependent relationship $(above\;R^2=0.80)$ between non-irradiated and irradiated samples during storage. These results suggest that detection of irradiated corn starches is possible using viscometric method during storage. Total viable count, TBA value, and Hunter color were determined as supplemental indices for measuring viscosities of samples. Total viable count and TBA values showed dose-dependent relationship $(2.5{\sim}15 kGy)$. Differences in viscosity and total viable count, and TBA values among non-irradiated samples showed little changes with the lapse of post-irradiation time, but were still distinguishable for more than 6 months at $0^{\circ}C$ and $20^{\circ}C$ for corn starches from korea and China.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.2
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• pp.177-182
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• 2003

In this study, we research the robust speech recognition for the syllables and phoneme units with the feature parameter including the voiced-unvoiced measures for the confusable words. In order to make it possible, we propose the measure representing the voiced-unvoiced degree by using the HPS(Harmonic Product Spectrum) information, used on pitch detection. We proposed this measures with the sharpnes, peak count and height measure of HPS. We reconstructed the feature parameter including this measures, then we performs the speech recognition experiments and compared with the typical feature parameters under the CVC type confusable syllables DB.

• Journal of the Korean Magnetics Society
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• v.5 no.1
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• pp.71-78
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• 1995

We introduced and compared the two methods, 'figure-8 coil method' and 's-parameter method', to measure high frequency permeability of magnetic films. We made a permeameter by using s-parameter method and discussed about problems and solutions in measuring permeability. We can measure the permeability rapidly and exactly up to 200 MHz with the aid of computer program and the low level permeance detection limit is about $1\mu\textrm{m}$.

• Journal of the Korea Society for Simulation
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• v.30 no.1
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• pp.21-29
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• 2021

This paper introduces experimental design and components model for analysing the impact of parameter(in the field of kinematics and sensor) on performance of hard-kill torpedo defence system. The simulation is implemented at the level of engagement and its scope is limited to final stage of engagement where main function of anti-torpedo system is operating. It improves the fidelity of physical realism by precise model of simulation components in the perspectives of kinematics, sensor capability and acoustic detection theory. This paper provides the experimentation methodology for evaluating parameter sensitivity which is required to analyze in advance of development the defense system with novel concepts. In addition, the experimental result shows the tendency of defense capability according to parameter adjustments.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.3
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• pp.99-112
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• 2015

Digital imaging technology has advanced beyond the limits of the multimedia industry IT convergence, and to develop a complex industry, particularly in the field of object recognition, face smart-phones associated with various Application technology are being actively researched. Recently, face recognition technology is evolving into an intelligent object recognition through image recognition technology, detection technology, the detection object recognition through image recognition processing techniques applied technology is applied to the IP camera through the 3D image object recognition technology Face Recognition been actively studied. In this paper, we first look at the essential human factor, technical factors and trends about the technology of the human object recognition based SPFACS(Smile Progress Facial Action Coding System)study measures the smile detection technology recognizes multi-faceted object recognition. Study Method: 1)Human cognitive skills necessary to analyze the 3D object imaging system was designed. 2)3D object recognition, face detection parameter identification and optimal measurement method using the AAM algorithm inside the proposals and 3)Face recognition objects (Face recognition Technology) to apply the result to the recognition of the person's teeth area detecting expression recognition demonstrated by the effect of extracting the feature points.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4419-4441
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• 2016

A cause of vehicle accidents is the reduced visibility due to bad weather conditions such as fog. Therefore, an onboard vision system should take visibility detection into account. In this paper, we propose a simple and effective approach for measuring the visibility distance using a single camera placed onboard a moving vehicle. The proposed algorithm is controlled by a few parameters and mainly includes camera parameter estimation, region of interest (ROI) estimation and visibility computation. Thanks to the ROI extraction, the position of the inflection point may be measured in practice. Thus, combined with the estimated camera parameters, the visibility distance of the input foggy image can be computed with a single camera and just the presence of road and sky in the scene. To assess the accuracy of the proposed approach, a reference target based visibility detection method is also introduced. The comparative study and quantitative evaluation show that the proposed method can obtain good visibility detection results with relatively fast speed.

• Journal of Korea Multimedia Society
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• v.22 no.12
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• pp.1447-1456
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• 2019

As artificial intelligence technology is actively used in image processing, it is possible to generate high-quality fake images based on deep learning. Fake images generated using GAN(Generative Adversarial Network), one of unsupervised learning algorithms, have reached levels that are hard to discriminate from the naked eye. Detecting these fake images is required as they can be abused for crimes such as illegal content production, identity fraud and defamation. In this paper, we develop a deep-learning model based on CNN(Convolutional Neural Network) for the detection of StyleGAN fake images. StyleGAN is one of GAN algorithms and has an excellent performance in generating face images. We experiment with 48 number of experimental scenarios developed by combining parameters of the proposed model. We train and test each scenario with 300,000 number of real and fake face images in order to present a model parameter that improves performance in the detection of fake faces.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.283-289
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• 2015

In this paper, a GNSS interference detection algorithm based on an adaptive fading Kalman filter is proposed to detect a spoofing signal which is one of the threatening GNSS intentional interferences. To detect and mitigate the spoofing signal, the fading factor of the filter is used as a detection parameter. For simulation, the effect of the spoofing signal is modeled by the ramp type bias error of the pseudorange to emulate a smart spoofer and the change of the fading factor value according to ramp type bias error is quantitatively analyzed. In addition, the detection threshold is established to detect the spoofing signal by analyzing the change of the error covariance and the effect of spoofing is mitigated by controlling the Kalman gain of the filter. To verify the performance analysis of the proposed algorithm, various simulations are implemented. Through the results of simulations, we confirmed that the proposed algorithm works well.

• Communications for Statistical Applications and Methods
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• v.18 no.2
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• pp.171-177
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• 2011

In order to construct approximation functions for real data, it is necessary to remove the outliers from the measured raw data before constructing the model. Conventionally, visualization and maximum residual error have been used for outlier detection, but they often fail to detect outliers for nonlinear functions with multidimensional input. Although the standard support vector regression based outlier detection methods for nonlinear function with multidimensional input have achieved good performance, they have practical issues in computational cost and parameter adjustments. In this paper we propose a practical approach to outlier detection using support vector regression that reduces computational time and defines outlier threshold suitably. We apply this approach to real data examples for validity.

• Journal of the Semiconductor & Display Technology
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• v.12 no.2
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• pp.67-72
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• 2013

Temperature is a critical parameter in yield improvement for wafer manufacturing. In chemical vapor deposition (CVD) equipment, crack defect in ceramic heater leads to yield reduction, however, there is no suitable ceramic heater fault detection system for conventional CVD equipment. This paper proposes a short-time zero-crossing rate based fault detection method for the ceramic heater in CVD equipment. The proposed method measures the output signal ($V_{pp}$) of RF filter and extracts the zero-crossing rate (ZCR) as feature vector. The extracted feature vectors have a discriminant power and Gaussian mixture model (GMM) based fault detection method can detect fault in ceramic heater. Experimental results, carried out by measured signals provided by a CVD equipment manufacturer, indicate that the proposed method detects effectively faults in various process conditions.