• Journal of Institute of Control, Robotics and Systems
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• v.17 no.1
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• pp.72-77
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• 2011

The checkpointing scheme is a well-known technique to cope with transient faults in digital systems. This paper proposes an adaptive checkpointing scheme for the reliability improvement of real-time control systems with concurrent fault detection capability. With concurrent fault detection capability the effect of transient faults are assumed to be detected with no latency. The proposed adaptive checkpointing scheme is based on the reliability analysis of an equidistant checkpointing scheme. Numerical data show the proposed adaptive scheme outperforms the equidistant scheme from a reliability point of view.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.2
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• pp.73-77
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• 2012

This paper reports a combined depth- and model-based face detection and tracking approach. The proposed algorithm consists of four functional modules; i) color-based candidate region extraction, ii) generation of the depth histogram for handling occlusion, iii) rotation-invariant face region detection using ellipse fitting, and iv) face tracking based on motion prediction. This technique solved the occlusion problem under complicated environment by detecting the face candidate region based on the depth-based histogram and skin colors. The angle of rotation was estimated by the ellipse fitting method in the detected candidate regions. The face region was finally determined by inversely rotating the candidate regions by the estimated angle using Haar-like features that were robustly trained robustly by the frontal face.

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2003.10a
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• pp.135.1-135
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• 2003

A technique for detection of Xanthomonas axonopodis pv. citri, a causal bacterium of canker on Unshiu orange fruits, was developed using bacteriophage. Procedure for the detection was designed on the basis of the previous reports that one group(CPI) of X. axonopodis pv. citri bacteriophage and corresponding two Iysotypes distributed in Korea. First, fruit surface was washed with sterile distilled water and pellet was obtained from centrifugation. The pellet was resuspended in Wakimoto's potato semi-synthetic broth medium and divided equally into two parts. One part was heated in boiling water to kill bacterial cells. Bacteriophages(CP$_1$) were respectively added into two parts and 0.1 ml from each part was mixed with soft agar medium. After incubation for 18 hrs at 25$^{\circ}C$, the causal bacterium of canker was determined based on plaques formed on the medium. This procedure can be effectively used for detection of living bacterial pathogen on fruit surfaces of Unshiu orange.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.4
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• pp.46-53
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• 1997

This paper presents a method of detection localized defects on tapered roller bearing in main spindle of machine tool system. The feature vectors, i.e. statistical parameters, in time-domain analysis technique have been calculated to extract useful features from acoustic emission signals. These feature vectors are used as the input feature of an neural network to classify and detect bearing defects. As a results, the detection of bearing defect conditions could be sucessfully performed by using an neural network with statistical parameters of acoustic emission signals.

• Journal of Biosystems Engineering
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• v.23 no.1
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• pp.67-74
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• 1998

A nondestructive quality inspection technique using acoustic impulse response method was developed for eggshell inspection. An experimental system was built to generate the impact force, to measure the response signal and to analyze the frequency spectrum. This system includes an impulse generating unit, an egg holding seal a microphone with preamplifier, and a DSP board installed on Personal Computer. A simple algorithm .was developed for crack detection. Using the developed system with algorithm, crack detection ability was evaluated and the error rate to estimate the normal egg as cracked was found to be 4% and the error rate to estimate the cracked egg as normal was also found to be 4%. This system could be adopted in industry with some modification.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.709-712
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• 2005

Ground processing for geostationary weather satellite such as GOES, MTSAT includes the process called image navigation. Image navigation means the retrieval of satellite navigational parameters from images and requires landmark detection by matching satellite images against landmark chips. For an automated preprocessing, a matching must be performed automatically. However, if match results contain errors, the accuracy of image navigation deteriorates. To overcome this problem, we propose the use of a robust estimation technique, called Random Sample Consensus (RANSAC), to automatically detect mismatches. We tested GOES-9 satellite images with 30 landmark chips. Landmark chips were extracted from the world shoreline database. To them, matching was applied and mismatch results were detected automatically by RANSAC. Results showed that all mismatches were detected correctly by RANSAC with a threshold value of 2.5 pixels.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2219-2226
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• 2017

This paper deals with artificial neural network approach for automatic detection of severity level of stator winding fault in induction motor. The problem is faced through modelling and simulation of induction motor with inter coil shorting in stator winding. The sum of the absolute values of difference in the peak values of phase currents from each half cycle has been chosen as the main input to the classifier. Sample values from workspace of Simulink model, which are verified with experiment setup practically, have been imported to neural network architecture. Consideration of a single input extracted from time domain simplifies and advances the fault detection technique. The output of the feed forward back propagation neural network classifies the short circuit fault level of the stator winding.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.4
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• pp.152-159
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• 2007

In this paper, a new design technique on the LRF which is useful for low power laser and a CBDA(Cummulative Binary Detection Algorithm) is proposed. The LD(Laser Diode) and Si-APD(Silicon Avalanche Photo Diode) are used for saving a power. In order to prove the detection range, the Si-APD binary data are accumulated before the range computation and the range finding algorithm. A prototype of the proposed DLRF(Diode Laser Range Finder) system was made and tested. An experimental result shows that the DLRF system have the same detection range using a less power(almost 1/32) than an usual military LRF. The proposed DLRF can be applied to the Unmanned Vehicles, Robot and Future Combat System of a tiny size and a low power LRF.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.04a
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• pp.81-82
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• 2014

Recently it is often reported about toxic nanomaterials to organisms. In other words, it is called nanotoxicity, toxic nanomaterials have extremely toxic properties. Zinc oxide is widely used as a promising nanomaterials, but some researchers are warning that nanotype zinc oxide has nanotoxicity. One of typical zinc oxide materials is a zinc oxide nanowire, especially, there is no technique which is detecting a zinc oxide nanowire because of its geometric. In here, we use reduced graphene oxide in order to detect zinc oxide nanowire and use DNA immobilized cantilever sensor, we detect graphene wrapped zinc oxide nanowire. Detection of a zinc oxide nanowire is measured by shifting of cantilever's resonance frequency based on vibration theory. It is proved that cantilever sensor is valid for nanomaterial detection. We showed that detection of a zinc oxide nanowire is successful.

• The Journal of Korea Robotics Society
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• v.12 no.2
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• pp.217-227
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• 2017

Crosswalk detection is an important part of the Pedestrian Protection System in autonomous vehicles. Different methods of crosswalk detection have been introduced so far using crosswalk edge features, the distance between crosswalk blocks, laser scanning, Hough Transformation, and Fourier Transformation. However, most of these methods failed to detect crosswalks accurately, when they are damaged, faded away or partly occluded. Furthermore, these methods face difficulties when applying on real road environment where there are lot of vehicles. In this paper, we solve this problem by first using a region based binarization technique and x-axis histogram to detect the candidate crosswalk areas. Then, we apply Support Vector Machine (SVM) based classification method to decide whether the candidate areas contain a crosswalk or not. Experiment results prove that our method can detect crosswalks in different environment conditions with higher recognition rate even they are faded away or partly occluded.