• Steel and Composite Structures
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• v.19 no.1
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• pp.191-208
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• 2015

The sensitivity-based finite element model updating method has received increasing attention in damage detection of structures based on measured modal parameters. Finding an optimization technique with high efficiency and fast convergence is one of the key issues for model updating-based damage detection. A new simple and computationally efficient optimization algorithm is proposed and applied to damage detection by using finite element model updating. The proposed method combines the Gauss-Newton method with region truncation of each iterative step, in which not only the constraints are introduced instead of penalty functions, but also the searching steps are restricted in a controlled region. The developed algorithm is illustrated by a numerically simulated 25-bar truss structure, and the results have been compared and verified with those obtained from the trust region method. In order to investigate the reliability of the proposed method in damage detection of structures, the influence of the uncertainties coming from measured modal parameters on the statistical characteristics of detection result is investigated by Monte-Carlo simulation, and the probability of damage detection is estimated using the probabilistic method.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.497-502
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• 2003

Content-based video copy detection is a complementary approach to watermarking. As opposed to watermarking, which relies on inserting a distinct pattern into the video stream, video copy detection techniques match content-based signatures to detect copies of video. Existing typical content-based copy detection schemes have relied on image matching which is based on key frame detection. This paper proposes a motion directional histogram, which is quantized and accumulated the direction of motion, for video copy detection. The video clip is represented by a motion directional histogram as a 1-dimensional graph. This method is suitable for real time indexing and counting the TV CF verification that is high motion video clips.

• Journal of Korean society of Dental Hygiene
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• v.14 no.5
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• pp.609-615
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• 2014

Objectives : In most developed countries there has been a substantial decrease in the prevalence of dental caries in children of 12 years old over the past 40 years. This change in epidemiology highlights the importance of preventive management in dentistry. For successful management of early caries lesions, it is essential to detect and assess the pathological changes of dental caries. Therefore, the purpose of this study was to investigate the overview of International Caries Detection and Assessment System(ICDAS) criteria for the detection and assessment of early caries lesions by literature reviews. Methods : The author reviewed the MEDLINE search by the key words of 'caries assessment', 'caries detection', 'caries measurement', and 'ICDAS'. Results : This literature review provided an overview of International Caries Detection and Assessment System(ICDAS) criteria for the detection and assessment of early caries lesions. This article showed the principles, concept, and primary caries detection criteria of the ICDAS. The ICDAS can macroscopically measure the enamel surface changes and potential histological depth of caries lesions by the surface characteristics of the teeth. The ICDAS criteria allow researchers and clinicians to choose the stage of dental caries and characteristics for assessment. Conclusions : ICDAS can be an adjunct method to clinical decision making and preventive treatment planning.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.7
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• pp.552-556
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• 2016

Obstacle detection is a key feature in the safe driving control of electric wheelchairs. The suggested obstacle detection algorithm was designed to provide obstacle avoidance direction and detect the existence of cliffs. By means of this information, the wheelchair can determine where to steer and whether to stop or go. A 3D depth camera (Microsoft KINECT) is used to scan the 3D point data of the scene, extract information on obstacles, and produce a steering direction for obstacle avoidance. To be specific, ground detection is applied to extract the obstacle candidates from the scanned data and the candidates are projected onto a 2D map. The 2D map provides discretized information of the extracted obstacles to decide on the avoidance direction (left or right) of the wheelchair. As an additional function, cliff detection is developed. By defining the "cliffband," the ratio of the predefined band area and the detected area within the band area, the cliff detection algorithm can decide if a cliff is in front of the wheelchair. Vehicle tests were carried out by applying the algorithm to the electric wheelchair. Additionally, detailed functions of obstacle detection, such as providing avoidance direction and detecting the existence of cliffs, were demonstrated.

• Journal of Radiation Protection and Research
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• v.35 no.4
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• pp.167-171
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• 2010

Fixed radiation portal monitors (RPMs) deployed at border, seaport, airport and key traffic checkpoints have played an important role in preventing the illicit trafficking and transport of nuclear and radioactive materials. However, the RPM is usually large and heavy and can't easily be moved to different locations. These reasons motivate us to develop a mobile radiation detection system. The objective of this paper is to report our experience on developing the mobile radiation detection system for search and detection of nuclear and radioactive materials during road transport. Field tests to characterize the developed detection system were performed at various speeds and distances between the radioactive isotope (RI) transporting car and the measurement car. Results of measurements and detection limits of our system are described in this paper. The mobile radiation detection system developed should contribute to defending public's health and safety and the environment against nuclear and radiological terrorism by detecting nuclear or radioactive material hidden illegally in a vehicle.

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.6
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• pp.540-549
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• 2015

Unintentional islanding results in safety hazards, reliability, and many other issues. Therefore, the islanding detection of a power conditioning system of a distributed generation, such as a grid-connected photovoltaic inverter, is a key function for standard compliance. Currently, many anti-islanding schemes have been examined, but existing anti-islanding schemes have poor power quality and non-detection zone issues. Therefore, this study analyzes the non-detection zone in a more deliberate manner than the existing analysis of the non-detection zone and proposes a new anti-islanding scheme, which has negligible power quality degradation and no non-detection zone. Simulation and experimental results validate that the proposed scheme shows much better performance than other existing schemes.

• ETRI Journal
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• v.33 no.4
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• pp.600-610
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• 2011

This paper presents a novel approach to face detection by localizing faces as the goal-specific saliencies in a scene, using the framework of selective visual attention of a human with a particular goal in mind. The proposed approach aims at achieving human-like robustness as well as efficiency in face detection under large scene variations. The key is to establish how the specific knowledge relevant to the goal interacts with the bottom-up process of external visual stimuli for saliency detection. We propose a direct incorporation of the goal-related knowledge into the specification and/or modification of the internal process of a general bottom-up saliency detection framework. More specifically, prior knowledge of the human face, such as its size, skin color, and shape, is directly set to the window size and color signature for computing the center of difference, as well as to modify the importance weight, as a means of transforming into a goal-specific saliency detection. The experimental evaluation shows that the proposed method reaches a detection rate of 93.4% with a false positive rate of 7.1%, indicating the robustness against a wide variation of scale and rotation.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1396-1406
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• 2018

Lane detection is a key function in developing autonomous vehicle technology. In this paper, we propose a lane marker detection algorithm robust to environmental variation targeting low cost embedded computing devices. The proposed algorithm consists of two phases: initialization phase which is slow but has relatively higher accuracy; and the tracking phase which is fast and has the reliable performance in a limited condition. The initialization phase detects lane markers using a set of filters utilizing the various features of lane markers. The tracking phase uses Kalman filter to accelerate the lane marker detection processing. In a tracking phase, we measure the reliability of the detection results and switch it to initialization phase if the confidence level becomes below a threshold. By combining the initialization and tracking phases we achieved high accuracy and acceptable computing speed even under a low cost computing resources in which we cannot use the computing intensive algorithm such as deep learning approach. Experimental results show that the detection accuracy is about 95% on average and the processing speed is about 20 frames per second with Raspberry Pi 3 which is low cost device.

• The Plant Pathology Journal
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• v.35 no.2
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• pp.172-177
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• 2019

A duplex PCR method was developed for simultaneous detection and identification of tobacco root rot pathogens Phytophthora nicotianae and Thielaviopsis basicola. The specific primers for P. nicotianae were developed based on its internal transcribed spacer (ITS) regions of ribosomal gene, ras gene and hgd gene, while the specific primers for T. basicola were designed based on its ITS regions and ${\beta}$-tubulin gene. The specificity of the primers was determined using isolates of P. nicotianae, T. basicola and control samples. The results showed that the target pathogens could be detected from diseased tobacco plants by a combination of the specific primers. The sensitivity limitation was $100fg/{\mu}l$ of pure genomic DNA of the pathogens. This new assay can be applied to screen out target pathogens rapidly and reliably in one PCR and will be an important tool for the identification and precise early prediction of these two destructive diseases of tobacco.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.5
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• pp.1019-1025
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• 2012

Fault attacks manipulate the computation of an algorithm and get information about the private key from the erroneous result. It is the most powerful attack for the cryptographic device. Currently, the research on error detection methods and fault attacks have been studied actively. S. Pontarelli et al. introduced an error detection method in 2009. It can detect an error that occurs during Elliptic Curve Scalar Multiplication (ECSM). In this paper, we present a new fault attack. Our attack can avoid the error detection method introduced by S. Pontarelli et al. We inject a bit flip error in the Euclidean Addition Chain (EAC) on the private key in ECSM and retrieve the private key.