• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.11
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• pp.997-1004
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• 2011

A fault detection algorithm of a charge and discharge system to ensure the safe use of hybrid electric vehicle is proposed in this paper. This algorithm can be used as a complementary way to existing fault detection technique for a charge and discharge system. The proposed algorithm uses a SVDD technique, which additionally utilizes two methods for learning a large amount of data; one is to incrementally learn a large amount of data, the other one is to remove the data that does not affect the next learning using a new data reduction technique. Removal of data is selected by using lines connecting support vectors. In the proposed method, the data processing speed is drastically improved and the storage space used is remarkably reduced than the conventional methods using the SVDD technique only. A battery data and speed data of a commercial hybrid electrical vehicle are utilized in this study. A fault boundary is produced via SVDD techniques using the input and output in normal operation of the system without using mathematical modeling. A fault detection simulation is performed using both an artificial fault data and the obtained fault boundary via SVDD techniques. In the fault detection simulation, fault detection time via proposed algorithm is compared with that of the peak-peak method. Also the proposed algorithm is revealed to detect fault in the region where conventional peak-peak method is never able to do.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.581-586
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• 2006

Incidents, which is unexpected unusual events such as traffic accidents, have increased on the most roads in Korea. The obstruction of a fluent traffic flow occurred by incidents causes the traffic congestion and decreases the capacity. The Wavelet technique was applied to detect the road section and the happening time of incidents on urban freeways in this study, and this technique has been widely used in many engineering fields such as an electrical engineering, etc. The availability and validity of the Wavelet technique to the detection of incidents was examined by the occupancy rate, the important element of traffic flows, which is extracted from the data of detectors installed on Seoul Urban freeways. Then, this result is compared to the California Algorithm and the Low-Pass Filtering Algorithm among basic present detection algorithms, which are based on the occupancy rate. As a result, the false alarm rate of this method was similar as that of the California algorithm and the Low-Pass Filtering algorithm, but the detection rate is higher.

• Journal of the Institute of Convergence Signal Processing
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• v.17 no.1
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• pp.18-25
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• 2016

As more people have cars, the threat of traffic accidents is posed on men and women of all ages. The main culprit of traffic accidents is driving while intoxicated or drowsy. The method to recognize and prevent the cause of traffic accidents is to use lane detection. In this study, a total of 4,000 frames (day image: 2,900 frames, night image: 1,100 frames) were used to test lane detection. According to the test, in the case of day image, when the threshold of Sobel edge detection technique was detected with second-order differential equation, there was the highest candidate lane detection rate which was 86.1%. In the threshold of Canny edge detection technique, the highest detection rate of 88.0% was found at Low=50, and High=300. In the case of night image, the threshold of Sobel edge detection technique, when horizontal calculation and vertical calculation had second-order differential equation, and when horizontal-vertical calculation had 1.5th-order differential equation, there was the highest detection rate which was 83.1%. In the threshold of Canny edge detection technique, the highest detection rate of 89.9% was found at Low=50, and High=300.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.613-621
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• 2019

Recently, with the development of the Internet of Things (IoT) and cloud computing technologies, security threats have increased as malicious codes infect IoT devices, and new malware spreads ransomware to cloud servers. In this study, we propose a threat-detection technique that checks obfuscated script patterns to compensate for the shortcomings of conventional signature-based and behavior-based detection methods. Proposed is a malicious code-detection technique that is based on malicious script-pattern analysis that can detect zero-day attacks while maintaining the existing detection rate by registering and checking derived distribution patterns after analyzing the types of malicious scripts distributed through websites. To verify the performance of the proposed technique, a prototype system was developed to collect a total of 390 malicious websites and experiment with 10 major malicious script-distribution patterns derived from analysis. The technique showed an average detection rate of about 86% of all items, while maintaining the existing detection speed based on the detection rule and also detecting zero-day attacks.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.5
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• pp.445-454
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• 2015

As the feature sizes and the operating charges continue to be scaled down, multi-bit soft errors are becoming more critical in SRAM designs of a few nanometers. In this paper, we propose an efficient error detection technique to reduce the size of parity bits by applying a 2D bit-interleaving technique to 3D bit-partitioned SRAM devices. Our proposed bit-interleaving technique uses only 1/K (where K is the number of dies) parity bits, compared with conventional bit-interleaving structures. Our simulation results show that 1/K parity bits are needed with only a 0.024-0.036% detection error increased over that of the existing bit-interleaving method. It is also possible for our technique to improve the burst error coverage, by adding more parity bits.

• Nuclear Engineering and Technology
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• v.44 no.8
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• pp.977-984
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• 2012

The cross-correlation technique has been widely used for leakage detection of buried pipes, and this technique can be successfully applied when the leakage signal has a high signal-to-noise ratio. In the case of a power plant, the measured leakage signals obtained from the sensors may contain background noise and mechanical noise generated by adjacent machinery. In such a case, the conventional method using the cross-correlation function may fail to estimate the leakage point. In order to enhance the leakage estimation capability of a buried pipe in a noisy environment, an improved cross-correlation technique is proposed. It uses a noise rejection technique in the frequency domain to effectively eliminate the tonal noise due to rotating machinery. Experiments were carried out to verify the validity of the proposed method. The results show that even in a tonal noisy environment, the proposed method can provide more reliable means for estimating the time delay of the leakage signals.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.7
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• pp.98-104
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• 2002

System condensation technique improves the efficiency of the inverse perturbation method of damage detection developed in the previous work. The technique is applied to transform the unmeasured DOFs to the measured DOFs. This approach makes it possible to eliminate the unmeasured DOFs, which accelerates the computational efficiency. The numerical instability problems due to the system condensation technique are also resolved by updating the transformation matrix for each step, and also by adopting the accelerated improved reduced system(AIRS) condensation method.

• Convergence Security Journal
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• v.21 no.1
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• pp.121-127
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• 2021

MANET, which does not have any infrastructure other than wireless nodes, has the advantage of being able to construct a fast network. However, the movement of nodes and wireless media are also the causes of security vulnerabilities of MANET. In particular, the damage caused by the attacking nodes existing on the network is considerably greater than that of other networks. Therefore, it is necessary to detection technique for attacking nodes and techniques to reduce damage caused by attacks. In this paper, we proposed a hierarchical structure technique to increase the efficiency of intrusion detection and collaboration-based intrusion detection technique applying a P2P mesh network configuration technique to reduce damage caused by attacks. There was excluded the network participation of the attacking node in advance through the reliability evaluation of the nodes in the cluster. In addition, when an attack by an attacking node is detected, this paper was applied a method of minimizing the damage of the attacking node by transmitting quickly the attack node information to the global network through the P2P mesh network between cluster heads. The ns-2 simulator was used to evaluate the performance of the proposed technique, and the excellent performance of the proposed technique was confirmed through comparative experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1795-1811
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• 2019

In order to achieve rapid and accurate detection of vehicle objects in complex traffic conditions, we propose a novel vehicle detection method. Firstly, more contextual and small-object vehicle information can be obtained by our Joint Feature Network (JFN). Secondly, our Evolved Region Proposal Network (EPRN) generates initial anchor boxes by adding an improved version of the region proposal network in this network, and at the same time filters out a large number of false vehicle boxes by soft-Non Maximum Suppression (NMS). Then, our Mask Network (MaskN) generates an example that includes the vehicle occlusion, the generator and discriminator can learn from each other in order to further improve the vehicle object detection capability. Finally, these candidate vehicle detection boxes are optimized to obtain the final vehicle detection boxes by the Fine-Tuning Network(FTN). Through the evaluation experiment on the DETRAC benchmark dataset, we find that in terms of mAP, our method exceeds Faster-RCNN by 11.15%, YOLO by 11.88%, and EB by 1.64%. Besides, our algorithm also has achieved top2 comaring with MS-CNN, YOLO-v3, RefineNet, RetinaNet, Faster-rcnn, DSSD and YOLO-v2 of vehicle category in KITTI dataset.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4889-4908
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• 2020

With the advances in Information Technology (IT), users can download or stream copyrighted works, such as videos, music, and webtoons, at their convenience. Thus, the frequency of use of copyrighted works has increased. Consequently, the number of unauthorized copies and sharing of copyrighted works has also increased. Monitoring is being conducted on sites suspected of conducting copyright infringement activities to reduce copyright holders' damage due to unauthorized sharing of copyrighted works. However, suspected copyright infringement sites respond by changing their domains or blocking access requests. Although research has been conducted for improving the effectiveness of suspected copyright infringement site detection by defining suspected copyright infringement sites' response techniques as a lifecycle step, there is a paucity of studies on automation techniques for lifecycle detection. This has reduced the accuracy of lifecycle step detection on suspected copyright infringement sites, which change domains and lifecycle steps in a short period of time. Thus, in this paper, an automated detection technique for suspected copyright infringement sites is proposed for efficient detection and response to suspected copyright infringement sites. Using our proposed technique, the response to each lifecycle step can be effectively conducted by automatically detecting the lifecycle step.