• Journal of Ocean Engineering and Technology
• /
• v.14 no.1
• /
• pp.80-87
• /
• 2000

Despite many combined research efforts outstanding needs exist to develop robust safety-estimation methods for large complex structures. This paper presents a practical damage identification scheme which can be applied to truss structures using only limited modal responses. firstly a theory of pattern recognition (PR) is described. Secondly existing damage-detection algorithms are outlined and a newly-derived algorithms for truss structures. Finally the feasibility of the proposed scheme is evaluated using numerical examples of plane truss structures.

• Journal of KIISE:Computer Systems and Theory
• /
• v.32 no.2
• /
• pp.49-54
• /
• 2005

This Paper Presents a non-blocking deadlock detection scheme with immediate cycle detection in multiprocessing systems. We assume an expedient state and a special case where each type of resource has one unit and each request is limited to one resource unit at a time. Unlike the previous deadlock detection schemes, this new method takes O(1) time for detecting a cycle and O(n+m) time for blocking or handling resource release where n and m are the number of processes and that of resources in the system. The deadlock detection latency is thus minimized and is constant regardless of n and m. However, in a multiprocessing system, the operating system can handle the blocking or release on-the-fly running on a separate processor, thus not interfering with user process execution. To some applications where deadlock is concerned, a predictable and zero-latency deadlock detection scheme could be very useful.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.5
• /
• pp.1463-1478
• /
• 2012

Based on the theory of local-world network, the composition self-similarity (CSS) of network traffic is presented for the first time in this paper for the study of DoS detection. We propose the concept of composition distribution graph and design the relative operations. The $(R/S)^d$ algorithm is designed for calculating the Hurst parameter. Based on composition distribution graph and Kullback Leibler (KL) divergence, we propose the composition self-similarity anomaly detection (CSSD) method for the detection of DoS attacks. We evaluate the effectiveness of the proposed method. Compared to other entropy based anomaly detection methods, our method is more accurate and with higher sensitivity in the detection of DoS attacks.

• Journal of The Korean Astronomical Society
• /
• v.41 no.4
• /
• pp.99-107
• /
• 2008

When a new counting experiment is proposed, it is crucial to predict whether the desired source signal will be detected, or how much observation time is required in order to detect the signal at a certain significance level. The concept of the a priori prediction of the detection limit in a newly proposed experiment should be distinguished from the a posteriori claim or decision whether a source signal was detected in an experiment already performed, and the calculation of statistical significance of a measured source signal. We formulate precise definitions of these concepts based on the statistical theory of hypothesis testing, and derive an approximate formula to estimate quickly the a priori detection limit of expected Poissonian source signals. A more accurate algorithm for calculating the detection limits in a counting experiment is also proposed. The formula and the proposed algorithm may be used for the estimation of required integration or observation time in proposals of new experiments. Applications include the calculation of integration time required for the detection of faint emission lines in a newly proposed spectroscopic observation, and the detection of faint sources in a new imaging observation. We apply the results to the calculation of observation time required to claim the detection of the surface thermal emission from neutron stars with two virtual instruments.

• Structural Engineering and Mechanics
• /
• v.30 no.4
• /
• pp.445-466
• /
• 2008

This paper presents a novel structural damage detection method with a new damage index based on the statistical moments of dynamic responses of a structure under a random excitation. After a brief introduction to statistical moment theory, the principle of the new method is put forward in terms of a single-degree-of-freedom (SDOF) system. The sensitivity of statistical moment to structural damage is discussed for various types of structural responses and different orders of statistical moment. The formulae for statistical moment-based damage detection are derived. The effect of measurement noise on damage detection is ascertained. The new damage index and the proposed statistical moment-based damage detection method are then extended to multi-degree-of-freedom (MDOF) systems with resort to the leastsquares method. As numerical studies, the proposed method is applied to both single and multi-story shear buildings. Numerical results show that the fourth-order statistical moment of story drifts is a more sensitive indicator to structural stiffness reduction than the natural frequencies, the second order moment of story drift, and the fourth-order moments of velocity and acceleration responses of the shear building. The fourth-order statistical moment of story drifts can be used to accurately identify both location and severity of structural stiffness reduction of the shear building. Furthermore, a significant advantage of the proposed damage detection method lies in that it is insensitive to measurement noise.

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

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.36 no.10
• /
• pp.996-1002
• /
• 2008

This paper presents the development of a real-time algorithm for collision detection, collision avoidance and guidance to way-point. Three-dimensional point-mass aircraft models are used. For collision detection, time of closest point of approach(CPA) and distance at CPA are compared to threshold values. For collision avoidance, optimal acceleration input which maximizes the terminal relative distance is calculated based on optimal control theory. For guidance to way-point, proportional navigation guidance, the well-known method, is used. Two scenarios of encounter situation are illustrated to validate performance of proposed algorithm.

• Journal of Communications and Networks
• /
• v.9 no.2
• /
• pp.185-191
• /
• 2007

Alpha stable distribution is better for modeling impulsive noises than Gaussian distribution in signal processing. This class of process has no closed form of probability density function and finite second order moments. In general, Wiener filter theory is not meaningful in S$\alpha$SG environments because the expectations may be unbounded. We proposed a new adaptive recursive least p-norm Kalman filtering algorithm based on least p-norm of innovation process with infinite variances, and a new robust multiuser detection method based on least p-norm Kalman filtering. The simulation experiments show that the proposed new algorithm is more robust than the conventional Kalman filtering multiuser detection algorithm.

• Journal of Biomedical Engineering Research
• /
• v.12 no.2
• /
• pp.99-106
• /
• 1991

For the automatic detection of pulmonary blood vessels, a new algorithm is proposed using the fact that human recognizes a pattern orderly according to their size. This method simulates the human recognition process by the pyramid images. For the detection of vessels using multilevel image, large and wtde ones are detected from the most compressed level, followed by the detection of small and narrow ones from the less compressed images with FCM(fuzzy c means) clustering algorithm which classifies similar data into a group. As the proposed algorithm detects blood vessels orderly according to their size, there is no need to consider the variation of parameters and the branch points which should be considered in other detection algirithms. In the detection of patterns whose size changes successively like pulmonary blood vessels, this proposed algorithm can be properly applied

• Journal of the Korean Operations Research and Management Science Society
• /
• v.40 no.2
• /
• pp.31-42
• /
• 2015

The purpose of airborne radars is to detect and identify approaching targets as early as possible. If the targets are identified as enemies, detection systems must provide defense systems with information of the targets to counter. Though many previous studies based on the detection theory of the target have shown various ways to derive detection probability of each radar, optimal arrangement of radars for effective detection, and determination of the search pattern, they did not reflect the fact that most military radar sites run multiple radars in order to increase the accuracy of identifications by radars. In this paper, we propose a model to analyze the probability of identification generated by the multiple radars using non-homogeneous absorbing markov chains. Our results are expected to help the military commanders counter the enemy targets effectively by using radars in a way to maximize the identification rate of targets.