• Journal of the Korean Society for Aviation and Aeronautics
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• v.19 no.4
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• pp.83-90
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• 2011

The evaluation of Conflict detection and Resolution Algorithms require the use of analytical that describe encounter flight safety and the costs and benefits of optimization maneuver. A number of such algorithms have been applied in the past to the free flight. Each algorithm has benefits and limitations, and flight safety may be facilitated by combining the best features of various techniques. This paper studied a summary of conflict detection and resolution algorithm approaches. Algorithm techniques are categorized and the fundamental assumptions, capabilities, and limitations of each approach are described. The Algorithms are evaluated and compared based on their applicability to free flight airspace conflict situations.

• Proceedings of the KIEE Conference
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• 2009.04a
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• pp.77-79
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• 2009

Nonlinear system fault detection and isolation of this paper is about the failure of unknown function approximation using neural network for fault detection and isolation techniques of induction motors were applied. observer-based fault signal residual value was used. Induction motor using the speed controller of the backstepping controller. Proposed fault detection and isolation to prove the performance of the simulation was applied to and the actual system.

• International Journal of Aeronautical and Space Sciences
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• v.7 no.1
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• pp.73-83
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• 2006

In this paper, a redundancy management system for aircraft is studied, and fault detection and isolation algorithms of inertial sensor system are proposed. Contrary to the conventional aircraft systems, UAV system cannot allow triple or quadruple hardware redundancy due to the limitations on space and weight. In the UAV system with dual sensors, it is very difficult to identify the faulty sensor. Also, conventional fault detection and isolation (FDI) method cannot isolate multiple faults in a triple redundancy system. In this paper, two FDI techniques are proposed. First, hardware based FDI technique is proposed, which combines a parity equation approach with a wavelet based technique. Second, analytic FDI technique based on the Kalman filter is proposed, which is a model-based FDI method utilizing the threshold value and the confirmation time. To provide the reference value for detecting the fault, residuals are calculated using the extended Kalman filter. To verify the effectiveness of the proposed FDI methods, numerical simulations are performed.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.381-384
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• 2002

In speech signal processing, it Is very important to detect the pitch exactly in speech recognition, synthesis and analysis. but, it is very difficult to pitch detection from speech signal because of formant and transition amplitude affect. therefore, in this paper, we proposed a pitch detection using the spectrum flattening techniques. Spectrum flattening is to eliminate the formant and transition amplitude affect. In time domain, positive center clipping is process in order to emphasize pitch period with a glottal component of removed vocal tract characteristic. And rough formant envelope is computed through peak-fitting spectrum of original speech signal in frequency domain. As a results, well get the flattened harmonics waveform with the algebra difference between spectrum of original speech signal and smoothed formant envelope. After all, we obtain residual signal which is removed vocal tract element The performance was compared with LPC and Cepstrum, ACF 0wing to this algorithm, we have obtained the pitch information improved the accuracy of pitch detection and gross error rate is reduced in voice speech region and in transition region of changing the phoneme.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.3
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• pp.270-279
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• 2003

Parametric studies have been conducted into the variability of the factors affecting the ultrasonic testing applied to weldments. The influence of ultrasonic equipment, transducer parameters, test technique, job parameters, defect type and characteristics on reliability far defect detection and sizing was investigated by experimentation. The investigation was able to build up substantial bank of information on the reliability of manual ultrasonic method for testing weldments. The major findings of the study separate into two parts, one dealing with correlation between ultrasonic techniques, equipment and defect parameters and inspection performance effectiveness and other with human factors. Defect detection abilities are dependent on the training, experience and proficiency of the UT operators, the equipment used, the effectiveness of procedures and techniques.

• Korean Journal of Remote Sensing
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• v.19 no.3
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• pp.263-269
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• 2003

This research examined the capabilities of KOMPSAT-1 EOC images for the application of urban environment, including the urban changes of the study areas. This research is constructed in three stages: Firstly, for the application of change detection techniques, which utilizes multi-temporal remotely sensed data, the data normalization process is carried out. Secondly, the change detection method is applied for the systematic monitoring of land-use changes. Lastly, using the results of the previous stages, the land-use map is updated. Consequently, the patterns of land-use changes are monitored by the proposed scheme. In this research, using the multi-temporal KOMPSAT-1 EOC images and land-use maps, monitoring of urban growth was carried out with the application of land-use changes, and the potential and scope of the application of the EOC images were also examined.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.107-118
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• 2024

With the seamless growth of the technology, network usage requirements are expanding day by day. The majority of electronic devices are capable of communication, which strongly requires a secure and reliable network. Network-based intrusion detection systems (NIDS) is a new method for preventing and alerting computers and networks from attacks. Machine Learning is an emerging field that provides a variety of ways to implement effective network intrusion detection systems (NIDS). Bagging and Boosting are two ensemble ML techniques, renowned for better performance in the learning and classification process. In this paper, the study provides a detailed literature review of the past work done and proposed a novel ensemble approach to develop a NIDS system based on the voting method using bagging and boosting ensemble techniques. The test results demonstrate that the ensemble of bagging and boosting through voting exhibits the highest classification accuracy of 99.98% and a minimum false positive rate (FPR) on both datasets. Although the model building time is average which can be a tradeoff by processor speed.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.123-127
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• 1986

The use of vibration signal for fault detection inside a machine (or its part) is not new, and a number of signal processing techniques are available at the moment. A common problem for all such techniques is the high level of background signals which often made it very difficult to distinguish the desired signals. We developed a new algorithm to detect the minute faults of rotating part based on spectral histogram analysis. The technique has subsequently been applied to the bearings and has proved to be useful.

• Nuclear Engineering and Technology
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• v.29 no.6
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• pp.500-507
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• 1997

The development of detection techniques is needed, in order for regulating authorities to determine whether or not a particular food sample has been irradiated, and label it accordingly so that a consumer's free choice can be exercised. The chemical and physical changes brought about in foods by practical doses of irradiation are very small, and therefore very sensitive methods are required. A number of promising approaches have been developed and evaluated. These include chemical, physical and biological methods ranging from the very simple to highly sophisticated techniques.

• Proceedings of the Korea Concrete Institute Conference
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• 1998.10b
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• pp.743-748
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• 1998

As nation's infrastructure is getting old, nondestructive evaluation of existing structures and construction quality control are getting important. In this thesis, flaw detection techniques of concrete members with asphalt using impact echo test were introduced. This techniques are based on stress wave propagation. In this field impact echo test, As load is gradually increased, frequency is increased. From this change of frequency through impact echo test, we can detect that the crack of bridge ascends and what the depth of crack is.