• Wind and Structures
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• 제21권6호
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• pp.657-675
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• 2015

In this study, the feasibility of vibration-based damage detection methods for the wind turbine tower (WTT) structure is evaluated. First, a frequency-based damage detection (FBDD) is outlined. A damage-localization algorithm is visited to locate damage from changes in natural frequencies. Second, a mode-shape-based damage detection (MBDD) method is outlined. A damage index algorithm is utilized to localize damage from estimating changes in modal strain energies. Third, a finite element (FE) model based on a real WTT is established by using commercial software, Midas FEA. Several damage scenarios are numerically simulated in the FE model of the WTT. Finally, both FBDD and MBDD methods are employed to identify the damage scenarios simulated in the WTT. Damage regions are chosen close to the bolt connection of WTT segments; from there, the stiffness of damage elements are reduced.

• Journal of information and communication convergence engineering
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• 제18권2호
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• pp.75-81
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• 2020

Approximately 1.3 million people die from traffic accidents each year, and smartphone usage while driving is one of the main causes of such accidents. Therefore, detection of smartphone usage by drivers has become an important part of distracted driving detection. Previous studies have used single camera-based methods to collect the driver images. However, smartphone usage detection by employing a single camera can be unsuccessful if the driver occludes the phone. In this paper, we present a driver smartphone usage detection system that uses multiple cameras to collect driver images from different perspectives, and then processes these images with ensemble convolutional neural networks. The ensemble method comprises three individual convolutional neural networks with a simple voting system. Each network provides a distinct image perspective and the voting mechanism selects the final classification. Experimental results verified that the proposed method avoided the limitations observed in single camera-based methods, and achieved 98.96% accuracy on our dataset.

• International Journal of Air-Conditioning and Refrigeration
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• 제11권3호
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• pp.125-131
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• 2003

The fault detection and diagnosis technology may be applied in order to decrease the energy consumption and the maintenance cost of the air-conditioning system. In this paper, two fault detection methods were considered. One is a generic neural network, and the other is an moving average neural network. In order to compare the performance of fault detection results from these methods, two different types of faults in an air-conditioning system were applied. These are the condenser 30% fouling and the evaporator fan 25% slowdown. Test results showed that the moving average neural network was more effective for the detection of partial faults in the air-conditioning system.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 추계학술대회
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• pp.937-939
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• 2014

최근 특정 대상을 목표로 하는 지능적이고 지속적인 공격(APT: Advanced Persistent Threat)이 급속히 증가하고 있다. APT는 악성코드 유입 시 완벽한 방어가 불가능하기 때문에 일반적인 탐지 기법으로 대응이 어려움이 있다. 따라서 본 논문에서는 악성코드 침투 이후의 콜백 단계를 차단하기 위하여 아웃바운드 트래픽을 분석하고 신뢰도를 기반으로 한 APT 공격 탐지기법에 대해 제안한다. 제안기법은 기존 탐지기법에 비해 탐지율을 크게 높이는 기반을 제공한다.

• 전자통신동향분석
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• 제36권5호
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• pp.82-91
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• 2021

This study reviews application of data-driven anomaly detection techniques to the aviation domain. Recent advances in deep learning have inspired significant anomaly detection research, and numerous methods have been proposed. However, some of these advances have not yet been explored in aviation systems. After briefly introducing aviation safety issues, data-driven anomaly detection models are introduced. Along with traditional statistical and well-established machine learning models, the state-of-the-art deep learning models for anomaly detection are reviewed. In particular, the pros and cons of hybrid techniques that incorporate an existing model and a deep model are reviewed. The characteristics and applications of deep learning models are described, and the possibility of applying deep learning methods in the aviation field is discussed.

• 공업화학
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• 제33권1호
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• pp.1-10
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• 2022

본 논문은 주요 폭발물 탐지 기술에 대한 원리, 장단점 및 향후 필요한 연구 분야에 대한 총설이다. 폭발물 탐지 기술은 분광학적 방법(spectroscopic methods), 감지기 기술(sensor techniques), 후각 감지기(olfactory type sensors)로 분류할 수 있다. 이러한 탐지 기술은 많은 발전이 있었지만 폭발물 탐지를 위한 판별성, 휴대성, 감도에 관한 연구 가능성이 높은 것으로 보인다.

• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.1-6
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• 2022

Scene change detection is an important topic because of the wide and growing range of its applications. Streaming services from many providers are increasing their capacity which causes the industry growth. The method for the scene change detection is described here and compared with the State-of-the-Art methods over the Open Video Scene Detection (OVSD) - an open dataset of Creative Commons licensed videos freely available for download and use to evaluate video scene detection algorithms. The proposed method is based on scene analysis using threshold values and smooth scene changes. A comparison of the presented method was conducted in this research. The obtained results demonstrated the high efficiency of the scene cut localization method proposed by authors, because its efficiency measured in terms of precision, recall, accuracy, and F-metrics score exceeds the best previously known results.

• 한국화재소방학회:학술대회논문집
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• 한국화재소방학회 1997년도 International Symposium on Fire Science and Technology
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• pp.573-581
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• 1997

Much activity is occurring throughout the world with respect to the implementation of new concepts and technology for fire detection and fire suppression applications. Obvious advances include tangible detection and suppression improvements, and also new methods and approaches such as performance based codes and standards. Examples of tangible advances include addressable detection systems, wireless detection technology, halon alternatives, water mist systems, advanced sprinkler technology, and so on. Examples of new approaches and methods include a revitalized focus on disaster planning and the need for a total fire protection plan. The concept of performance based codes and standards for the design and installation fire detection and suppression systems will be explored in detail.

• The Plant Pathology Journal
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• 제39권1호
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• pp.141-148
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• 2023

Black shoot blight disease caused by Erwinia pyrifoliae has serious impacts on quality and yield in pear production in Korea; therefore, rapid and accurate methods for its detection are needed. However, traditional detection methods require a great deal of time and fail to achieve absolute quantification. In the present study, we developed a droplet digital polymerase chain reaction (ddPCR) method for the detection and absolute quantification of E. pyrifoliae using a pair of species-specific primers. The detection range was 10³-10⁷ copies/ml (DNA templates) and cfu/ml (cell culture templates). This new method exhibited good linearity and repeatability and was validated by absolute quantification of E. pyrifoliae DNA copies from samples of artificially inoculated immature pear fruits. Here, we present the first study of ddPCR assay for the detection and quantification of E. pyrifoliae. This method has potential applications in epidemiology and for the early prediction of black shoot blight outbreaks.

• Journal of Power Electronics
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• 제13권2호
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• pp.304-312
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• 2013

The most common power quality problems in distribution systems are related to unbalanced voltage sags. Voltage sags must be detected quickly and corrected in a minimum amount of time. One of the most widely used methods for sag detection is based on the d-q transformation. This method has the disadvantage of missing the detection of unbalanced faults, because this method uses a voltage sag level signal obtained from the average of 3 phases for sag detection. In this paper, an adaptive filter sag detection method is proposed for Dynamic Voltage Restorers (DVR) under unbalanced fault conditions. The proposed DVR controller is able to detect balanced, unbalanced and single phase voltage sags. A novel reference voltage generation method is also presented. To validate the proposed control methods, a 3-phase DSP controlling a DVR prototype with a power rating of 1.5-kVA has been developed. Finally, experimental results are presented to verify the performance of the proposed control methods.