• Smart Structures and Systems
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• 제7권2호
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• pp.117-132
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• 2011

This paper is aimed at presenting two methods on the basis of pattern search and genetic algorithms to detect and estimate damage in plates using the modal data of a damaged plate. The proposed methods determine the damages of plate structures using optimization of an objective function by pattern search and genetic algorithms. These methods have been applied to two numerical examples, namely four-fixed supported and cantilever plates with and without noise in the modal data and containing one or several damages. The obtained results clearly reveal that the proposed methods can be viewed as a powerful and reliable method for structural damage detection in plates using the modal data.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2002년도 봄 학술발표회 논문집
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• pp.300-307
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• 2002

Damage estimation methods are classified into two groups according to the dependence on the FE model : signal-based and model-based methods. Signal-based damage estimation methods are generally appropriate for detection of damage location, whereas not effective for estimation of damage severities. Model-based damage estimation methods are difficult to apply directly to the structures with a large number of the probable damaged members. It is difficult to obtain the exact model representing the real bridge behavior due to the modeling errors. The modeling errors even may exceed the modal sensitivity on damage. In this study, Model-based damage detection method which can effectively consider the modeling errors is suggested. Two numerical example analyses on a simple beam and a multi-girder bridge are presented to demonstrate the effectiveness of the presented method.

• 식품과학과 산업
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• 제55권1호
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• pp.45-57
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• 2022

This study was proceeded the analytical methods using various analytical instruments for polycyclic aromatic hydrocarbons (PAHs) in food products. Various analytical methods were developed to determine levels of PAHs including benzo[a]pyrene, benzo[a]anthracene, benzo[b]fluoranthene, and chrysene formed in various food products using gas chromatography-mass spectrometry (GC-MS), enzyme-linked immunosorbent assay (ELISA) and raman spectroscopy. Recently, the rapid on-site response for the detection of hazardous substances in food aims to develop an onsite rapid detection of a simplified technical analysis method to reduce the time and cost required for analysis of PAHs. Current PAHs detection methods have been reviewed along with new raman spectroscopy analytical method.

• ETRI Journal
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• 제45권6호
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• pp.929-938
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• 2023

The detection of all the symbols transmitted simultaneously in multiuser systems using limited wireless resources is challenging. Traditional model-based methods show high performance with perfect channel state information (CSI); however, severe performance degradation will occur if perfect CSI cannot be acquired. In contrast, data-driven methods perform slightly worse than model-based methods in terms of symbol error ratio performance in perfect CSI states; however, they are also able to overcome extreme performance degradation in imperfect CSI states. This study proposes a novel deep learning-based method by improving a state-of-the-art data-driven technique called deep soft interference cancellation (DSIC). The enhanced DSIC (EDSIC) method detects multiuser symbols in a fully sequential manner and uses an efficient neural network structure to ensure high performance. Additionally, error-propagation mitigation techniques are used to ensure robustness against channel uncertainty. The EDSIC guarantees a performance that is very close to the optimal performance of the existing model-based methods in perfect CSI environments and the best performance in imperfect CSI environments.

• 대한수의학회지
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• 제14권2호
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• pp.243-252
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• 1974

The experiment was performed in order to investigate the applicability of the rapid detection of salmonellae in various animal-origin foods by means of the direct fluorescent antibody technique. Egg, sausage and chicken were inoculated with various concentrations of Sal.paratuphi A, Sal. paratyhi B and Sal. thompson, and the fluorescent antibody technique was applied and compared with the conventional cultura method for the sensitivity of detection of the organisms. Two methods were employed in the fluorescent antibody technique; the direct smear method in which the smear being made directly from the specimens, and the enrichment smear method in which the smear being made from the enrichment broth. The effect of various enrichment time (1,5,8,11 and 13 hours) in tetrathionate broth on the detection of salmonellae in the fluoresent antibody technique was also studied. The results obtained were summarized as followings; 1. Of the three methods, the enrichment smear method of fluorescedt antibody technique was highly effective as cultural method for the detection of salmonella organisms. 2. Direct smear method of fluorescent antibody technique was effective as two other methods $5{\times}10^4$ organisms presented in 50 g(ml) of specimens. This method may not be applicable when the specimens contained $5{\times}10^2$ or less organisms. 3. Of the three specimens, the recovery rate of Salmonella organisms from egg was slightly higher than that of sausage and chicken. 4. In fluorescent antibody technique and cultural method, the specimens inoculated with Sal. thompson were found to be higher detection rate than the specimens inoculated with Sal. paratyphi A, 5. The optimum enrichment time of Salmonella organisms in tetrathionate broth on the detection by fluorscent antibody technique was found to be 11 hours or longer when the specimens of egg, sausage and chicken were inoculated with approximately 500 organisms. The longer enrichment time was the higher detection rate up to 11 hours tested.

• 한국물환경학회지
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• 제40권1호
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• pp.19-35
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• 2024

The global pandemic, coronavirus disease caused by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to the implementation of wastewater surveillance as a means to monitor the spread of SARS-CoV-2 prevalence in the community. The challenging aspect of establishing wastewater surveillance requires a well-equipped laboratory for wastewater sample analysis. According to previous studies, RT-PCR-based molecular tests are the most widely used and popular detection method worldwide. However, this approach for the detection or quantification of SARS-CoV-2 from wastewater demands a specialized laboratory, skilled personnel, expensive instruments, and a workflow that typically takes 6 to 8 hours to provide results for a few samples. Rapid and reliable alternative detection methods are needed to enable less-well-qualified practitioners to set up and provide sensitive detection of SARS-CoV-2 within wastewater at regional laboratories. In some cases, the structural and molecular characteristics of SARS-CoV-2 are unknown, and various strategies for the correct diagnosis of COVID-19 have been proposed by research laboratories. The ongoing research and development of alternative and rapid technologies, namely RT-LAMP, ELISA, Biosensors, and GeneXpert, offer a wide range of potential options not only for SARS-CoV-2 detection but also for other viruses. This study aims to discuss the effective regional rapid detection and quantification methods in community wastewater.

• 대한전자공학회논문지TC
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• 제44권2호
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• pp.46-54
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• 2007

본 논문에서는 중첩의 차분상관방식에 의한 향상된 OFDM 신호의 심볼 동기타이밍검출 성능을 보여준다. 또한, 곱의 상관과 차분상관의 동기타이밍 검출방식에 있어서 멀티패스 채널 지연프로필의 각 수신지연파에서 심벌 동기타이밍으로 검출될 최대 검출확률을 보여준다. $70nsec{\sim}217nsec$의 지연확산 채널모델들에서 상관의 동기타이밍 검출방식에서는 진폭이 가장 큰n번째 수신지연파의 선두에서 동기타이밍을 취할 확률이 높게 나타나는데 대하여 차분방식에서는 언제나 첫 번째 수신지연파의 선두에서 동기타이밍을 취할 확률이 높게 나타나는 특성을 보여준다. 이러한 시뮬레이션의 결과는 정확한 동기타이밍의 검출이 가능함을 나타내는 것이며 중첩의 차분방식에서 eb/n0에 대해 향상된 S/N와 OFDM 신호의 동기타이밍검출성능의 결과와도 잘 부합하고 있다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1949-1952
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• 2004

GPS is widely used for outdoor positioning in many applications. But it is not suitable for positioning in an obstacle environment such as urban area, tunnels and so on, due to variable signal level. So new technology of the positioning is required to provide the consistent error level regardless of any changes in any environment. Abrupt changes of GPS signal can be detected by various fault detection and isolation methods. Conventional FDI (Fault Detection and Isolation) methods are categorized into two approaches. One approach is the snapshot method that uses measurements only at present step. The other approach is the filtering method that uses measurements stacked from previous step to present step. The FDI result of the snapshot method can be considered reliable independently with previous results and the FDI result of the filtering method is more reliable and detection time is a little longer. Therefore combining approach of two methods is proposed for increasing FDI performance in this paper. Three approaches that are the snapshot method, the filtering method and the combining method are compared to show the probability of correct FDI in simulations. The combining approach presents best result of FDI among them and shows the consistent accuracy irrespective of any changes in outdoor environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권9호
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• pp.3797-3822
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• 2020

The inspection of cracks on the surface of tunnel linings is a common method of evaluate the condition of the tunnel. In particular, determining the thickness and shape of a crack is important because it indicates the external forces applied to the tunnel and the current condition of the concrete structure. Recently, several automatic crack detection methods have been proposed to identify cracks using captured tunnel lining images. These methods apply an image-segmentation mechanism with well-annotated datasets. However, generating the ground truths requires many resources, and the small proportion of cracks in the images cause a class-imbalance problem. A weakly annotated dataset is generated to reduce resource consumption and avoid the class-imbalance problem. However, the use of the dataset results in a large number of false positives and requires post-processing for accurate crack detection. To overcome these issues, we propose a crack detection method using a ternary classifier. The proposed method significantly reduces the false positive rate, and the performance (as measured by the F1 score) is improved by 0.33 compared to previous methods. These results demonstrate the effectiveness of the proposed method.

• Journal of Communications and Networks
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• 제18권5호
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• pp.818-825
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• 2016

Network management and anomaly detection are challenges in high-speed networks due to the high volume of packets that has to be analysed. Flow-based analysis is a scalable method which reduces the high volume of network traffic by dividing it into flows. As sampling methods are extensively used in flow generators such as NetFlow, the impact of sampling on the performance of flow-based analysis needs to be investigated. Monitoring using sampled traffic is a well-studied research area, however, the impact of sampling on flow-based anomaly detection is a poorly researched area. This paper investigates flow sampling methods and shows that these methods have negative impact on flow-based anomaly detection. Therefore, we propose an efficient probabilistic flow sampling method that can preserve flow traffic distribution. The proposed sampling method takes into account two flow features: Destination IP address and octet. The destination IP addresses are sampled based on the number of received bytes. Our method provides efficient sampled traffic which has the required traffic features for both flow-based anomaly detection and monitoring. The proposed sampling method is evaluated using a number of generated flow-based datasets. The results show improvement in preserved malicious flows.