• The Plant Pathology Journal
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• v.38 no.2
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• pp.159-166
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• 2022

Barley yellow dwarf virus (BYDV) has been a major viral pathogen causing significant losses of cereal crops including oats worldwide. It spreads naturally through aphids, and a rapid, specific, and reliable diagnostic method is imperative for disease monitoring and management. Here, we established a rapid and reliable method for isothermal reverse transcription recombinase polymerase amplification (RT-RPA) combined with a lateral flow strips (LFS) assay for the detection of BYDV-infected oat samples based on the conserved sequences of the BYDV coat protein gene. Specific primers and a probe for RT-RPA reacted and optimally incubated at 42℃ for 10 min, and the end-labeled amplification products were visualized on LFS within 10 min. The RT-RPA-LFS assay showed no cross-reactivity with other major cereal viruses, including barley mild mosaic virus, barley yellow mosaic virus, and rice black streaked dwarf virus, indicating high specificity of the assay. The sensitivity of the RT-RPA-LFS assay was similar to that of reverse transcription polymerase chain reaction, and it was successfully validated to detect BYDV in oat samples from six different regions and in individual aphids. These results confirm the outstanding potential of the RT-RPA-LFS assay for rapid detection of BYDV.

• The KIPS Transactions:PartC
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• v.12C no.5 s.101
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• pp.695-700
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• 2005

To provide the fair rate and achieve the fair bandwidth allocation, many per-flow scheduling algorithms have been proposed such as fair queueing algorithm for congestion control. But these algorithms need to maintain the state, manage buffer and schedule packets on a per-flow basis; the complexity of these functions may prevent them from being cost-effectively implemented. In this paper, therefore, to acquire cost-effectively for implementation, we propose a CS-FNE(Core Stateless FNE) algorithm that is based on FM(Flow Number Estimation), and evaluated CS-FNE scheme together with CSFQ(Core Stateless Fair Queueing), FRED(Fair Random Early Detection), RED(Random Early Detection), and DRR(Dynamic Round Robin) in several different configurations and traffic sources. Through the simulation results, we showed that CS-FNE algorithm can allocate fair bandwidth approximately than other algorithms, and CS-FNE is simpler than many per-flow basis queueing mechanisms and it can be easily implemented.

• Journal of KIISE:Information Networking
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• v.32 no.3
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• pp.279-290
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• 2005

Recently, as the serious damage caused by DDoS attacks increases, the rapid detection and the proper response mechanisms are urgent. However, existing security mechanisms do not effectively defend against these attacks, or the defense capability of some mechanisms is only limited to specific DDoS attacks. In this paper, we propose a detection architecture against DDoS attack using data mining technology that can classify the latest types of DDoS attack, and can detect the modification of existing attacks as well as the novel attacks. This architecture consists of a Misuse Detection Module modeling to classify the existing attacks, and an Anomaly Detection Module modeling to detect the novel attacks. And it utilizes the off-line generated models in order to detect the DDoS attack using the real-time traffic. We gathered the NetFlow data generated at an access router of our network in order to model the real network traffic and test it. The NetFlow provides the useful flow-based statistical information without tremendous preprocessing. Also, we mounted the well-known DDoS attack tools to gather the attack traffic. And then, our experimental results show that our approach can provide the outstanding performance against existing attacks, and provide the possibility of detection against the novel attack.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.1
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• pp.8-15
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• 2005

Field measurement data on water leakage are not readily available and it causes inaccurate assessment of water demand and poor supply planning. In this study, the procedure for leakage detection and unaccounted water calculation is proposed and applied to a city. The city has suffered from the significant amount of leak water and the financial loss as a result. Measurements were made for pressure and flow at 18 locations before and after the repair. Repair of the leakage increased pressure up to $2.0kgf/cm^2$ and saved 17.1% of water supply from distribution reservoirs. Monetary value of annual water savings for the entire city amounts to 1 billion won. It is believed that leakage detection and data analysis conducted in this study will contribute to the change of current practice and to the establishment of better water supply management system.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.10
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• pp.1359-1367
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• 2000

In-situ particle monitors(ISPMs) are widely used for monitoring contaminant particles in vacuum-based semiconductor manufacturing equipment. In the present research, the performance of a Particle Measuring Systems(PMS) Vaculaz-2 ISPM at low pressures has been studied. We generated the uniform sized methylene blue particle beams using three identical aerodynamic lenses in the center of the vacuum line, and measured the detection efficiency of the ISPM. The effects of particle size, particle concentration, mass flow rate, system pressure, and arrangement of aerodynamic lenses on the detection efficiency of the ISPM were examined. Results show that the detection efficiency of the ISPM greatly depends on the mass flow rate, and the particle Stokes number. We also found that the optimum Stokes number ranges from 0.4 to 1.9 for the experimental conditions.

• The KIPS Transactions:PartC
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• v.12C no.1 s.97
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• pp.19-28
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• 2005

Recently, it has been sharply increased the interests to detect the network traffic anomalies to help protect the computer network from unknown attacks. In this paper, we propose a new anomaly detection scheme using the simple linear regression analysis for the exported LetFlow data, such as bits per second and flows per second, from a border router at a campus network. In order to verify the proposed scheme, we apply it to a real campus network and compare the results with the Holt-Winters seasonal algorithm. In particular, we integrate it into the RRDtooi for detecting the anomalies in real time.

• Journal of Korea Multimedia Society
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• v.18 no.2
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• pp.189-198
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• 2015

Despite the fact that traffic engineering techniques have been comprehensively utilized in the past to enhance the performance of communication networks, the distinctive characteristics of Software Defined Networking (SDN) demand new traffic engineering techniques for better traffic control and management. Considering the behavior of traffic, large flows normally carry out transfers of large blocks of data and are naturally packet latency insensitive. However, small flows are often latency-sensitive. Without intelligent traffic engineering, these small flows may be blocked in the same queue behind megabytes of file transfer traffic. So it is very important to identify large flows for different applications. In the scope of this paper, we present an approach to detect large flows in real-time without even a short delay. After the detection of large flows, the next problem is how to control these large flows effectively and prevent network jam. In order to address this issue, we propose an approach in which when the controller is enabled, the large flow is mitigated the moment it hits the predefined threshold value in the control application. This real-time detection, marking, and controlling of large flows will assure an optimize usage of an overall network.

• Proceedings of the KACD Conference
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• 2003.11a
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• pp.546.1-546
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• 2003

Laser doppler flowmeter (LDF) has been applied to the measurement of pulpal blood flow (PBF) in human teeth. As far as we searched, the detection area of the pulp in the blood flow measurement has not been clarified, yet. Therefore, the purpose of this study was to obtain information of the detection area in PBF measurement using LDF. The experiments were performed on the artificial blood circulation in extracted human upper central incisors. The apical portions of examined teeth (n=6) were severed and root canals were enlarged from the apical end to the 2mm incisal to the level of enamel-cement junction. An individual resin cap of each tooth was prepared and a hole was drilled 2mm incisal to enamel-cement junction of the labial side of the cap. The measurement probe of LDF (MBF3D, Moor Instrument, UK) was plugged into the hole of the cap. Heparinized human peripheral blood, which was in advance collected and diluted 3 times with physiological saline, was pumped through the apical foramen of the teeth via a silicone tube and a disposable needle (o.d. 0.7mm) and blood flow signals were monitored. The flux signal significantly increased with the enlargement of the root canal to incisal direction (p<0.01, Friedman analysis). The result indicates that the performance of LDF in PBF with human teeth is limited.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.4
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• pp.1-11
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• 2014

Traffic congestion cost is more likely to occur in the inner city than interregional road, and it accounts for about 63.39% of the whole. Therefore, it is important to mitigate traffic congestion of the inner city. Traffic congestion in the urban could be divided into Recurrent congestion and Non-recurrent congestion. Quick and accurate detection of Non-recurrent congestion is also important in order to relieve traffic congestion. The existing studies about incident detection have been variously conducted, however it was limited to Uninterrupted Traffic Flow Facilities such as freeway. Moreover study of incident detection on the interrupted Traffic Flow Facilities is still inadequate due to complex geometric structure such as traffic signals and intersections. Therefore, in this study, incident detection model was constructed using by Artificial Neural Network to aim at urban arterial road that is interrupted traffic flow facility. In the result of the reliability assessment, the detection rate were 46.15% and false alarm rate were 25.00%. These results have a meaning as a result of the initial study aimed at interrupted traffic flow. Furthermore, it demonstrates the possibility that Non-recurrent congestion can be detected by using car navigation data such as car navigator system device.

• Journal of Marine Bioscience and Biotechnology
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• v.6 no.1
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• pp.1-7
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• 2014

Marine-derived pathogens threat health and life of human and animals. Therefore, rapid and specific detection methods need to be developed. Here, we summarized various groups of detection methods, including conventional method, flow cytometry, nucleic acid-based method, and protein-based method. In addition, perspective of detection technique was discussed as a unified detection system for pathogens.