• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1217-1228
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• 2014

A method for faulted line detection of four parallel lines on the same tower is presented, based on four-summing and double-differential sequences of one terminal current. Four-summing and double-differential sequences of fault current can be calculated using a certain transformation matrix for parameter decoupling of four parallel transmission lines. According to fault boundary conditions, the amplitude and phase characteristics of four-summing and double-differential sequences of fault current is studied under conditions of different types of fault. Through the analysis of the relationship of terminal current and fault current, a novel methodology for fault line detection of four parallel transmission line on the same tower is put forward, which can pick out the fault lines no matter the fault occurs in single line or cross double lines. Simulation results validate that the methodology is correct and reliable under conditions of different load currents, transient resistances and fault locations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1597-1610
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• 2022

At present, the main method of high-speed train chassis detection is using computer vision technology to extract keypoints from two related chassis images firstly, then matching these keypoints to find the pixel-level correspondence between these two images, finally, detection and other steps are performed. The quality and accuracy of image matching are very important for subsequent defect detection. Current traditional matching methods are difficult to meet the actual requirements for the generalization of complex scenes such as weather, illumination, and seasonal changes. Therefore, it is of great significance to study the high-speed train image matching method based on deep learning. This paper establishes a high-speed train chassis image matching dataset, including random perspective changes and optical distortion, to simulate the changes in the actual working environment of the high-speed rail system as much as possible. This work designs a convolutional neural network to intensively extract keypoints, so as to alleviate the problems of current methods. With multi-level features, on the one hand, the network restores low-level details, thereby improving the localization accuracy of keypoints, on the other hand, the network can generate robust keypoint descriptors. Detailed experiments show the huge improvement of the proposed network over traditional methods.

• Journal of Veterinary Science
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• v.22 no.6
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• pp.41.1-41.14
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• 2021

Background: Our previously prepared ceftiofur (CEF) hydrochloride oily suspension shows potential wide applications for controlling swine Streptococcus suis infections, while the irrational dose has not been formulated. Objectives: The rational dose regimens of CEF oily suspension against S. suis were systematically studied using a pharmacokinetic-pharmacodynamic model method. Methods: The healthy and infected pigs were intramuscularly administered CEF hydrochloride oily suspension at a single dose of 5 mg/kg, and then the plasma and pulmonary epithelial lining fluid (PELF) were collected at different times. The minimum inhibitory concentration (MIC), minimal bactericidal concentration, mutant prevention concentration (MPC), post-antibiotic effect (PAE), and time-killing curves were determined. Subsequently, the area under the curve by the MIC (AUC_0-24h/MIC) values of desfuroylceftiofur (DFC) in the PELF was obtained by integrating in vivo pharmacokinetic data of the infected pigs and ex vivo pharmacodynamic data using the sigmoid E_max (Hill) equation. The dose was calculated based on the AUC_0-24h/MIC values for bacteriostatic action, bactericidal action, and bacterial elimination. Results: The peak concentration, the area under the concentration-time curve, and the time to peak for PELF's DFC were 24.76 ± 0.92 ㎍/mL, 811.99 ± 54.70 ㎍·h/mL, and 8.00 h in healthy pigs, and 33.04 ± 0.99 ㎍/mL, 735.85 ± 26.20 ㎍·h/mL, and 8.00 h in infected pigs, respectively. The MIC of PELF's DFC against S. suis strain was 0.25 ㎍/mL. There was strong concentration-dependent activity as determined by MPC, PAE, and the time-killing curves. The AUC_0-24h/MIC values of PELF's DFC for bacteriostatic activity, bactericidal activity, and virtual eradication of bacteria were 6.54 h, 9.69 h, and 11.49 h, respectively. Thus, a dosage regimen of 1.94 mg/kg every 72 h could be sufficient to reach bactericidal activity. Conclusions: A rational dosage regimen was recommended, and it could assist in increasing the treatment effectiveness of CEF hydrochloride oily suspension against S. Suis infections.

• Journal of Veterinary Science
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• v.23 no.4
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• pp.51.1-51.10
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• 2022

Background: Due to the unavailability of an effective vaccine or antiviral drug against the African swine fever virus (ASFV), rapid diagnosis methods are needed to prevent highly contagious African swine fever. Objectives: The objective of this study was to establish the ladder-shape melting temperature isothermal amplification (LMTIA) assay for the detection of ASFV. Methods: LMTIA primers were designed with the p72 gene of ASFV as the target, and plasmid pUC57 was used to clone the gene. The LMTIA reaction system was optimized with the plasmid as the positive control, and the performance of the LMTIA assay was compared with that of the commercial real-time polymerase chain reaction (PCR) kit in terms of sensitivity and detection rate using 200 serum samples. Results: Our results showed that the LMTIA assay could detect the 10⁴ dilution of DNA extracted from the positive reference serum sample, which was the same as that of the commercial real-time PCR kit. The coincidence rate between the two assays was 100%. Conclusions: The LMTIA assay had high sensitivity, good detection, and simple operation. Thus, it is suitable for facilitating preliminary and cost-effective surveillance for the prevention and control of ASFV.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1008-1014
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• 2020

Aiming at the defect detection quality of denim fabric, this paper designs an improved algorithm based on the optimized Gabor filter. Firstly, we propose an improved defect detection algorithm of jean fabric based on the maximum two-dimensional image entropy and the loss evaluation function. Secondly, 24 Gabor filter banks with 4 scales and 6 directions are created and the optimal filter is selected from the filter banks by the one-dimensional image entropy algorithm and the two-dimensional image entropy algorithm respectively. Thirdly, these two optimized Gabor filters are compared to realize the common defect detection of denim fabric, such as normal texture, miss of weft, hole and oil stain. The results show that the improved algorithm has better detection effect on common defects of denim fabrics and the average detection rate is more than 91.25%.

• Journal of Communications and Networks
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• v.11 no.6
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• pp.556-563
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• 2009

A side channel analysis is a very efficient attack against small devices such as smart cards and wireless sensor nodes. In this paper, we propose an efficient key detection method using a peak selection algorithm in order to find the advanced encryption standard secret key from electromagnetic signals. The proposed method is applied to a correlation electromagnetic analysis (CEMA) attack against a wireless sensor node. Our approach results in increase in the correlation coefficient in comparison with the general CEMA. The experimental results show that the proposed method can efficiently and reliably uncover the entire 128-bit key with a small number of traces, whereas some extant methods can reveal only partial subkeys by using a large number of traces in the same conditions.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.75-80
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• 2018

The smart city is developing an energy system efficiently through a common management of the city resource for the growth and a low carbon social. However, the smart city doesn't counter a verification effectively about a anomaly pattern detection when existing security technology (authentication, integrity, confidentiality) is used by fixed security key and key deodorization according to generated big data. This paper is proposed the "security nonce generation based on security nonce generation" for anomaly pattern detection of the adversary and a safety of the key is high through the key generation of the KDC (Key Distribution Center; KDC) for improvement. The proposed scheme distributes the generated security nonce and authentication keys to each facilities system by the KDC. This proposed scheme can be enhanced to the security by doing the external pattern detection and changed new security key through distributed security nonce with keys. Therefore, this paper can do improving the security and a responsibility of the smart city platform management data through the anomaly pattern detection and the safety of the keys.

• Journal of Communications and Networks
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• v.14 no.1
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• pp.34-39
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• 2012

Collisions between tags greatly reduce the identification speed in radio frequency identification (RFID) systems and increase communication overhead. In particular for an active RFID system, tags are powered by small batteries, and a large number of re-transmissions caused by collisions can deteriorate and exhaust the tag energy which may result in missing tags. An efficient collision-free arbitration protocol for active RFID systems is proposed in this paper. In this protocol, a new mechanism involving collision detection, collision avoidance, and fast tag access is introduced. Specifically, the pulse burst duration and busy-tone-detection delay are introduced between the preamble and data portion of a tag-to-reader (T-R) frame. The reader identifies tag collision by detecting pulses and transmits a busy tone to avoid unnecessary transmission when collision occurs. A polling process is then designed to quickly access the collided tags. It is shown that the use of the proposed protocol results in a system throughput of 0.612, which is an obvious improvement when compared to the framed-slotted ALOHA (FSA) arbitration protocol for ISO/IEC 18000-7 standard. Furthermore, the proposed protocol greatly reduces communication overhead, which leads to energy conservation.

• Journal of Microbiology and Biotechnology
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• v.27 no.3
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• pp.417-428
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• 2017

Diseases caused by foodborne or waterborne pathogens are emerging. Many pathogens can enter into the viable but nonculturable (VBNC) state, which is a survival strategy when exposed to harsh environmental stresses. Pathogens in the VBNC state have the ability to evade conventional microbiological detection methods, posing a significant and potential health risk. Therefore, controlling VBNC bacteria in food processing and the environment is of great importance. As the typical one of the gram-negatives, Escherichia coli (E. coli) is a widespread foodborne and waterborne pathogenic bacterium and is able to enter into a VBNC state in extreme conditions (similar to the other gram-negative bacteria), including inducing factors and resuscitation stimulus. VBNC E. coli has the ability to recover both culturability and pathogenicity, which may bring potential health risk. This review describes the concrete factors (nonthermal treatment, chemical agents, and environmental factors) that induce E. coli into the VBNC state, the condition or stimulus required for resuscitation of VBNC E. coli, and the methods for detecting VBNC E. coli. Furthermore, the mechanism of genes and proteins involved in the VBNC E. coli is also discussed in this review.

• Journal of Veterinary Science
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• v.25 no.1
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• pp.18.1-18.27
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• 2024

Mastitis is one of the most widespread infectious diseases that adversely affects the profitability of the dairy industry worldwide. Accurate diagnosis and identification of pathogens early to cull infected animals and minimize the spread of infection in herds is critical for improving treatment effects and dairy farm welfare. The major pathogens causing mastitis and pathogenesis are assessed first. The most recent and advanced strategies for detecting mastitis, including genomics and proteomics approaches, are then evaluated. Finally, the advantages and disadvantages of each technique, potential research directions, and future perspectives are reported. This review provides a theoretical basis to help veterinarians select the most sensitive, specific, and cost-effective approach for detecting bovine mastitis early.