Fast Detection of Explosives Vapours and Particles by Chemiluminescence Technique

2004 ◽  
pp. 71-80 ◽  
Author(s):  
Dao Hinh Nguyen ◽  
Shirley Locquiao ◽  
Phuong Huynh ◽  
Qiaoling Zhong ◽  
Wen He ◽  
...  
Keyword(s):  
Fast Detection ◽  
Detection Of Explosives

Fast Detection of Ground Penetrating Radar Objects Based on Cross Correlation and Hough Transform

2014 ◽  
Vol 35 (5) ◽  
pp. 1156-1162 ◽  
Author(s):  
Jian Wang ◽  
Xiao Yuan ◽  
Yu Li ◽  
Chun-lin Huang ◽  
Yi Su
Keyword(s):  
Ground Penetrating Radar ◽  
Hough Transform ◽  
Cross Correlation ◽  
Fast Detection ◽  
Ground Penetrating

Improving Mycobacterium spp. detection in water: a new methodological proposal

2004 ◽  
Vol 4 (2) ◽  
pp. 103-106
Author(s):  
R. Santos ◽  
S. Gonçalves ◽  
F. Macieira ◽  
F. Oliveira ◽  
R. Rodrigues ◽  
...  
Keyword(s):  
Water Samples ◽  
Recovery Rate ◽  
Opportunistic Infections ◽  
Environmental Water ◽  
Environmental Water Samples ◽  
Sample Treatment ◽  
Detection Time ◽  
Fast Detection ◽  
Enrichment Step ◽  
Mycobacterium Spp

In recent years, non-tuberculous mycobacteria (NTM), once considered merely environmental saprophytes, have emerged as a major cause of opportunistic infections. There is no evidence of human-to-human transmission but they have been found in several environmental water samples. It is, therefore, of the utmost importance to develop methods of rapidly and accurately detecting non-tuberculous mycobacteria in water samples. To obtain a maximum recovery rate and a reduction of Mycobacterium spp. detection time in water samples, different decontamination, enrichment procedures and antibiotics supplements were tested before the inoculation into the Bactec® system. The proposed method of sample treatment (decrease in the decontamination time, followed for a peptone pre-enrichment step and an aztreonam and cefepime supplement) before the inoculation into the Bactec® system proved to be a good option for reliable and fast detection of Mycobacterium spp. in water samples.

Fast detection of system nonlinearity using nonstationary signals

2010 ◽  
Vol 24 (7) ◽  
pp. 2065-2075 ◽  
Author(s):  
E. Zhang ◽  
J. Antoni ◽  
R. Pintelon ◽  
J. Schoukens
Keyword(s):  
Nonstationary Signals ◽  
Fast Detection ◽  
System Nonlinearity

scholarly journals On Combining DeepSnake and Global Saliency for Detection of Orchard Apples

2021 ◽  
Vol 11 (14) ◽  
pp. 6269
Author(s):  
Wang Jing ◽  
Wang Leqi ◽  
Han Yanling ◽  
Zhang Yun ◽  
Zhou Ruyan
Keyword(s):  
Saliency Detection ◽  
Color Difference ◽  
Saliency Map ◽  
Apple Fruit ◽  
Initial Contour ◽  
Detection Accuracy ◽  
Natural Environments ◽  
Fast Detection ◽  
Single Target ◽  
Training Samples

For the fast detection and recognition of apple fruit targets, based on the real-time DeepSnake deep learning instance segmentation model, this paper provided an algorithm basis for the practical application and promotion of apple picking robots. Since the initial detection results have an important impact on the subsequent edge prediction, this paper proposed an automatic detection method for apple fruit targets in natural environments based on saliency detection and traditional color difference methods. Combined with the original image, the histogram backprojection algorithm was used to further optimize the salient image results. A dynamic adaptive overlapping target separation algorithm was proposed to locate the single target fruit and further to determine the initial contour for DeepSnake, in view of the possible overlapping fruit regions in the saliency map. Finally, the target fruit was labeled based on the segmentation results of the examples. In the experiment, 300 training datasets were used to train the DeepSnake model, and the self-built dataset containing 1036 pictures of apples in various situations under natural environment was tested. The detection accuracy of target fruits under non-overlapping shaded fruits, overlapping fruits, shaded branches and leaves, and poor illumination conditions were 99.12%, 94.78%, 90.71%, and 94.46% respectively. The comprehensive detection accuracy was 95.66%, and the average processing time was 0.42 s in 1036 test images, which showed that the proposed algorithm can effectively separate the overlapping fruits through a not-very-large training samples and realize the rapid and accurate detection of apple targets.

Implementation of medium voltage remote controlled switches to improve quality performance indexes – a case study

2020 ◽  
Vol 21 (4) ◽  
Author(s):  
Julio Cezar Santos ◽  
Wagner Santos ◽  
Guilherme Cestaro ◽  
Marcio Zamboti Fortes ◽  
Henrique Henriques
Keyword(s):  
Energy Distribution ◽  
Electric Energy ◽  
Regulatory Agencies ◽  
Quality Performance ◽  
Medium Voltage ◽  
Fast Detection ◽  
Performance Indexes ◽  
Short Time ◽  
Operation Center

AbstractThe growing demand for quality in the Energy Distribution Service, both by consumers and by regulatory agencies, obliges most distribution utilities to apply technologies that can be easily implemented and produce results in a short term horizon. The telecontrol technology is an essential tool every time it is necessary to fast restore the energy supply. This technology, which is completely supervised and controlled by the system operation center, allows the fast detection of a fault at a distance and switch an equipment without the aid of the operating crew, thus reducing the time that the power supply is unavailable. The present paper describes a Telecontrol Project, incorporated in an electric energy distribution utility in Brazil and compares the results in quality improvement with others usual investment actions, such as operating and maintenance procedures, laterals protection and network reinforcement. This paper shows, analyzing the results, that to improve the reliability indexes in a short time, when the company’s economic recovery is more important, the application of remotely controlled switch is more effective.

scholarly journals Nanopore Technology for the Application of Protein Detection

Nanomaterials ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1942
Author(s):  
Xiaoqing Zeng ◽  
Yang Xiang ◽  
Qianshan Liu ◽  
Liang Wang ◽  
Qianyun Ma ◽  
...  
Keyword(s):  
Single Molecule ◽  
Protein Detection ◽  
High Sensitivity ◽  
Single Molecule Detection ◽  
Sequence Detection ◽  
Fast Detection ◽  
Material Basis ◽  
Sensing Technology ◽  
Detection Technology ◽  
Structure Recognition

Protein is an important component of all the cells and tissues of the human body and is the material basis of life. Its content, sequence, and spatial structure have a great impact on proteomics and human biology. It can reflect the important information of normal or pathophysiological processes and promote the development of new diagnoses and treatment methods. However, the current techniques of proteomics for protein analysis are limited by chemical modifications, large sample sizes, or cumbersome operations. Solving this problem requires overcoming huge challenges. Nanopore single molecule detection technology overcomes this shortcoming. As a new sensing technology, it has the advantages of no labeling, high sensitivity, fast detection speed, real-time monitoring, and simple operation. It is widely used in gene sequencing, detection of peptides and proteins, markers and microorganisms, and other biomolecules and metal ions. Therefore, based on the advantages of novel nanopore single-molecule detection technology, its application to protein sequence detection and structure recognition has also been proposed and developed. In this paper, the application of nanopore single-molecule detection technology in protein detection in recent years is reviewed, and its development prospect is investigated.

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