Wavelet Fusion Application in Water Quality Warning Based on Bio-Detection Technology

2013 ◽  
Vol 295-298 ◽  
pp. 924-927 ◽  
Author(s):  
Yi Hong Wang ◽  
Jun Chen ◽  
Shi Feng Tao
Keyword(s):  
Water Quality ◽  
Edge Detection ◽  
Warning System ◽  
Abnormal Behavior ◽  
Fish Movement ◽  
Movement Model ◽  
Core Technology ◽  
Detection Technology ◽  
Segmented Images ◽  
Fused Image

In water quality early warning system based on the abnormal behavior of fish, the core technology is building the fish movement model and obtaining the movement parameter based on this model. The fish body image accurate segmentation is the key to the implementation of this core technique. The single edge detection method can not accurately detect fish all edges. In the paper, the proposed solution is that the original image is firstly segmented by Canny operator and Log operator respectively and then the two segmented images are fused based on the wavelet transform. The fused image will obtain more complete target information from the two segmented images. The fish image acquired by the machine vision is processed according to the idea. The result shows that this method can obtain better edge detection effect. It will provide technical support for the live fish movement modeling.

Study on Driver's Unsafe Gaze Behavior Detection Technology

2013 ◽  
Vol 427-429 ◽  
pp. 1903-1906
Author(s):  
Peng Wang ◽  
Zhi Qiang Liu
Keyword(s):  
Detection System ◽  
Characteristic Curve ◽  
Abnormal Behavior ◽  
Gaze Behavior ◽  
Source Information ◽  
Eyelid Closure ◽  
Behavior Detection ◽  
Detection Technology ◽  
Level Information ◽  
Behavior Characteristics

A system for detecting and evaluating drivers gaze behavior was proposed. A system for recognizing the drivers unsafe gaze behavior was established using multi-level information and fusion decision method as well. The driving environment and condition is complex as well as the gaze behavior characteristics, and given that, a solution consists of patten classification and the multi-information decision-level fusion were put forward to estimate the different kind model of the driver's gaze behavior. In order to test the proposed strategies,the real time driver's gaze behavior detection system was established. The T characteristic curve proposed through the abnormal behavior parameters of the transverse width between the eyes and the vertical distance between mouth and the midpoint of two eyes, combined with the driver's eyelid closure and the proportion and location characteristics of iris - sclera were studied to get the characterization of the drivers gaze status information. The simulation results indicate that the adaptability and accuracy as well as the intelligent level is significantly improved by using the pattern classification and decision-making technology through multi-source information fusion.

scholarly journals GPS-Spoofing Attack Detection Technology for UAVs Based on Kullback–Leibler Divergence

Drones ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 8
Author(s):  
Elena Basan ◽  
Alexandr Basan ◽  
Alexey Nekrasov ◽  
Colin Fidge ◽  
Nikita Sushkin ◽  
...  
Keyword(s):  
Cyber Security ◽  
Detection System ◽  
Attack Detection ◽  
Abnormal Behavior ◽  
Mathematical Methods ◽  
Training Time ◽  
Detection Technology ◽  
Normal Behavior ◽  
Leibler Divergence ◽  
Aerial Vehicle

Here, we developed a method for detecting cyber security attacks aimed at spoofing the Global Positioning System (GPS) signal of an Unmanned Aerial Vehicle (UAV). Most methods for detecting UAV anomalies indicative of an attack use machine learning or other such methods that compare normal behavior with abnormal behavior. Such approaches require large amounts of data and significant “training” time to prepare and implement the system. Instead, we consider a new approach based on other mathematical methods for detecting UAV anomalies without the need to first collect a large amount of data and describe normal behavior patterns. Doing so can simplify the process of creating an anomaly detection system, which can further facilitate easier implementation of intrusion detection systems in UAVs. This article presents issues related to ensuring the information security of UAVs. Development of the GPS spoofing detection method for UAVs is then described, based on a preliminary study that made it possible to form a mathematical apparatus for solving the problem. We then explain the necessary analysis of parameters and methods of data normalization, and the analysis of the Kullback—Leibler divergence measure needed to detect anomalies in UAV systems.

scholarly journals Study on Pre-Warning Method of the Lateral Security of Heavy Vehicle in Deteriorative Weather

2014 ◽  
Vol 8 (1) ◽  
pp. 292-296
Author(s):  
Zhi-Guo Zhao ◽  
Min Chen ◽  
Nan Chen ◽  
Yong-Bing Zhao ◽  
Xin Chen
Keyword(s):  
Friction Coefficient ◽  
Critical Speed ◽  
Warning System ◽  
Heavy Vehicle ◽  
Heavy Vehicles ◽  
Core Technology ◽  
Road Friction ◽  
Turning Radius ◽  
Safety Features ◽  
Road Friction Coefficient

The lateral security of heavy vehicle in deteriorative weather is one of the main causes of accidents of vehicles on roads. Road safety has become a subject of great concern to institutions of higher education and scientific research institutions. There are important theoretical and practical significances to explore applicable and effective lateral safety warning methods of heavy vehicles. One of the purposes of this paper is to provide a good theoretical basis for the core technology of heavy vehicle safety features for our country's independent research and development. Aiming at the issue of lateral security of heavy vehicle for road conditions in deteriorative weather, this paper constructs the framework of the lateral security pre-warning system of heavy vehicles based on cooperative vehicle infrastructure. Moreover, it establishes vehicle lateral security statics model through analysis of the force of the car in the slope with section bending and states the parameters of vehicles for no rollover. The side slip is indexed to calculate critical speed of vehicles in a bend. This paper also analyzes the influence of road friction coefficient, the road gradient and the turning radius on the lateral security of the vehicle with critical speed on the asphalt pavement with surface conditions ranging from wet, dry, snowing or icy. The calculation results show that the bad weather road conditions, road friction coefficient and turning radius have obvious influence on the lateral security critical speed. Experimental results indicate that the critical speed error warning is within 4% and it meets the design requirements.

New Design for Water Quality Early Warning System

2012 ◽  
pp. 681-685
Author(s):  
Tian Jing ◽  
Zheng Shuyin ◽  
Zhang Guangxin ◽  
Hou Dibo ◽  
Huang Pingjie ◽  
...  
Keyword(s):  
Water Quality ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System

scholarly journals Fluctuations of Phytophthora and Pythium spp. in Components of a Recycling Irrigation System

Plant Disease ◽  
2003 ◽  
Vol 87 (12) ◽  
pp. 1500-1506 ◽  
Author(s):  
Elizabeth A. Bush ◽  
Chuanxue Hong ◽  
Erik L. Stromberg
Keyword(s):  
Water Quality ◽  
Plant Pathogens ◽  
Management Practices ◽  
Irrigation System ◽  
Phytophthora Capsici ◽  
Selective Media ◽  
Irrigation Reservoir ◽  
Phytophthora Spp ◽  
Detection Technology ◽  
Pollutant Discharge

Stringent standards of water quality have prompted many horticultural enterprises to limit pollutant discharge associated with nutrient and pesticide applications. Collecting and recycling effluent is a method that has been implemented by many operations to contain pollutants; however, plant pathogens may be spread through recycled effluent. In this study, Phytophthora and Pythium spp. present in a water-recycling irrigation system at a perennial container nursery in southwestern Virginia were characterized using filtering and baiting techniques with two selective media. Members of Phytophthora were identified to species, whereas Pythium spp. were identified to genus only. Pythium spp. were recovered more frequently and in greater numbers than Phytophthora spp. Phytophthora capsici, P. citricola, P. citrophthora, P. cryptogea, P. drechsleri, and P. nicotianae were recovered in filtering assays. Only P. cryptogea and P. drechsleri were identified from baits placed on the surface of the irrigation reservoir, whereas P. cactorum, P. capsici, P. citricola, P. citrophthora, P. cryptogea, and P. drechsleri were recovered at depths, specifically at 1 and 1.5 m. This research provides data for development of detection technology and management practices for plant pathogens in irrigation water and may lead to improvements in conventional assay protocols.

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