Data Analysis and Temperature Compensation of Laser CH4 Detection System

2012 ◽  
Vol 608-609 ◽  
pp. 433-436 ◽  
Author(s):  
Yan Fang Li ◽  
Chang Wang ◽  
Yu Bei Wei ◽  
Yan Jie Zhao ◽  
Tingting Zhang ◽  
...  
Keyword(s):  
Data Analysis ◽  
Absorption Coefficient ◽  
Fiber Laser ◽  
Temperature Compensation ◽  
Detection System ◽  
Fast Response ◽  
High Accuracy ◽  
Environment Temperature

One fiber laser CH4 detection system based on the spectrum absorption is provided. The system has the advantages such as high accuracy, fast response and highly specific and so on. But the absorption coefficient of the methane and the characteristic of the electronic and optic device are all affected by the temperature. So the test value has interdependency to the environment temperature. In this paper, we give the measure principle of the detector and the analyses of the data which last one month uninterrupted. And then the temperature compensate was introduced to improve the performance of the detector.

Estimating Pigment Concentrations from Spectral Images Using an Encoder‐Decoder Neural Network

2020 ◽  
Vol 64 (3) ◽  
pp. 30502-1-30502-15
Author(s):  
Kensuke Fukumoto ◽  
Norimichi Tsumura ◽  
Roy Berns
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Absorption Coefficient ◽  
Spectral Data ◽  
High Accuracy ◽  
Pigment Concentration ◽  
Scattering Coefficient ◽  
A Value ◽  
Input And Output ◽  
Pigment Concentrations

Abstract A method is proposed to estimate the concentration of pigments mixed in a painting, using the encoder‐decoder model of neural networks. The model is trained to output a value that is the same as its input, and its middle output extracts a certain feature as compressed information about the input. In this instance, the input and output are spectral data of a painting. The model is trained with pigment concentration as the middle output. A dataset containing the scattering coefficient and absorption coefficient of each of 19 pigments was used. The Kubelka‐Munk theory was applied to the coefficients to obtain many patterns of synthetic spectral data, which were used for training. The proposed method was tested using spectral images of 33 paintings, which showed that the method estimates, with high accuracy, the concentrations that have a similar spectrum of the target pigments.

Modelling the effects of distance on the probability of fire detection from lookouts

2006 ◽  
Vol 15 (2) ◽  
pp. 197 ◽  
Author(s):  
Francisco Castro Rego ◽  
Filipe Xavier Catry
Keyword(s):  
Forest Fires ◽  
Detection System ◽  
Fire Detection ◽  
Fast Response ◽  
Fire Loss ◽  
Detection Function ◽  
Related Factors ◽  
New Approach ◽  
Forest Fire Management ◽  
In Fire

In the management of forest fires, early detection and fast response are known to be the two major actions that limit both fire loss and fire-associated costs. There are several inter-related factors that are crucial in producing an efficient fire detection system: the strategic placement and networking of lookout towers, the knowledge of the fire detection radius for lookout observers at a given location and the ability to produce visibility maps. This study proposes a new methodology in the field of forest fire management, using the widely accepted Fire Detection Function Model to evaluate the effect of distance and other variables on the probability that an object is detected by an observer. In spite of the known variability, the model seems robust when applied to a wide variety of situations, and the results obtained for the effective detection radius (13.4 km for poor conditions and 20.6 km for good conditions) are in general agreement with those proposed by other authors. We encourage the application of the new approach in the evaluation or planning of lookout networks, in addition to other integrated systems used in fire detection.

Extended Mobility Carried Out with a Double Hexapod Robot

2010 ◽  
Vol 166-167 ◽  
pp. 271-276 ◽  
Author(s):  
Mihai Margaritescu ◽  
Ana Maria Eulampia Ivan ◽  
Vlad Vaduva ◽  
Cornel Brisan
Keyword(s):  
Fast Response ◽  
High Accuracy ◽  
Positioning System ◽  
Hexapod Robot ◽  
Parallel Kinematics ◽  
High Stiffness ◽  
Serial Robots ◽  
Visual Comparison ◽  
Operating Space

The double hexapod robot consists in two staged hexapod platforms – Stewart Gough platforms - combining in a certain measure the advantages of the robots with parallel kinematics and of the serial robots: high accuracy, high stiffness, fast response and small dimensions, having an extended operating space. Different modelling and construction aspects were described in few previous articles. Some examples of trajectories generated with this positioning system are now presented to illustrate its mobility, as well as the workspaces for one and two hexapods in order to make possible a visual comparison between the two volumes.

scholarly journals Intrusion Detection System Methodologies Based on Data Analysis

2010 ◽  
Vol 5 (2) ◽  
pp. 10-20 ◽  
Author(s):  
Shaik Akbar ◽  
Dr.K.Nageswara Rao ◽  
Dr.J.A. Chandulal
Keyword(s):  
Data Analysis ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System

scholarly journals PENDETEKSIAN OBJEK ROKOK PADA VIDEO BERBASIS PENGOLAHAN CITRA DENGAN MENGGUNAKAN METODE HAAR CASCADE CLASSIFIER

2018 ◽  
Vol 1 (3) ◽  
pp. 92
Author(s):  
Kadek Oki Sanjaya ◽  
Gede Indrawan ◽  
Kadek Yota Ernanda Aryanto
Keyword(s):  
Image Processing ◽  
Detection System ◽  
High Accuracy ◽  
Special Study ◽  
Cascade Classifier ◽  
Integral Image ◽  
Main Method ◽  
Average Accuracy ◽  
Haar Features ◽  
Haar Cascade

Object detection is a topic widely studied by the scientists as a special study in image processing. Although applications of this topic have been implemented, but basically this technology is not yet mature, futher research is needed to developed to obtain the desired result. The aim of the present study is to detect cigarette objects on video by using the Viola Jones method (Haar Cascade Classifier). This method known to have speed and high accuracy because of combining some concept (Haar features, integral image, Adaboost, and Cascade Classifier) to be a main method to detect objects. In this research, detection testing of cigarettes object is in samples of video with the resolution 160x120 pixels, 320x240 pixels, 640x480 pixels under condition of on 1 cigarette object and condition 2 cigarettes object. The result of this research indicated that percentage of average accuracy highest 93.3% at condition 1 cigarette object and 86,7% in the condition 2 cigarette object that was detected on the video with resolution 640x480 pixels, while the percentage of accuracy lowest 90% at condition 1cigarette object, and 81,7% at the condition 2 cigarette objects, detected on the video with the lowest resolution 160x120 pixels. The percentage of average errors at detection cigarettes object was inversely with percentage of accuracy. So that the detection system is able to better recognize the object of the cigarette, then the number of samples in the database needs to be improved and able to represent various types of cigarettes under various conditions and can be added new parameters related to cigarette object

scholarly journals Efficient Detection of Phishing Websites Using Multilayer Perceptron

2020 ◽  
Vol 14 (11) ◽  
pp. 22
Author(s):  
Ammar Jamil Odeh ◽  
Ismail Keshta ◽  
Eman Abdelfattah
Keyword(s):  
Neural Network ◽  
Multilayer Perceptron ◽  
Detection System ◽  
High Accuracy ◽  
Internet Fraud ◽  
Efficient Detection ◽  
Novel Approach

Phishing is a type of Internet fraud that aims to acquire the credential of users via scamming websites. In this paper, a novel approach is utilized that uses a Neural Network with a multilayer perceptron to detect the scam URL. The proposed system improves the accuracy of the scam detection system as it achieves a high accuracy percentage of 98.5%.

Design of Self-Compensated High Accuracy Fuel Level Sensor

2013 ◽  
Vol 281 ◽  
pp. 23-27
Author(s):  
Mei Yuan ◽  
Si Si Xiong ◽  
Shao Peng Dong
Keyword(s):  
Data Analysis ◽  
Sampling Technique ◽  
High Accuracy ◽  
Initial Position ◽  
The Self ◽  
Level Measurement ◽  
Level Sensor ◽  
Capacitive Level ◽  
Fuel Level ◽  
Adhesion Effect

A brand new self-compensated capacitive fuel level sensor has been proposed in this paper. Through mathematics manipulation and theoretical analysis, we design the self-compensated structure of capacitive level sensor. The multiple segmentation structure makes compensation for temperature and medium possible. Furthermore, the effect caused by adhesion on the sensor electrodes if the adhesion fails to return initial position when the plane’s attitude is changing has been analyzed. Additionally, based on RF admittance theory, the transducer which can eliminate the adhesion effect has been designed and implemented using phase-locked sampling technique. Through level experiment and data analysis, the fuel level sensor proved to achieve all the destinations, including compensation for temperature and medium and elimination of adhesion effect. Hence, the accuracy of level measurement has been improved.

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