Calculation model and analysis of laser echo power based on dual‐transmitter and dual‐receiver laser circumferential scanning detection mechanism

2021 ◽  
Author(s):  
Zhijun Shi ◽  
Zhiyong Lei
Keyword(s):  
Calculation Model ◽  
Detection Mechanism ◽  
Scanning Detection

A fuzzy neural network approach for modeling the growth kinetics of FeB and Fe2B layers during the boronizing process

2018 ◽  
Vol 106 (6) ◽  
pp. 603 ◽  
Author(s):  
Bendaoud Mebarek ◽  
Mourad Keddam
Keyword(s):  
Neural Network ◽  
Experimental Data ◽  
Fuzzy Neural Network ◽  
Treatment Time ◽  
Calculation Model ◽  
Average Error ◽  
Network Approach ◽  
Neural Network Approach ◽  
Fuzzy Neural ◽  
Kinetics Of

In this paper, we develop a boronizing process simulation model based on fuzzy neural network (FNN) approach for estimating the thickness of the FeB and Fe2B layers. The model represents a synthesis of two artificial intelligence techniques; the fuzzy logic and the neural network. Characteristics of the fuzzy neural network approach for the modelling of boronizing process are presented in this study. In order to validate the results of our calculation model, we have used the learning base of experimental data of the powder-pack boronizing of Fe-15Cr alloy in the temperature range from 800 to 1050 °C and for a treatment time ranging from 0.5 to 12 h. The obtained results show that it is possible to estimate the influence of different process parameters. Comparing the results obtained by the artificial neural network to experimental data, the average error generated from the fuzzy neural network was 3% for the FeB layer and 3.5% for the Fe2B layer. The results obtained from the fuzzy neural network approach are in agreement with the experimental data. Finally, the utilization of fuzzy neural network approach is well adapted for the boronizing kinetics of Fe-15Cr alloy.

Development of the Partial Discharge Inception Calculation Model in a Non-uniform Air Gap Considering the Effect of Humidity

2011 ◽  
Vol 131 (12) ◽  
pp. 1017-1023 ◽  
Author(s):  
Norihito Yanagita ◽  
Tatsuro Kato ◽  
Toshiaki Rokunohe ◽  
Takeshi Iwata ◽  
Hiroki Kojima ◽  
...  
Keyword(s):  
Partial Discharge ◽  
Calculation Model ◽  
Air Gap

HULK and DDoS Attacks in Web Applications with Detection Mechanism

2018 ◽  
Vol 6 (6) ◽  
pp. 192
Author(s):  
Amit Sharma
Keyword(s):  
Web Applications ◽  
Denial Of Service ◽  
Single Server ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Application Layer ◽  
Detection Mechanism ◽  
Plan Execution ◽  
Social Affair ◽  
Server Application

Distributed Denial of Service attacks are significant dangers these days over web applications and web administrations. These assaults pushing ahead towards application layer to procure furthermore, squander most extreme CPU cycles. By asking for assets from web benefits in gigantic sum utilizing quick fire of solicitations, assailant robotized programs use all the capacity of handling of single server application or circulated environment application. The periods of the plan execution is client conduct checking and identification. In to beginning with stage by social affair the data of client conduct and computing individual user’s trust score will happen and Entropy of a similar client will be ascertained. HTTP Unbearable Load King (HULK) attacks are also evaluated. In light of first stage, in recognition stage, variety in entropy will be watched and malevolent clients will be recognized. Rate limiter is additionally acquainted with stop or downsize serving the noxious clients. This paper introduces the FAÇADE layer for discovery also, hindering the unapproved client from assaulting the framework.

A Surface Plasmon Resonance Based Inhibition Immunoassay for Sensitive and Selective Detection of 17β-Estradiol

2018 ◽  
Author(s):  
Yong Cao ◽  
Mark T. McDermott
Keyword(s):  
Surface Plasmon Resonance ◽  
Surface Plasmon ◽  
Plasmon Resonance ◽  
Quantitative Measurement ◽  
Dynamic Range ◽  
Indirect Detection ◽  
Negative Slope ◽  
Chip Surface ◽  
Detection Mechanism ◽  
17Β Estradiol

<div> <div> <div> <p>Quantitative measurement of small-molecule metabolites is now emerging as an effective way to link the metabolite profile to disease state. Surface plasmon resonance (SPR) is a sensing platform that has demonstrated applicability for a large range of biomolecules. However, direct detection of small molecules with SPR challenges the refractive index based detection mechanism. Herein, we utilized an indirect detection format and developed an inhibition immunoassay for the quantitative measurement of 17β-estradiol (E2) using SPR. One competitor, BSA-E2 conjugate, was immobilized to the SPR chip via the reaction between the primary amino group of the conjugate and the succinimide group (NHS) introduced by the formation of a thiol-NHS monolayer on gold surface. Free E2 molecules compete with BSA-E2 on chip surface for binding sites provided by a monoclonal anti-E2 antibody. It was found the binding affinity of the antibody to BSA-E2 conjugate increases with decreasing surface coverage of BSA-E2 conjugate. Under optimal conditions, a sigmoidal calibration curve with a negative slope and a dynamic range from 10 pM to 2 nM was generated. The detection limit of the immunoassay is estimated to be 0.3 pM. Moreover, the immunoassay exhibits high specificity for E2 detection using estrone (E1) as a potential interference.</p></div></div></div>

Regression analysis of indicators of a numerical experiment to determine the cooling time of oil

2020 ◽  
pp. 89-97
Author(s):  
A. U. Yakupov ◽  
D. A. Cherentsov ◽  
K. S. Voronin ◽  
Yu. D. Zemenkov
Keyword(s):  
Regression Analysis ◽  
Computer Experiment ◽  
Calculation Model ◽  
Cooling Time ◽  
Regression Coefficients ◽  
Fisher Criterion ◽  
Empirical Relationships ◽  
Factors Affecting ◽  
Oil Pipeline ◽  
Significant Regression

The article performed the processing of the results of a computer experiment to determine the cooling time of oil in a stopped oil pipeline. We proposed a calculation model in previous works that allows you to simulate the process of cooling oil.There was a need to verify the previously obtained results when conducting a laboratory experiment on a stand with soil. To conduct the experiment, it was necessary to conduct the planning of the experiment. The factors affecting the cooling time of oil in the oil pipeline, which will vary in the proposed experiment, are determined, empirical relationships are established. A regression analysis was carried out, and the dispersion homogeneity was checked using the Cochren criterion. The estimates of reproducibility variances are calculated. The adequacy hypothesis was tested using the Fisher criterion. Significant regression coefficients are established.

Case study: Theoretical calculation model and variable condition analysis research on the water-splashing noise for natural draft wet cooling towers

2020 ◽  
Vol 68 (2) ◽  
pp. 137-145
Author(s):  
Yang Zhouo ◽  
Ming Gao ◽  
Suoying He ◽  
Yuetao Shi ◽  
Fengzhong Sun
Keyword(s):  
Theoretical Model ◽  
Sound Pressure Level ◽  
Water Droplet ◽  
Water Distribution ◽  
Sound Pressure ◽  
Cooling Tower ◽  
Distribution Patterns ◽  
Calculation Model ◽  
Pressure Level ◽  
Cooling Towers

Based on the basic theory of water droplets impact noise, the generation mechanism and calculation model of the water-splashing noise for natural draft wet cooling towers were established in this study, and then by means of the custom software, the water-splashing noise was studied under different water droplet diameters and water-spraying densities as well as partition water distribution patterns conditions. Comparedwith the water-splashing noise of the field test, the average difference of the theoretical and the measured value is 0.82 dB, which validates the accuracy of the established theoretical model. The results based on theoretical model showed that, when the water droplet diameters are smaller in cooling tower, the attenuation of total sound pressure level of the water-splashing noise is greater. From 0 m to 8 m away from the cooling tower, the sound pressure level of the watersplashing noise of 3 mm and 6 mm water droplets decreases by 8.20 dB and 4.36 dB, respectively. Additionally, when the water-spraying density becomes twice of the designed value, the sound pressure level of water-splashing noise all increases by 3.01 dB for the cooling towers of 300 MW, 600 MW and 1000 MW units. Finally, under the partition water distribution patterns, the change of the sound pressure level is small. For the R s/2 and Rs/3 partition radius (Rs is the radius of water-spraying area), when the water-spraying density ratio between the outer and inner zone increases from 1 to 3, the sound pressure level of water-splashing noise increases by 0.7 dB and 0.3 dB, respectively.

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