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DAMAGE DETECTION AND LOCATION FOR IN AND OUT-OFPLANE CURVED BEAMS USING FUZZY LOGIC BASED ON FREQUENCY DIFFERENCE
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In this study, structures damage identification method based on changes in the dynamic characteristics
(frequencies) of the structure are examined, stiffness as well as mass matrices of the curved
(in and out-of-plane vibration) beam elements is formulated using Hamilton's principle. Each node
of both of them possesses seven degrees of freedom including the warping degree of freedom. The
curved beam element had been derived based on the Kang and Yoo’s thin-walled curved beam theory
in 1994. A computer program was developing to carry out free vibration analyses of the curved
beam as well as straight beam. Comparing with the frequencies for other researchers using the general
purpose program MATLAB. Fuzzy logic system (FLS) applied in two stages to calculate the
damage extent and location in simply in and out-of- plane curved beam, the damage deduce by reduction
in stiffness for three levels (20%, 40%, 60%). At the first stage the output faults of the fuzzy system represented by four levels of damage in curved beam (undamaged, slight, moderate, and severe), and at second stage indicate damage location at element with two defuzzification methods (centroid and middle of maximum). The results show that the frequency difference method is efficient to indicate and quantify
damage with accuracy about (99.5%) for slight and moderate damage about (100%) for severe damage. Consequently fuzzy logic performs well for detecting, locating and quantifying damage in curved beam.

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Publication Date
Fri Jan 01 2016
Journal Name
International Journal Of Advanced Computer Science And Applications
Face Detection and Recognition Using Viola-Jones with PCA-LDA and Square Euclidean Distance
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Publication Date
Mon May 14 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Detection and Detoxification of Aflatoxin B1 from Fish Feedstuff Using Microwave and Ozone Gas
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    The current study was designed to investigate the occurrence of aflatoxin B1 in thirty two samples of fish feedstuff were collected randomly from some Iraqi local markets using ELISA technique. Aflatoxin B1 was detected in thirty samples and the concentration of toxin ranged from 50 ppb to 1000 ppb.  

   Microwave and ozone were used for detoxification of aflatoxin B1 from sample with highest concentration (1000 ppb), two degree of temperature and two times (50°C and 100°C for 5 minute and 10 minute to each degree) of microwave, also two doses and two times (2 g and 4 g for 5 minute and 10 minute to each dose) of ozone gas were used.

   Degradation of aflatoxin B1 by

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Publication Date
Thu Feb 28 2019
Journal Name
Iraqi Journal Of Science
Skin Detection using Improved ID3 Algorithm
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Skin detection is classification the pixels of the image into two types of pixels skin and non-skin. Whereas, skin color affected by many issues like various races of people, various ages of people gender type. Some previous researchers attempted to solve these issues by applying a threshold that depends on certain ranges of skin colors. Despite, it is fast and simple implementation, it does not give a high detection for distinguishing all colors of the skin of people. In this paper suggests improved ID3 (Iterative Dichotomiser) to enhance the performance of skin detection. Three color spaces have been used a dataset of RGB obtained from machine learning repository, the University of California Irvine (UCI), RGB color space, HSV color sp

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Publication Date
Thu Dec 21 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Recovering Time-Dependent Coefficients in a Two-Dimensional Parabolic Equation Using Nonlocal Overspecified Conditions via ADE Finite Difference Schemes
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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Sun Jan 01 2023
Journal Name
Advances In The Theory Of Nonlinear Analysis And Its Application
The Influence of the Magnetic Domain on The Peristaltic Motion of The Non-Newtonian Fluid in A Curved Tube
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Publication Date
Tue Jan 18 2022
Journal Name
Iraqi Journal Of Science
The Fuzzy Length of Fuzzy Bounded Operator
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In this paper we recall the definition of fuzzy length space on a fuzzy set after that we recall basic definitions and properties of fuzzy length. We define fuzzy bounded operator as an introduction to defined fuzzy length of an operator then we proved that the fuzzy length space FB ̃ ̃ consisting of all fuzzy bounded linear operators from a fuzzy length space ̃ into a fuzzy length space ̃ is fuzzy complete if ̃ is fuzzy complete. Also we proved that every finite dimensional fuzzy length space is fuzzy complete.

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Publication Date
Tue Sep 01 2015
Journal Name
2015 7th Computer Science And Electronic Engineering Conference (ceec)
An experimental investigation on PCA based on cosine similarity and correlation for text feature dimensionality reduction
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Publication Date
Fri Oct 02 2009
Journal Name
Noise And Health
Expert system to predict effects of noise pollution on operators of power plant using neuro-fuzzy approach
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Ration power plants, to generate power, have become common worldwide. One such one is the steam power plant. In such plants, various moving parts of heavy machines generate a lot of noise. Operators are subjected to high levels of noise. High noise level exposure leads to psychological as well physiological problems; different kinds of ill effects. It results in deteriorated work efficiency, although the exact nature of work performance is still unknown. To predict work efficiency deterioration, neuro-fuzzy tools are being used in research. It has been established that a neuro-fuzzy computing system helps in identification and analysis of fuzzy models. The last decade has seen substantial growth in development of various neuro-fuzzy systems

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Publication Date
Wed May 10 2017
Journal Name
Australian Journal Of Basic And Applied Sciences
Block-based Image Steganography for Text Hiding Using YUV Color Model and Secret Key Cryptography Methods
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