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.
The Imam Ibn al-Mundhir is likely in Shafi'i school. He has outlined some issues and disagreed with his doctrine. And that the vocabulary on which he relied on the weighting is correct and correct and I choose which I say. One of the most likely issues is the delay of Isha prayer to the darkness. And other issues simplified in the folds of research and study.
In this work, the detection of zinc (Zn) ions that cause water pollution is studied using the CSNPs- Linker-alkaloids compound that was prepared by linking extracted alkaloids from Iraqi Catharanthus roseus plant with Chitosan nanoparticles (CSNPs) using maleic anhydride. This compound is characterized by an X-ray diffractometer (XRD) which shows that it has an orthorhombic structure with crystallite size in the nano dimension. Zeta Potential results show that the CSNPs-Linker-alkaloids carried a positive charge of 54.4 mV, which means it possesses high stability. The Fourier transform infrared spectroscopy (FTIR) shows a new distinct band at 1708.93 cm-1 due to C=O esterification. Scanning electron microscope (SEM) image
... Show MoreA total of 48 experiments were conducted to investigate the impact of slit weir dimensions and locations on the maximum scour depth and scour area created upstream. The slit weir model was a 110 mm slit opening, and it was installed at the end of the working section in a laboratory flume. The flume was 10.0 m long, 30 cm wide, 30 cm deep, and almost middle. It includes a 2 m working section with a mobile bed with 110 mm in thickness. In the mobile bed, two types of nonuniform sand (with a geometric standard deviation of 1.58 and 1.6) were tested separately. The weir dimensions and location were changed with flow rates. Then dimensions of the slit weir were changed from 60 x 110 mm to 60 x 70 mm (width x height), while th
... Show MoreLeft ventricular hypertrophy (LVH) caused by high blood pressure is linked to increased mortality and arrhythmia risk. This study aimed to evaluate arrhythmia in hypertensive patients due to left ventricular hypertrophy (LVH). A cross-sectional study was performed, assessing participants' blood pressure, echocardiography and electrocardiography, and Holter monitoring in certain cases. There were 300 hypertensive patients >18 years attending the cardiology unit of Baghdad medical city. The study was conducted between January–June 2022. The electrocardiograms at rest for 300 adults with hypertension were investigated. 130 (43.5%) were females, and 170 (56.5%) were males. The mean age of participants was 58 years. Forty-nine (16.3
... Show MoreSoftware-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
... Show MoreBackground: Poly-ether-ether-ketone(PEEK) has been introduced to many dental fields. Recently it was tested as a retainer wire‎ following orthodontic treatment. This study aimed to investigate the effect of changing the bonding spot size and location on the performance of PEEK retainer wires. Methods: A biomechanical study involving four three-dimensional finite element models was performed. The basic model was with a 0.8 mm cylindrical cross-section PEEK wire, bonded at the center of the lingual surface of the mandibular incisors with 4 mm in diameter composite spots. Two other models were designed with 3 mm and 5 mm composite sizes. The last model was created with the composite bonding spot of the canine away from the center of t
... Show MoreBackground: Poly-ether-ether-ketone(PEEK) has been introduced to many dental fields. Recently it was tested as a retainer wire‎ following orthodontic treatment. This study aimed to investigate the effect of changing the bonding spot size and location on the performance of PEEK retainer wires. Methods: A biomechanical study involving four three-dimensional finite element models was performed. The basic model was with a 0.8 mm cylindrical cross-section PEEK wire, bonded at the center of the lingual surface of the mandibular incisors with 4 mm in diameter composite spots. Two other models were designed with 3 mm and 5 mm composite sizes. The last model was created with the composite bonding spot of the canine away from the center
... Show MoreClinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b
Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob
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