The Dynamic Load Factor (DLF) is defined as the ratio between the maximum dynamic and static responses in terms of stress, strain, deflection, reaction, etc. DLF adopted by different design codes is based on parameters such as bridge span length, traffic load models, and bridge natural frequency. During the last decades, a lot of researches have been made to study the DLF of simply supported bridges due to vehicle loading. On the other hand, fewer works have been reported on continuous bridges especially with skew supports. This paper focuses on the investigation of the DLF for a highly skewed steel I-girder bridge, namely the US13 Bridge in Delaware State, USA. Field testing under various load passes of a weighed load vehicle was used to validate full-scale three-dimensional finite element models and to evaluate the dynamic response of the bridge more thoroughly. The results are presented as a function of the static and dynamic tensile and compressive stresses and are compared to DLF code provisions. The result shows that most codes of practice are conservative in the regions of the girder that would govern the flexural design. However, the DLF sometimes exceeds the code-recommended values in the vicinity of skewed supports. The discrepancy of the DLF determined based on the stress analysis of the present study, exceeds by 13% and 16% the values determined according to AASHTO (2002) for tension and compression stresses respectively, while, in comparison to BS5400, the differences reach 6% and 8% respectively.
The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. The measurement results demonstrate a highly efficient capability for target detection in terms of frequency response and peak forming that was isola
... Show MoreThe intellectual and religious characteristics were an influential presence in the same Andalusian poet, especially among the poets of Beni El-Ahmar because they are part of the heritage of poets, and that is to push them towards the glory of this heritage and to take care of it and benefit from its inclusion, inspiration and similarity.
That this inflection on the poetic heritage is justified by the poets of the sons of the Red were inclined to preserve the inherited values, especially as it was related to their poetry, especially that the Andalusian poet did not find embarrassment in the inspiration of heritage and emerged when he mentioned the homes and the ruins and the camel and the journey, although the community Andalusian
... Show MoreThe exponential growth of audio data shared over the internet and communication channels has raised significant concerns about the security and privacy of transmitted information. Due to high processing requirements, traditional encryption algorithms demand considerable computational effort for real-time audio encryption. To address these challenges, this paper presents a permutation for secure audio encryption using a combination of Tent and 1D logistic maps. The audio data is first shuffled using Tent map for the random permutation. The high random secret key with a length equal to the size of the audio data is then generated using a 1D logistic map. Finally, the Exclusive OR (XOR) operation is applied between the generated key and the sh
... Show MoreCeruloplasmin (Cp) is one of the acute phase protein, in this review ,we studied the level of ceruloplasmin with copper (Cu) and iron in 90 patients with coronary heart diseas ( those patients are divided into three groups, whom are stable angina , unstable angina and myocardial infarction compared with 30 healthy volunteers) and the roles of them as diagnostic and prognostic tools.The diagnosis was attend by a clinical examination carried out by the consult medical staff in Ibn AL-Nafis hospital. The result: ceruloplasmin recorded a significantly(p<0.05)higher level in all patient groups compared with the control, so this result supports the hypothesis that a high serum ceruloplasmin level is a risk factor for coronary heart di
... Show MoreAtmospheric transmission is disturbed by scintillation, where scintillation caused more beam divergence. In this work target image spot radius was calculated in presence of atmospheric scintillation. The calculation depend on few relevant equation based on atmospheric parameter (for Middle East), tracking range, expansion ratio of applied beam expander's, receiving unit lens F-number, and the laser wavelength besides photodetector parameter. At maximum target range Rmax =20 km, target image radius is at its maximum Rs=0.4 mm. As the range decreases spot radius decreases too, until the range reaches limit (4 km) at which target image spot radius at its minimum value (0.22 mm). Then as the range decreases, spot radius increases due to geom
... Show MoreA nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.
In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
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