In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. It was found that the maximum vibration occurs when the load speed is about 0.58 of the critical speed of the beam. Furthermore, the vibration amplitude resulting from a moving load can amplify to 1.65 times the deflection produced by an equivalent static load.
The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .
The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result. &nbs
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
... Show MoreCodes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de
... Show MoreIn globalization, the world became open area to competition for the attractive of investment, and the abilities of each country to win the confidence of investors depend upon the preparation to optimize circumstances. The competitiveness is an essential means of expanding the capacity of developed to coexist in an international environment characterized by globalization. While competition describes the market structure, the behavior of investors and business, competitiveness is interested in the evaluation of business performance or countries and compare them in the conditions of competition available in these markets. Regarding Malaysia, which is depend on FDI-Export- Led Growth strategy, it has taking on diffe
... Show MoreDetecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulate
... Show MoreAdolescence important and sensitive stage in social terms, being a stage where learns teenager bear social responsibilities and composition of their ideas about family life, as well as it is the stage where the teenager looking to himself for an important place in the community to become independent socially people, so it highlights the role of Social Work to do better effort and I believe him in order to prepare for the adolescent stage of adolescence and help him overcome the problems so that makes it adapts to the society in which he lives
Background: Cystinosis is a rare autosomal recessive lysosomal storage disease with high morbidity and mortality. It is caused by mutations in the CTNS gene that encodes the cystine transporter, cystinosin, which leads to lysosomal cystine accumulation. It is the major cause of inherited Fanconi syndrome, and should be suspected in young children with failure to thrive and signs of renal proximal tubular damage. The diagnosis can be missed in infants, because not all signs of renal Fanconi syndrome are present during the first months of life. Elevated white blood cell cystine content is the cornerstone of the diagnosis. Since chitotriosidase (CHIT1 or chitinase-1) is mainly produced by activated macrophages both in normal and inflammator
... Show MoreErosion and deposition are natural phenomena in many estuaries that can cause morphological changes, leading to navigation and offshore structure problems. Many previous studies have focused on investigating the morphological changes of estuaries depending on different parameters and their combined effects with erosion and deposition processes, such as maximum flow amplitude, waves, currents, tidal flow, storms, rising sea elevation, maximum turbidity, salinity, and bed roughness height as input parameters. These studies are based on field measurements and numerical simulations by using topographic surveys, soil samples, satellite images, geological data, and bathymetric maps with the aid of ArcGIS. Some of these studies examine the
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