Prediction of the structural response of reinforced concrete to the time-dependent, creep and shrinkage, volume changes is complex. Creep is usually determined by measuring the change, with time, in the strain of specimens subjected to a constant stress and stored under appropriate conditions. This paper brings into view the development of creep strain for four self-compacting concrete mixes: A40, AL40, B60 and BL60 (where 40 and 60 represent the compressive strength level at 28 days and L indicates to Portlandlimestone cement). Specimens were put under sustained load and exposed to controlled conditions in a creep chamber (ASTM C512). The test results showed that normal strength Portland-limestone mixes have yielded lower ultimate c

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

The charge transfer at C23H17F8N8O2PRu, C44H30BF4N5O4Ru, C56H52CL5N5OOsP2 and C76H88F80N24O11P10Ru4 nitrosyl complexes are investigation and studies theoretically using the quantum consideration. Charge transfer behavior largely rely to the electric properties of nitrosyl complexes system whose depending on the main important parameters for the transmission rate constant such that: orientation transition energy, overlapping coupling coefficient, driving force energy, height barrier and Temperature T (K). Data results have been evaluated using a MATLAB program. Results show that rate of charge transfer increases due to increases the orientation transition energy.

The purpose of this article is to improve and minimize noise from the signal by studying wavelet transforms and showing how to use the most effective ones for processing and analysis. As both the Discrete Wavelet Transformation method was used, we will outline some transformation techniques along with the methodology for applying them to remove noise from the signal. Proceeds based on the threshold value and the threshold functions Lifting Transformation, Wavelet Transformation, and Packet Discrete Wavelet Transformation. Using AMSE, A comparison was made between them , and the best was selected. When the aforementioned techniques were applied to actual data that was represented by each of the prices, it became evident that the lift

the research ptesents a proposed method to compare or determine the linear equivalence of the key-stream from linear or nonlinear key-stream

RM Abbas, AA Abdulhameed, AI Salahaldin, International Conference on Geotechnical Engineering, 2010

Worldwide, there is an increased reliance on COVID-19-related health messages to curb the COVID-19 outbreak. Therefore, it is vital to provide a well-prepared and authentic translation of English-language messages to reach culturally and linguistically diverse audiences. However, few studies, if any, focus on how non-English-speaking readers receive and linguistically accept the lexical choices in the messages translated into their language. The present study tested a sample of translated Arabic COVID-19-related texts that were obtained from the World Health Organization and Australian New South Wales Health websites. This study investigated to that extent Arabic readers would receive translated COVID-19 health messages and whether the t

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

Sixty-four isolate were klebsiella pneumoniae. Fourteen bacteria isolates “Kelbsiella species” were taken from soil and water hospital in the period between October to December 2018, those isolated were cultured on a blood agar to test their ability to hydrolytic due to formation the inhibition zone . Twenty one isolates of K. pneumoniae were selected to be cultured in mineral salt agarfor testing their efficiency to produce laccase enzyme .The efficient isolate was diagnosed depending on phenotypic, microscopic and biochemical tests to be Klebsiella pneumoniae K7. Laccases (benzenediol: oxygen oxidoreductases; EC: 1.10.3.2) are subfamily of multicopper oxidases (MCOs) from Klebsiellapneumoniae K7 has been partially characterized by