This paper is devoted to investigate the effect of internal curing technique on the properties of self-compacting concrete (SCC). In this study, SCC is produced by using silica fume (SF) as partial replacement by weight of cement with percentage of (5%), sand is partially replaced by volume with saturated fine lightweight aggregate (LWA) which is thermostone chips as internal curing material in three percentages of (5%, 10% and 15%) for SCC, two external curing conditions water and air. The experimental work was divided into three parts: in the first part, the workability tests of fresh SCC were conducted. The second part included conducting compressive strength test and modulus of rupture test at ages of (7, 28 and 90). The third part included the shrinkage test, at ages (7, 14, 21, 28) days. The results show that internally cured SCC has the best workability, and the best properties of hardened concrete which include (compressive strength and modulus of rupture) then the externally cured SCC with both water and air as compared with reference concretes. Also, the hardened properties of internally cured SCC with replacement percentage of (10%) by thermostone chips is the best as compared with that of percentages (5% and 15%) for both external curing conditions. In general, the results of hrinkage test, showed reduction in shrinkage of internally cured SCC as compared with reference concrete.
In this paper, the ability of using corn leaves as low-cost natural biowaste adsorbent material for the removal of Indigo Carmen (IC) dye was studied. Batch mode system was used to study several parameters such as, contact time (4 days), concentration of dye (10-50) ppm, adsorbent dosage (0.05-0.25) gram, pH (2-12) and temperature (30-60) oC. The corn leaf was characterized by Fourier-transform infrared spectroscopy device before and after the adsorption process of the IC dye and scanning electron microscope device was used to find the morphology of the adsorbent material. The experimental data was imputing with several isotherms where it fits with Freundlich (R2 = 0.9937) and followed pseudo second order kinetic. The hi
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The research aims to determine the mix of production optimization in the case of several conflicting objectives to be achieved at the same time, therefore, discussions dealt with the concept of programming goals and entrances to be resolved and dealt with the general formula for the programming model the goals and finally determine the mix of production optimization using a programming model targets to the default case.
The use of biopolymer material Chitosan impregnated granular activated carbon CHGAC as adsorbent in the removal of lead ions pb.2+ from aqueous solution was studied using batch adsorption mode. The prepared CHGAC was characterized by Scanning Electronic Microscopy (SEM) and atomic-absorption pectrophotometer. The adsorption of lead ions onto Chitosan-impregnated granular activated carbon was examined as a function of adsorbent weight, pH and
contact time in Batch system. Langmuir and Freundlich models were employed to analyze the resulting experimental data demonstrated that better fitted by Langmuir isotherm model than Freundlich model, with good correlation coefficient. The maximum adsorption capacity calculated f
The current research creates an overall relative analysis concerning the estimation of Meixner process parameters via the wavelet packet transform. Of noteworthy presentation relevance, it compares the moment method and the wavelet packet estimator for the four parameters of the Meixner process. In this paper, the research focuses on finding the best threshold value using the square root log and modified square root log methods with the wavelet packets in the presence of noise to enhance the efficiency and effectiveness of the denoising process for the financial asset market signal. In this regard, a simulation study compares the performance of moment estimation and wavelet packets for different sample sizes. The results show that wavelet p
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Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a
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The quality of groundwater in the Al-Hawija area was assessed using a water quality index. Data of nine physico-chemical parameters of 28 groundwater wells were used to calculate the water quality index (WQI). A heterogeneous water quality was reported, where in close proximity to the Lesser Zab River (LZR), it has low WQI values and permissible for human consumptions due to the dilution processes by fresh water; whereas, it becomes deteriorated in areas located far away the river. The values of WQI ranges from 22 to 336, indicating a good to very poor groundwater quality.
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
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