The study was conducted in the poultry field, College of Agriculture, Al-Muthanna University from 1/3/2018 to 6/4/2018 to determine the effect of commercial Ascomax powder produced from seaweed (Ascophyllum nodocum) on some productive performance of broilers. A total of 400, one day, Ross 308 broiler chicks were used for 35 days. The chicks were randomly distributed to 4 treatments, four replicates per treatment (25 chick / replicate). The treatments were as follows: T1: (control treatment), while T2, T3 and T4 added diet by Ascomax powder by 1, 1.5 and 2 g per 1 kg of the basal diet, respectively. The results of the study showed a significant superiority (P <0.05) for the added Ascomax powder treatments compared to the treatment of control

The research aims to identify the extent to which Iraqi private banks practice profit management motivated by reducing the taxable base by increasing the provision for loan losses by relying on the LLP it model, which consists of a main independent variable (net profit before tax) and independent sub-variables (bank size, total debts to total equity, loans granted to total obligations) under the name of the variables governing the banking business. (Colmgrove-Smirnov) was used to test the normal distribution of data for all banks during the period 2017-2020, and then find the correlation between the main independent variable sub and the dependent variable by means of the correlation coefficient person, and then using the multiple

One of the most effective ways of managing solid waste is microwave-assisted pyrolysis. This research used MW-assisted catalytic co-pyrolysis to extract essential oils from algae powder (AP) and date seed (DS). Graphite and a CaO nanocatalyst were utilized. As for the feedstock, it was a 1:1 mixture of AP and DS. The char content, oil production, and gas generation of co-pyrolysis yields varied between 18.8 wt% and 24.31 wt%, 43.08 wt%, and 55.295 wt%, and 25.905% to 32.60 wt%, respectively. The effect of the CaO nanocatalyst on product yields, feedstock conversion, and heating rates was analyzed. Product yields, average heating rates, and conversion factors were among the metrics studied to determine the synergistic effects and pyr

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

Future generations of wireless communications systems are expected to evolve toward allowing massive ubiquitous connectivity and achieving ultra-reliable and low-latency communications (URLLC) with extremely high data rates. Massive multiple-input multiple-output (m-MIMO) is a crucial transmission technique to fulfill the demands of high data rates in the upcoming wireless systems. However, obtaining a downlink (DL) training sequence (TS) that is feasible for fast channel estimation, i.e., meeting the low-latency communications required by future generations of wireless systems, in m-MIMO with frequency-division-duplex (FDD) when users have different channel correlations is very challenging. Therefore, a low-complexity solution for

     In the present work effect of recycled heating and cooling on the values of concrete compressive strength due to high temperature of 400⁰C was studied.

    The tests show that the percent of reduction in compressive strength of the samples which exposed to a temperature of 400⁰C for one cycle was 32.5%, while the reduction was 52.7% for the samples which were exposed to recycled heating and cooling of ten times .      

   Moreover a study of the effect of specimen sizes on the percentages of compressive strength reduction due to high temperature