Feed Forward Back Propagation artificial neural network (ANN) model utilizing the MATLAB Neural Network Toolbox is designed for the prediction of surface roughness of Duplex Stainless Steel during orthogonal turning with uncoated carbide insert tool. Turning experiments were performed at various process conditions (feed rate, cutting speed, and cutting depth). Utilizing the Taguchi experimental design method, an optimum ANN architecture with the Levenberg-Marquardt training algorithm was obtained. Parametric research was performed with the optimized ANN architecture to report the impact of every turning parameter on the roughness of the surface. The results suggested that machining at a cutting speed of 355 rpm with a feed rate of 0.07 mm/rev and a depth of cut 0.4 mm was found to achieve lower surface roughness with, an increase in the cutting speed and feed rate with the increases of the surface roughness. In addition, an increase in the depth of cut was found to reduces the surface roughness. The outcome of this study showed that ANN is a versatile tool for prediction of surface roughness and may be easily extended with greater confidence to various metal cutting processes.
Electromyogram (EMG)-based Pattern Recognition (PR) systems for upper-limb prosthesis control provide promising ways to enable an intuitive control of the prostheses with multiple degrees of freedom and fast reaction times. However, the lack of robustness of the PR systems may limit their usability. In this paper, a novel adaptive time windowing framework is proposed to enhance the performance of the PR systems by focusing on their windowing and classification steps. The proposed framework estimates the output probabilities of each class and outputs a movement only if a decision with a probability above a certain threshold is achieved. Otherwise (i.e., all probability values are below the threshold), the window size of the EMG signa
... Show MoreGenome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id
... Show MoreThis paper compare the accurecy of HF propagation prediction programs for HF circuits links between Iraq and different points world wide during August 2018 when solar cycle 24 (start 2009 end 2020) is at minimun activity and also find out the best communication mode used. The prediction programs like Voice of America Coverage Analysis Program (VOACAP) and ITU Recommendation RS 533 (REC533 ) had been used to generat HF circuit link parameters like Maximum Usable Frequency ( MUF) and Frequency of Transsmision (FOT) .Depending on the predicted parameters (data) , real radio contacts had been done using a radio transceiver from Icom model IC 7100 with 100W RF
... Show MoreA fast laser texturing technique has been utilized to produce micro/nano surface textures in Silicon by means of UV femtosecond laser. We have prepared good absorber surface for photovoltaic cells. The textured Silicon surface absorbs the incident light greater than the non-textured surface. The results show a photovoltaic current increase about 21.3% for photovoltaic cell with two-dimensional pattern as compared to the same cell without texturing.
tA novel synthesis procedure is presented for preparing triethanolamine-treated graphene nanoplatelets(TEA-GNPs) with different specific areas (SSAs). Using ultrasonication, the covalently functionalizedTEA-GNPs with different weight concentrations and SSAs were dispersed in distilled water to prepareTEA-GNPs nanofluids. A simple direct coupling of GNPs with TEA molecules is implemented to synthesizestable water-based nanofluids. The effectiveness of the functionalization procedure was validated by thecharacterization and morphology tests, i.e., FTIR, Raman spectroscopy, EDS, and TEM. Thermal conduc-tivity, dispersion stability, and rheological properties were investigated. Using UV–vis spectrometer, ahighest dispersion stability of 0.876
... Show MoreThis study was conducted at the poultry farm located in the College of Agricultural Engineering Sciences, University of Baghdad, Abu Gharib (the old site), and laboratories of the Animal Production Department, Jadriya, to investigate the effect of adding hydrogen peroxide H2O2 at nanoscale levels to semen diluents of local roosters sperm in a number of semen characteristics. In this study, 80 roosters local Iraqi chickens were used, the roosters were trained three times a week, to collect semen, until the largest number of them responded. Then the best 40 of the roosters were elected for the purpose of collecting the semen with a pooled sample, and then the samples were diluted and divided equally into four parts. The concentrations of 0, 1
... Show MoreColorectal cancer CRC is the third most commonly diagnosed cancer in males and the second in female, so it is a common and life-threatening disease serum of 48 males and 40 females suffering from CRC disease as group one (G1) without taking a chemotherapy dose, the same patients group tow (G2) after taking the first chemotherapy dose, while group three (G3) whose patients in (G1) and (G2) after second taking a chemotherapy dose. and group four (G4) consist of (30 males and 30 females) healthy Iraqi control. Results showed a significant increase in IL-17, IL-17RA and CEA in G1, while there was a significant decrease in vitamin D concentration in G1 than other groups, also there was positive (+ ve) significant correlation between IL-17 and CE
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