Design and Implementation of Automated Predictive Magnetic Abrasive Finishing Machine

Magnetic abrasive finishing (MAF) is one of the non-traditional methods, that produce high quality condition of surface roughness (Ra) and is primarily controlled by magnetic field. This process can remove materials depending on magnetic energy.The aims of this research have been made to design and implement MA automated predictive machine, which plays an important role to the values of parameters (voltage of electromagnetic, magnetic pole velocity, working gap, and working time) to obtain the desired values for Ra.The microcontroller (Arduino Mega) was used for controlling the four parameters, and can predict the working time from regression model using optimum values parameters.  The automated machine can be programmed to control the electromagnetic voltage, the poles rotation, working gap, turn on and off the rotation of workpiece, and working time.The results indicated that the optimum parameters for the surface roughness are calculated according to Taguchi method and the S/N ratio, and the optimum values before automated the machine are voltage (7V), the working time (7min), poles speed (30r.p.m) and the working gap (1mm) for Ra. The results also indicated that the predict values for Ra is  nearly equal to the values from the automated machine about 95% for  Ra, that mean the automated predictive MA machine are very efficient. Keywords: Automated Machine, MAF Method, Arduino, Surface Roughness

Molecular Modeling Simulation Study of Interactions in Starch/Poly(acrylic acid) Blend

In this work we have studied the nature of interactions between starch and poly(acrylic acid) by using semi-empirical AM1 and PM3 methods. Theoretical computations involved the determination of optimal geometries, binding energies and vibrational frequencies of the blended polymers. Calculations are performed for four pairs of complexes of glucose (Glu) in starch and acrylic acid (mAA) in poly(acrylic acid) PAA. Based on results of calculation, the binding energies show negative values, which indicate that the interactions of glucose and acrylic acid are favorable at the lower energy. This means that the interactions of starch and PAA are stable. Vibrational frequency analysis of hydroxyl OH and carboxyl C=O groups of the 1Glu–1mAA, 1Glu–2mAA and 1Glu–3mAA complexes with single hydrogen bond showed that the stretching of these groups shifts to a lower wave number due to the formation of hydrogen bonds. Keywords:Polymer blends, AM1, PM3

Real-Time classification of various types of falls and activities of daily livings based on CNN LSTM network

In this research, two multiclass models have been developed and implemented, namely, a standard long-short-term memory (LSTM) model and a Convolutional neural network (CNN) combined with LSTM (CNN-LSTM) model. Both models operate on raw acceleration data stored in the Sisfall public dataset. These models have been trained using the TensorFlow framework to classify and recognize among ten different events: five separate falls and five activities of daily livings (ADLs). An accuracy of more than 96% has been reached in the first 200 epochs of the training process. Furthermore, a real-time prototype for recognizing falls and ADLs has been implemented and developed using the TensorFlow lite framework and Raspberry PI, which resulted in an acceptable performance

Development of a convolutional neural network joint detector for non-orthogonal multiple access uplink receivers

We present a novel approach to signal detection for Non-Orthogonal Multiple Access (NOMA) uplink receivers using Convolutional Neural Networks (CNNs) in a single-shot fashion. The defacto NOMA detection method is the so-called Successive Interference Cancellation which requires precise channel estimation and accurate successive detection of the user equipment with the higher powers. It is proposed converting incoming packets into 2D image-like streams. These images are fed to a CNN-based deep learning network commonly used in the image processing literature for image classification. The classification label for each packet converted to an image is the transmitted symbols by all user equipment joined together. CNN network is trained using uniformly distributed samples of incoming packets at different signals to noise ratios. Furthermore, let’s performed hyperparameter optimization using the exhaustive search method. Our approach is tested using a modeled system of two user equipment systems in a 64-subcarrier Orthogonal Frequency Division Multiplexing (OFDM) and Rayleigh channel. It is found that a three-layer CNN with 32 filters of size 7×7 has registered the highest training and testing accuracy of about 81. In addition, our result showed significant improvement in Symbol Error Rate (SER) vs. Signal to Noise Ratio (SNR) compared to other state-of-the-art approaches such as least square, minimum mean square error, and maximum likelihood under various channel conditions. When the channel length is fixed at 20, our approach is at least one significant Figure better than the maximum likelihood method at (SNR) of 2 dB. Finally, the channel length to 12 is varied and it is registered about the same performance. Hence, our approach is more robust to joint detection in NOMA receivers, particularly in low signal-to-noise environment

TECHNOLOGICAL ANALYSIS OF FLAT SURFACE CONDITIONS BY MAGNETIC ABRASIVE FINISHING METHOD (MAF)

This study introduced the effect of using magnetic abrasive finishing method (MAF) for finishing flat surfaces. The results of experiment allow considering the MAF method as a perspective for finishing flat surfaces, forming optimum physical mechanical properties of surfaces layer, removing the defective layers and decreasing the height of micro irregularities. Study the characteristics which permit judgment parameters of surface quality after MAF method then comparative with grinding

The Effect of Magnetic Abrasive Finishing on the Flat Surface for Ferromagnetic and non-Ferromagnetic materials

Magnetic Abrasive Finishing (MAF) is an advanced finishing method, which improves the quality of surfaces and performance of the products. The finishing technology for flat surfaces by MAF method is very economical in manufacturing fields an electromagnetic inductor was designed and manufactured for flat surface finishing formed in vertical milling machine. Magnetic abrasive powder was also produced under controlled condition. There are various parameters, such as the coil current, working gap, the volume of powder portion and feed rate, that are known to have a large impact on surface quality. This paper describes how Taguchi design of experiments is applied to find out important parameters influencing the surface quality generated during MAF method. In the experimental part, two types of materials from non-ferromagnetic and ferromagnetic (Aluminum alloy 7020 and stainless Steel 410 respectively) were considered with different parameters. Regressions models based on statistical-mathematical approach were obtained by using SPSS software for two materials

Comparing the clinical efficacy and safety of high doses of beclomethasone inhaler with medium doses of beclomethasone inhaler combined with oral aminophylline or montelukast tablets in persistent asthmatic Iraqi patients.

Asthma is a chronic inflammatory disorder of the airways in which many cells and cellular elements play a role. The treatment guidelines recommend the use of a second controller drug in addition to medium doses of inhaled corticosteroids (ICSs) rather than the use of high doses ICS alone in the treatment of moderate-severe persistent asthma. This study was conducted to compare the clinical efficacy and safety of three treatment regimens in Iraqi patients with moderate-severe persistent asthma. The study included three groups; each group included 15 patients. Patients were administered beclomethasone inhaler alone 1500-2000 μg/day, beclomethasone inhaler 750-1000 μg/day plus oral controlled release aminophylline tablets 450 mg/day or beclomethasone inhaler 750-1000 μg/day plus oral montelukast tablets 10 mg/day for 4-5 weeks. Patients were followed 2 weeks and 4-5 weeks after the baseline visit. In all of the three groups, significant improvements were noticed in pulmonary function test parameters (FEV1, FVC, FEF50%) and the asthma symptom records (day-time symptoms, night-time symptoms, number of salbutamol puffs per 24 hours), while there were no significant differences among the groups. Regarding side effects, only the group of inhaled steroid plus aminophylline tablets showed discontinuation of drug therapy in some patients which could be attributed to the development of serious side effects. It was concluded that the administration of a second controller agent was important to use lower doses of inhaled beclomethasone. It was concluded also that montelukast was associated with a lower incidence of serious side effects than aminophylline which could make aminophylline an alternative to montelukast as combination therapy with medium doses ICS in the treatment of moderate-severe persistent asthm

Utilization of natural dyes from Zingiber officinale leaves and Clitoria ternatea flowers to prepare new photosensitisers for dye-sensitised solar cells

Chlorophyll and ternatin were extracted from Zingiber officinale leaves and Clitoria ternatea flowers respectively. These natural dyes were applied as sensitisers in TiO2-based dye-sensitised solar cells (DSSCs). Among 10 different solvents, the ethanol extracts revealed the highest absorption spectra of natural dyes extracted from Z. officinale and C. ternatea. A major effect of temperature increase was the increased extraction yield. High chlorophyll and ternatin yields were obtained under extraction temperatures of 80 °C and 70 °C, respectively. A notable decrease in C. ternatea dye concentration at temperatures >70 °C was also observed. High dye concentrations were obtained using acidic extraction solutions, particularly those with a pH value of 4. Experimental results showed that the DSSC fabricated with chlorophyll extracted from Z. officinale leaves exhibited a conversion efficiency of 0.30%, open-circuit voltage (Voc) of 0.56 V, short-circuit current (Isc) of 0.8 mA/cm−2 and fill factor (FF) of 57.93%. The DSSC sensitized with ternatin from C. ternatea flowers displayed a conversion efficiency of 0.13%, Voc of 0.54 V, Isc of 0.3 mA/cm−2 and FF of 81.82%

Modeling ionic liquids mixture viscosity using Eyring theory combined with a SAFT-based EOS

This work aims to calculate the viscosities of ionic liquid mixtures using the Eyring theory combined with the SAFT-VR Morse EOS. The free volume theory was used to correlate the pure viscosity of ionic liquids (ILs) and solvents. Three model parameters have been adjusted using experimental viscosity data of ILs between 282 K and 413 K and 1 bar to 350 bar. The average ARD%, Bias%, and rmsd between model estimation and viscosity experimental data for pure ILs have been obtained 4.9 %, 1.015 %, and 0.67, respectively. The average error of the proposed model tends to increase at a pressure higher than 200 bar. The average ARD% for [C2mim][Tf2N] and [C6mim][Tf2N] is about 3.8 % and 3.4 % at pressures lower than 200 bar, while the average ARD% values increase sharply at higher pressures. This is due to the weak performance of the SAFT-VR Morse EOS for the calculation of IL density at high pressures. The SAFT-VR Morse EOS has been coupled with the Eyring theory, and the Redlich-Kister mixing rule to estimate the mixture viscosity of ILs-ILs and ILs-solvent systems. The thermal contribution of excess activation free energy has been calculated using the Redlich-Kister mixing rule with four adjustable parameters. The average ARD%, rmsd, and Bias% for fifteen binary mixtures have been obtained 3.9 %, 2.51, and 0.57 %, respectively. The average error values for mixture viscosity of ILs-polar solvent are higher than non-polar solvents. In the case of binary IL-IL systems, the model results are in good agreement with experimental data. The model performance has been evaluated using the viscosity deviation property. The SAFT-VR Morse EOS predicts the negative viscosity deviation. The strong attractive interaction in the mixture than a pure component is the major contribution to negative viscosity deviation. The results show that the new model can calculate the mixture viscosity and viscosity deviation of binary systems satisfactory. The obtained error values of mixture viscosity show that the Eyring theory can be coupled with a SAFT-based EOS to calculate the viscosity of ILs over a wide range of pressures and temperatures satisfactory