Neuro-fuzzy control modelling for gas metal arc welding process

Weld quality features are difficult or impossible to directly measure and control during welding, therefore indirect methods are necessary. Penetration is the most important geometric feature since in most applications it is the most significant factor affecting joint strength. Observation of penetration is only possible from the back face of the full penetration weld. In all other cases, since direct measurement of depth of penetration is not possible, real time control of penetration in the Gas Metal Arc Welding (GMAW) process by sensing conditions at the top surface of the joint is necessary. This continues to be a major area of interest for automation of the process. The objective of this research has been to develop an on-line intelligent process control model for GMAW, which can monitor and control the welding process. The model uses measurement of the temperature at a point on the surface of the workpiece to predict the depth of penetration being achieved, and to provide feedback for corrective adjustment of welding variables. Neural Network and Fuzzy Logic technologies have been used to achieve a reliable Neuro-Fuzzy control model for GMAW of a typical closed butt joint having 60° Vee edge preparation. The neural network model predicts the surface temperature expected for a set of fixed and adjustable welding variables when a prescribed level of penetration is achieved. This predicted temperature is compared with the actual surface temperature occurring during welding, as measured by an infrared sensor. If there is a difference between the measured temperature and the temperature predicted by the neural network, a fuzzy logic model will recommend changes to the adjustable welding variables necessary to achieve the desired weld penetration. Large scale experiments to obtain data for modelling and for model validation, and various other modelling studies are described. The results are used to establish the relationships between the output surface temperature measurement, welding variables and the corresponding achieved weld quality criteria. The effectiveness of the modelling methodology in dealing with fixed or variable root gap has also been tested. The result shows that the Neuro-fuzzy models are capable of providing control of penetration to an acceptable degree of accuracy, and a potential control response time, using modestly powerful computing hardware, of the order of one hundred milliseconds. This is more than adequate for real time control of GMAW. The application potential for control using these models is significant since, unlike many other top surface monitoring methods, it does not require sensing of the highly transient weld pool shape or surface

Predicting Students Performance in Online Education through Deep Learning Model

This epidemic has prompted the development of Education 4.0, virtual learning, and the demand to adapt educational practices to meet the needs of younger demographics. A rising epidemic has necessitated the shutdown of campuses where education programs are now being carried out online in educational institutions all over the globe. The report includes a study on the effectiveness and perceptions of students toward digital learning during the pandemic. A Convolutional Neural Network (CNN) and Particle swarm optimization model, which forecasts the student’s learning rates, are used to tackle this issue. This study will categorize student performance into low, medium, and high grades to forecast student achievement. The Kaggle student’s performance assessment database is utilized to gather the student information logs, which are then pre-processed to eliminate noise and redundant data. The CNN derives features based on the student’s attention and arbitrary patterns sequencing by examining the pre-processed information. Then, utilizing the Minimum Redundancy Maximum Relevance (mRMR) approach, the retrieved characteristics are evaluated. The lowest one that treats each characteristic individually is chosen as the greatest feature by mRMR. CNN uses stochastic Gradient Descent (SGD) to calculate the characteristic weights, which are then modified for improved extracting features. Finally, the CNN-WOA method forecasts the final academic achievement forecast outcome. Studies revealed that the suggested approach outperforms existing ones in terms of accuracy, precision, recall, and F-score while requiring less computing time

The Effect of using Augmented Reality Technology on the Cognitive Holding Power and the Attitude Towards it Among Middle School Students in Al-Qurayyat Governorate, Saudi Arabia

The current study was to use augmented reality technology (ART) in the science course (SC) at the middle school level in Al-Qurayyat Governorate, Saudi Arabia, and to assess how it affected the students attitudes toward AR (ATAR) and cognitive holding power (CHP). The ART is utilized to enhance learning results, particularly when generating challenging, novel, and abstract scientific theories. The CHP measure, and the ATAR measure were developed for this research. 58 school students took part in this study. They have been split into two categories: the experimental group was in group one, and the control group was in group two. In each group, there were 29 students. Whereas the second group learned the SC through the conventional approach, the first group did it using ART. The outcomes demonstrated the first group (Experimental group) superiority. The study suggested that in order to improve students understanding of scientific topics, it is essential to increase knowledge of the value of ART

DNA minor groove binders-inspired by nature

The synthesis and biological activity of a variety of analogues to the naturally occurring anti-bacterial and anti-fungal Distamycin A were explored by a number of authors. These compounds were subject to a large array of assays. Some of these compounds showed high activity against a range of Gram-positive, Gram-negative bacteria as well as fungi. To explore the anti-parasitic activity of this class of compounds, specific modifications had to be made. A number of these compounds proved to be active against Trypanosoma brucei. The binding of a number of these compounds to short sequences of DNA were also examined using footprinting assays as well as NMR spectroscopy. Computer modelling was employed on selected compounds to understand the way these compounds bind to specific DNA sequences. A large number of variations were made to the standard structure of Distamycin. These changes involved the replacement of the pyrrole moieties as well as the head and tail groups with a number of heterocyclic compounds. Some of these MGBs were also investigated for their capability for the treatment of cancer and in particular lung cancer

ANTIFUNGAL AND SYNERGISTIC EFFECTS OF ZNO NANOPARTICLES AGAINST T.VERRUCOSUM CAUSED RINGWORM IN COWS

The current study was aimed to determined the main causes of ringworm in cows and antifungal and synergistic effects of ZnO nanoparticles. For this purpose 50  skin scrapes were collected from cows infected with ringworm, culture media, staining and genetic methods used for diagnosis. MIC and MFC for antifungal and ZnO were determined. The result showed that Trichophyton spp was isolated in rate of 76%. The isolation rate of T.verrucosum, T. mentagrophytes  and T. rubrum were 68.4%, 21.0% and 10.5% respectively. MIC of Nystatin, fluocytosin, ZnO, Nystatin+ ZnO  and Fluocytosin + ZnO were 200,150,200,150 and 100 μg/ml  respectively. in conclusion, that  T.verrucosum is main caused of Ringworm and ZnO has antifungal and synergistic effects

Effect of electronic cigarette (EC) aerosols on particle size distribution in indoor air and in a radon chamber

Particle size distribution is an important factor governing whether aerosols can be deposited in various respiratory tract regions in humans. Recently, electronic cigarette (EC), as the alternative of tobacco cigarette, has become increasingly popular all over the world. However, emissions from ECs may contribute to both indoor and outdoor air pollution; moreover, comments about their safety remain controversial, and the number of users is increasing rapidly. In this investigation, aerosols were generated from ECs and studied in the indoor air and in a chamber under controlled conditions of radon concentration. The generated aerosols were characterized in terms of particle number concentrations, size, and activity distributions by using aerosol diffusion spectrometer (ADS), diffusion battery, and cascade impactor. The range of ADS assessment was from 10 -3 μm to 10 μm. The number concentration of the injected aerosol particles was between 40 000 and 100 000 particles/cm 3 . The distribution of these particles was the most within the ultrafi ne particle size range (0-0.2 μm), and the other particle were in the size range from 0.3 μm to 1 μm. The surface area distribution and the mass size distribution are presented and compared with bimodal distribution. In the radon chamber, all distributions were clearly bimodal, as the free radon decay product was approximately 1 nm in diameter, with a fraction of ~0.7 for a clean chamber (without any additional source of aerosols). The attached fraction with the aerosol particles from the ECs had a size not exceeding 1.0 μm. © 2019 H. N. Khalaf, M. Y. A. Mostafa & M. Zhukovsky

On Contra SS-Continuous Functions

In this paper, we apply the notion of -open set in topological spaces to introduce and investigate the concept of contra -continuous which is a subclass of the class of contra semi continuous functions. Keywords: -closed, contra -continuous, contra SS –closed and strongly contra SS –closed

Modeling and simulation of a 3-ф induction motor based on two types of WFA

This paper has been proposed to simulate the transient model of 3-Ф cage rotor induction motor based on winding function approach (WFA). According to this method the motor is assumed to be consist of an electrical circuits on both stator and rotor. The magneto motive forces (MMF) that have been generated by these circuits play a role for coupling them together. Then mutual and self-inductances will be easily computed using WFA. Two types of WFA have been used to build and simulate the model of the induction motor. In the one part type, it’s assumed that the coupling MMF between stator and rotor have a non-sinusoidal shapes according to the actual windings distribution over the motor slots. While in second part type the generated MMF in are assumed to have sinusoidal waveform. The suggested models may be used to simulate the dynamic as well as steady state performance of a faulty and non-faulty motor. A simulation of the suggested models that consists of m-rotor bars and n-stator phases multiple coupled circuit-based has been performed using matlab m.file and the results of the motor current have been proved in its nonlinear way by using WFA