The monitoring weld quality is increasingly important because great financial savings are possible because of it, and this especially happens in manufacturing where defective welds lead to losses in production and necessitate time consuming and expensive repair. This research deals with the monitoring and controllability of the fusion arc welding process using Artificial Neural Network (ANN) model. The effect of weld parameters on the weld quality was studied by implementing the experimental results obtained from welding a non-Galvanized steel plate ASTM BN 1323 of 6 mm thickness in different weld parameters (current, voltage, and travel speed) monitored by electronic systems that are followed by destructive (Tensile and Bending) and non

The seizure epilepsy is risky because it happens randomly and leads to death in some cases. The standard epileptic seizures monitoring system involves video/EEG (electro-encephalography), which bothers the patient, as EEG electrodes are attached to the patient’s head.

Seriously, helping or alerting the patient before the seizure is one of the issue that attracts the researchers and designers attention. So that there are spectrums of portable seizure detection systems available in markets which are based on non-EEG signal.

The aim of this article is to provide a literature survey for the latest articles that cover many issues in the field of designing portable real-time seizure detection that includes the use of multiple

In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.

Conventional dosage forms for topical and transdermal drug delivery have several disadvantages related mainly to its poor skin permeation and patient compliance. Many approaches have been developed to improve these dosage forms. Film forming drug delivery systems represents a recent advancement in this field. It provides improved patient compliance with enhanced skin permeation of drugs. In its simplest form, these consist of a polymeric solution, usually in a supersaturated state, in a suitable solvent. A plasticizer is usually added to improve the flexibility and enhance the tensile strength to the film. It is also possible to control and sustain the drug release from the films by controlling the polymeric content, concentration o

The challenge in studying fusion reaction when the projectile is neutron or proton rich halo nuclei is the coupling mechanism between the elastic and the breakup channel, therefore the motivation from the present calculations is to estimate the best coupling parameter to introduce the effect of coupled-channels for the calculations of the total cross section of the fusion  , the barrier distribution of the fusion   and the average angular momentum ⟨L⟩ for the systems ⁶He+²⁰⁶Pb, ⁸B+²⁸Si, ¹¹Be+²⁰⁹Bi, ¹⁷F+²⁰⁸Pb, ⁶He+²³⁸U, ⁸He+¹⁹⁷Au and ¹⁵C+²³²Th using quantum mechanical approach.  A

Objective: Hesperidin (HSP) is a pharmacologically active organic compound found in citrus fruits and peppermint. We synthesized a new HSP derivative by reacting it with 5-Amino-1,3,4-thiadiazole-2-thiol in acetic acid. Methods: This compound was characterized by Fourier-transform infrared, proton nuclear magnetic resonance, and electron impact mass spectra. A molecular docking study explores the predicted binding of the compound and its possible mode of action. Bioavailability, site of absorption, drug mimic, and topological polar surface was predicted using absorption, distribution, metabolism, and excretion (ADME) studies. Results: The docking study predicts that the new compound binds to the active sites of Aurora-B

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

The aim of this research is analysis the effect of the changes in (GDA, g, inflation) at average and standard economic curriculum in composition of the models, depending on SPSS program in analysis, and according to available date from central bank of Iraq and during the period from 2003 to 2018 and by using OLS and estimate of the equation and the results showed a statistical significance relation in incorporeal level 5% and the R² value equal  to 92.1 refer to the changes in independent variables explain 92% of changes of unemployment and the independent variables effect are very limit depend on estimated parameters in the model and respectively (0.986,0.229,-0.060), the research recommended necessity to active the inve

Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed  method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi