Todays, World is faced an energy crisis because of a continuous increasing the consumption of fuels due to intension demand for all types of vehicles. This study is one of the efforts dealing with reduce the weight of vehicles by using a new material of sandwich steel, which consists of two skin steel sheets with core of a polymer material. Resistance spot welding (RSW) can be easily implemented on metals; however a cupper shunt tool was designed to perform the resistance welding of sandwich steel with DP800 cover sheets to resolve a non-conductivity problem of a polymer core. Numerical simulations with SORPAS^®3D were employed to test the weldability of this new material and supported by many practical experiments. In conclus

Nanostructural cupric oxide (CuO) films were prepared on Si and glass substrate by pulsed laser deposition technique (PLD) using laser Nd:YAG, using different laser pulses energies from 200 to 600 mJ. The X-ray diffraction pattern (XRD) of the films showed a polycrystalline structure with a monoclinic symmetry and preferred orientation toward (111) plane with nano structure. The crystallite size was increasing with increasing of laser pulse energy. Optical properties was characterized by using UV–vis spectrometer in the wave lengthrange (200-1100) nm at room temperature. The results showed that the transmission spectrum decreases with the laser pulses energy increase. Sensitivity of NO2 gas at different operating temperatures, (50°C,

Copper nanoparticles (CuNPs) were prepared with different diameters by sonoelectrodeposition technique using Electrodeposition process coupled with high-power ultrasound horn (Sonoelectrodeposition). The particle diameter of the CuNPs was adjusted by varying CuSO4 solution acidity (pH) and current density. The morphology and structure of the CuNPs were examined by X-ray diffraction (XRD) and Scanning Electron Microscopy (SEM). It was found that the size of the produced copper nanoparticles ranged between 22 to 77 nm, where the diameter of CuNPs increases with reduction the solution acidity from 0.5 to 1.5 pH and increasing the current density of the deposition from 100 to 400 nm. Finally the produced CuNPs were pressed to fabricate disc

Optical Mark Recognition (OMR) is the technology of electronically extracting intended data from marked fields, such as squareand bubbles fields, on printed forms. OMR technology is particularly useful for applications in which large numbers of hand-filled forms need to be processed quickly and with a great degree of accuracy. The technique is particularly popular with schools and universities for the reading in of multiple choice exam papers. This paper proposed OMRbased on Modify Multi-Connect Architecture (MMCA) associative memory, its work in two phases: training phase and recognition phase. The proposed method was also able to detect more than one or no selected choice. Among 800 test samples with 8 types of grid answer sheets and tota

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

          Graphite Coated Electrodes (GCE) based on molecularly imprinted polymers were fabricated for the selective potentiometric determination of Risperidone (Ris). The molecularly imprinted (MIP) and nonimprinted (NIP) polymers were synthesized by bulk polymerization using (Ris.) as a template, acrylic acid (AA) and acrylamide (AAm) as monomers, ethylene glycol dimethacrylate (EGDMA) as a cross-linker and benzoyl peroxide (BPO) as an initiator. The imprinted membranes and the non-imprinted membranes were prepared using dioctyl phthalate (DOP) and Dibutylphthalate (DBP) as plasticizers in PVC matrix. The membranes were coated on graphite electrodes. The MIP electrodes using

This investigation proposed an identification system of offline signature by utilizing rotation compensation depending on the features that were saved in the database. The proposed system contains five principle stages, they are: (1) data acquisition, (2) signature data file loading, (3) signature preprocessing, (4) feature extraction, and (5) feature matching. The feature extraction includes determination of the center point coordinates, and the angle for rotation compensation (θ), implementation of rotation compensation, determination of discriminating features and statistical condition. During this work seven essential collections of features are utilized to acquire the characteristics: (i) density (D), (ii) average (A), (iii) s

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration