Quantum dots (QDs) of zinc sulfide (ZnS) was prepared by chemical reaction with different potential of hydrogen (pH) and used to fabricate organic quantum dot hybrid junction device. The optical properties of QDs were characterized by ultraviolet-visible (UV-Vis.) and photoluminescence (PL) spectrometer. The results show that the prepared QDs were nanocrystalline with defects formation. The energy gap (E_g)calculated from PL were 3.64, 3.53 and 3.35 eV for pH=8, 10 and 12 respectively. This decreasing of energy gaps is results of the effect the pH solution increases, which in turn leads to the shifted of the PL spectrum toward red shifted, which makes the energy bands at surface states are shallow ban

Diamond-like carbon (DLC) homogeneous thin films were deposited from cyclohexane (Ccyclohexane (Ccyclohexane (Ccyclohexane (C cyclohexane (Ccyclohexane (Ccyclohexane (C cyclohexane (Ccyclohexane (C 6H12 ) liquid by using a plasma jet system which operates with alternating high voltage 7.5 which operates with alternating high voltage 7.5which operates with alternating high voltage 7.5which operates with alternating high voltage 7.5 which operates with alternating high voltage 7.5which operates with alternating high voltage 7.5which operates with alternating high voltage 7.5 which operates with alternating high voltage 7.5which operates with alternating high voltage 7.5 which operates with alternating high voltage 7.5which operates with al

PMMA/TiO2 homogeneous thin films were deposited by using plasma jet system under normal atmospheric pressure and room temperature. PMMA/TiO2 nanocomposite thin film synthesized by plasma polymerization. Titanium oxide was mixed with Methyl Methacrylate Monomer (MMA) with specific weight ratios (1, 3 and 5 grams of TiO2 per 100 ml of MMA). Optical properties of PMMA/TiO2 nanocomposite thin films were characterized by UV-Visible absorption spectra using a double beam UV-Vis-NIR Spectrophotometer. The thin films surface morphological analysis is carried out by employing SEM. The structure analysis are achieved by X-ray diffraction. UV-Visible absorption spectra shows that the increasing the concentration of titanium oxide added to the polym

Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit

The present work aimed to study effect of (N749 & N3) dyes on TiO2 optical and electrical properties for optoelectronic application. The TiO2 paste prepared by using a doctor blade method. The samples were UV-VIS specterophometricall analyzes of TiO2 before and after immersed in dyes (N749 & N3). The results showed absorption spectra shift toward the visible region due to the adsorption of dye molecules on the surface of oxide nanoparticles. It is seen that the Eg determined to give a value of 3.3eV for TiO2 before immersing in dyes, and immersing in dyes (N749 & N3) are (1.4 &1.6 eV) respectively. The structural properties (XRD), (FTIR) and (SEM) for the sample prepared were investigated and (J-V) characteristics was stu

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

Ultraviolet photodetectors have been widely utilized in several applications, such as advanced communication, ozone sensing, air purification, flame detection, etc. Gallium nitride and its compound semiconductors have been promising candidates in photodetection applications. Unlike polar gallium nitride-based optoelectronics, non-polar gallium nitride-based optoelectronics have gained huge attention due to the piezoelectric and spontaneous polarization effect–induced quantum confined-stark effect being eliminated. In turn, non-polar gallium nitride-based photodetectors portray higher efficiency and faster response compared to the polar growth direction. To date, however, a systematic literature review of non-polar gallium nitride-

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample