In this work, ZnS thin films have been deposited by developed laser deposition technique on glass substrates at room temperature. After deposition process, the films were annealed at different temperatures (200ºC , 300 ºC and 400ºC ) using thermal furnace.The developed technique was used to obtain homogeneous thin films of ZnS depending on vaporization of this semiconductor material by continuous CO2 laser with a simple fan to ensure obtaining homogeneous films. ZnS thin films were annealed at temperature 200ºC, 300 ºC and 400ºC for (20) minute in vacuum environment. Optical properties of ZnS thin film such as absorbance, transmittance, reflectance, optical band gap, refractive index extinction coefficient and absorption coefficien

Tin dioxide doped silver oxide thin films with different x content (0, 0.03, 0.05, 0.07) have been prepared by pulse laser deposition technique (PLD) at room temperatures (RT). The effect of doping concentration on the structural and electrical properties of the films were studied. Atomic Force Measurement (AFM) measurements found that the average value of grain size for all films at RT decrease with increasing of AgO content. While an average roughness values increase with increasing x content. The electrical properties of these films were studied with different x content. The D.C conductivity for all films increases with increasing x content. Also, it found that activation energies decrease with increasing of AgO content for all films.

In this research ,Undoped Nio and 1%Li doped Nio thin films were deposited utilizing chemical spray pyrolysis on the glass substrates heated (450C). The effects of non-thermal plasma on the structural and optical properties were studied. XRD measurement shows that Nio and Nio:1%Li films were found to be polycrystalline and have cubic structure with a preferred orientation (111). Decreased crystal size after exposure especially at (7) sec. AFM data indicate that the surface roughness average and (RMS) values of the prepared doped films are increasing after exposure to plasma, the transmittance increases after doped samples exposure to plasma, it was found that the energy gap value decreased when doped samples exposure to plasma, also, thickn

This paper presents the Extended State Observer (ESO) based repetitive control (RC) for piezoelectric actuator (PEA) based nano-positioning systems. The system stability is proved using Linear Matrix Inequalities (LMIs), which guarantees the asymptotic stability of the system. The ESObased RC used in this paper has the ability to eliminate periodic disturbances, aperiodic disturbances and model uncertainties. Moreover, ESO can be tuned using only two parameters and the model free approach of ESO-based RC, makes it an ideal solution to overcome the challenges of nano-positioning system control. Different types of periodic and aperiodic disturbances are used in simulation to demonstrate the effectiveness of the algorithm. The comparison studi

This paper presents a new algorithm in an important research field which is the semantic word similarity estimation. A new feature-based algorithm is proposed for measuring the word semantic similarity for the Arabic language. It is a highly systematic language where its words exhibit elegant and rigorous logic. The score of sematic similarity between two Arabic words is calculated as a function of their common and total taxonomical features. An Arabic knowledge source is employed for extracting the taxonomical features as a set of all concepts that subsumed the concepts containing the compared words. The previously developed Arabic word benchmark datasets are used for optimizing and evaluating the proposed algorithm. In this paper,

     Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin

A medical- service platform is a mobile application through which patients are provided with doctor’s diagnoses based on information gleaned from medical images. The content of these diagnostic results must not be illegitimately altered during transmission and must be returned to the correct patient. In this paper, we present a solution to these problems using blind, reversible, and fragile watermarking based on authentication of the host image. In our proposed algorithm, the binary version of the Bose_Chaudhuri_Hocquengham (BCH) code for patient medical report (PMR) and binary patient medical image (PMI) after fuzzy exclusive or (F-XoR) are used to produce the patient's unique mark using secret sharing schema (SSS). The patient’s un

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med