Java is a high-level , third generation programming language were introduced Javaoptics Open Source Physics (OSP) as a new simulation for design one of the most important interference optical coating called antireflection coating. It is recent developments in deign thin-film coatings. (OSP) shows multiple beam interferences from a parallel dielectric thin film and the evolution of reflection factors. It is simple to use and efficiently also can serve educational purposes. The obtained results have been compared with needle method

   The research  includes the study and calculation of the modulation function of Optical Semiconductor Fractal  Modulator and spatial frequency for different values of Silicon modulator transmittance percentage(10%,35%,45%,58%),it found the relation between the modulation function of Silicon and spatial frequency, the exponential relation of all values of the transmittance , the best state of modulation function when the value of transmittance is T=58% ,also the research includes the study of the relation of transmittance with different values of refractive index of Silicon . So the research involves building a computer program of output data which would relate to fractal optical modulation made of semiconductor mate

It is known that life is as series of variety of difficult problems that individual looks
forward to overcome so as to achieve adaptation and to reach the desired aims .The transition
of the students from the school stage to the stage of the university is actually regarded a
dramatic change where students face when they enter university life that differs from what
they lived in secondary school.
The executive functions are considered the main element that participate in solving the
problems of high orders , because it involves the mental abilities that assist individual to
think and initiative as well as solving problems .
These functions include operational planning and the activated memory and inhibition of
q

Abstract: Polarization beam splitter (PBS) integrated waveguides are the key components in the receiver of quantum key distribution (QKD) systems. Their function is to analyze the polarization of polarized light and separate the transverse-electric (TE) and transverse-magnetic (TM) polarizations into different waveguides. In this paper, a performance study of polarization beam splitters based on horizontal slot waveguide has been investigated for a wavelength of . PBS based on horizontal slot waveguide structure shows a polarization extinction ratio for quasi-TE and quasi-TM modes larger than  with insertion loss below  and a bandwidth of . Also, the fabrication tolerance of the structure is analyzed.<

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

Nowadays, the mobile communication networks have become a consistent part of our everyday life by transforming huge amount of data through communicating devices, that leads to new challenges. According to the Cisco Networking Index, more than 29.3 billion networked devices will be connected to the network during the year 2023. It is obvious that the existing infrastructures in current networks will not be able to support all the generated data due to the bandwidth limits, processing and transmission overhead. To cope with these issues, future mobile communication networks must achieve high requirements to reduce the amount of transferred data, decrease latency and computation costs. One of the essential challenging tasks in this subject