Tchebichef polynomials (TPs) play a crucial role in various fields of mathematics and applied sciences, including numerical analysis, image and signal processing, and computer vision. This is due to the unique properties of the TPs and their remarkable performance. Nowadays, the demand for high-quality images (2D signals) is increasing and is expected to continue growing. The processing of these signals requires the generation of accurate and fast polynomials. The existing algorithms generate the TPs sequentially, and this is considered as computationally costly for high-order and larger-sized polynomials. To this end, we present a new efficient solution to overcome the limitation of sequential algorithms. The presented algorithm us

In this work, porous silicon (PS) are fabricated using electrochemical etching (ECE) process for p-type crystalline silicon (c-Si) wafers of (100) orientation. The structural, morphological and electrical properties of PS synthesized at etching current density of (10, 20, 30) mA/cm2 at constant etching time 10 min are studied. From X-ray diffraction (XRD) measurement, the value of FWHM is in general decreases with increasing current density for p-type porous silicon (p-PS). Atomic force microscope (AFM) showed that for p-PS the average pore diameter decreases at 20 mA. Porous silicon which formed on silicon will be a junction so I-V characteristics have been studied in the dark to calculate ideality factor (n), and saturation current (Is

Abstract

               The research aimed to prepare an audit program focusing on the activities of municipal institutions related to the environmental dimension as one of the dimensions of sustainable development, and applying the program for the purpose of preparing an oversight report related to assessing the impact of the activities of municipal institutions on the environmental reality as the main channel through which municipal institutions contribute to achieving the part related to it. Among the requirements of sustainable development, the proposed program was prepared and applied to the institutions affiliated to the Directorate of Mu

The effectiveness of upward training with weights to develop explosive power, characterized by speed and some functional variables for young volleyball players Many efforts of sports laboratories in various countries have been devoted to laying scientific foundations and rules in caring for the physical, skilled, planning, and psychological preparation of players and creating the conditions and requirements for reaching players to higher standards. The research aims to:1- Preparing an ascending training program with weights to develop explosive strength, which is characterized by speed and some functional variables for volleyball players.2- Identify the effect of the training program with upward training in weights to develop explosive stre

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of