Orthogonal polynomials and their moments have significant role in image processing and computer vision field. One of the polynomials is discrete Hahn polynomials (DHaPs), which are used for compression, and feature extraction. However, when the moment order becomes high, they suffer from numerical instability. This paper proposes a fast approach for computing the high orders DHaPs. This work takes advantage of the multithread for the calculation of Hahn polynomials coefficients. To take advantage of the available processing capabilities, independent calculations are divided among threads. The research provides a distribution method to achieve a more balanced processing burden among the threads. The proposed methods are tested for va

This paper proposes a hybrid learning-based navigation framework that integrates classical path planning with a spiking neural network model to achieve scalable and computationally efficient robot navigation in grid - based environments. Optimal reference trajectories are generated using the Spiking Wavefront Planner (SWP) over occupancy maps derived from the KITTI Odometry dataset. These expert paths are employed to train a Super Elman Spiking Neural Network (SE-SNN) using the e-prop learning rule to capture sequential navigation decisions. The framework is evaluated across map sizes ranging from 100×100 to 400×400 and compared with classical planners such as A* and D* Lite. Results show that the proposed SWP-SE-SNN model reduces plannin

Nanosilica was extracted from rice husk, which was locally collected from the Iraqi mill at Al-Mishikhab district in Najaf Governorate, Iraq. The precipitation method was used to prepared Nanosilica powder from rice husk ash, after treating it thermally at 700°C, followed by dissolving the silica in the alkaline solution and getting a sodium silicate solution. Two samples of the final solution were collected to study the effect of filtration on the purity of the sample by X-ray fluorescence spectrometry (XRF). The result shows that the filtered samples have purity above  while the non-filtered sample purity was around  The structure analysis investigated by the X-ray diffraction (XRD), found that the Nanosilica powder has an amorphous

We have studied Bayesian method in this paper by using the modified exponential growth model, where this model is more using to represent the growth phenomena. We focus on three of prior functions (Informative, Natural Conjugate, and the function that depends on previous experiments) to use it in the Bayesian method. Where almost of observations for the growth phenomena are depended on one another, which in turn leads to a correlation between those observations, which calls to treat such this problem, called Autocorrelation, and to verified this has been used Bayesian method.

The goal of this study is to knowledge the effect of Autocorrelation on the estimation by using Bayesian method. F

This researchpaper includes the incorporation of Alliin at various energy levels and angles 

With Metformin using Gaussian 09 and Gaussian view 06. Two computers were used in this work. Samples were generated to draw, integrate, simulate and measure the value of the potential energy surface by means of which the lowest energy value was (-1227.408au). The best correlation compound was achieved between Alliin and Metformin through the low energy values where the best place for metformin to b

The process of accurate localization of the basic components of human faces (i.e., eyebrows, eyes, nose, mouth, etc.) from images is an important step in face processing techniques like face tracking, facial expression recognition or face recognition. However, it is a challenging task due to the variations in scale, orientation, pose, facial expressions, partial occlusions and lighting conditions. In the current paper, a scheme includes the method of three-hierarchal stages for facial components extraction is presented; it works regardless of illumination variance. Adaptive linear contrast enhancement methods like gamma correction and contrast stretching are used to simulate the variance in light condition among images. As testing material

Response of cross-ply plates subjected to transient load is obtained using five variables refined plate theory, and four variables plate theory. Equations of motion are derived through the principleof virtual work. Navier series used for simply supported laminated plates. The results of this work are presented for different parameters, such as the ply number, thickness, and modulus ratio with mechanical load (sinusoidal and step pulses), which are compared with those obtained using high-order shear plate theory. Five variables of refined plate theory give results that are considerably different from the four variables of refined plate theory and higher-order theory. The obtained results from the four variables theory have the same behavior

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

An experimental study on a KIA pride (SAIPA 131) car model with scale of 1:14 in the wind tunnel was made beside the real car tests. Some of the modifications to passive flow control which are (vortex generator, spoiler and slice diffuser) were added to the car to reduce the drag force which its undesirable characteristic that increase fuel consumption and exhaust toxic gases. Two types of calculations were used to determine the drag force acting on the car body. Firstly, is by the integrating the values of pressure recorded along the pressure taps (for the wind tunnel and the real car testing), secondly, is by using one component balance device (wind tunnel testing) to measure the force. The results show that, the avera

In this paper, a simple fast lossless image compression method is introduced for compressing medical images, it is based on integrates multiresolution coding along with polynomial approximation of linear based to decompose image signal followed by efficient coding. The test results indicate that the suggested method can lead to promising performance due to flexibility in overcoming the limitations or restrictions of the model order length and extra overhead information required compared to traditional predictive coding techniques.