In this research, the effect of the rotation variable on the peristaltic flow of Sutterby fluid in an asymmetric channel with heat transfer is investigated. The modeling of mathematics is created in the presence of the effect of rotation, using constitutive equations following the Sutterby fluid model. In flow analysis, assumptions such as long wave length approximation and low Reynolds number are utilized. The resulting nonlinear equation is numerically solved using the perturbation method. The effects of the Grashof number, the Hartmann number, the Hall parameter, the magnetic field, the Sutterby fluid parameter, and heat transfer analysis on the velocity and the pressure gradient are analyzed graphically. Utilizing MATHEMATIC

This work is concerned with studying the optimal classical continuous control quaternary vector problem. It is consisted of; the quaternary nonlinear hyperbolic boundary value problem and the cost functional. At first, the weak form of the quaternary nonlinear hyperbolic boundary value problem is obtained. Then under suitable hypotheses, the existence theorem of a unique state quaternary vector solution for the weak form where the classical continuous control quaternary vector is considered known is stated and demonstrated by employing the method of Galerkin and the compactness theorem. In addition, the continuity operator between the state quaternary vector solution of the weak form and the corresponding classical continuous control qua

Melanoma, a highly malignant form of skin cancer, affects individuals of all genders and is associated with high mortality rates, especially in advanced stages. The use of tele-dermatology has emerged as a proficient diagnostic approach for skin lesions and is particularly beneficial in rural areas with limited access to dermatologists. However, accurately, and efficiently segmenting melanoma remains a challenging task due to the significant diversity observed in the morphology, pigmentation, and dimensions of cutaneous nevi. To address this challenge, we propose a novel approach called DenseUNet-169 with a dilated convolution encoder-decoder for automatic segmentation of RGB dermascopic images. By incorporating dilated convolution,

As of late, humankind has experienced radiation issues either computerized tomography (CT) or X-rays. In this investigation, we endeavor to limit the effect of examination hardware. To do this the medical image is cropping (cut and zoom) then represented the vascular network as a graph such that each contraction as the vertices and the vessel represented as an edges, the area of the coagulation was processed already, in the current search the shortest distance to reach to the place of the blood vessel clot is computed

The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

   Real life scheduling problems require the decision maker to consider a number of criteria before arriving at any decision. In this paper, we consider the multi-criteria scheduling problem of n jobs on single machine to minimize a function of five criteria denoted by total completion times (∑), total tardiness (∑), total earliness (∑), maximum tardiness () and maximum earliness (). The single machine total tardiness problem and total earliness problem are already NP-hard, so the considered problem is strongly NP-hard.

We apply two local search algorithms (LSAs) descent method (DM) and simulated annealing method (SM) for the 1// (∑∑∑

     The healthcare sector has traditionally been an early adopter of technological progress, gaining significant advantages, particularly in machine learning applications such as disease prediction. One of the most important diseases is stroke. Early detection of a brain stroke is exceptionally critical to saving human lives. A brain stroke is a condition that happens when the blood flow to the brain is disturbed or reduced, leading brain cells to die and resulting in impairment or death. Furthermore, the World Health Organization (WHO) classifies brain stroke as the world's second-deadliest disease. Brain stroke is still an essential factor in the healthcare sector. Controlling the risk of a brain stroke is important for the surviv

This study aimed at identity baying the difficulties which face public basic school
principals in jar ash governorate in editing formal letters and correspondence and means of
debating with these problems to collect data the researchers developed a question air were
established the population of the study which represents its sample consisted of 129 principals
65 males and 64 females
The results of the study revealed that the principals face difficulties in office and file
management in preparing plans and reports and writing formal letters and answering them
saved recommendations were presented among which were organizing training sessions and
workshops to train the principals on how to dead with there problems.<