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

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

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

Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin

Shear wave velocity is an important feature in the seismic exploration that could be utilized in reservoir development strategy and characterization. Its vital applications in petrophysics, seismic, and geomechanics to predict rock elastic and inelastic properties are essential elements of good stability and fracturing orientation, identification of matrix mineral and gas-bearing formations. However, the shear wave velocity that is usually obtained from core analysis which is an expensive and time-consuming process and dipole sonic imager tool is not commonly available in all wells. In this study, a statistical method is presented to predict shear wave velocity from wireline log data. The model concentrated to predict shear wave velocity fr

Background: Recent advancements in molecular techniques have identified over 450 genotypes of Human Papillomavirus (HPV), classified into low- and high-oncogenic risk categories. The rise in high-oncogenic risk HPV genotypes has been linked to various cancers, including those affecting the oral, oropharyngeal, and nasopharyngeal regions in both pediatric and adult populations. Methods: In this study, a cohort of 102 tonsillar tissue samples was included. This comprised 40 specimens from pediatric patients aged 4 to 9 years with nasopharyngeal adenoid hypertrophies, and 42 specimens from pediatric patients aged 5 to 12 years with palatine tonsillar hypertrophies. Among the 82 tonsillar tissue samples analyzed, 38 were from pediatric patients

The paper include study the effect thickness of the polymeric sample which is manufactured by thermo press way. The sample was used as an active tunable R6G laser media. The remarks show that, when the thickness of the samples is increased, with the same concentration, the spectrum will shift towards the short wavelength, & the quantum fluorescence yield will increased. The best result we obtained for the quantum fluorescence yield is (0.68) at the sample, with thickness (0.304mm) in Ethanol solvent, while when we used the Pure Water as a solvent, we found that the best quantum fluorescence yield is (0.63) at (0.18mm) thickness of the sample.