Various speech enhancement Algorithms (SEA) have been developed in the last few decades. Each algorithm has its advantages and disadvantages because the speech signal is affected by environmental situations. Distortion of speech results in the loss of important features that make this signal challenging to understand. SEA aims to improve the intelligibility and quality of speech that different types of noise have degraded. In most applications, quality improvement is highly desirable as it can reduce listener fatigue, especially when the listener is exposed to high noise levels for extended periods (e.g., manufacturing). SEA reduces or suppresses the background noise to some degree, sometimes called noise suppression alg

 Inflammatory bowel disease includes both Crohn’s disease and ulcerative colitis, is a chronic, progressive relapsing disease of gastrointestinal tract that require long-term treatment or maintenance therapy. Taking patient’s beliefs about the prescribed medication in consideration had been shown to be an important factor that affects compliance of the patient in whom having positive beliefs is a prerequisite for better compliance. The aim of the current study was to investigate and assess beliefs about medicines among a sample of Iraqi patients with inflammatory bowel disease and to determine possible association between these beliefs and some patient-specific factors.

This study is a cross-sectional study carried out o

Increasing the power conversion efficiency (PCE) of silicon solar cells by improving their junction properties or minimizing light reflection losses remains a major challenge. Extensive studies were carried out in order to develop an effective antireflection coating for monocrystalline solar cells. Here we report on the preparation of a nanostructured cerium oxide thin film by pulsed laser deposition (PLD) as an antireflection coating for silicon solar cell. The structural, optical, and electrical properties of a cerium oxide nanostructure film are investigated as a function of the number of laser pulses. The X-ray diffraction results reveal that the deposited cerium oxide films are crystalline in nature and have a cubic fluorite. The field

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

In this investigation, Rayleigh–Ritz method is used to calculate the natural frequencies of rectangular isotropic and laminated symmetric and anti-symmetric cross and angle ply composite plate with general elastic supports along its edges. Each of the admissible functions here is composed of a trigonometric function and an arbitrary continuous function that is introduced to ensure the sufficient smoothness of the so-called residual displacement function at the edges. Perhaps more importantly, this study has developed a general approach for deriving a complete set of admissible functions that can be applied to various boundary conditions. Several numerical examples are studied to demonstrate the accuracy and convergence of the current s

The gypseous soil may be one of the problems that face the engineers especially when it used as a foundation for hydraulic structures, roads, and other structures. Gypseous soil is strong soil and has good properties when it is dry, but the problem arises when building hydraulic installations or heavy buildings on this soil after wetting the water to the soil by raising the water table level from any source or from rainfall which leads to dissolve the gypsum content. Cement-stabilized soil has been successfully used as a facing or lining for earth channel, highway embankments and drainage ditches to reduce the risk of erosion and collapsibility of soil. This study is deliberate the treatment of gypseous soil by using a mixture

To evaluate and improve the efficiency of photovoltaic solar modules connected with linear pipes for water supply, a three-dimensional numerical simulation is created and simulated via commercial software (Ansys-Fluent). The optimization utilizes the principles of the 1st and 2nd laws of thermodynamics by employing the Response Surface Method (RSM). Various design parameters, including the coolant inlet velocity, tube diameter, panel dimensions, and solar radiation intensity, are systematically varied to investigate their impacts on energetic and exergitic efficiencies and destroyed exergy. The relationship between the design parameters and the system responses is validated through the development of a predictive model. Both single and mult

This paper is concerned with the numerical solutions of the vorticity transport equation (VTE) in two-dimensional space with homogenous Dirichlet boundary conditions. Namely, for this problem, the Crank-Nicolson finite difference equation is derived.  In addition, the consistency and stability of the Crank-Nicolson method are studied. Moreover, a numerical experiment is considered to study the convergence of the Crank-Nicolson scheme and to visualize the discrete graphs for the vorticity and stream functions. The analytical result shows that the proposed scheme is consistent, whereas the numerical results show that the solutions are stable with small space-steps and at any time levels.

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D