The consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying

Was expanded display high reflectivity of the spectral remote infrared (m j 14-8) adoption order Alcolmtin ????????? thickness optical northeastern quarter wavelength and compared with results of previous studies based Aldrashalhalah on Ndharah matrix distinctive amended and fall of light close to the vertical arrangement multilayer materials buffer and in thin films homogeneous and uniform properties deposited on germanium basis results showed that the best choice for governments and their kills to expand bandwidth high reflectivity is much easier for the infrared than the area visible in addition to the order of these stacks is the cornerstone of the filters other visual...

The High Modulus Asphalt Concrete Mixture (HMACM) or (EME) (Enrobes a Module Eleve) developed in France, since, 1980 by Laboratories Central des Ponts et Chaussees (LCPC). Due to the increasing in traffic intensity and axle loading this type of mixing were suitable for pavement subjected to heavy duty. Experiments showed that EME mixtures have an excellent moisture damage resistance permanent deformation, fatigue cracking and reducing costs of maintenance and a significant reduction in thickness of pavement. Because of the high stiffness of EME mixes, the stresses transformed to the bottom laid layer by repeated traffic wheel loads were reduced effectively. This study intend to focus the light into the possibility of producing asphalt mixtu

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

Autorías: Abdulsahıb Mohammed Muneer, Habeeb Sabhan Maytham, Kazim Abed Emad. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 1, 2021. Artículo de Revista en Psyke.

Background: For patients with coronavirus disease(COVID-19), continuous positive airway pressure (CPAP) has been considered as a useful treatment. The goal of CPAP therapy is to enhance oxygenation, relieve breathing muscle strain, and maybe avoid intubation. If applied in a medical ward with a multidisciplinary approach, CPAP has the potential to reduce the burden on intensive care units. Methods: Cross-sectional design was conducted in the ALSHEFAA center for crises in Baghdad. Questionnaire filled by 80 nurses who work in Respiratory Isolation Unit who had chosen by non-probability (purposive) selection collected the data. Then the researcher used an observational checklist to evaluate nurses’ practice. The data was analyzed us

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample