Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

      In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-

Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s

Meloxicam (MLX) is non-steroidal anti -inflammatory, poorly water soluble, highly permeable drug and the rate of its oral absorption is often controlled by the dissolution rate in the gastrointestinal tract. Solid dispersion (SD) is an effective technique for enhancing the solubility and dissolution rate of such drug.

    The present study aims to enhance the solubility and the dissolution rate of MLX by SD technique by solvent evaporation method using sodium alginate (SA), hyaluronic acid (HA), collagen and xyloglucan (XG) as gastro-protective hydrophilic natural polymers.

Twelve formulas were prepared in different drug: polymer ratios and evaluated for their, percentage yield, drug content,  water so

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

In this paper, the researchers investigate Prime Minister Benjamin Netanyahu's speech before a joint session of the US Congress on July 25, 2024. The researchers primarily aim at highlighting the ideology behind Netanyahu's speech by using qualitative research through the application of critical discourse analysis (CDA), which is employed here in in order to show how certain linguistic choices can manipulate and determine concepts related to power and ideology. The CDA method used is Discourse Historical Approach with the main focus on argumentation management through discursive strategies. The researchers adopt DHA by Wodak (2009) with focusing on the taxonomy of social actor representation by Van Leeuwen (2008). The study reveals th

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

Abstract

   It is clear to everyone how important it is to implement transactions electronically, as it facilitates the provision of services to beneficiaries, whether individuals or institutions, to achieve many benefits that are not exclusive to the beneficiary or the applicant, but extends to the governmental and international bodies. And the number of users has reached millions since its emergence in 1995, because the concepts of electronic transactions have great advantages for the economy in general and the banking sector in particular, so cooperation in various fields with the aim of becoming an information society has become paramount, It allows customers to pay money to any company they want t