The main work of this paper is devoted to a new technique of constructing approximated solutions for linear delay differential equations using the basis functions power series functions with the aid of Weighted residual methods (collocations method, Galerkin’s method and least square method).

The aims of the research is to know the role of Organisational learning in building talent management strategies in the Ministry of Science and Technology , where we see the challenges facing organizations today dictate now and in the future activation of scientific expertise to meet these challenges and the dissemination of these concepts within the priorities and data organizational culture of these organizations despite having a lot of the importance of organizational knowledge and learning applications .Despite learning and adopting some of the organizations have to enhance their competitiveness, we find a lot of organizations, including (The ministry researched) still do not realize the importance of the role of organization

Early detection of eye diseases can forestall visual deficiency and vision loss. There are several types of human eye diseases, for example, diabetic retinopathy, glaucoma, arteriosclerosis, and hypertension. Diabetic retinopathy (DR) which is brought about by diabetes causes the retinal vessels harmed and blood leakage in the retina. Retinal blood vessels have a huge job in the detection and treatment of different retinal diseases. Thus, retinal vasculature extraction is significant to help experts for the finding and treatment of systematic diseases. Accordingly, early detection and consequent treatment are fundamental for influenced patients to protect their vision. The aim of this paper is to detect blood vessels from

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

Unter dem Titel " Technische Methoden im Fremdsprachunterricht als eine neueste Methode im Fremdsprachlernen, die Spiele als Muster"

versteht man, dass die Forschung  sich mit einer neuen Methoden im Fremdsprachunterricht beschäftigt. Von den neuen Methoden im Unterricht sind die Spiele. So man sieht  in den letzten Jahren viele Artikel zum Thema Spiele im Fremdsprschunterricht. Davon gehen wir aus, dass die Spiele im Unterricht eine groβe Rolle spielt, denn diese Methode macht Lust, Spaβ im Lernenprozeβ. Die Spiele im Unterricht bezeichnen als ein Mittel, um Unterricht etwas Schönes , Nützliches und Lebendigs zu sein. Die Spiele sind vielfälltig und unterscheidet sich nach den Themen und Materialien. In dieser F

Background: Acne is a common disorder experienced by adolescents and persists into adulthood in approximately 12%–14% of cases with psychological and social implications of high gravity. Fractional resurfacing employs a unique mechanism of action that repairs a fraction of skin at a time. The untreated healthy skin remains intact and actually aids the repair process, promoting rapid healing with only a day or two of downtime. Aims: This study, was designed to evaluate the safety and effectiveness of fractional photothermolysis (fractionated Er: YAG laser 2940nm) in treating atrophic acne scars. Methods: 7 females and 3 males with moderate to severe atrophic acne scarring were enrolled in this study that attained private clinic for Derm

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F