Increasing hydrocarbon recovery from tight reservoirs is an essential goal of oil industry in the recent years. Building real dynamic simulation models and selecting and designing suitable development strategies for such reservoirs need basically to construct accurate structural static model construction. The uncertainties in building 3-D reservoir models are a real challenge for such micro to nano pore scale structure. Based on data from 24 wells distributed throughout the Sadi tight formation. An application of building a 3-D static model for a tight limestone oil reservoir in Iraq is presented in this study. The most common uncertainties confronted while building the model were illustrated. Such as accurate estimations of cut-off

In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri

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

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

In this paper, the Active Suspension System (ASS) of road vehicles was investigated. In addition to the conventional stiffness and damper, the proposed ASS includes a fuzzy controller, a hydraulic actuator, and an LVDT position sensor. Furthermore, this paper presents a nonlinear model describing the operation of the hydraulic actuator as a part of the suspension system. Additionally, the detailed steps of the fuzzy controller design for such a system are introduced. A MATLAB/Simulink model was constructed to study the proposed ASS at different profiles of road irregularities. The results have shown that the proposed ASS has superior performance compared to the conventional Passive Suspension System (PSS), where the body displacemen

 The article critically analyzes traditional translation models. The most influential models of translation in the second half of the 20th century have been mentioned, among which the theory of formal and dynamic equivalence, the theory of regular correspondences, informative, situational-denotative, functional-pragmatic theory of communication levels have been considered. The selected models have been analyzed from the point of view of the universality of their use for different types and types of translation, as well as the ability to comprehend the deep links established between the original and the translation.

Аннотация

Coronavirus: (COVID-19) is a recently discovered viral disease caused by a new strain of coronavirus.

The majority of patients with corona-virus infections will have a mild-moderate respiratory disease that recovers without special care. Most often, the elderly, and others with chronic medical conditions such as asthma, coronary disease, respiratory illness, and malignancy are seriously ill.

    COVID-19 is spread mostly by salivary droplets or nasal secretions when an infected person coughs or sneezes.

    COVID-19 causes severe acute respiratory illness (SARS-COV-2). The first incidence was recorded in Wuhan, China, in 2019.  Since then it spreads leading to a pandemic.

Introduction: Methadone hydrochloride (MDN) is an effective pharmacological substitution treatment for opioids dependence, adopted in different countries as methadone maintenance treatment (MMT) programmes. However, MDN can exacerbate the addiction problem if it is abused and injected intravenously, and the frequent visits to the MMT centres can reduce patient compliance. The overall aim of this study is to develop a novel extended-release capsule of MDN using the sol-gel silica (SGS) technique that has the potential to counteract medication-tampering techniques and associated health risks and reduce the frequent visits to MMT centres. Methods: For MDN recrystallisation, a closed container method (CCM) and hot-stage method (HSM) were conduc

The purpose of this study is aimed to lay down an arranged platform suited to Iraqi constructional associations which in charge to carry out multi constructional projects, as it fulfilled management requirements and supervising, so that low - cost projects will be controlled in due term and quality. Based on primary info and observed data collected, the study thesis has been formulated in this way: Iraqi constructional sector bodies which are in charge to implement simultaneously multi constructional projects in need to reformulate its organized structure so that it will be more fitted to management and control of these projects. This thesis includes a
theoretical part contained presenting the most important resources locally and int