Drilling well design optimization reduces total Authorization for Expenditures (AFE) by decreasing well constructing time and expense. Well design is not a constant pattern during the life cycle of the field. It should be optimized by continuous improvements for all aspects of redesigning the well depending on the actual field conditions and problems. The core objective of this study is to deliver a general review of the well design optimization processes and the available studies and applications to employ the well design optimization to solve problems encountered with well design so that cost effectiveness and perfect drilling well performance are achievable. Well design optimization processes include unconventional design(slimhole) co

This paper explores VANET topics: architecture, characteristics, security, routing protocols, applications, simulators, and 5G integration. We update, edit, and summarize some of the published data as we analyze each notion. For ease of comprehension and clarity, we give part of the data as tables and figures. This survey also raises issues for potential future research topics, such as how to integrate VANET with a 5G cellular network and how to use trust mechanisms to enhance security, scalability, effectiveness, and other VANET features and services. In short, this review may aid academics and developers in choosing the key VANET characteristics for their objectives in a single document.

Objectives: To review the failure rates of molar tubes and the effect of molar tube base design, adhesive type, and bonding technique on the failure rates of molar tubes. Data: The revolution of molar bonding greatly impacted fixed orthodontic appliance treatment by reducing chair-side time and improving patient comfort. Even with the many advantages of molar bonding, clinicians sometimes hesitate to use molar tubes due to their failure rates. Sources: Internet sources, such as Pubmed and Google Scholar. Study selection: studies testing the bond failure rate of molar tubes. Conclusions: The failure rate of the molar tubes can be reduced and the bond strength of the molar tubes can be improved by changing the design of the molar tube base

The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

Genome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id

The aim of the research is to:. Preparation and implementation of special educational units using multimedia to learn the skill of scrolling from below. 2 to recognize the impact of the use of multimedia in learning the skill of scrolling from below. 3 to identify the differences between the tests after the two groups research in learning the skill of passing from the bottom volleyball. The research represented the students of the first stage and the sample of the research was drawn randomly and the number of (50) students were divided into two experimental and control groups and each group (25) students were used standardized tests and conducting pre-tests and the implementation of the main exp

Designing Teaching Aids and Their Effects on Learning and Retaining Diving and Cartwheel on Floor Exercises in Women’s’ Artistic Gymnastics

The research aimed at designing teaching aids that develop and help retain diving and cartwheel for third year college of physical education and sport sciences students in women’s artistic gymnastics. In addition to that, the researchers aimed at identifying the effect of these aids on learning and retaining cartwheel and diving in floor exercises. The researchers used the experimental method. The subjects were (20) third year female students from the college of physical education and sport sciences/ university of Baghdad sections K and H. the main experiment lasted for

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep