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bsj-3479
Fog Computing Resource Optimization: A Review on Current Scenarios and Resource Management
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            The unpredictable and huge data generation nowadays by smart computing devices like (Sensors, Actuators, Wi-Fi routers), to handle and maintain their computational processing power in real time environment by centralized cloud platform is difficult because of its limitations, issues and challenges, to overcome these, Cisco introduced the Fog computing paradigm as an alternative for cloud-based computing. This recent IT trend is taking the computing experience to the next level. It is an extended and advantageous extension of the centralized cloud computing technology. In this article, we tried to highlight the various issues that currently cloud computing is facing. Here in this research article, we present a comprehensive review of fog computing, differentiating it from cloud computing, also present various use-cases of fog computing in different domains, we came to conclude that Fog computing leads in an efficient energy resource management, leveraging the energy both in terms of consumption and cost scenarios. Further, we highlighted its key features, challenges and issues, resource optimization methods.

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Publication Date
Sat Nov 25 2023
Journal Name
Al-kitab Journal For Pure Sciences
Diverse Applications of β-enaminone Ligands and their Metal Complexes: A Review Article
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As they include both nucleophilic and electrophilic moieties on the same skeleton, enaminones are an important subclass of chemical compounds that contain conjugated NC=CC=O fragments. These active sites aid in the production of organic molecules containing linear or cyclic heteroatoms. Enaminones and the chemica1 compounds produced from them are both biologically active against the most dangerous bacteria. As a result, they have been utilized as starting materials for the synthesis of anti-inf1ammatory, antibacteria1, anticonvulsant, anticancer, anti-urease, anti-malaria1, optically luminescent, corrosion inhibition, and antitumor agents. Their synthesis has usually a terrific deal of interest and a plethora of synthetic paths have been na

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Artificial Intelligent Models for Detection and Prediction of Lost Circulation Events: A Review
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Lost circulation or losses in drilling fluid is one of the most important problems in the oil and gas industry, and it appeared at the beginning of this industry, which caused many problems during the drilling process, which may lead to closing the well and stopping the drilling process. The drilling muds are relatively expensive, especially the muds that contain oil-based mud or that contain special additives, so it is not economically beneficial to waste and lose these muds. The treatment of drilling fluid losses is also somewhat expensive as a result of the wasted time that it caused, as well as the high cost of materials used in the treatment such as heavy materials, cement, and others. The best way to deal with drilling fluid losses

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Wed Mar 08 2023
Journal Name
Sensors
A Critical Review of Remote Sensing Approaches and Deep Learning Techniques in Archaeology
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To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip

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Publication Date
Thu Feb 19 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Stem cells a novel approach to periodontal regeneration (A review of literature)
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In this review of literature, the light will be concentrated on the role of stem cells as an approach in periodontal regeneration.

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Publication Date
Mon Mar 03 2014
Journal Name
Journal Of Baghdad College Of Dentistry
Stem Cells a Novel Approach to Periodontal Regeneration: A Review of Literature
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Publication Date
Sun Sep 03 2023
Journal Name
Al-mansour Journal
Biometrics Systems Challenges in a Post-COVID-19 Pandemic World: A review
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One of the most serious health disasters in recent memory is the COVID-19 epidemic. Several restriction rules have been forced to reduce the virus spreading. Masks that are properly fitted can help prevent the virus from spreading from the person wearing the mask to others. Masks alone will not protect against COVID-19; they must be used in conjunction with physical separation and avoidance of direct contact. The fast spread of this disease, as well as the growing usage of prevention methods, underscore the critical need for a shift in biometrics-based authentication schemes. Biometrics systems are affected differently depending on whether are used as one of the preventive techniques based on COVID-19 pandemic rules. This study provides an

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Optimization and Prediction of Process Parameters in SPIF that Affecting on Surface Quality Using Simulated Annealing Algorithm
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Incremental sheet metal forming is a modern technique of sheet metal forming in which a uniform sheet is locally deformed during the progressive action of a forming tool. The tool movement is governed by a CNC milling machine. The tool locally deforms by this way the sheet with pure deformation stretching. In SPIF process, the research is concentrate on the development of predict models for estimate the product quality. Using simulated annealing algorithm (SAA), Surface quality in SPIF has been modeled. In the development of this predictive model, spindle speed, feed rate and step depth have been considered as model parameters. Maximum peak height (Rz) and Arithmetic mean surface roughness (Ra) are used as response parameter to assess th

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Publication Date
Mon Nov 11 2019
Journal Name
Day 3 Wed, November 13, 2019
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
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Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the</p> ... Show More
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Publication Date
Mon Jul 23 2018
Journal Name
Journal Of Clinical Nursing
Factors influencing nurses’ knowledge acquisition of diabetes care and its management: A qualitative study
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Aim

To identify and explore the factors nurses perceive as influencing their knowledge acquisition in relation to diabetes care and its management in Saudi Arabia.

Background

Diabetes continues to pose major healthcare challenges despite advances in diabetes management. Nurses have a crucial role in diabetes care, but diabetes knowledge deficits deter effective collaboration with other healthcare providers in educating patients about diabetes self‐management.

Design

An exploratory descriptive qualitative design.

Method
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