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Performance of a tubular machine driven by an external‐combustion free‐piston engine
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Publication Date
Mon Jan 01 2024
Journal Name
Proceedings Of The 31th Minisymposium
Towards the Requirement-Driven Generation and Evaluation of Hyperledger Fabric Network Designs
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Publication Date
Mon Oct 30 2023
Journal Name
Traitement Du Signal
A Comprehensive Review on Machine Learning Approaches for Enhancing Human Speech Recognition
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Publication Date
Sat Dec 17 2022
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn: 2789-3219 )
Organic Synthesis under Solvent-free Condition (Green Chemistry): A Mini Literature Review
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Solvents are important components in the pharmaceutical and chemical industries, and they are increasingly being used in catalytic reactions. Solvents have a significant influence on the kinetics and thermodynamics of reactions, and they can significantly change product selectivity. Solvents can influence product selectivity, conversion rates, and reaction rates. However, solvents have received a lot of attention in the field of green chemistry. This is due to the large amount of solvent that is frequently used in a process or formulation, particularly during the purification steps. However, neither the solvent nor the active ingredient in a formulation is directly responsible for the reaction product's composition. Because these ch

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Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
A Survey on Arabic Text Classification Using Deep and Machine Learning Algorithms
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    Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th

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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Engineering
The Potential of Recycling Used Engine Oil for Biogas Generation by Co-Digestion with Animals’ Manure: Experimental and Kinetic Study
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This study investigates the potential of biogas recovery from used engine oil (UEO) by co-digestion with animals’ manure, including cow dung (CD), poultry manure (PM), and cattle manure (CM). The experimental work was carried out in anaerobic biodigesters at mesophilic conditions (37°C). Two groups of biodigesters were prepared. Each group consisted of 4 digesters. UEO was the main component in the first group of biodigesters with and without inoculum, whereby a mix of UEO and petroleum refinery oily sludge (ROS) was the component in the second group of biodigesters. The results revealed that for UEO-based biodigesters, maximum biogas production was 0.98, 1.23, 1.93, and 0 ml/g VS from UEO±CD, UEO±CM, UEO±PM, and U

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Publication Date
Sun Jan 22 2023
Journal Name
Mesopotamian Journal Of Big Data
Parallel Machine Learning Algorithms
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 To expedite the learning process, a group of algorithms known as parallel machine learning algorithmscan be executed simultaneously on several computers or processors. As data grows in both size andcomplexity, and as businesses seek efficient ways to mine that data for insights, algorithms like thesewill become increasingly crucial. Data parallelism, model parallelism, and hybrid techniques are justsome of the methods described in this article for speeding up machine learning algorithms. We alsocover the benefits and threats associated with parallel machine learning, such as data splitting,communication, and scalability. We compare how well various methods perform on a variety ofmachine learning tasks and datasets, and we talk abo

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Publication Date
Wed Jul 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Scoping Review of Machine Learning Techniques and Their Utilisation in Predicting Heart Diseases
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Heart diseases are diverse, common, and dangerous diseases that affect the heart's function. They appear as a result of genetic factors or unhealthy practices. Furthermore, they are the leading cause of mortalities in the world. Cardiovascular diseases seriously concern the health and activity of the heart by narrowing the arteries and reducing the amount of blood received by the heart, which leads to high blood pressure and high cholesterol. In addition, healthcare workers and physicians need intelligent technologies that help them analyze and predict based on patients’ data for early detection of heart diseases to find the appropriate treatment for them because these diseases appear on the patient without pain or noticeable symptoms,

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Publication Date
Wed Apr 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Simulation and Analysis the Effect of the Lorentz Force in a Free Electron Laser
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Due to the scientific and technical development in the free electron laser devices and the accompanying industrial and technological progress in various fields of civil and military life, it became necessary to expand the understanding of the mechanism of interaction of electrons (as an effective medium) with the magnetic field that they pass through to form coherent photons.

    In this paper, the Lorentz force effect is simulated and analysed. The results showed that the Lorentz force originates from the magnetic field, making the electron move through it oscillate. This sinusoidal motion of the electron causes it to emit two photons for every electron wavelength. It has been concluded that the electron velocity directly affe

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Publication Date
Fri Aug 02 2024
Journal Name
Quantum Studies: Mathematics And Foundations
Implementation of a modified noise-free and noisy multistage quantum cryptography protocol using QISKIT
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Classical cryptography systems exhibit major vulnerabilities because of the rapid development of quan tum computing algorithms and devices. These vulnerabilities were mitigated utilizing quantum key distribution (QKD), which is based on a quantum no-cloning algorithm that assures the safe generation and transmission of the encryption keys. A quantum computing platform, named Qiskit, was utilized by many recent researchers to analyze the security of several QKD protocols, such as BB84 and B92. In this paper, we demonstrate the simulation and implementation of a modified multistage QKD protocol by Qiskit. The simulation and implementation studies were based on the “local_qasm” simulator and the “FakeVigo” backend, respectively. T

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Publication Date
Thu Dec 09 2021
Journal Name
Journal Of Polymer Research
A new generation of cable grade poly(vinyl chloride) containing heavy metal free modifier
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Abstract<p>Many additives are used to improve the performance of cables in terms of increasing their flame retardancy, thermal stability, thermal conductivity, and other characteristics. Unfortunately, most of these additives contain heavy metals. Therefore, the main objective of this study is to introduce a material representing a new generation of environmentally friendly heavy metal-free stabilizers for cable grade poly(vinyl chloride) that can compete with traditional materials in terms of performance and distinctive properties. This unique additive is Oxydtron, a synthetic silicate or simply nanocement. The tests performed are rheological properties represented by a capillary rheometry analysis, limiting o</p> ... Show More
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