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Experimental investigation of a new sustainable approach for recycling waste styrofoam food containers in lightweight concrete
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Publication Date
Thu Nov 03 2022
Journal Name
Frontiers In Applied Mathematics And Statistics
Prey fear of a specialist predator in a tri-trophic food web can eliminate the superpredator
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We propose an intraguild predation ecological system consisting of a tri-trophic food web with a fear response for the basal prey and a Lotka–Volterra functional response for predation by both a specialist predator (intraguild prey) and a generalist predator (intraguild predator), which we call the superpredator. We prove the positivity, existence, uniqueness, and boundedness of solutions, determine all equilibrium points, prove global stability, determine local bifurcations, and illustrate our results with numerical simulations. An unexpected outcome of the prey's fear of its specialist predator is the potential eradication of the superpredator.

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Cybersecurity And Information Management
A New Automated System Approach to Detect Digital Forensics using Natural Language Processing to Recommend Jobs and Courses
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A resume is the first impression between you and a potential employer. Therefore, the importance of a resume can never be underestimated. Selecting the right candidates for a job within a company can be a daunting task for recruiters when they have to review hundreds of resumes. To reduce time and effort, we can use NLTK and Natural Language Processing (NLP) techniques to extract essential data from a resume. NLTK is a free, open source, community-driven project and the leading platform for building Python programs to work with human language data. To select the best resume according to the company’s requirements, an algorithm such as KNN is used. To be selected from hundreds of resumes, your resume must be one of the best. Theref

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Publication Date
Wed Jan 01 2025
Journal Name
Iv. International Rimar Congress Of Pure, Applied Sciences
A New Intrusion Detection Approach Based on RNA Encoding and K-Means Clustering Algorithm Using KDD-Cup99 Dataset
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Intrusion detection systems (IDS) are useful tools that help security administrators in the developing task to secure the network and alert in any possible harmful event. IDS can be classified either as misuse or anomaly, depending on the detection methodology. Where Misuse IDS can recognize the known attack based on their signatures, the main disadvantage of these systems is that they cannot detect new attacks. At the same time, the anomaly IDS depends on normal behaviour, where the main advantage of this system is its ability to discover new attacks. On the other hand, the main drawback of anomaly IDS is high false alarm rate results. Therefore, a hybrid IDS is a combination of misuse and anomaly and acts as a solution to overcome the dis

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Publication Date
Wed May 13 2026
Journal Name
Journal Of Engineering
Experimental Investigation of Nano Alumina and Nano Silica on Strength and Consistency of Oil Well Cement
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Publication Date
Sun Jun 30 2019
Journal Name
Journal Of Engineering
An experimental and numerical investigation of heat transfer effect on cyclic fatigue of gas turbine blade
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Blades of gas turbine are usually suffered from high thermal cyclic load which leads to crack initiated and then crack growth and finally failure. The high thermal cyclic load is usually coming from high temperature, high pressure, start-up, shut-down and load change. An experimental and numerical analysis was carried out on the real blade and model of blade to simulate the real condition in gas turbine. The pressure, temperature distribution, stress intensity factor and the thermal stress in model of blade have been investigated numerically using ANSYS V.17 software. The experimental works were carried out using a particular designed and manufactured rig to simulate the real condition that blade suffers from. A new cont

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Publication Date
Sun Nov 26 2017
Journal Name
Journal Of Engineering
Experimental Investigation of Nano Alumina and Nano Silica on Strength and Consistency of Oil Well Cement
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In oil and gas well cementing, a strong cement sheath is wanted to insure long-term safety of the wells. Successful completion of cementing job has become more complex, as drilling is being done in highly deviated and high pressure-high temperature wells. Use of nano materials in enhanced oil recovery, drilling fluid, oil well cementing and other applications is being investigated. This study is an attempt to investigate the effect of nano materials on oil well cement properties. Two types of nano materials were investigated, which are Nano silica (>40 nm) and Nano Alumina (80 nm) and high sulfate-resistant glass G cement is used. The investigated properties of oil well cement included compressive strength, thickening

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Publication Date
Tue Mar 01 2022
Journal Name
Journal Of Engineering
Numerical Investigation of the Flexure Behavior of Reinforced Concrete Spandrel Beams with Distributed Tension Reinforcement
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When the flange of a reinforced concrete spandrel beam is in tension, current design codes and specifications enable a portion of the bonded flexure tension reinforcement to be distributed over an effective flange width. The flexural behavior of the RC L-shaped spandrel beam when reinforcement is laterally displaced in the tension flange is investigated experimentally and numerically in this work. Numerical analysis utilizing the finite element method is performed on discretized flanged beam models validated using experimentally verified L-shaped beam specimens to achieve study objectives. A parametric study was carried out to evaluate the influence of various factors on the beam’s flexure behavior. Results showed that

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Publication Date
Mon Jan 01 2024
Journal Name
The Scientific World Journal
Mathematical Modeling and Experimental Investigation of the Dynamic Response for an Annular Circular Plate Made of Glass/Polyester Composite Under Different Boundary Conditions
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Fiber‐reinforced elastic laminated composites are extensively used in several domains owing to their high specific stiffness and strength and low specific density. Several studies were performed to ascertain the factors that affect the composite plates’ dynamic properties. This study aims to derive a mathematical model for the dynamic response of the processed composite material in the form of an annular circular shape made of polyester/E‐glass composite. The mathematical model was developed based on modified classical annular circular plate theory under dynamic loading, and all its formulas were solved using MATLAB 2023. The mathematical model was also verified with real experimental work involving the vibration test of the f

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Publication Date
Sun Mar 15 2020
Journal Name
Journal Of The College Of Education For Women
Data-Driven Approach for Teaching Arabic as a Foreign Language: Eygpt
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Corpus linguistics is a methodology in studying language through corpus-based research. It differs from a traditional approach in studying a language (prescriptive approach) in its insistence on the systematic study of authentic examples of language in use (descriptive approach).A “corpus” is a large body of machine-readable structurally collected naturally occurring linguistic data, either written texts or a transcription of recorded speech, which can be used as a starting-point of linguistic description or as a means of verifying hypotheses about a language.  In the past decade, interest has grown tremendously in the use of language corpora for language education. The ways in which corpora have been employed in language pedago

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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