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Development, Validation, and Performance Evaluation of An Air-Driven Free-Piston Linear Expander Numerical Model
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Publication Date
Sun Sep 29 2019
Journal Name
Iraqi Journal Of Science
Dependent Element and Free Actions of Centralizer and Reverse Centralizer on Prime and Semiprime Semirings
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     This paper develops the work of Mary Florence et.al. on centralizer of semiprime semirings and presents reverse centralizer of semirings with several propositions and lemmas. Also introduces the notion of dependent element and free actions on semirings with some results of free action of centralizer and reverse centralizer on semiprime semirings and some another mappings.

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Publication Date
Fri Oct 04 2024
Journal Name
Analytical And Bioanalytical Chemistry Research
Optimization and Validation of a GC-FID/QuEChERS Method for Quantitative Determination of Spiromesifen Residues in Tomato Fruits, Leaves and Soil Matrices
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Pesticides serve a crucial function in contemporary farming practices, safeguarding agricultural crops against pest infestations and boosting production outputs. However, indiscriminate use has caused environmental and human health damage. This study aimed to develop and validate a gas chromatography-flame ionization detection (GC-FID) methodology for the direct and routine analysis of spiromesifen residues in soil, leaves, and tomato fruits. The proposed method prioritizes simplicity by avoiding derivatization steps, offering advantages over existing approaches that utilize lengthy multi-step extraction or derivatization prior to GC analysis. A key novelty of this work is the development of a QuEChERS extraction coupled directly to GC-FID

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Publication Date
Thu Feb 01 2018
Journal Name
Italian Journal Of Pure And Applied Mathematics
A note on s-acts and bounded linear operators
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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Speech Signal Compression Using Wavelet And Linear Predictive Coding
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A new algorithm is proposed to compress speech signals using wavelet transform and linear predictive coding. Signal compression based on the concept of selecting a small number of approximation coefficients after they are compressed by the wavelet decomposition (Haar and db4) at a suitable chosen level and ignored details coefficients, and then approximation coefficients are windowed by a rectangular window and fed to the linear predictor. Levinson Durbin algorithm is used to compute LP coefficients, reflection coefficients and predictor error. The compress files contain LP coefficients and previous sample. These files are very small in size compared to the size of the original signals. Compression ratio is calculated from the size of th

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Publication Date
Wed Nov 15 2023
Journal Name
Bionatura
Evaluation of frictional forces between aesthetic brackets and archwires in wet conditions (An in-vitro study)
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Frictional resistance occurs whenever sliding happens, negatively impacting treatment outcomes and duration. It is a clinical challenge and must be dealt with efficiently to achieve the best orthodontic results. Aims of this study: compare and evaluate the static frictional forces under the wet condition to mimic the oral environment produced by using a polycrystalline ceramic bracket, monocrystalline ceramic bracket, 0.014 of an inch nickel-titanium (Rhodium coated archwires, and ilusio aesthetic archwires), and 0.019 x 0.025 of an inch stainless steel (Rhodium coated archwires, and ilusio aesthetic archwires). Ninety-six aesthetic brackets (48 monocrystalline and 48 polycrystalline brackets) were used and stored in different incub

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Publication Date
Fri Nov 29 2024
Journal Name
The Iraqi Geological Journal
Data Driven Approach for Predicting Pore Pressure of Oil and Gas Wells, Case Study of Iraq Southern Oilfields
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Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Engineering
Evaluation of the Performance of Online GPS/GNSS Data Processing Services for Monitoring the Land Deformations and Movements
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In recent years, the Global Navigation Satellite Services (GNSS) technology has been frequently employed for monitoring the Earth crust deformation and movement. Such applications necessitate high positional accuracy that can be achieved through processing GPS/GNSS data with scientific software such as BERENSE, GAMIT, and GIPSY-OSIS. Nevertheless, these scientific softwares are sophisticated and have not been published as free open source software. Therefore, this study has been conducted to evaluate an alternative solution, GNSS online processing services, which may obtain this privilege freely. In this study, eight years of GNSS raw data for TEHN station, which located in Iran, have been downloaded from UNAVCO website

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Publication Date
Fri Jul 01 2011
Journal Name
Energy
Experimental and numerical analysis of electrical metal foam heater
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A novel concept of air heater using a heating element made from Aluminum metal porous disc surrounded by a DC resistive electrical heater inserted in the mid-plane of a copper tube of (52.8 mm) diameter and (480 mm) length is presented herein. Study of the developed heater is conducted; using different porous disc thicknesses of (20, 40, 60 mm), heater wall temperatures (106 °C and 119 °C), and flow rates rare varied from (100–300 L/min). Al-metal foam disc has been made using the metal powder technology. Different resistive electrical heaters according to the type of porous disc used have been manufactured. A 2-D computational model is developed, using continuity, momentum, and energy equations for turbulent forced flow in plain tube,

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
EXPERIMENTAL AND NUMERICAL STRESS ANALYSIS OF INVOLUTE SPLINED SHAFT
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In this study, the induced splined shaft teeth contact and bending stresses have been investigated numerically using finite element method(Ansys package version 11.0) with changing the most effecting design parameter,(pressure angle, teeth number, fillet radius and normal module), for internal and external splined shaft. Experimental work has been achieved using two dimensional photoelastic techniques to get the contact and bending stresses; the used material is Bakelite sheet type “PSM-4”.
The results of numerical stress analysis indicate that, the increasing of the pressure angle and fillet radius decrease the bending stress and increase the contact stress for both internal and external spline shaft teeth while the increasing of

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