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jcoeduw-211
The Services in Central Library of Salah Eldeen University and The Attitude to Computerize (Cause Study)
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The aim object of research is to show the computerized services library of Salahaldeen University in Erbil city in Iraq, so the research treatment all side of library such as building, location ,staff ,finance, resource collection and services ,we refer to. problem which face library such as administration and finance through the using Of case study method, reference source ,meeting , online comment and data record .The study focus develop in library departments, users services, management ,staff, the resource collection, building and location.
The study ending with many results and recommendation to develop the library services by using modern Information system to all users inside and outside the university and link them with other modern communities.

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Publication Date
Sun Dec 30 2018
Journal Name
Journal Of Engineering
Adsorptive Removal of Furfural from Wastewater on Prepared Activated Carbon from Sawdust
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Furfural is a toxic aromatic aldehyde that can cause a severe environmental problem especially the wastewater drown from petroleum refinery units. In the present work, a useless by-product from local furniture manufacturing industry; sawdust was used as raw material for the preparation of activated carbon which is chemically activated with phosphoric acid. The effect of adsorption variables which include initial pH of solution (2-9), agitation speed (50-250) rpm, agitation time (15-120) min, initial concentration of furfural (50-250) ppm, and amount of adsorbent material (0.5-2.5) g for the three adsorbents used (prepared activated carbon, commercial activated carbon and raw sawdust) were investigated in a batch process

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Strengthening of Reinforced Concrete T- Section Beams Using External Post-Tensioning Technique
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This research is carried out to investigate the externally post-tensioning technique for strengthening RC beams. In this research, four T-section  RC beams having the same dimensions and material properties were casted and tested up to failure by applying two mid-third concentrated loads. Three of these beams are strengthened by using external tendons, while the remaining beam is kept without strengthening as a control beam. Two external strands of 12 mm diameter were fixed at each side of the web of the strengthened beams and located at depth of 200 mm from top fiber of the section (dps). So that the depth of strands to overall depth of the section ratio (dps

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Publication Date
Fri Jul 01 2022
Journal Name
Ieee Transactions On Systems, Man, And Cybernetics: Systems
Design of Robust Terminal Sliding Mode Control for Underactuated Flexible Joint Robot
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Flexible joint robot (FJR) manipulators can offer many attractive features over rigid manipulators, including light weight, safe operation, and high power efficiency. However, the tracking control of the FJR is challenging due to its inherent problems, such as underactuation, coupling, nonlinearities, uncertainties, and unknown external disturbances. In this article, a terminal sliding mode control (TSMC) is proposed for the FJR system to guarantee the finite-time convergence of the systems output, and to achieve the total robustness against the lumped disturbance and estimation error. By using two coordinate transformations, the FJR dynamics is turned into a canonical form. A cascaded finite-time sliding mode observer (CFTSMO) is construct

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Wed Sep 20 2023
Journal Name
International Journal Of Dentistry
Improving Surface Properties of PEEK for Dental Applications by Using Piranha Solution
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Background. “Polyetheretherketone (PEEK)” is a biocompatible, high-strength polymer that is well-suited for use in dental applications due to its unique properties. However, achieving good adhesion between PEEK and hydrophilic materials such as dental adhesives or cement can be challenging. Also, this hydrophobicity may affect the use of PEEK as an implant material. Surface treatment or conditioning is often necessary to improve surface properties. The piranha solution is the treatment of choice to be explored for this purpose. Methods. PEEK disks of 10 mm diameter and 2 mm thickness were used in this study. Those samples were divided into five groups (each group has five samples). The first is the control group, in which no

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Publication Date
Sun Apr 02 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Traffic Classification of IoT Devices by Utilizing Spike Neural Network Learning Approach
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Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Engineering
Improvement of Earth Canals Constructed on Gypseous Soil by Soil Cement Mixture
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The gypseous soil may be one of the problems that face the engineers especially when it used as a foundation for hydraulic structures, roads, and other structures. Gypseous soil is strong soil and has good properties when it is dry, but the problem arises when building hydraulic installations or heavy buildings on this soil after wetting the water to the soil by raising the water table level from any source or from rainfall which leads to dissolve the gypsum content.

Cement-stabilized soil has been successfully used as a facing or lining for earth channel, highway embankments and drainage ditches to reduce the risk of erosion and collapsibility of soil. This study is deliberate the treatment of gypseous soil by u

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Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
Regression Modeling of EDM Process for AISI D2 Tool Steel with RSM
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In this paper, Response Surface Method (RSM) is utilized to carry out an investigation of the impact of input parameters: electrode type (E.T.) [Gr, Cu and CuW], pulse duration of current (Ip), pulse duration on time (Ton), and pulse duration off time (Toff) on the surface finish in EDM operation. To approximate and concentrate the suggested second- order regression model is generally accepted for Surface Roughness Ra, a Central Composite Design (CCD) is utilized for evaluating the model constant coefficients of the input parameters on Surface Roughness (Ra). Examinations were performed on AISI D2 tool steel. The important coefficients are gotten by achieving successfully an Analysis of V

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Publication Date
Wed May 10 2023
Journal Name
Diagnostics
A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

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Publication Date
Sun Oct 01 2023
Journal Name
Nanostructures
Effect of Selenium Nanoparticles with Cress Extract on Polycystic Ovary Syndrome (PCOS)
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Selenium is naturally present in the human body, animals, and plants, and is one of the important elements in their growth and maintenance. Recently, the nanoform of selenium has attracted attention due to its low toxicity and a high degree of adsorption compared to its organic and inorganic forms. The current study aimed to examine the effect of Cress leaves (Lepidium sativum L.) extract in combination with selenium nanoparticles in alleviating polycystic ovary syndrome in letrozole-induced PCOS in adult female rats. Nonthermal or cold plasma was used in the synthesis of selenium nanoparticles. Subsequently, the produced nanoparticles were identified, the 30 rats were divided into 6 equal groups, the first group was healthy (negative contr

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