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An in vitro assessment of the physical properties of manually- mixed and encapsulated glass-ionomer cements
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Abstract<sec> <title>Objectives

The last decade has seen a variety of modifications of glass-ionomer cements (GICs), such as inclusion of bioactive glass particles and dispensing systems. Hence, the aim was to systematically evaluate effect of mixing modes and presence of reactive glass additives on the physical properties of several GICs.

Materials and methods

The physical properties of eight commercial restorative GICs; Fuji IX GP Extra (C&H), KetacTM Fill Plus Applicap (C&H), Fuji II LC (C&H), Glass Carbomer Cement and Equia® Forte Fil, capsulated versus manually mixed were assessed. 256 cylindrical specimens were prepared for compressive strength and microhardness, whilst 128 disc-shaped specimens were prepared for biaxial flexural strength tests. Fluid uptake and fluoride release were assessed. Data were analysed using one-way ANOVA and Games-Howell post-hoc tests (alpha = 0.05).

Results

Both encapsulated GIC/RMGICs exhibited significantly improved mechanical properties in comparison to manually mixed equivalents, which in turn showed higher fluid uptake and early fluoride release (p < 0.05). The glass carbomer cement exhibited improved mechanical properties post ageing and evidence of mineral deposits were apparent in the microstructure.

Conclusions

The mixing mode and inclusion of reactive glass additives in cements had a statistically significant effect on physical properties of the selected GICs-RMGICs.

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Publication Date
Tue Jun 01 2021
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
An efficient method for stamps recognition using Haar wavelet sub-bands
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Publication Date
Mon Sep 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Synthesized 2nd Generation Zeolite as an Acid-Catalyst for Esterification Reaction
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MCM-48 zeolites have unique properties from the surfaces and structure point of view as it’s shown in the results ,and unique and very sensitive to be prepared, have been experimentally prepared and utilized as a second-generation/ acid - catalyst for esterification reactions of oleic acid as a model oil for a free fatty acid source with Ethanol. The characterization of the catalyst used in the reaction has been identified by various methods indicating the prepared MCM-48 is highly matching the profile of common commercial MCM-48 zeolite. The XRF results show domination of SiO2 on the chemical structure with 99.1% and  agreeable with the expected from MCM-48 for it's of silica-based, and the SEM results show the cubic c

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Publication Date
Sun Jan 01 2012
Journal Name
International Journal Of Reasoning-based Intelligent Systems
SLMS: a smart library management system based on an RFID technology
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Publication Date
Sat Feb 01 2025
Journal Name
Algorithms
Three-Dimensional Object Recognition Using Orthogonal Polynomials: An Embedded Kernel Approach
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Computer vision seeks to mimic the human visual system and plays an essential role in artificial intelligence. It is based on different signal reprocessing techniques; therefore, developing efficient techniques becomes essential to achieving fast and reliable processing. Various signal preprocessing operations have been used for computer vision, including smoothing techniques, signal analyzing, resizing, sharpening, and enhancement, to reduce reluctant falsifications, segmentation, and image feature improvement. For example, to reduce the noise in a disturbed signal, smoothing kernels can be effectively used. This is achievedby convolving the distributed signal with smoothing kernels. In addition, orthogonal moments (OMs) are a cruc

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Publication Date
Tue Jun 18 2024
Journal Name
2024 Ieee 33rd International Symposium On Industrial Electronics (isie)
An Adaptive Integral Sliding Mode Control for Disturbed Servo Motor Systems
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Abstract-Servo motors are important parts of industry automation due to their several advantages such as cost and energy efficiency, simple design, and flexibility. However, the position control of the servo motor is a difficult task because of different factors of external disturbances, nonlinearities, and uncertainties. To tackle these challenges, an adaptive integral sliding mode control (AISMC) is proposed, in which a novel bidirectional adaptive law is constructed to reduce the control chattering. The proposed control has three steps to be designed. Firstly, a full-order integral sliding manifold is designed to improve the servo motor position tracking performance, in which the reaching phase is eliminated to achieve the invariance of

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Publication Date
Tue Sep 23 2025
Journal Name
Journal Of Plant Protection Research
Smart sprayer for weed control using an object detection algorithm (yolov5)
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Spraying pesticides is one of the most common procedures that is conducted to control pests. However, excessive use of these chemicals inversely affects the surrounding environments including the soil, plants, animals, and the operator itself. Therefore, researchers have been encouraged to...

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Publication Date
Thu Jan 04 2018
Journal Name
Journal Of Electrical Engineering And Technology
An efficient selective method for audio watermarking against de-synchronization attacks
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Publication Date
Fri Mar 01 2024
Journal Name
International Journal Of Medical Informatics
An artificial intelligence approach to predict infants’ health status at birth
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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
An Empirical Investigation on Snort NIDS versus Supervised Machine Learning Classifiers
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With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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