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Enhancing the Delta Training Rule for a Single Layer Feedforward Heteroassociative Memory Neural Network
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In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

Publication Date
Sun May 27 2018
Journal Name
Journal Of Advanced Transportation
Accident Management System Based on Vehicular Network for an Intelligent Transportation System in Urban Environments
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As cities across the world grow and the mobility of populations increases, there has also been a corresponding increase in the number of vehicles on roads. The result of this has been a proliferation of challenges for authorities with regard to road traffic management. A consequence of this has been congestion of traffic, more accidents, and pollution. Accidents are a still major cause of death, despite the development of sophisticated systems for traffic management and other technologies linked with vehicles. Hence, it is necessary that a common system for accident management is developed. For instance, traffic congestion in most urban areas can be alleviated by the real-time planning of routes. However, the designing of an efficie

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Publication Date
Mon Feb 25 2019
Journal Name
Iraqi Journal Of Physics
Comparison study of CC and CH vibration frequencies and eelectronic properties for mono, Di, Tri, and tetra-rings layer of arm chair (SWCNTs)
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Semi-empirical methods were applied for calculating the vibration frequencies and IR absorption intensities for normal coordinates of the {mono (C56H28), di (C84H28), tri (C112H28) and tetra (C140H28)} -rings layer for (7,7) armchair single wall carbon nanotube at their equilibrium geometries which were all found to have D7d symmetry point group.

Assignment of the modes of vibration (3N-6) was done depending on the pictures of their modes by applying (Gaussian 03) program. Comparison of the vibration frequencies of (mono, di, tri and tetra) rings layer which are active in IR, and inactive in Ramman spectra. For C-H stretching vibrat

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Materials Science: Materials In Electronics
Influence of cobalt doping on structural and optical properties of copper oxide expected as an inorganic hole transport layer for perovskite solar cell
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Publication Date
Wed Apr 05 2023
Journal Name
Journal Of Engineering
Effect of Nb Addition on Hardness and Wear Resist of Cu-Al-Ni Shape Memory Alloy Fabricated By Powder Metallurgy
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Cu-Al-Ni shape memory alloy specimens has been fabricated using powder metallurgy technique with tube furnace and vacuum sintering environment , three range of Nb powder weight percentage (0.3,0.6,0.9)% has been added. Micro hardness and sliding wear resist has been tested followed by X-ray diffraction, scanning electron microscope (SEM) and energy dispersive X-ray spectroscope (EDX) for micro structure observation. The experimental test for the samples has showed that the increase of Nb powder weight percentage in the master alloy has a significant effect on increasing the hardness and decreasing the wear resist therefore it will enhance the mechanical properties for this alloy.

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Publication Date
Fri Jun 30 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Enhanced Prosthesis Control Through Improved Shoulder Girdle Motion Recognition Using Time-Dependent Power Spectrum Descriptors and Long Short-Term Memory
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Surface electromyography (sEMG) and accelerometer (Acc) signals play crucial roles in controlling prosthetic and upper limb orthotic devices, as well as in assessing electrical muscle activity for various biomedical engineering and rehabilitation applications. In this study, an advanced discrimination system is proposed for the identification of seven distinct shoulder girdle motions, aimed at improving prosthesis control. Feature extraction from Time-Dependent Power Spectrum Descriptors (TDPSD) is employed to enhance motion recognition. Subsequently, the Spectral Regression (SR) method is utilized to reduce the dimensionality of the extracted features. A comparative analysis is conducted between the Linear Discriminant Analysis (LDA) class

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
The Transfer Of Training In Framework Of Supporting The Work Environment Characteristics (Filed Research of The Generals lnspectors Offices)
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The  transfer of  training  process occupies a great importance in achieving the ultimate goal of participating in the training programs , it  is sure that this does not take place without the support of the working environment for trainees,  and The research aims to personification role the work environment characteristics  of supporting the transfer of training.                                    

The research problem is the weakness transfer of training to the work en

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Publication Date
Tue Nov 01 2016
Journal Name
Materials Science Forum
Study the Effect of Liquid Layer Level on the Formation of Zinc Oxide Nanoparticles Synthesized by Liquid-Phase Pulsed Laser Ablation
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This work is focused on studying the effect of liquid layer level (height above a target material) on zinc oxide nanoparticles (ZnO and ZnO2) production using liquid-phase pulsed laser ablation (LP-PLA) technique. A plate of Zn metal inside different heights of an aqueous environment of cetyl trimethyl ammonium bromide (CTAB) with molarity (10-3 M) was irradiated with femtosecond pulses. The effect of liquid layer height on the optical properties and structure of ZnO was studied and characterized through UV-visible absorption test at three peaks at 213 nm, 216 nm and 218 nm for three liquid heights 4, 6 and 8 mm respectively. The obtained results of UV–visible spectra test show a blue shift accomp

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Publication Date
Sun Dec 29 2024
Journal Name
Muthanna Journal Of Pure Science
Two-Fold Cryptography: Enhancing Image Security with Henon Map
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This paper introduces an innovative method for image encryption called "Two-Fold Cryptography," which leverages the Henon map in a dual-layer encryption framework. By applying two distinct encryption processes, this approach offers enhanced security for images. Key parameters generated by the Henon map dynamically shape both stages of encryption, creating a sophisticated and robust security system. The findings reveal that Two-Fold Cryptography provides a notable improvement in image protection, outperforming traditional single-layer encryption techniques.

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Publication Date
Thu Dec 21 2023
Journal Name
Mikrobiolohichnyi Zhurnal
Focus on Synergistic Bacteriocin-Nanoparticles Enhancing Antimicrobial Activity Assay
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Antimicrobial resistance is one of the most significant threats to public health worldwide. As opposed to using traditional antibiotics, which are effective against diseases that are multidrug-resistant, it is vital to concentrate on the most innovative antibacterial compounds. These innate bacterial arsenals under the term «bacteriocins» refer to low-molecularweight, heat-stable, membrane-active, proteolytically degradable, and pore-forming cationic peptides. Due to their ability to attack bacteria, viruses, fungi, and biofilm, bacteriocins appear to be the most promising, currently accessible alternative for addressing the antimicrobial resistance (AMR) problem and minimizing the negative effects of antibiotics on the host’s m

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Publication Date
Fri Feb 21 2025
Journal Name
2025 First International Conference On Advances In Computer Science, Electrical, Electronics, And Communication Technologies (ce2ct)
Enhancing Cloud Security Implementing AI-Based Intrusion Detection Systems
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The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion

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