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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
Sat Aug 01 2015
Journal Name
Journal Of Engineering
Improving the productivity of single effect double slope solar still by modification simple
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The present paper is an experimental study to improve the productivity of the conventional solar still. This done by modifying conventional still in a way that the distilled basin is larger than distillation basin, thus providing an increase in the condensation surface and speeding up the condensation process. Moreover, increase in the dimensions of the distilled base helps coupling reflective panels to the distilled base to reflect incident solar radiation to the distillation basin. For this purpose , two solar stills were made, one conventional designand another made according to the proposed design. The two solar stills were tested during the period from February to July 2009 under varying weather conditions of Basra, Iraq (latitude o

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
"Compared some of the semi-parametric methods in analysis of single index model "
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As the process of  estimate for model and variable selection significant is a crucial process in the semi-parametric modeling At the beginning of the modeling process often At there are many explanatory variables to Avoid the loss of any explanatory elements may be important as a result , the selection of significant variables become necessary , so the process of variable selection is not intended to simplifying  model complexity explanation , and also predicting. In this research was to use some of the semi-parametric methods (LASSO-MAVE , MAVE and The proposal method (Adaptive LASSO-MAVE) for variable selection and estimate semi-parametric single index model (SSIM) at the same time .

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Publication Date
Sun Jan 27 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Impact dimensions the Training process of the in components intellectual capital: Exploratory search in the National Insurance Company
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The concept of training is no longer traditionally understood Limited organize traditional training courses, but has become a strategic choice in the investment and development of human resources system, attic trying to find the answer to the core problem of the study which

is the extent to which the training process, the traditional form that meets the needs of the company the development of intellectual capital.This research aimstostatementof the impact dimensions the training process(training role, support or top management , training programs, modern technology)of the in components Intellectual Capital(Human Capital, Structural Capital, Customer Capital) and provide the top management of the Company for the development of sci

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Publication Date
Fri Oct 19 2018
Journal Name
Journal Of Economics And Administrative Sciences
THE IMPACT OF TRAINING BASED UPON MERITS IN IMPROVING THE EMPLOYEES PERFORMANCE AT THE JORDANIAN UNIVERSITY HOSPITALS Abstract
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The study aims to identify the impact of competency-based training in its dimensions (skills, cognitive abilities, attitudes, and attitudes) in improving the performance of employees (achievement, strategic thinking and problem solving) in Jordanian university hospitals.

The study based on analytical descriptive method. The study population consisted of the Jordanian University Hospitals, the University Hospital of Jordan and the King Abdullah Hospital, as applied study case. The sample of the study consists of all upper and middle administrative employees of these hospitals; questionnaire distributed all of them and the number of valid questionnaires for analysis were 182 questionnaire.

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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
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
Mon Apr 01 2013
Journal Name
Journal Of Drugs In Dermatology (jdd)
The Therapeutic Role of Isotretinoin in the Management of Behçet's Disease: A Single-Blinded, Controlled Therapeutic Study - JDDonline - Journal of Drugs in Dermatology
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AbstractOBJECTIVES: To evaluate the long-term remission efficacy and safety of isotretinoin in the treatment of Behcet's disease (BD). PATIENTS and METHODS: This single-blind, controlled therapeutic study was conducted in the Department of Dermatology and Venereology at Baghdad Teaching Hospital from February 2011 to January 2012. Thirty patients with BD were included in this work. Each patient received isotretinoin 20 mg orally once daily for 3 months. They were assessed at week 2 and then monthly depending on the Clinical Manifestation Index (CMI) and to record any side effects. At week 12, isotretinoin was stopped and patients were given placebo therapy in a form of glucose capsules for another 3 months. RESULTS: Thirty patients were tre

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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
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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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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