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Crescent Moon Visibility: A New Criterion using Deep learned Artificial Neural-Network
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     Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certainly visible. This criterion was used on the dataset for ANN learning to compare its efficiency with the actual moon visibility events.

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Clinical And Experimental Dentistry
Resistance of bonded premolars to four artificial ageing models post enamel conditioning with a novel calcium-phosphate paste
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Background: This in vitro study compares a novel calcium-phosphate etchant paste to conventional 37% phosphoric acid gel for bonding metal and ceramic brackets by evaluating the shear bond strength, remnant adhesive and enamel damage following water storage, acid challenge and fatigue loading. Material and Methods: Metal and ceramic brackets were bonded to 240 extracted human premolars using two enamel conditioning protocols: conventional 37% phosphoric acid (PA) gel (control), and an acidic calcium-phosphate (CaP) paste. The CaP paste was prepared from β-tricalcium phosphate and monocalcium phosphate monohydrate powders mixed with 37% phosphoric acid solution, and the resulting phase was confirmed using FTIR. The bonded premolars were exp

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Publication Date
Fri Jan 01 2021
Journal Name
Artificial Intelligence For Covid-19
An Efficient Mixture of Deep and Machine Learning Models for COVID-19 and Tuberculosis Detection Using X-Ray Images in Resource Limited Settings
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
On Training Of Feed Forward Neural Networks
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In this paper we describe several different training algorithms for feed forward neural networks(FFNN). In all of these algorithms we use the gradient of the performance function, energy function, to determine how to adjust the weights such that the performance function is minimized, where the back propagation algorithm has been used to increase the speed of training. The above algorithms have a variety of different computation and thus different type of form of search direction and storage requirements, however non of the above algorithms has a global properties which suited to all problems.

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Publication Date
Mon Jun 19 2017
Journal Name
Arabian Journal For Science And Engineering
A New Method to Tune a Fractional-Order PID Controller for a Twin Rotor Aerodynamic System
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Publication Date
Wed May 09 2018
Journal Name
International Journal Of Advanced Computer Science And Applications
New Techniques to Enhance Data Deduplication using Content based-TTTD Chunking Algorithm
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Publication Date
Wed Feb 29 2012
Journal Name
Al-khwarizmi Engineering Journal
WLAN Integrated with GPRS Network Securely
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In this paper a WLAN network that accesses the Internet through a GPRS network was implemented and tested. The proposed network is managed by the Linux based server. Because of the limited facilities of GPRS such as dynamic IP addressing besides to its limited bandwidth a number of techniques are implemented to overcome these limitations.

      Dynamic Host Configuration Protocol (DHCP) server was added to provide a single central control for all TCP/IP resources. Squid Proxy  was added to provide caching of the redundant accessed Web content to reduce the Internet bandwidth usage and speeding up the client’s download time. Network Address Translation (NAT) service was configured to share one IP ad

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Publication Date
Tue May 16 2023
Journal Name
Journal Of Engineering
Parallel Routing in Wireless Sensor Network
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The limitations of wireless sensor nodes are power, computational capabilities, and memory. This paper suggests a method to reduce the power consumption by a sensor node. This work is based on the analogy of the routing problem to distribute an electrical field in a physical media with a given density of charges. From this analogy a set of partial differential equations (Poisson's equation) is obtained. A finite difference method is utilized to solve this set numerically. Then a parallel implementation is presented. The parallel implementation is based on domain decomposition, where the original calculation domain is decomposed into several blocks, each of which given to a processing element. All nodes then execute computations in parall

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Communications
SDN Implementation in Data Center Network
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Publication Date
Mon Jun 01 2009
Journal Name
2009 Etp International Conference On Future Computer And Communication
Ultra Wideband Cognitive Network Objective Issues
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Due to that the Ultra Wide Band (UWB) technology has some attractive features like robustness to multipath fading, high data rate, low cost and low power consumption, it is widely use to implement cognitive radio network. Intuitively, one of the most important tasks required for cognitive network is the spectrum sensing. A framework for implementing spectrum sensing for UWB-Cognitive Network will be presented in this paper. Since the information about primary licensed users are known to the cognitive radios then the best spectrum sensing scheme for UWB-cognitive network is the matched filter detection scheme. Simulation results verified and demonstrated the using of matched filter spectrum sensing in cognitive radio network with UWB and pro

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Publication Date
Sun Dec 04 2011
Journal Name
Baghdad Science Journal
Modifying Hebbian Network for Text Cipher
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The objective of this work is to design and implement a cryptography system that enables the sender to send message through any channel (even if this channel is insecure) and the receiver to decrypt the received message without allowing any intruder to break the system and extracting the secret information. This work modernize the feedforward neural network, so the secret message will be encrypted by unsupervised neural network method to get the cipher text that can be decrypted using the same network to get the original text. The security of any cipher system depends on the security of the related keys (that are used by the encryption and the decryption processes) and their corresponding lengths. In this work, the key is the final weights

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