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Employ Mathematical Model and Neural Networks for Determining Rate Environmental Contamination
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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
An Evolutionary Algorithm With Heuristic Operator for Detecting Protein Complexes in Protein Interaction Networks With Negative Controls
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Publication Date
Mon Feb 01 2016
Journal Name
Swarm And Evolutionary Computation
Improving the performance of evolutionary multi-objective co-clustering models for community detection in complex social networks
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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
STATIC PERFORMANCE CHARACTERISTICS OF VORTEX RATE SENSOR
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The vortex rate sensor is a fluidic gyroscope with no moving parts and can be used in very difficult
conditions like radiation, high temperature and noise with minimum cost of manufacturing and
maintenance. A vortex rate sensor made of wood has been designed and manufactured to study
theoretically and experimentally its static performance .A rig has been built to carry out the study,
the test carried out with three different air flow rates (100, 150, and 200 l/min).The results show that
the relation between the differential pressure taken from the sensor pickoff points and the angular
velocity of the sensor was linear.The present work involved theoretical and experimental study of
vortex rate sensor static characteri

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Static Performance Characteristics Of Vortex Rate Sensor
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The vortex rate sensor is a fluidic gyroscope with no moving parts and can be used in very difficult conditions like radiation, high temperature and noise with minimum cost of manufacturing and maintenance. A vortex rate sensor made of wood has been designed and manufactured to study theoretically and experimentally its static performance .A rig has been built to carry out the study,
the test carried out with three different air flow rates (100, 150, and 200 l/min).The results show that the relation between the differential pressure taken from the sensor pickoff points and the angular velocity of the sensor was linear.The present work involved theoretical and experimental study of vortex rate sensor static characteristics .Vortex rat

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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
Oscillation of the per capita growth rate
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in this paper cquations of the per capita growth rate are considered sufficient conditions for oscillation of all solutions are obtained the asymptotie behavior of the nonoscillatory solution of all souliotions are obtained

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Publication Date
Thu Aug 30 2018
Journal Name
Journal Of Engineering
Babylon Governorate Municipal Solid Waste Generation Rate
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Municipal solid waste generation in Babylon Governorate is often affected by changes in lifestyles, population growth, social and cultural habits and improved economic conditions. This effect will make it difficult to plan and draw up future plans for solid waste management.In this study, municipal solid waste was divided into residential and commercial solid wastes. Residential solid wastes were represented by household wastes, while commercial solid wastes included commercial, institutional and municipal services wastes.For residential solid wastes, the relational stratified random sampling was implemented, that is the total population should be divided into clusters (socio-income level), a random sample was taken in e

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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Engineering
Spiking Neural Network in Precision Agriculture
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In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Data Classification using Quantum Neural Network
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In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

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Publication Date
Sun Sep 07 2008
Journal Name
Baghdad Science Journal
Hybrid Cipher System using Neural Network
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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. In this work, we implement an interaction between the feedforward neural network and the stream cipher, so the secret message will be encrypted by unsupervised neural network method in addition to the first encryption process which is performed by the stream cipher method. 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 le

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Publication Date
Sun Jun 06 2010
Journal Name
Baghdad Science Journal
Using Neural Network with Speaker Applications
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In Automatic Speech Recognition (ASR) the non-linear data projection provided by a one hidden layer Multilayer Perceptron (MLP), trained to recognize phonemes, and has previous experiments to provide feature enhancement substantially increased ASR performance, especially in noise. Previous attempts to apply an analogous approach to speaker identification have not succeeded in improving performance, except by combining MLP processed features with other features. We present test results for the TIMIT database which show that the advantage of MLP preprocessing for open set speaker identification increases with the number of speakers used to train the MLP and that improved identification is obtained as this number increases beyond sixty.

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