Single channel informed signal separation using artificial-stereophonic mixtures and exemplar-guided matrix factor deconvolution
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Publication Date
Tue Jan 01 2019
Journal Name
Open Access Journal Of Chemistry
Publication Date
Tue Jan 01 2019
Journal Name
Open Access Journal Of Chemistry
Publication Date
Wed Feb 01 2023
Journal Name
Trends Technological And Science ,engineering
Automated Sorting for Tomatoes using Artificial Neural Network
A .technology analysis image using crops agricultural of grading and sorting the test to conducted was experiment The device coupling the of sensor a with camera a and 75 * 75 * 50 dimensions with shape cube studio made-factory locally the study to studio the in taken were photos and ,)blue-green - red (lighting triple with equipped was studio The .used were neural artificial and technology processing image using maturity and quality ,damage of fruits the of characteristics external value the quality 0.92062, of was value regression the damage predict to used was network neural artificial The .network the using scheme regression a of means by 0.98654 of was regression the of maturity and 0.97981 of was regression the of .algorithm Marr
... Show MorePublication Date
Tue Dec 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Using Artificial Neural Network Models For Forecasting & Comparison
نماذج الشبكات العصبية الاصطناعية
Artificial Neural Network Models
The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from
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Publication Date
Sun Jan 01 2017
Journal Name
Ieee/acm Transactions On Audio, Speech, And Language Processing
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Publication Date
Tue Dec 01 2015
Journal Name
Second Engineering Scientific Conference
SEPARATION OF ALKALOIDS FROM PLANTS BY BULK LIQUID MEMBRANE TECHNIQUE USING ROTATING DISCS CONTACTOR
Liquid membrane
Extraction
Pelletierine
Alkaloids
This paper describes the transport of Alkaloids through Rotating Discs Contactor (RDC) using n-decane as a liquid membrane. The transport of Pelletierine Alkaloid from a source phase through bulk liquid membrane to the receiving phase has been investigated. The general behaviour of Pertraction process indicates that% Extraction of pelletierine Alkaloid increased with increase in the number of stages and the agitation speed but high agitation speed was not favoured due to the increased risk of droplet formation during the operation. The pH of source and receiving phases were also investigated. The effect of organic solvent membrane on the extraction of Pelletierine was evaluated using ndecane, n-hexane and methyl cyclohexane. The results sho
... Show MorePublication Date
Fri Jan 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Studying the Classification of Texture Images by K-Means of Co-Occurrence Matrix and Confusion Matrix
K-Means
Feature Extraction
Confusion Matrix
Agreement Percent
Class Projection
In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between every
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(5)
Publication Date
Wed Mar 01 2017
Journal Name
Journal Of Collage Of Education
Publication Date
Mon Jul 01 2019
Journal Name
Journal Of Physics: Conference Series
Fibrewise Pairwise Soft Separation Axioms
Abstract<p>The main idea of this research is to study fibrewise pairwise soft forms of the more important separation axioms of ordinary bitopology named fibrewise pairwise soft <italic>T</italic>
<sub>0</sub> spaces, fibrewise pairwise soft <italic>T</italic>
<sub>1</sub> spaces, fibrewise pairwise soft <italic>R</italic>
<sub>0</sub> spaces, fibrewise pairwise soft Hausdorff spaces, fibrewise pairwise soft functionally Hausdorff spaces, fibrewise pairwise soft regular spaces, fibrewise pairwise soft completely regular spaces, fibrewise pairwise soft normal spaces and fibrewise pairw</p>
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Fibrewise bitopological spaces
Fibrewise pairwise soft spaces
Fibrewise pairwise soft spaces
Fibrewise pairwise soft spaces
fibrewise pairwise soft Hausdorff spaces
Fibrewise pairwise soft regular spaces
and fibrewise pairwise soft normal spaces.
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(1)
Publication Date
Mon Nov 11 2019
Journal Name
Spe
Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame</p>
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neural network
strength
machine learning
ROP prediction
Upstream Oil & Gas
prediction
ANN model
input parameter
multiple regression analysis
artificial neural network
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