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Using Remote Sensing and GIS in Measuring Vegetation Cover Change from Satellite Imagery in Mosul City, North of Iraq
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Abstract<p>The aim of the study is the assessment of changes in the land cover within Mosul City in the north of Iraq using Geographic Information Systems (GIS) and remote sensing techniques during the period (2014-2018). Satellite images of the Landsat 8 on this period have been selected to classify images in order to measure normalized difference vegetation index (NDVI) to assess land cover changes within Mosul City. The results indicated that the vegetative distribution ratio in 2014 is 4.98% of the total area under study, decreased to 4.77% in 2015 and then decreased to 4.54 <italic>%</italic> in 2016, after then decreased to 3,59% in 2017,then increased to 4.39% in 2018. Land cover change of the area was identified using Normalized Difference Vegetation Index (NDVI) technique. Highest NDVI value was found in 2015 (6.26%) which denotes presence of moderate-high vegetation cover at that time period. After 2015, highest NDVI value was found following a decreasing trend (6.05% in 2016 and 5.96% in 2018) which clearly represents the vegetation cover change in the study area, also Green Normalized. Difference Vegetation Index (GNDVI) is studied in this paper. Statistical properties for NDVI and GNDVI were illustrated has been computed. From the results of this study one can clearly notice that there are the spatial variation in the vegetal cover from 2014 to 2018 in Mosul city, north of Iraq.</p>
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Publication Date
Tue Aug 01 2017
Journal Name
International Journal Of Advanced Research In Computer And Communication Engineering
Information hiding by using Developed M8PAM Technique
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Publication Date
Tue Oct 27 2020
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
AUTOMATIC ARABIC KEYWORD EXTRACTION USING LOGISTIC REGRESSION
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Publication Date
Mon Oct 01 2018
Journal Name
International Journal Of Modern Trends In Engineering And Research
Quadtree Partitioning Scheme using Fixed Predictor Base
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Publication Date
Sun Mar 06 2011
Journal Name
Baghdad Science Journal
Numeral Recognition Using Statistical Methods Comparison Study
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The area of character recognition has received a considerable attention by researchers all over the world during the last three decades. However, this research explores best sets of feature extraction techniques and studies the accuracy of well-known classifiers for Arabic numeral using the Statistical styles in two methods and making comparison study between them. First method Linear Discriminant function that is yield results with accuracy as high as 90% of original grouped cases correctly classified. In the second method, we proposed algorithm, The results show the efficiency of the proposed algorithms, where it is found to achieve recognition accuracy of 92.9% and 91.4%. This is providing efficiency more than the first method.

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Publication Date
Wed Jan 01 2020
Journal Name
Solid State Technology
Image Fusion Using A Convolutional Neural Network
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Image Fusion Using A Convolutional Neural Network

Publication Date
Thu Jul 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Application
Forecasting enhancement using a hodrick-prescott filter
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: Sound forecasts are essential elements of planning, especially for dealing with seasonality, sudden changes in demand levels, strikes, large fluctuations in the economy, and price-cutting manoeuvres for competition. Forecasting can help decision maker to manage these problems by identifying which technologies are appropriate for their needs. The proposal forecasting model is utilized to extract the trend and cyclical component individually through developing the Hodrick–Prescott filter technique. Then, the fit models of these two real components are estimated to predict the future behaviour of electricity peak load. Accordingly, the optimal model obtained to fit the periodic component is estimated using spectrum analysis and Fourier mod

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Scopus
Publication Date
Sun Jun 01 2008
Journal Name
Baghdad Science Journal
The Writer Authentication by Using Syllables Frequency
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An approach is depended in the recent years to distinguish any author or writer from other by analyzing his writings or essays. This is done by analyzing the syllables of writings of an author. The syllable is composed of two letters; therefore the words of the writing are fragmented to syllables and extract the most frequency syllables to become trait of that author. The research work depend on analyzed the frequency syllables in two cases, the first, when there is a space between the words, the second, when these spaces are ignored. The results is obtained from a program which scan the syllables in the text file, the performance is best in the first case since the sequence of the selected syllables is higher than the same syllables in

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Publication Date
Sun Jan 04 2015
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Laparoscopic splenectomy using bipolar vessel sealing system
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Background: Newly developed vessels sealing device built upon bipolar diathermy technology had a great
impact on facilitating advances laparoscopic surgery. Laparoscopic splenectomy is well established procedure
but in this study the procedure is totally based on bipolar vessel sealing system in devascularization of the
spleen.
Objective: To evaluate the safety of laparoscopic splenectomy with vessels sealing device and its
outcome.
Patient and method: Prospective study conducted in Baghdad Teaching Hospital and Dijlah private hospital
from October 2009 to October 2013. Thirty patients with idiopathic thrombocytopenic purpura(ITP) were
included and had laparoscopic splenectomy . The adapted procedure was stapleles

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Publication Date
Wed Mar 01 2017
Journal Name
2017 Annual Conference On New Trends In Information &amp; Communications Technology Applications (ntict)
An efficient color quantization using color histogram
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Publication Date
Thu Nov 01 2018
Journal Name
2018 1st Annual International Conference On Information And Sciences (aicis)
Speech Emotion Recognition Using Minimum Extracted Features
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Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

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