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Forecasting The Wet and Dry Rainy Seasons in Mosul Using Standardized Precipitation Index (SPI)
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Iraq suffers the continuing lack of water resources in generdwether it is surface or underearth water or rain. The study of rain has got the utmost importance in order to the rain direction in Iraq and in Mosul in particular and what it will be in future. It also shows the wet as well as the dry seasons and the possibility of expecting them and expecting their quantities in order to invest them and to keep this vital resource The research deals with predict the wet and dry rainy seasons in Mosul using (SPI) Standardized precipitation index extracted from conversion of Gamma distribution to standardized normal distribution , depending on data of monthly rain amounts for 1940-2013 . Results showed existence of 31 wet rainy seasons , and 42 dry rainy seasons for the whole time of study which is 73 rainy seasons. Results of rainy seasons prediction for the time 2014-2023 showed five wet rainy seasons and five dry rainy seasons , although the general trend of rain in Mosul station refer to declines with time

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Human Face Recognition Using Wavelet Network
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            This paper presents a study of wavelet self-organizing maps (WSOM) for face recognition. The WSOM is a feed forward network that estimates optimized wavelet based for the discrete wavelet transform (DWT) on the basis of the distribution of the input data, where wavelet basis transforms are used as activation function.

 

 

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Publication Date
Mon Dec 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Experimental Investigation of Using Evaporative Air Cooler for Winter Air-Conditioning in Baghdad
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This paper presents an efficient methodology to design modified evaporative air-cooler for winter air-conditioning in Baghdad city as well as using it for summer air-conditioning by adding a heating process after the humidification process. laboratory tests were performed on a direct evaporative cooler (DEC) followed by passing the air on hot water through heat exchanger placed in the coolers air duct exit. The tests were conducted on the 2nd of December /2011 when the ambient temperature was 8.1°C and the relative humidity was  (68%). The air flow rate is assumed to vary between 0.069 to 0.209 kg/s with constant water flow rate of 0.03 kg/s in the heat exchanger. The performance is reported in terms of effectiveness of DEC, satura

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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
CORRELATIONS OF POINT LOAD INDEX AND PULSE VELOCITY WITH THE UNIAXIAL COMPRESSIVE STRENGTH FOR ROCKS
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Rock engineers widely use the uniaxial compressive strength (UCS) of rocks in designing
surface and underground structures. The procedure for measuring this rock strength has been
standardized by both the International Society for Rock Mechanics (ISRM) and American Society
for Testing and Materials (ASTM), Akram and Bakar(2007).
In this paper, an experimental study was performed to correlate of Point Load Index ( Is(50))
and Pulse Wave Velocity (Vp) to the Unconfined Compressive Strength (UCS) of Rocks. The effect
of several parameters was studied. Point load test, Unconfined Compressive Strength (UCS) and
Pulse Wave Velocity (Vp) were used for testing several rock samples with different diameters.
The predicted e

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Publication Date
Sun Dec 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
The Effect of Solvent Extraction of Light Lubricating Oil on Viscosity Index and Chemical Composition
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An investigation was conducted for the improvement of viscosity index of light lubricating oil fraction (40 stock)
obtained from vacuum distillation unit of lube oil plant of Daura Refinery, using solvent extraction process.
In this study furfural solvent was used to extract the undesirable materials which reduce the viscosity index of raw
lubricating oil fraction.
The studied effecting variables of extraction were extraction temperature range from 70 to 110°C, and solvent to oil
ratio range from 1:1 to 4:1 (wt/wt).
The n-d-M method was used for calculation of carbon distribution and structural group analysis of the raffinate
produced from furfural extraction.
Also the three component phase diagram for a mixed-ba

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
Detecting Keratoconus by Using SVM and Decision Tree Classifiers with the Aid of Image Processing
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 Researchers used different methods such as image processing and machine learning techniques in addition to medical instruments such as Placido disc, Keratoscopy, Pentacam;to help diagnosing variety of diseases that affect the eye. Our paper aims to detect one of these diseases that affect the cornea, which is Keratoconus. This is done by using image processing techniques and pattern classification methods. Pentacam is the device that is used to detect the cornea’s health; it provides four maps that can distinguish the changes on the surface of the cornea which can be used for Keratoconus detection. In this study, sixteen features were extracted from the four refractive maps along with five readings from the Pentacam software. The

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Classification of Arabic Alphabets Using a Combination of a Convolutional Neural Network and the Morphological Gradient Method
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The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

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Publication Date
Fri Feb 28 2025
Journal Name
Energies
Synergizing Machine Learning and Physical Models for Enhanced Gas Production Forecasting: A Comparative Study of Short- and Long-Term Feasibility
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

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Publication Date
Wed Mar 13 2019
Journal Name
Al-khwarizmi Engineering Journal
Investigation Microwave Furnace Effects on Mechanical Properties and Fatigue Life of AA 7075-T73 with Dry and Acid Treatments
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Microwave heating is caused by the ability of the materials to absorb microwave energy and convert it to heat. The aim of this study is to know the difference that will occur when heat treating the high strength aluminum alloys AA7075-T73 in a microwave furnace within different mediums (dry and acidic solution) at different times (30 and 60) minutes, on mechanical properties and fatigue life. The experimental results of microwave furnace heat energy showed that there were variations in the mechanical properties (ultimate stress, yielding stress, fatigue strength, fatigue life and hardness) with the variation in mediums and duration times when compared with samples without treatment. The ultimate stress, yielding stress and fatigue streng

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
An Enhanced Approach of Image Steganographic Using Discrete Shearlet Transform and Secret Sharing
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Recently, the internet has made the users able to transmit the digital media in the easiest manner. In spite of this facility of the internet, this may lead to several threats that are concerned with confidentiality of transferred media contents such as media authentication and integrity verification. For these reasons, data hiding methods and cryptography are used to protect the contents of digital media. In this paper, an enhanced method of image steganography combined with visual cryptography has been proposed. A secret logo (binary image) of size (128x128) is encrypted by applying (2 out 2 share) visual cryptography on it to generate two secret share. During the embedding process, a cover red, green, and blue (RGB) image of size (512

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers
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Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

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