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A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq
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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comparison to the actual observational results. ANN simulation gives a clear insight into three crescent moon visibility regions: invisible (I), probably visible (P), and certainly visible (V). The proposed ANN is suitable for building lunar calendars, so it was used to build a four-year calendar on the horizon of Baghdad. The built calendar was compared with the official Hijri calendar in Iraq.

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Publication Date
Sun Mar 07 2010
Journal Name
Baghdad Science Journal
A systematical study about the genus Lycopus L. (Labiatae) in Iraq
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The study included gross morphology and pollen of plants – which collected during field trips , and dry ones for most specimen preserved with the Iraqi herbaria – related to the genus Lycopus L. , and to identify the unidentified species and rectify the error there in , so according to that the species L. europaeus L. only were specified for the genus . Through this work the varity L. europaeus var. glabrescens Schmidely were found at the first time , and suggested to record anew for Iraq . Pollen were of medium size, and had an ellipsoid shape in the equatorial view , and hexagonal in the polar view. The ecological and soil quality where these genus plants grows were specified , and were geographically distribut

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Publication Date
Sat Oct 29 2022
Journal Name
Current Trends In Geotechnical Engineering And Construction
Simulation Design and Performance of a Residential Complex Using Liquefied Petroleum Gas Network
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The population has been trying to use clean energy instead of combustion. The choice was to use liquefied petroleum gas (LPG) for domestic use, especially for cooking due to its advantages as a light gas, a lower cost, and clean energy. Residential complexes are supplied with liquefied petroleum gas for each housing unit, transported by pipes from LPG tanks to the equipment. This research aims to simulate the design and performance design of the LPG system in the building that is applied to a residential complex in Baghdad taken as a study case with eight buildings. The building has 11 floors, and each floor has four apartments. The design in this study has been done in two parts, part one is the design of an LPG system for one building, an

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
A Software Defined Network of Video Surveillance System Based on Enhanced Routing Algorithms
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Software Defined Network (SDN) is a new technology that separate the ‎control plane from the data plane. SDN provides a choice in automation and ‎programmability faster than traditional network. It supports the ‎Quality of Service (QoS) for video surveillance application. One of most ‎significant issues in video surveillance is how to find the best path for routing the packets ‎between the source (IP cameras) and destination (monitoring center). The ‎video surveillance system requires fast transmission and reliable delivery ‎and high QoS. To improve the QoS and to achieve the optimal path, the ‎SDN architecture is used in this paper. In addition, different routing algorithms are ‎used with different steps. First, we eva

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Fri Dec 01 2017
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
NEW RECORD OF PROTOZOAN NYCTOTHERUS HARDWICKII (JANAKIDEVI, 1961) FROM ROUGH-TAILED GECKO CYRTOPODION SCABRUM IN BAGHDAD, IRAQ
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    The ciliate species isolated from midgut and hindgut of Rough-tailed gecko Cyrtopodion scabrum (Heyden, 1827), identified as Nyctotherus hardwickii was collected from many regions of Baghdad, Iraq. The current study deals with a description and comparison of the morphology and morphometric characters of this species for the first time in Iraq.

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Publication Date
Sun Jun 08 2025
Journal Name
Journal Of Natural Science, Biology And Medicine
The Value of White Blood Cells and Platelets Indices in Prediction of Tubal Ectopic Pregnancy Rupture
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Publication Date
Sun Jun 08 2025
Journal Name
J Nat Sc Biol Med
The Value of White Blood Cells and Platelets Indices in Prediction of Tubal Ectopic Pregnancy Rupture
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Publication Date
Thu Dec 26 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Factors affecting the support of local investment in iraq for the period(1996-2015)
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This paper aims to explain the effect of the taxes policy including direct & indirect taxes on supporting the domestic Investment in Iraq. This could help the official planners for drawing the future policies that help provoking (istumlating) the domestic investment in Iraq the quantitative analysis approach was adopted using regression model. The results showed the significance of the effects of both direct & indirect taxes policies on domestic as a simple correlation coefficient ( r ) of ( 0.6 ) , ( 0.64 ) respectively.  

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Publication Date
Mon Mar 09 2020
Journal Name
Agrosystems, Geosciences & Environment
In-season potato yield prediction with active optical sensors
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Crop yield prediction is a critical measurement, especially in the time when parts of the world are suffering from farming issues. Yield forecasting gives an alert regarding economic trading, food production monitoring, and global food security. This research was conducted to investigate whether active optical sensors could be utilized for potato (Solanum tuberosum L.) yield prediction at the mid.le of the growing season. Three potato cultivars (Russet Burbank, Superior, and Shepody) were planted and six rates of N (0, 56, 112, 168, 224, and 280 kg ha−1), ammonium sulfate, which was replaced by ammonium nitrate in the 2nd year, were applied on 11 sites in a randomized complete block design, with four replications. Normalized difference ve

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Publication Date
Thu Feb 13 2025
Journal Name
Technology In Agronomy
Challenges and innovations in potato harvester design: the role of artificial intelligence in improving crop sorting
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As population growth increases the demand for crops increases and their quality improves, and it becomes necessary to find innovative and modern solutions to enhance production. In this context, artificial intelligence plays a pivotal role in developing new technologies to improve crop sorting and increase agricultural yields. The present review discusses the main differences between manual and mechanical potato harvesting, explaining the advantages and disadvantages of each method. Manual harvesting is highlighted as a traditional method that allows for greater precision in handling the crop, but it requires more time and effort. In contrast, mechanical harvesting provides greater efficiency and speed in the process, but it may damage some

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