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Population Density and Susceptibility of Some Varieties of Potato to Infested by Aphid and Thrips on Spring Plantation in the Middle of Iraq
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Aphid Aphis spp (Hemiptera:Aphididae) and Thrips Thrips spp (Thysanoptera: Thripidae) an economically important pests on several crops in the world and Iraq, that transfer many viruses diseases to it. Field studies were conducted to assessment the population density of these insects and susceptibility of six varieties (Barin, Revera, Divela, Rudlph, Alazata and Pleny) to infestation during 2013 spring season. The results were showed that all Potato varieties were infested by Aphis and Thrips on spring plantation but with different percentage. The Divela variety was higher percentage of infestation and high population density of aphid which averaged 1.47 insect/ leaf while in Alazata was the lower population density which averaged 1.02 insect/ leaf .The higher population density of thrips was recorded on Revera variety with average 2.44 insect / leaf while the lower population density was recorded on Alazata with average 1.61 insect / leaf. The results also showed that the population density of both insect were high at the beginning of the season, reaching 5 insect /leaf for aphid and 6 insect / leaf for thrips in the season half of February,which coincided with emergence of the plants and the beginning of vegetation growth. Different susceptibility were found between varieties to infested by Aphis and Thrips on spring plantation in middle of Iraq.

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Publication Date
Wed Mar 20 2024
Journal Name
Journal Of Petroleum Research And Studies
Advanced Machine Learning application for Permeability Prediction for (M) Formation in an Iraqi Oil Field
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Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

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Publication Date
Fri Oct 26 2018
Journal Name
Al–bahith Al–a'alami
University youth attitudes towards mobile phone Companies advertisements in Social networking sites): :(Facebook as sample
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The advertising has emerged as an effective force and an effective instrument upon with all organizations and companies depend on achieving their goals. In additional to the need to use promote sales, The nature and objective of advertising go beyond the scope of specific personal communication to a broader and more effective range for consumers from multiple groups and combination play need to use as well as the need to use means of communication than com convey the message more professional, The coincides with the rapid and remarkable development of all different media technologies and as much as possible social networking sites including mobile phone companies. The advertising has emerged as an effective force and an effective instrum

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Publication Date
Sun Feb 10 2019
Journal Name
Iraqi National Journal Of Nursing Specialties
Nurses' Practices regarding Patients Discharge Planning post Cardiac Surgery at Cardiac Centers in Baghdad city
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Objective (s): to assess nurses' practices regarding discharge planning post-cardiac surgery and to find out the relationship between nurse practices and demographic characteristic (age, gander, level of education, years of experiences, and years of experiences in surgical ward).
Methodology: A descriptive study was carried out at cardiac centers and hospitals in Baghdad (Ibn Al- Bitar specialized center for cardiac surgery; Iraqi center for heart disease and Ibn al Nafees hospital). For the period of 6th February 2017 up to 1st of June 2018. A non-probability (purposive) sample of (58) nurses (male & female) who were working in surgical wards. The data was collected, by using of a questionnaire, which consists of two parts, part

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Publication Date
Tue Jan 20 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Correlation between crevicular C-reactive protein level with its serum level in chronic periodontitis patients
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Background: The main purpose of this study is to find if there is any correlation between the level of C-reactive protein (CRP) in gingival crevicular fluid with its serum level in chronic periodontitis patients and to explore the differences between them according to the probing depth. Materials and methods: Forty seven male subjects enrolled in this study. Thirty males with chronic periodontitis considered as study group whom further subdivided according to probing depth into subgroup 1 with pocket depth ≤6mm, subgroup 2 with pocket depth >6mm. The other 17 subjects considered as controls. For all subjects, clinical examination where done for periodontal parameters plaque index (PLI), gingival index (GI), bleeding on probing (BOP),

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Publication Date
Sat Apr 01 2023
Journal Name
Digital Communications And Networks
Dynamic channel estimation-aware routing protocol in mobile cognitive radio networks for smart IIoT applications
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Publication Date
Mon Jul 18 2022
Journal Name
Ieee Access
Moderately Multispike Return Neural Network for SDN Accurate Traffic Awareness in Effective 5G Network Slicing
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Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi

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Publication Date
Sat Dec 01 2018
Journal Name
Applied Soft Computing
A new evolutionary algorithm with locally assisted heuristic for complex detection in protein interaction networks
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Publication Date
Thu Dec 05 2019
Journal Name
Advances In Intelligent Systems And Computing
An Enhanced Evolutionary Algorithm for Detecting Complexes in Protein Interaction Networks with Heuristic Biological Operator
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Publication Date
Tue Jan 15 2019
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Natural Convective Heat Transfer in an Inclined Open Porous Cavity with Non-Uniformly Heated Wall
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Theoretical and experimental investigations of free convection through a cubic cavity with sinusoidal heat flux at bottom wall, the top wall is exposed to an outside ambient while the other walls are adiabatic saturated in porous medium had been approved in the present work. The range of Rayleigh number was and Darcy number values were . The theoretical part involved a numerical solution while the experimental part included a set of tests carried out to study the free convection heat transfer in a porous media (glass beads) for sinusoidal heat flux boundary condition. The investigation enclosed values of Rayleigh number (5845.6, 8801, 9456, 15034, 19188 and 22148) and angles of inclinations (0, 15, 30, 45 and 60 degree). The numerical an

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Publication Date
Wed Nov 05 2025
Journal Name
Irrigation And Drainage
Predicting Potential Salinity in River Water for Irrigation Water Purposes Using Integrative Machine Learning Models
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ABSTRACT<p>Accurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct</p> ... Show More
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