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Ultra Wideband Cognitive Network Objective Issues
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Due to that the Ultra Wide Band (UWB) technology has some attractive features like robustness to multipath fading, high data rate, low cost and low power consumption, it is widely use to implement cognitive radio network. Intuitively, one of the most important tasks required for cognitive network is the spectrum sensing. A framework for implementing spectrum sensing for UWB-Cognitive Network will be presented in this paper. Since the information about primary licensed users are known to the cognitive radios then the best spectrum sensing scheme for UWB-cognitive network is the matched filter detection scheme. Simulation results verified and demonstrated the using of matched filter spectrum sensing in cognitive radio network with UWB and proved that the bit error rate for this detection scheme can be considered acceptable.

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Intelligent Systems
An efficient node selection algorithm in the context of IoT-based vehicular ad hoc network for emergency service
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Abstract<p>With the recent growth of global populations, main roads in cities have witnessed an evident increase in the number of vehicles. This has led to unprecedented challenges for authorities in managing the traffic of ambulance vehicles to provide medical services in emergency cases. Despite the high technologies associated with medical tracks and advanced traffic management systems, there is still a current delay in ambulances’ attendance in times of emergency to provide patients with vital aid. Therefore, it is indispensable to introduce a new emergency service system that enables the ambulance to reach the patient in the least congested and shortest paths. However, designing an effici</p> ... Show More
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Publication Date
Wed Oct 01 2014
Journal Name
Engineering And Technology Journal
Investigating Forward kinematic Analysis of a 5-axes Robotic Manipulator using Denavit-Hartenberg Method and Artificial Neural Network
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Publication Date
Fri Sep 24 2021
Journal Name
Journal Of The College Of Education For Women
Arabic Language Teachers’ Training Needs for Implementing Cognitive Trips Strategy when Teaching Arabic Language Courses in the Kingdom of Saudi Arabia: أمل ناصر الحربي, و وفاء العويضي
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The present work focuses on examining the strategy of cognitive trips and the Arabic language teachers’ training needs of such a strategy when teaching Arabic language courses in the Saudi Arabia Kingdom. To achieve the objective of the study, and check whether this strategy is used in lesson planning, lesson teaching, or lesson assessment, a descriptive approach and a questionnaire have been adopted. The researchers used a number of statistical tools, and chose a purposive sample, which consists of (58) Arabic language teachers from Saudi Arabia Kingdom. Results have shown that the training needs of Arabic language teachers for implemining the strategy of cognitive journeys while teaching Arabic language courses came in the following

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Publication Date
Sat Nov 26 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Measuring the tax gap resulting from the application of the direct deduction method and its reflection on the financial objective of the tax: Applied research in the General Directorate of education in Diyala
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The research aims to shed light on the nature of the tax gap in the income tax by the method of direct deduction and its reflection on the financial objective of the tax, and to determine the reasons for this gap in the deduction between the tax due in accordance with the laws and instructions in force and the tax actually paid. The tax gap is a real problem that cannot be ignored for what it represents loss of financial revenues due to the state.

The research problem is represented in the existence of a gap between the tax due according to direct deduction instructions and the tax actually paid according to the financial statements, and to achieve the objectives of the research and test the hypotheses, t

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Publication Date
Sun Dec 17 2017
Journal Name
Al-khwarizmi Engineering Journal
Experimental and Prediction Using Artificial Neural Network of Bed Porosity and Solid Holdup in Viscous 3-Phase Inverse Fluidization
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In the present investigation, bed porosity and solid holdup in viscous three-phase inverse fluidized bed (TPIFB) are determined for aqueous solutions of carboxy methyl cellulose (CMC) system using polyethylene and polypropylene as  a particles with low-density and diameter (5 mm) in a (9.2 cm) inner diameter with height (200 cm) of vertical perspex column. The effectiveness of gas velocity Ug , liquid velocity UL, liquid viscosity μL, and particle density ρs on bed porosity BP and solid holdups εg were determined. The bed porosity increases with "increasing gas velocity", "liquid velocity", and "liquid viscosity". Solid holdup decreases with increasing gas, liquid

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
Water Quality Assessment and Total Dissolved Solids Prediction using Artificial Neural Network in Al-Hawizeh Marsh South of Iraq
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The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The develope

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Publication Date
Fri Dec 06 2019
Journal Name
Ssociation Of Arab Universities Journal Of Engineering Sciences
Application of Artificial Neural Network and GeographicalInformation System Models to Predict and Evaluate the Quality ofDiyala River Water, Iraq
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This research discusses application Artificial Neural Network (ANN) and Geographical InformationSystem (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameterswere used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium,Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity.These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala provincewhile it is poor to very polluted at the south of Baghdad City. The selected parameters wer

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Publication Date
Thu Aug 01 2024
Journal Name
Water Practice &amp; Technology
Artificial neural network and response surface methodology for modeling oil content in produced water from an Iraqi oil field
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ABSTRACT<p>The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value &lt;0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe</p> ... Show More
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Publication Date
Sun Jun 30 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Development of Intelligent Control Strategy for an Anesthesia System Based on Radial Basis Function Neural Network Like PID Controller
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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Engineering/
Water quality assessment and total dissolved solids prediction using artificial neural network in Al-Hawizeh marsh south of Iraq
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The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The

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