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bsj-6086
Perceptually Important Points-Based Data Aggregation Method for Wireless Sensor Networks
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The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the sink. By utilizing Intel Berkeley Research Lab (IBRL) dataset, the efficiency of the proposed method was measured. The experimental findings illustrate the benefits of the proposed method as it reduces the overhead on the sensor node level up to 1.25% in remaining data and reduces the energy consumption up to 93% compared to prefix frequency filtering (PFF) and ATP protocols.

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Publication Date
Fri Dec 15 2023
Journal Name
Iraqi Journal Of Laser
Silver Nanoflowers as an Interfacial Liquid-State Surface Enhanced Raman Spectroscopy (SERS) Sensor for Water Pollution
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Water pollution has created a critical threat to the environment.‎‎ A lot of research has been done ‎recently to use surface-enhanced Raman spectroscopy (SERS) to detect multiple pollutants in water. This study aims to use Ag colloid nanoflowers as liquid SERS enhancer. Tri sodium phosphate (Na3PO4) was investigated as a pollutant using liquid SERS ‎based on colloidal Ag ‎nanoflowers. The chemical method was used to synthesize nanoflowers from silver ‎ions. Atomic Force Microscope (AFM), Scanning Electron Microscope (SEM), and X-ray diffractometer (XRD) were employed to characterize the silver nanoflowers. This ‎nanoflowers SERS action in detecting Na3PO4 was reported and analyzed

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Publication Date
Sun Jun 30 2013
Journal Name
Al-khwarizmi Engineering Journal
Estimated Outlet Temperatures in Shell-and-Tube Heat Exchanger Using Artificial Neural Network Approach Based on Practical Data
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The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

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Publication Date
Wed Dec 29 2021
Journal Name
Al-khwarizmi Engineering Journal
Comparison of Prediction Programs for Short Wave Circuit Link from Iraq to Test points on Both Earth Hemispheres during Solar Minimum
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This paper compare  the accurecy of HF propagation  prediction programs for  HF circuits links between Iraq and  different points world wide  during August 2018 when  solar cycle 24 (start 2009 end 2020) is at minimun activity and also find out the best communication mode  used. The prediction   programs like Voice of America Coverage Analysis Program (VOACAP) and ITU Recommendation RS 533 (REC533 )  had been used to generat HF circuit link  parameters like Maximum Usable Frequency ( MUF) and Frequency of Transsmision (FOT) .Depending  on the predicted parameters (data)  , real radio contacts had been done using a radio transceiver from Icom  model IC 7100 with 100W RF

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Publication Date
Sun Mar 07 2010
Journal Name
Baghdad Science Journal
Simultaneous influences of hematocrit in the erythrocyte medium on erythrocyte aggregation and sedimentation: a kinetic study by a laser scattering technique
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The erythrocyte aggregation is an important physiological phenomenon in the circulation of blood. It is a basic characteristic of normal blood that plays a major role in the cardiovascular system, especially in the microcirculation. This study explained the kinetics of single cells rouleaux formation one- dimensional aggregate and three- dimensional aggregate, during simultaneous, and the effect of hematocrit on the process of aggregation and sedimentation. The present study was done on forty one healthy subjects. Laser light is passed through a well mixed sample of blood and the forward scattered light intensities recorded continuously. The samples were prepared with different hematocrit, (10%, 15%, 20%, and 25%). Increasing

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Publication Date
Wed May 12 2021
Journal Name
Annals Of The Romanian Society For Cell Biology
Determining Grades and Standard Levels for the Most Important Physical and Motor Abilities of Sepak Takraw Juniors in Iraq
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(Sepak takraw) is a game that mixes football and volleyball, it is played on a court similar to a badminton court, in which players have the right to play the ball with any part of the body except the arm and hand. The object of the game is to return the ball to the opponent's court and score a point. Since it is a newly emerging game, all aspects related to it must be studied and covered in order to reach the highest levels, and it is known that each game or sporting activity has its own physical and motor capabilities, which is important to determine the level of technical performance, as the game's abilities contribute to mastering the skills. The importance of research in determining standard levels of physical and motor abilities for y

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Measurement of Government Debt Indicators and the most Its important Effects in Iraq for The period of 1990 – 2013
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Indicators of government debt is of extreme importanse in economic activity through knowledge of the economic impact of government debt, if the phenomenon is accepted or prepared to dangerous stage by stage, and there fore it can Through these indicators to measure the degree of indebtedness in relation to the economic activity of the Government on the one hand, the governments  ability to repay  the other hand.

      Due to this it inferred that the degree of indebtedness in Iraq  specificratio has exceed 60% during the period 1990 – 2002 ntejh lack of political and economic stability of the government, which led to the governments  inability to repay the ma

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Applications
Big data analysis by using one covariate at a time multiple testing (Ocmt) method: Early school dropout in iraq
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Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Statistical Sciences
Use the robust RFCH method with a polychoric correlation matrix in structural equation modeling When you are ordinal data
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Publication Date
Sat Dec 17 2022
Journal Name
Iraqi Journal Of Laser
PDF S and U shape offset studying of the refractive index sensor based on coreless fiber: Aya R. Mejble* Hanan J.Taher
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Abstract:  Two different shapes of offset optical fiber was studied based on coreless fiber for refractive index (RI)/concentration (con.) measurement, and compare them. These shapes are U and S-shapes, both shapes structures were formed by one segment of coreless fiber (CF) was joined between two single mode (SMF) lead in /lead out with the same displacement (12.268µm) at both sides, the results shows the high sensitive was achieved in a novel S-shape equal 98.768nm/RIU, to our knowledge, no one has ever mentioned or experienced it, it’s the best shape rather than the U-shape which equal 85.628nm/RIU. In this research, it was proved that the offset form has a significant effect on the sensitivity of the sensor. Addi

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Publication Date
Mon Apr 11 2011
Journal Name
Icgst
Employing Neural Network and Naive Bayesian Classifier in Mining Data for Car Evaluation
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In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.