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A comparison study on node clustering techniques used in target tracking WSNs for efficient data aggregation
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Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregation process. In this paper, we have highlighted the gains of the existing schemes for node clustering based data aggregation along with a detailed discussion on their advantages and issues that may degrade the performance. Also, the boundary issues in each type of clustering technique have been analyzed. Simulation results reveal that the efficacy and validity of these clustering-based data aggregation algorithms are limited to specific sensing situations only, while failing to exhibit adaptive behavior in various other environmental conditions.

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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Some NONPARAMETRIC ESTIMATORS FOR RIGHT CENSORED SURVIVAL DATA
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The using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible parametric models and these models were nonparametric, many researchers, are interested in the study of the function of permanence and its estimation methods, one of these non-parametric methods.

For work of purpose statistical inference parameters around the statistical distribution for life times which censored data , on the experimental section of this thesis has been the comparison of non-parametric methods of permanence function, the existence

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
A Comparative Study of Some Methods of Estimating Robust Variance Covariance Matrix of the Parameters Estimated by (OLS) in Cross-Sectional Data
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Abstract

The Classical Normal Linear Regression Model Based on Several hypotheses, one of them is Heteroscedasticity as it is known that the wing of least squares method (OLS), under the existence of these two problems make the estimators, lose their desirable properties, in addition the statistical inference becomes unaccepted table. According that we put tow alternative,  the first one is  (Generalized Least Square) Which is denoted by (GLS), and the second alternative is to (Robust covariance matrix estimation) the estimated parameters method(OLS), and that the way (GLS) method neat and certified, if the capabilities (Efficient) and the statistical inference Thread on the basis of an acceptable

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Publication Date
Tue Aug 03 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The impact of tax techniques on the quality of services provided to income taxpayers: An exploratory study in a sample of the branches of the General Tax Authority / Baghdad Governorate
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The research aims to demonstrate the impact of tax techniques on the quality of services provided to income taxpayers by studying the correlational and influencing relationships between the exploited variable (tax techniques) and the dependent variable (the quality of services provided to income taxpayers), and in line with the research objectives, the main hypothesis of the research was formulated (there is a relationship Significance between tax techniques and the quality of services provided to income taxpayers) a number of sub-hypotheses emerged from this hypothesis that were stated in the research methodology, and a number of conclusions were reached, the most important of which were (through the use of the correlation coeff

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
The Effect of Assessment Techniques on EFL Learners’ achievement in TOEFL Test
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While many educators are highly focused on state test, it is important to consider that
over the course of a year, instructors can build in many opportunities to assess how learners
are learning. Therefore, assessment techniques are considered a good method to get benefit
for both instructors and learners in the process of teaching and learning. The sample consists
of 27 learners who participated in TOEFL training course in the Development and Continuous
Education Centre. Validity and reliability were verified.
To fulfill the aims and verify the hypothesis which reads as follows” It is hypothesized
that the TOEFL learners' scores will not be increased after TOEFL course training.” T-test
for two dependent samp

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Publication Date
Mon Mar 23 2020
Journal Name
Journal Of Engineering
Improving Photovoltaic Panel (PV) Efficiency via Two Axis Sun Tracking System
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In this paper two axis sun tracking method is used to absorb maximum power from the sun's rays on the solar panel via calculating the sun’s altitude and azimuth angles, which describe the solar position on the Iraqi capital Baghdad for the hours 6:00, 7:00, 8:00, 9:00, 12:00, 15:00 and 17:00 per day. The angles were calculated in an average approach within one month, so certain values were determined for each month. The daily energy achieved was calculated for the solar tracking method compared with the fixed tracking method. Designed, modeled and simulated a control circuit consisting of reference position truth table, PI Controller and two servomotors that tracked the sun position to adjust the PV panel perpendicular

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Publication Date
Mon Feb 27 2023
Journal Name
Applied Sciences
Comparison of ML/DL Approaches for Detecting DDoS Attacks in SDN
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Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
A study for Bacterial Infection in Acute Diarrhea Patients
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500 samples of diarrhea stool were collected from different ages(less than 1year –upto30years) and for both genders from some patients in (Alwiya hospital for children, Al-kendi, central health public laboratory and some gavernarated labs) period(1/11/2009—1/10/2010). Kinds of bacteria and parasites agents were isolated and identified from patients with diarrhea. Nine species of gram negative bacteria from enterobacteriaceae were isolated, E. coli isolated are the higher ratio 4.8% of all, then Salmonella typhi4.6% while the lowest ratios is Citrobacterfreundii 0.4%, while the other identified species were be among the previous rotios. also Plesomonasshigelloides was isolated which concedride one of the bacterial local studies.many met

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Publication Date
Thu Sep 25 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Evaluation of en-masse retraction using microimplant versus conventional techniques: An in vitro study
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Background: The study aimed to investigate the effect of different techniques of en masse retraction on the vertical and sagittal position, axial inclination, rate of space closure, and type of movement of maxillary central incisor. Materials and methods: A typodont simulation system was used (CL II division 2 malocclusion). Three groups were used group 1(N=10, T-loop), group 2(N=10, Time-Saving loop), and group 3(N=10, Microimplant). Photographs were taken before and after retraction and measurements were made using Autodesk AutoCAD© software 2010. Kruskal-Wallis one-way analyses of variance and Mann-Whitney U test (p?0.05) were used. Results: The rate of space closure showed no significant difference among the three groups (p?0.05), whi

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Publication Date
Wed Aug 31 2022
Journal Name
Al-kindy College Medical Journal
Towards a Better Dacryocystorhinostomy, Evaluation of Multimodal Surgical Techniques in Nasolacrimal Duct Obstruction
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Background: This study aimed to evaluate the outcome of long-term results of dacryocystorhinostomy (DCR) techniques in specialized eye care center in Iraq.

Subjects and Method: This is a prospective study of 650 patients from July 2014 to July 2019 with nasolacrimal duct obstruction in Ibn Al Haitham Eye Teaching Hospital. A preoperative questionnaire was done, then one month, three months, six months and one year postoperatively. The success of surgery defined as follow; Absence of epiphora completely, Resolve of dacryocele or mucocele or any new attack of daryocystitis, Appearance of fluorescein dye from nose in fluorescein disappearance test, Successful irriga

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Publication Date
Wed Mar 08 2023
Journal Name
Sensors
A Critical Review of Remote Sensing Approaches and Deep Learning Techniques in Archaeology
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To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip

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