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.
Accurate estimation of permeability is essential for reliable reservoir characterization and simulation. However, core data are often limited due to their high cost and operational constraints, leading to significant uncertainty in uncored intervals. This study aims to reduce the dependence on core data for permeability estimation by integrating electrofacies derived from well logs and flow zone indicator analysis in the Mishrif Formation, Nasiriyah oil field. Electrofacies were generated using dynamic clustering based on the log data from 13 wells. This led to the identification of five electrofacies units that represent intervals with similar log responses, formed by merging 75 electrofacies, where flow zone indicators analysis id
... Show MoreAbstract This research adopted a novel mixed-method approach combining quantitative analysis and geospatial statistics with artificial intelligence (AI) techniques to evaluate U5MR in the Middle Euphrates provinces of Iraq in 2022. We investigated spatial patterns, socioeconomic determinants and health system factors related to child mortality, Using data from the Iraqi Ministry of Health in 2022. We uncovered significant disparities across the regions, where the highest death rate in Al Diwaniyah province was 33.1 per 1000 and dropped to 16.6 per 1000 live births in al-Muthanna province. An exhaustive statistical analysis brought to the fore the main factors that accounted for such a variation, that is to say population density in rural a
... Show MoreThis study aims at identifying the extent of SMS usage and understanding the role it plays in satisfying users' needs and motivations. In order to achieve this aim, an analytical descriptive method was adopted by conducting a field survey among students at Petra University.
The study resulted in many conclusions, the most important of which is that using SMS meets the students' cognitive, social and communicational needs and desires, the highest being communicating with friends at 75%, followed by exchanging songs and videos at 52%, as well as exchanging photos at 45%. In regards to their motivation for using text messaging, forgetting daily problems scored highest at 81.4% and spending free time followed at 77.4%. This proves th
... Show MoreThis study evaluated the extent to which obturation materials bypass fractured endodontic instruments positioned in the middle and apical thirds of severely curved simulated root canals using different obturation techniques. Sixty resin blocks with simulated root canals were used, each with a 50° curvature, a 6.5 mm radius of curvature, and a length of 16.5 mm, prepared to an ISO #15 diameter and taper. Canals were shaped using ProTaper Universal files (Dentsply Maillefer) attached to an X-smart Plus endo motor (Dentsply), set at 3.5 Ncm torque and 250 rpm, up to size S2 at working length. To simulate fractures, F2 and F3 files were weakened 3 mm from the tip, then twisted to break in the apical and middle sections of the canal, re
... Show MoreThyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
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Objective(s): A descriptive study aimed to determine nurses' knowledge about chest physiotherapy techniques for patients with Corona virus disease and observe the relationship between nurses' knowledge and their socio-demographic characteristics.
Methodology: The study was directed in isolation units of Al- Hussein teaching hospitals in Thi-Qar, Iraq for the period from June 1st, 2022 to November 27th, 2022. Non- probability (purposively) sample comprised 41 nurses. A questionnaire was used for data collection and it consists of two parts: the first part comprises socio demographic features, the second part includes self- administered questionnaire sheet wa
... Show MoreNatural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are
... Show MorePrecise and interpretable classification of autism-related behaviors is important for initial diagnosis, personalized intervention, and support arrangements. This study proposes an interpretable machine learning (ML) model using Light Gradient Boosting Machine (LightGBM) and Categorical Boosting (CatBoost) to classify behavioral patterns into four categories (normal, mild, moderate, and severe) associated with Autism Spectrum Disorder (ASD) based on a custom 377-instance survey dataset from Iraqi parents and teachers of children aged 6-12. The model observes 16 key features across communication and social interaction, repetitive behaviors, language, and adaptive skills, preprocessed via interquartile range (IQR) outlier removal, me
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That Iraq's dependence on the revenues of the oil product in financing its development programs and growth rates , Making the economy affected by external forces represented by fluctuations in crude oil prices in the global market, Which is directly reflected on the performance and efficiency of the Iraqi economy.
The study adopted its objectives to analyze the time series for the period (1988 - 2015) through the use of standard and statistical methods, Four standard models were estimated to reach those targets, Where the results of the stability test showed instability of most variables at their original level, But to achieve stability when taking the first differences, While the result
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