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ijs-2093
Dynamic Fault Tolerance Aware Scheduling for Healthcare System on Fog Computing
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 Internet of Things (IoT) contributes to improve the quality of life as it supports many applications, especially healthcare systems. Data generated from IoT devices is sent to the Cloud Computing (CC) for processing and storage, despite the latency caused by the distance. Because of the revolution in IoT devices, data sent to CC has been increasing. As a result, another problem added to the latency was increasing congestion on the cloud network. Fog Computing (FC) was used to solve these problems because of its proximity to IoT devices, while filtering data is sent to the CC. FC is a middle layer located between IoT devices and the CC layer. Due to the massive data generated by IoT devices on FC, Dynamic Weighted Round Robin (DWRR) algorithm was used, which represents a load balancing (LB) algorithm that is applied to schedule and distributes data among fog servers by reading CPU and memory values of these servers in order to improve system performance. The results proved that DWRR algorithm provides high throughput which reaches 3290 req/sec at 919 users. A lot of research is concerned with distribution of workload by using LB techniques without paying much attention to Fault Tolerance (FT), which implies that the system continues to operate even when fault occurs. Therefore, we proposed a replication FT technique called primary-backup replication based on dynamic checkpoint interval on FC. Checkpoint was used to replicate new data from a primary server to a backup server dynamically by monitoring CPU values of primary fog server, so that checkpoint occurs only when the CPU value is larger than 0.2 to reduce overhead. The results showed that the execution time of data filtering process on the FC with a dynamic checkpoint is less than the time spent in the case of the static checkpoint that is independent on the CPU status.

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Publication Date
Thu Dec 31 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Application of data content analysis (DEA) technology to evaluate performance efficiency: applied research in the General Tax Authority
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The aim of the research is to use the data content analysis technique (DEA) in evaluating the efficiency of the performance of the eight branches of the General Tax Authority, located in Baghdad, represented by Karrada, Karkh parties, Karkh Center, Dora, Bayaa, Kadhimiya, New Baghdad, Rusafa according to the determination of the inputs represented by the number of non-accountable taxpayers and according to the categories professions and commercial business, deduction, transfer of property ownership, real estate and tenders, In addition to determining the outputs according to the checklist that contains nine dimensions to assess the efficiency of the performance of the investigated branches by investing their available resources T

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Publication Date
Sat Apr 30 2022
Journal Name
Iraqi Journal Of Science
2D Seismic Data Analysis of Judaida Structure, Northern Iraq
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This research aims to study the structural analysis of the 2D reflection seismic data for the Judaida subsurface structure located in Kirkuk province, northern Iraq. It is located 60 Km southwest of Kirkuk oil field, and 35 Km southwest of Jambur oil field, the Daquq River passes through the study area. The reflectors in the seismic section were picked and identified by using the synthetic seismograms generated from the logs data of the Jd-1 well. Three main seismic reflectors, Fatha, Jeribe, and the Euphrates were chosen. These mentioned sedimentary formations were deposited during the Middle Miocene, Lower Miocene, and Early-Mid Miocene respectively. Time and depth maps were drawn for these three reflectors by processing average data f

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Science
Design and Construction of Ultraviolet and Incoming Solar Irradiance Sensing Device
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     In-situ measurements of ultraviolet (UV) and solar irradiance is very sparse in Nigeria because of cost; it is  estimated using meteorological parameters. In this work, a low-cost UV and pyranometer device, using locally sourced materials, was developed. The instrument consists of a UV sensor (ML8511), a photodiode (BPW34) housed in a carefully sealed vacuumed glass bulb, the UV and solar irradiance sensor amplifiers, a 16-bit analog-to-digital converter (ADS1115), Arduino mega 2560, liquid crystal display (LCD) and microSD card for data logging. The designed amplifier has an offset voltage of 0.8676 mV. The sensitivity of the irradiance device is 86.819 Wm-2/mV with a correcting factor of 27.77 Wm-2 and a

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Ten Years of OpenStreetMap Project: Have We Addressed Data Quality Appropriately? – Review Paper
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It has increasingly been recognised that the future developments in geospatial data handling will centre on geospatial data on the web: Volunteered Geographic Information (VGI). The evaluation of VGI data quality, including positional and shape similarity, has become a recurrent subject in the scientific literature in the last ten years. The OpenStreetMap (OSM) project is the most popular one of the leading platforms of VGI datasets. It is an online geospatial database to produce and supply free editable geospatial datasets for a worldwide. The goal of this paper is to present a comprehensive overview of the quality assurance of OSM data. In addition, the credibility of open source geospatial data is discussed, highlight

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Publication Date
Tue Jun 01 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Improved Certificate-Based Encryption Scheme in the Big Data: Combining AES and (ECDSA – ECDH)
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      Big data usually running in large-scale and centralized key management systems. However, the centralized key management systems are increasing the problems such as single point of failure, exchanging a secret key over insecure channels, third-party query, and key escrow problem. To avoid these problems, we propose an improved certificate-based encryption scheme that ensures data confidentiality by combining symmetric and asymmetric cryptography schemes. The combination can be implemented by using the Advanced Encryption Standard (AES) and Elliptic Curve Diffie-Hellman (ECDH). The proposed scheme is an enhanced version of the Certificate-Based Encryption (CBE) scheme and preserves all its advantages. However

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Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
An Assessment of the Temperature Change Scenarios Using RS & GIS Techniques-A Case study of Sindh
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The rising temperatures are the most significant aspect in the period of climate variability. In this study PRECIS model data and observed data are used for assessing the temperature change scenarios of Sindh province during the first half of the present century. Observed data from various meteorological stations of Sindh are the primary source for temperature change detection. The current scenario (1961–1990) and future one (2010-2050) are acted by the PRECIS Regional Climate Model at a spatial resolution of 25 * 25 km. Regional Climate Model (RCM) can yield reasonably suitable projections to be used in the climate - scenario. The main objective of the study is to prepare maps. The simulated temperature as obtained from climate model-

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Publication Date
Sat Jul 31 2021
Journal Name
Iraqi Journal Of Science
A review of Medical Diagnostics Via Data Mining Techniques
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Data mining is one of the most popular analysis methods in medical research. It involves finding patterns and correlations in previously unknown datasets. Data mining encompasses various areas of biomedical research, including data collection, clinical decision support, illness or safety monitoring, public health, and inquiry research. Health analytics frequently uses computational methods for data mining, such as clustering, classification, and regression. Studies of large numbers of diverse heterogeneous documents, including biological and electronic information, provided extensive material to medical and health studies.

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Publication Date
Wed Jul 31 2019
Journal Name
Journal Of Engineering
Evaluation of the Accuracy of Digital Elevation Model Produced from Different Open Source Data
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This study aims to estimate the accuracy of digital elevation models (DEM) which are created with exploitation of open source Google Earth data and comparing with the widely available DEM datasets, Shuttle Radar Topography Mission (SRTM), version 3, and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), version 2. The GPS technique is used in this study to produce digital elevation raster with a high level of accuracy, as reference raster, compared to the DEM datasets. Baghdad University, Al Jadriya campus, is selected as a study area. Besides, 151 reference points were created within the study area to evaluate the results based on the values of RMS.Furthermore, th

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid 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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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Measuring Positive and Negative Association of Apriori Algorithm with Cosine Correlation Analysis
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This work aims to see the positive association rules and negative association rules in the Apriori algorithm by using cosine correlation analysis. The default and the modified Association Rule Mining algorithm are implemented against the mushroom database to find out the difference of the results. The experimental results showed that the modified Association Rule Mining algorithm could generate negative association rules. The addition of cosine correlation analysis returns a smaller amount of association rules than the amounts of the default Association Rule Mining algorithm. From the top ten association rules, it can be seen that there are different rules between the default and the modified Apriori algorithm. The difference of the obta

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