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Anomaly detection in text data that represented as a graph using dbscan algorithm
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Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the improved algorithm can detect this type of anomaly. Thus, our approach is effective in finding abnormalities.

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Publication Date
Fri Aug 28 2020
Journal Name
2 Nd Al-noor International Conference For Science And Technology
Removal of Sulfur Compounds in Iraqi Kerosene Using 1-Ethyl -3- Methyllimidazolium Acetate
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In the present study, 1-ethyl -3-methyllimidazolium acetate ionic liquid is introduced for extractive desulfurization of Iraqi kerosene (1622ppm) and compared with 1-ethyl -3- methyllimidazolium tetrafloroborate. The effect of ionic liquid/ fuel ratio (1/9, 1/4, 1/2), temperature (25, 30,40oC), stirring speed (300,450rpm) and time (10, 30, 90, 180, 360 min) were studied. Sulfur compound analysis was performed using X-Ray fluorescence. The ionic liquid with acetate anion (OAc) showed better performance than tetrafloborate (BF4). The maximum extraction efficiency was 32% achieved at 1/2 IL/Fuel and 40oC after 90min. The oxidation step using hydrogen peroxide (8ml/200ml), catalyzed by acetic acid (2ml) and followed by ionic liquid extraction h

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Publication Date
Sat Jan 26 2019
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Secure Mobile Sink Node location in Wireless Sensor Network using Dynamic Routing Protocol
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The important device in the Wireless Sensor Network (WSN) is the Sink Node (SN). That is used to store, collect and analyze data from every sensor node in the network. Thus the main role of SN in WSN makes it a big target for traffic analysis attack. Therefore, securing the SN position is a substantial issue. This study presents Security for Mobile Sink Node location using Dynamic Routing Protocol called (SMSNDRP), in order to increase complexity for adversary trying to discover mobile SN location. In addition to that, it minimizes network energy consumption. The proposed protocol which is applied on WSN framework consists of 50 nodes with static and mobile SN. The results havw shown in each round a dynamic change in the route to reach mobi

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Publication Date
Sat Jun 26 2021
Journal Name
Asian Journal Of Civil Engineering
Using AHP to prioritize the corruption risk practices in the Iraqi construction sector
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Publication Date
Wed Dec 01 2021
Journal Name
Civil And Environmental Engineering
Prediction of the Delay in the Portfolio Construction Using Naïve Bayesian Classification Algorithms
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Abstract<p>Projects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postpo</p> ... Show More
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Publication Date
Fri Oct 14 2022
Journal Name
المجلة العراقية لعلوم التربة
REVIEW: USING MACHINE VISION AND DEEP LEARINING IN AUTOMATED SORTING OF LOCAL LEMONS
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Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

Publication Date
Mon Oct 01 2018
Journal Name
2018 International Conference On Advanced Science And Engineering (icoase)
Performance of BCH and RS Codes in MIMO System Using MPFEC Diversity Technique
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Publication Date
Sat Apr 01 2023
Journal Name
Fluid Phase Equilibria
Prediction of solubility of vitamins in the mixed solvents using equation of state
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Publication Date
Thu Mar 21 2019
Journal Name
Biochemical & Cellular Archives
EVALUATION OF THE POTASSIUM AVAILABILITY IN THE SALINE SOILS USING THE THERMODYNAMIC CRITERION
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Publication Date
Sat Mar 13 2021
Journal Name
Al-nahrain Journal Of Science
Hiding Multi Short Audio Signals in Color Image by using Fast Fourier Transform
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Many purposes require communicating audio files between the users using different applications of social media. The security level of these applications is limited; at the same time many audio files are secured and must be accessed by authorized persons only, while, most present works attempt to hide single audio file in certain cover media. In this paper, a new approach of hiding three audio signals with unequal sizes in single color digital image has been proposed using the frequencies transform of this image. In the proposed approach, the Fast Fourier Transform was adopted where each audio signal is embedded in specific region with high frequencies in the frequency spectrum of the cover image to sa

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Publication Date
Fri Dec 01 2023
Journal Name
Political Sciences Journal
Using the Nudge Theory in Improving Security Policies and Crime Prevention: Integrative Review
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The "Nudge" Theory is considered one of the most recent theories, which is clear in the economic, health, and educational sectors, due to the intensity of studies on it and its applications, but it has not yet been included in crime prevention studies. The use of  Nudge theory appears to enrich the theory in the field of crime prevention, and to provide modern, effective, and implementable mechanisms.

The study deals with the "integrative review" approach, which is a distinctive form of research that generates new knowledge on a topic through reviewing, criticizing, and synthesizing representative literature on the topic in an integrated manner so that new frameworks and perspectives are created around it.

The study is bas

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