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Identification and Extraction of Digital Forensic Evidence from Multimedia Data Sources using Multi-algorithmic Fusion
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Publication Date
Mon Feb 28 2022
Journal Name
Journal Of Educational And Psychological Researches
The Identification Party of University Students
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The Political loyalties of the individual considered as the most important democracies through direct psychological identification in a particular party. The political parties regarded as the important elements and the foundations of the democratic system. They have effective interaction between the voters and the government institutions. The aim of the current research is to identify the quality of Islamic, the Civilian parties, and the most preferred for students. also, the research attempt to identify the level of identification  party that the  university students have, and the difference of identification party  according to the gender (male, female), the difference of of social class (upper, middle, poor). The sample

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Publication Date
Thu Dec 01 2022
Journal Name
Kirkuk University Journal For Agricultural Sciences
THE IMPORTANCE OF HAVING SOME BASIC COMPETENCIES AMONG WORKERS IN DIGITAL AGRICULTURAL EXTENSION FROM THE POINT OF VIEW OF SENIOR MANAGEMENT, MIDDLE MANAGEMENT AND HIGHER DEGREE HOLDERS
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The research aims to identify the availability of some basic competencies that are required to be available to workers in digital agricultural Extension from the point of view of senior management, middle management, and, employees with Post-graduate education degrees, represented by the following: Transition to digital agricultural Extension for sustainable and smart family farms, benefiting from international expertise and experiences in applying for Digital agricultural Extension, preparing and implementing Extension messages through platforms, factors affecting the effectiveness of digital agricultural Extension and its platforms, following up and evaluating the activities and programs of the digital Extension platform. The research pop

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Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
The Cluster Analysis by Using Nonparametric Cubic B-Spline Modeling for Longitudinal Data
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Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroup

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Publication Date
Sun Jan 01 2017
Journal Name
Iraqi Journal Of Science
Strong Triple Data Encryption Standard Algorithm using Nth Degree Truncated Polynomial Ring Unit
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Cryptography is the process of transforming message to avoid an unauthorized access of data. One of the main problems and an important part in cryptography with secret key algorithms is key. For higher level of secure communication key plays an important role. For increasing the level of security in any communication, both parties must have a copy of the secret key which, unfortunately, is not that easy to achieve. Triple Data Encryption Standard algorithm is weak due to its weak key generation, so that key must be reconfigured to make this algorithm more secure, effective, and strong. Encryption key enhances the Triple Data Encryption Standard algorithm securities. This paper proposed a combination of two efficient encryption algorithms to

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Publication Date
Wed Feb 06 2013
Journal Name
Eng. & Tech. Journal
A proposal to detect computer worms (malicious codes) using data mining classification algorithms
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Malicious software (malware) performs a malicious function that compromising a computer system’s security. Many methods have been developed to improve the security of the computer system resources, among them the use of firewall, encryption, and Intrusion Detection System (IDS). IDS can detect newly unrecognized attack attempt and raising an early alarm to inform the system about this suspicious intrusion attempt. This paper proposed a hybrid IDS for detection intrusion, especially malware, with considering network packet and host features. The hybrid IDS designed using Data Mining (DM) classification methods that for its ability to detect new, previously unseen intrusions accurately and automatically. It uses both anomaly and misuse dete

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Geological Journal
Evaluating Machine Learning Techniques for Carbonate Formation Permeability Prediction Using Well Log Data
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Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

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Publication Date
Mon May 15 2017
Journal Name
Journal Of Theoretical And Applied Information Technology
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

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Scopus
Publication Date
Tue Jan 01 2019
Journal Name
Plant Archives
Effect of organic fertilizer sources and application methods on qualitativeand quantitativeapricot (Prunus armeniaca L.) fruit characteristics
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Scopus
Publication Date
Mon Oct 31 2022
Journal Name
International Journal Of Intelligent Engineering And Systems
Robot Path Planning in Unknown Environments with Multi-Objectives Using an Improved COOT Optimization Algorithm
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Scopus (8)
Crossref (2)
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Publication Date
Fri Dec 29 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Clinical Evidence: The Prolonged Dust Exposure The Disorder In Serum Oxidant - Antioxidant Balance
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Dust can  be considered as  an  important factor in  environmental

pollution which has a direct eOect on human health. In this study ,we

attempted to eval uate serum oxidant -antiox idant balance in workers dust exposed continuously and also the effect of iron and silicon content in exposed dust on the mentioned balance .The study included tbrcc groups: A group  included 20  workers of  building block factories, B  group included 20 workers in general company of grains production and C group included 15 healthy' subjects which represented control group. !ron and  silicon  contents in  dust samples of  two  studied  regions were measured. Higher levels o

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