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Enhancing Cloud Security Implementing AI-Based Intrusion Detection Systems
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The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion detection systems in the cloud may provide challenges. The pre-established IDS design may overburden a cloud segment due to the additional detection overhead. Within the framework of an adaptively designed networked system. We demonstrate how to fully use available resources without placing undue load on any one cloud server using an intrusion detection system (IDS) based on neural networks. To even more successfully detect new threats, the suggested IDS make use of neural network machine learning (ML).

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Publication Date
Sat Jul 06 2024
Journal Name
Multimedia Tools And Applications
Text classification based on optimization feature selection methods: a review and future directions
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A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification
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This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

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Publication Date
Sun Dec 25 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Detection of Epicatechin in Camellia sinensis Leaves by Thin Layer Chromatography and High Performance Liquid Chromatography Techniques
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    The current study performed in order to detect and quantify epicatechin in two tea samples of Camellia sinensis (black and green tea) by thin layer chromatography (TLC) and high performance liquid chromatography (HPLC). Extraction of epicatechin from black and green tea was done by using two different methods: maceration (cold extraction method) and decoction (hot extraction method) involved using three different solvents which are  absolute ethanol, 50% aqueous ethanol and water  for both extraction methods using room temperature and direct heat respectively. Crude extracts of two tea samples that obtained from two methods were fractionated by using two solvents with different polarity (chloroform and

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Publication Date
Sun Mar 01 2015
Journal Name
Baghdad Science Journal
Determination of Serum CA125 and evaluate its efficiency as screening tool For Early Detection of Ovarian Tumors
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Epithelial ovarian cancer is the leading cause of cancer deaths in women. To date, an effective screening tool for ovarian cancer has not been identified Several clinical and biological factors including serum cancer antigen 125 (CA- 125) have been assessed for prognostic and predictive relevance CA-125 is an epithelial marker derived from coelomic epithelium. It is elevated in 90% of advanced ovarian cancers and in 50% of early ovarian cancers while 20% of ovarian cancers have low or no expression of CA- 125 CA-125 concentrations were measured by Mini Vidas test (VIDAS CA125 II / BIOMERIEUX / France). The median CA-125 levels were significantly higher in the sera of ovarian cancer patients than in those with benign tumors an

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Publication Date
Sat Feb 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Concept And Importance Of Detection Failureś Possibilities Of Corporation Proposed Model For Application In The Iraqi Environment
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Research aims to shed light on the concept of corporate failures , display and analysis the most distinctive models used to predicting corporate failure; with suggesting  a model to reveal the probabilities of corporate failures which including internal and external financial and non-financial indicators, A tested is made for the research objectivity and its indicators weight and by a  number of academics professionals experts, in addition to  financial analysts  and have concluded a set of conclusions ,  the most distinctive of them that failure is not considered a sudden phenomena for the company and its stakeholders , it is an Event passes through numerous stages; each have their symptoms that lead eve

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Publication Date
Fri Mar 15 2019
Journal Name
Journal Of Baghdad College Of Dentistry
Detection of early occlusal caries of the first permanent molar using different techniques (An in vivo study)
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Background: Molars and premolars are considered as the most vulnerable teeth of caries attack, which is related to the morphology of their occlusal surfaces along with the difficulty of plaque removal. different methods were used for early caries detection that provide sensitive, accurate preoperative diagnosis of caries depths to establish adequate preventive measures and avoid premature tooth treatment by restoration. The aim of the present study was to evaluate the clinical sensitivity and specificity rates of DIAGNOdent and visual inspection as opposed to the ICDAS for the detection of initial occlusal caries in noncavitated first permanent molars. Materials and Methods: This study examined 139 occlusal surface of the first permanent

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Publication Date
Mon Jan 01 2024
Journal Name
Open Veterinary Journal
Detection of biofilm formation and antibiotics resistance of Staphylococcus spp. isolated from humans’ and birds’ oral cavities
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Background: Staphylococcus spp. are widely distributed in nature and can cause nosocomial, skin infections, and foodborne illness, and it may lead to severe financial losses in birds by causing systemic infection in numerous organs. Aim: This study was conducted to determine the prevalence of Staphylococcus spp. in humans and birds in Baghdad city. Methods: Seventy-six oral cavity swabs were collected, including 41 from birds and 35 from breeders. All samples were examined by bacteriological methods and identified by using the VITEK technique, the samples were then further studied to test the ability of biofilm formation, and MDR factors and MAR index were tested with the use of seven antibiotics. Results: Among the 76 oral swa

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Publication Date
Mon Feb 01 2016
Journal Name
Swarm And Evolutionary Computation
Improving the performance of evolutionary multi-objective co-clustering models for community detection in complex social networks
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Publication Date
Wed Feb 15 2023
Journal Name
Full Text Book Of Minar Congress 7
EVALUATING THE CHANGE DETECTION OF(NDVI) FOR BABYLON CITY USING REMOTE SENSING AND GIS TECHNIQUES (2015-2020)
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The normalized difference vegetation index (NDVI) is an effective graphical indicator that can be used to analyze remote sensing measurements using a space platform, in order to investigate the trend of the live green vegetation in the observed target. In this research, the change detection of vegetation in Babylon city was done by tracing the NDVI factor for temporal Landsat satellite images. These images were used and utilized in two different terms: in March 19th in 2015 and March 5th in 2020. The Arc-GIS program ver. 10.7 was adopted to analyze the collected data. The final results indicate a spatial variation in the (NDVI), where it increases from (1666.91 𝑘𝑚2) in 2015 to (1697.01 𝑘𝑚2)) in 2020 between the t

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Publication Date
Tue Apr 01 2025
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Serological and Molecular Detection of Prevalence of Human Parvovirus (B19) in Beta Thalassemia Major Patients in Baghdad
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Background: Beta thalassemia major (β-TM) is an inheritable condition with many complications, especially in children. The blood-borne viral infection was proposed as a risk factor due to the recurrent blood transfusion regimen (hemotherapy) as human parvovirus B19 (B19V). Objective: This study investigated the B19V seroprevalence, DNA presence, B19V viral load, and B19V genotypes in β-TM patients and blood donors. Methods: This is a cross-sectional study incorporating 180 subjects, segregated into three distinct groups each of 60 patients, namely control, β-TM, and β-TM infected with Hepatitis C Virus (HCV).  For the B19V prevalence in the studied group, the ELISA technique and real-time PCR were used. The genotyping was follo

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