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bsj-2989
A Software Defined Network of Video Surveillance System Based on Enhanced Routing Algorithms
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Software Defined Network (SDN) is a new technology that separate the ‎control plane from the data plane. SDN provides a choice in automation and ‎programmability faster than traditional network. It supports the ‎Quality of Service (QoS) for video surveillance application. One of most ‎significant issues in video surveillance is how to find the best path for routing the packets ‎between the source (IP cameras) and destination (monitoring center). The ‎video surveillance system requires fast transmission and reliable delivery ‎and high QoS. To improve the QoS and to achieve the optimal path, the ‎SDN architecture is used in this paper. In addition, different routing algorithms are ‎used with different steps. First, we evaluate the video transmission over the SDN with ‎Bellman Ford algorithm. Then, because the limitation of Bellman ford ‎algorithm, the Dijkstra algorithm is used to change the path when a congestion occurs. Furthermore, the Dijkstra algorithm is used with two ‎controllers to reduce the time consumed by the SDN controller. ‎ POX and Pyretic SDN controllers are used such that POX controller is ‎responsible for the network monitoring, while Pyretic controller is responsible for the ‎routing algorithm and path selection. Finally, a modified Dijkstra algorithm is further proposed and evaluated with two ‎controllers to enhance the performance.  The results show that the modified Dijkstra algorithm outperformed the other approaches in the aspect of QoS parameters.

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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
Sat Apr 19 2025
Journal Name
Plos One
Early Detection of Autism Spectrum Disorder in Children Using Different Machine Learning Algorithms
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Abstract<p>Autism spectrum disorder(ASD) is a neurological condition marked by impaired communication abilities, social detachment, and repetitive behaviors in individuals. Global health organization facing difficulties in establishing an effective ASD diagnostic system that facilitates precise analysis and early autism prediction. It is a scientific issue that necessitates resolution. This research presents an approach for the early prediction of children with ASD utilizing significant variables through machine learning (ML) methods. Three stages comprise the suggested technique. First, a 1250-case ASD dataset was identified and preprocessed. Five extremely effective traits with high Pearson c</p> ... Show More
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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of Engineering
Efficient Intrusion Detection Through the Fusion of AI Algorithms and Feature Selection Methods
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With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Results on a Pre-T_2 Space and Pre-Stability
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This paper contains an equivalent statements of a pre-  space, where  are considered subsets of with the product topology. An equivalence relation between the preclosed set  and a pre-  space, and a relation between a pre-  space and the preclosed set  with some conditions on a function  are found. In addition, we have proved that the graph  of  is preclosed in if  is a pre-  space, where the equivalence relation  on  is open.

     On the other hand, we introduce the definition of a pre-stable ( pre-stable) set by depending on the concept of a pre-neighborhood, where we get that every stable set is pre-stable. Moreover, we obtain that

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Publication Date
Wed Jan 01 2020
Journal Name
Advanced Composites Letters
Enhanced thermal and electrical properties of epoxy/carbon fiber–silicon carbide composites
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The silicon carbide/carbon fiber (SiC/CF) hybrid fillers were introduced to improve the electrical and thermal conductivities of the epoxy resin composites. Results of Fourier transform infrared spectroscopy revealed that the peaks at 3532 and 2850 cm−1 relate to carboxylic acid O–H stretching and aldehyde C–H stretching appearing deeper with an increased volume fraction of SiC. Scanning electron microscopic image shows a better interface bonding between the fiber and the matrix when the volume fraction of SiC particles are increased. As frequency increases from 102 Hz to 106 Hz, dielectric constants decrease slightly. Dissipation factor (tan δ) values keep low a

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Publication Date
Wed Jan 01 2025
Journal Name
Opennano
Development and characterization of bilastine nanosuspension for enhanced dissolution in orodispersible films
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Abstract Bilastine, a second-generation antihistamine, is commonly prescribed for managing allergic rhinoconjunctivitis and urticaria due to its prolonged action. However, its therapeutic potential is constrained by poor water solubility and low oral bioavailability. This study aimed to enhance bilastine dissolution and patient compliance by formulating a nanosuspension-based orodispersible film (ODF). An anti-solvent precipitation method was employed to produce nanosuspension using different hydrophilic stabilizers (Soluplus®, Poloxamer 188, and PEG 6000). The influence of formulation parameters, such as the stabilizer ratio, the anti-solvent ratio, stirring speed, and the stabilizer type, on particle size and polydispersity index (PDI)

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Publication Date
Sun Jun 30 2024
Journal Name
Science And Technology Indonesia
Evaluating the Biocompatibility of Maxillofacial Silicone Enhanced by Hexagonal Boron Nitride Particles
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This study aims to evaluate the biocompatibility of a novel filler material intended to improve the longevity of polymer systems used in prosthetics in respect of cytotoxicity and skin irritation. RTV50F silicone elastomer incorporated with various percentages of hexagonal boron nitride (H-BN) (0.1, 0.3, 0.5, 0.7, and 1 wt%) have been tested. Silicone without H-BN was utilized as the control for comparison. The in vitro cytotoxicity test includes specimens (n=18) with 10 mm in diameter and 2 mm in thickness applied directly to the normal human fibroblast cell line (NHF) and incubated for 72 hours, then 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay was used to determine the cell viability. The skin irritati

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Publication Date
Tue Dec 29 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Electronic Payment System and its impact on the efficiency of the performance of banking: An applied research on a sample of banking sector in Iraq
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The electronic payment systems are considered the most important infrastructure for the work of banks, particularly after a steady and remarkable development in information and communication technology, Which created the reality of the work of the infrastructure for these systems and these systems also become one of the most important components of infrastructure for the work of banks, cause it is one of the most important channels through which the transfer of cash, financial instruments between financial institutions in general and banking in particular.

     In order to achieve the objectives of the research, the most important to identify the concept of electronic payment systems, and its divisions, and th

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Publication Date
Wed Jul 22 2026
Journal Name
Pharmaceutics
Aqueous Artemisia herba-alba Asso Preparation as a Botanical Adjunct to Dapagliflozin: Enhanced Glycemic Control in Streptozotocin-Induced Diabetic Rats
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Background/Objectives: optimization of the therapeutic efficacy of antidiabetic agents is still a great challenge in the management of type 2 diabetes mellitus (T2DM), and attention is becoming more and more focused on the use of adjunctive agents that help target the drug action beyond the classic glycemic target. This study examined the effect of co-administration of an Artemisia herba-alba Asso (Asteraceae) aqueous extract on the glucose-lowering effect of dapagliflozin, a sodium–glucose cotransporter-2 (SGLT2) inhibitor. Methods: qualitative phytochemical screening and total phenolic and total flavonoid content were used to characterize the aqueous preparation. Male Wistar albino rats were divided into eight groups (10 rats ea

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Publication Date
Fri Jun 29 2018
Journal Name
Journal Of The College Of Education For Women
Audio Classification Based on Content Features
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Audio classification is the process to classify different audio types according to contents. It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification. This workintroduces several sets of features according to the type, two types of audio (datasets) were studied. Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to

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