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FDPHI: Fast Deep Packet Header Inspection for Data Traffic Classification and Management

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational characteristics of traffic flow types; by considering only the position of the selected bits from the packet header. The proposal a learning approach based on deep packet inspection which integrates both feature extraction and classification phases into one system. The results show that the FDPHI works very well on the applications of feature learning. Also, it presents powerful adequate traffic classification results in terms of energy consumption (70% less power CPU utilization around 48% less), and processing time (310% for IPv4 and 595% for IPv6).

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Publication Date
Sat Apr 27 2019
Journal Name
Civil Engineering Journal
Characteristics of Traffic Accidents in Baghdad

Road traffic accidents (RTAs) are events that suddenly, inadvertently and unexpectedly occur under unforeseen circumstances that involve at least one moving vehicle and result in one or more road users being killed or injured. Unfortunately, Iraqi governorates suffer from higher rates of traffic accident casualties compared with the rates of casualties from terrorist attacks; this situation reveals a serious and growing problem. Road traffic accidents are not easy to eradicate. However, their prevalence can be reduced to the barest minimum via periodic assessments of traffic accident characteristics and the most important aspects for road authorities to consider when designing and evaluating the performance of a road to improve traf

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Publication Date
Mon Apr 26 2021
Journal Name
Journal Of Real-time Image Processing
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Publication Date
Tue Jan 30 2024
Journal Name
Iraqi Journal Of Science
NS2 – Based Experimental Analysis of Throughput for TCP and UDP Traffic During Link Failure of The Network

     Link failure refers to the failure between two connections/nodes in a perfectly working simulation scenario at a particular instance. Transport layer routing protocols form an important basis of setting up a simulation, with Transmission Control Protocol and User Datagram Protocol being the primary of them. The research makes use of Network Simulator v2.35 to conduct different simulation experiments for link failure and provide validation results. In this paper, both protocols, TCP and UDP are compared based on the throughput of packets delivered from one node to the other constrained to the condition that for a certain interval of time the link fails and the simulation time remains the same for either of the protocols. Overall,

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Investigation of Shielding for Fast Neutrons Using Polymer Composites with Pb Reinforcement

    Manufacturing high-efficiency polymeric materials to moderate fast neutrons by converting them into slow or thermal neutrons. These materials absorb thermal neutrons as well as gamma rays associated with neutrons. Materials of small mass number are used to slow down fast neutrons because neutrons have a high cross-section when they interact with these materials. Materials of high mass number absorb gamma rays. Polyurethane and epoxy were mixed in various ratios to create a blend to serve as neutrons shield, lead (Pb) was then added to the blend at weight percentages of 20%, 30%, 40%, 50%, and 70% to produce a polymer composite.

    Polymeric materials reinforced with lead in various ratios were tested to select the best

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Publication Date
Sun Oct 10 2021
Journal Name
Journal Of Physics
A novel kite cross hexagonal search algorithm for fast block motion estimation

The performance quality and searching speed of Block Matching (BM) algorithm are affected by shapes and sizes of the search patterns used in the algorithm. In this paper, Kite Cross Hexagonal Search (KCHS) is proposed. This algorithm uses different search patterns (kite, cross, and hexagonal) to search for the best Motion Vector (MV). In first step, KCHS uses cross search pattern. In second step, it uses one of kite search patterns (up, down, left, or right depending on the first step). In subsequent steps, it uses large/small Hexagonal Search (HS) patterns. This new algorithm is compared with several known fast block matching algorithms. Comparisons are based on search points and Peak Signal to Noise Ratio (PSNR). According to resul

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A Suggested Model For Using Customer's Data Management Information System/ A Case Study In Al-Rasheed Bank/General Agent Office/ Nothren Reigon

This study aim to  identify the concept of  web based information systems since its one of the important topics that is  usually omitted by our organizations, in addition to,  designing a web based information system in order to manage the customers data of Al- Rasheed bank, as a unified information system that is specialized to the banking deals of the customers with the bank, and providing a suggested model to apply the virtual private network as a tool that is to protect the transmitted data through the web based information system.

This study is considered important because it deals with one of the vital topics nowadays, namely: how to make it possible to use a distributed informat

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
A Review for Arabic Sentiment Analysis Using Deep Learning

     Sentiment Analysis is a research field that studies human opinion, sentiment, evaluation, and emotions towards entities such as products, services, organizations, events, topics, and their attributes. It is also a task of natural language processing. However, sentiment analysis research has mainly been carried out for the English language. Although the Arabic language is one of the most used languages on the Internet, only a few studies have focused on Arabic language sentiment analysis.

     In this paper, a review of the most important research works in the field of Arabic text sentiment analysis using deep learning algorithms is presented. This review illustrates the main steps used in these studies, which include

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Publication Date
Wed Dec 30 2020
Journal Name
Iraqi Journal Of Science
Hybrid vs Ensemble Classification Models for Phishing Websites

Phishing is an internet crime achieved by imitating a legitimate website of a host in order to steal confidential information. Many researchers have developed phishing classification models that are limited in real-time and computational efficiency.  This paper presents an ensemble learning model composed of DTree and NBayes, by STACKING method, with DTree as base learner. The aim is to combine the advantages of simplicity and effectiveness of DTree with the lower complexity time of NBayes. The models were integrated and appraised independently for data training and the probabilities of each class were averaged by their accuracy on the trained data through testing process. The present results of the empirical study on phishing websi

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Publication Date
Sat Feb 27 2021
Journal Name
Iraqi Journal Of Science
Complete Classification of Degree 7 for Genus 1

Assume that  is a meromorphic fuction of degree n where X is compact Riemann surface of genus g. The meromorphic function gives a branched cover of the compact Riemann surface X. Classes of such covers are in one to one correspondence with conjugacy classes of r-tuples (  of permutations in the symmetric group , in which  and s generate a transitive subgroup G of  This work is a contribution to the classification of all primitive groups of degree 7, where X is of genus one.

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Publication Date
Tue Mar 30 2021
Journal Name
Iraqi Journal Of Science
Weighted k-Nearest Neighbour for Image Spam Classification

E-mail is an efficient and reliable data exchange service. Spams are undesired e-mail messages which are randomly sent in bulk usually for commercial aims. Obfuscated image spamming is one of the new tricks to bypass text-based and Optical Character Recognition (OCR)-based spam filters. Image spam detection based on image visual features has the advantage of efficiency in terms of reducing the computational cost and improving the performance. In this paper, an image spam detection schema is presented. Suitable image processing techniques were used to capture the image features that can differentiate spam images from non-spam ones. Weighted k-nearest neighbor, which is a simple, yet powerful, machine learning algorithm, was used as a clas

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