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FDPHI: Fast Deep Packet Header Inspection for Data Traffic Classification and Management
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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
Thu Nov 30 2023
Journal Name
Iraqi Geological Journal
Inverting Gravity Data to Density and Velocity Models for Selected Area in Southwestern Iraq
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The gravity method is a measurement of relatively noticeable variations in the Earth’s gravitational field caused by lateral variations in rock's density. In the current research, a new technique is applied on the previous Bouguer map of gravity surveys (conducted from 1940–1950) of the last century, by selecting certain areas in the South-Western desert of Iraqi-territory within the provinces' administrative boundary of Najaf and Anbar. Depending on the theory of gravity inversion where gravity values could be reflected to density-contrast variations with the depths; so, gravity data inversion can be utilized to calculate the models of density and velocity from four selected depth-slices 9.63 Km, 1.1 Km, 0.682 Km and 0.407 Km.

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Publication Date
Fri Aug 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Efficiency Measurement Model for Postgraduate Programs and Undergraduate Programs by Using Data Envelopment Analysis
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Measuring the efficiency of postgraduate and undergraduate programs is one of the essential elements in educational process. In this study, colleges of Baghdad University and data for the academic year (2011-2012) have been chosen to measure the relative efficiencies of postgraduate and undergraduate programs in terms of their inputs and outputs. A relevant method to conduct the analysis of this data is Data Envelopment Analysis (DEA). The effect of academic staff to the number of enrolled and alumni students to the postgraduate and undergraduate programs are the main focus of the study.

 

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
A Novel System for Confidential Medical Data Storage Using Chaskey Encryption and Blockchain Technology
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Secure storage of confidential medical information is critical to healthcare organizations seeking to protect patient's privacy and comply with regulatory requirements. This paper presents a new scheme for secure storage of medical data using Chaskey cryptography and blockchain technology. The system uses Chaskey encryption to ensure integrity and confidentiality of medical data, blockchain technology to provide a scalable and decentralized storage solution. The system also uses Bflow segmentation and vertical segmentation technologies to enhance scalability and manage the stored data. In addition, the system uses smart contracts to enforce access control policies and other security measures. The description of the system detailing and p

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Publication Date
Sat Jan 20 2024
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fast New Method for Estimation of Captopril in Pure and Pharmaceutical Preparation by Reaction with Ammonium Ce (IV) Sulfate in Acid Medium
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The determination of captopril (CAP) using a new continuous flow injection analysis (CFIA) method was given in this work CAP in its pure state and some of its pharmaceutical preparations. The technique can be described as simple, fast, sensitive, easy to operate, and low-cost. The CAP reacted with ammonium ceric(IV) sulfate (ACS)2(NH4 )2SO4Ce(SO4)2. 3 H2O in an acidic medium and the reaction led to the formation of a white, slightly yellowish precipitate. The formed precipitate was studied using Ayah 6S×1-ST-2D Solar cell-CFI Analyzer, a through the reflection of accident light on the surfaces of the precipitate particles at (0-1800), expressed as the response

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Publication Date
Tue Jan 01 2008
Journal Name
Lecture Notes In Computer Science
IRPS – An Efficient Test Data Generation Strategy for Pairwise Testing
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Publication Date
Thu Jul 10 2025
Journal Name
University Of Kirkuk Journal For Administrative And Economic Science
Anova For Fuzzy Data With Practical in The Medical Field
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This research study Blur groups (Fuzzy Sets) which is the perception of the most modern in the application in various practical and theoretical areas and in various fields of life, was addressed to the fuzzy random variable whose value is not real, but the numbers Millbh because it expresses the mysterious phenomena or uncertain with measurements are not assertive. Fuzzy data were presented for binocular test and analysis of variance method of random Fuzzy variables , where this method depends on a number of assumptions, which is a problem that prevents the use of this method in the case of non-realized.

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
User (K-Means) for clustering in Data Mining with application
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  The great scientific progress has led to widespread Information as information accumulates in large databases is important in trying to revise and compile this vast amount of data and, where its purpose to extract hidden information or classified data under their relations with each other in order to take advantage of them for technical purposes.

      And work with data mining (DM) is appropriate in this area because of the importance of research in the (K-Means) algorithm for clustering data in fact applied with effect can be observed in variables by changing the sample size (n) and the number of clusters (K)

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Publication Date
Wed Oct 01 2008
Journal Name
2008 First International Conference On Distributed Framework And Applications
A strategy for Grid based t-way test data generation
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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Improved Firefly Algorithm with Variable Neighborhood Search for Data Clustering
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Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the

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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Geological Journal
Wellbore Instability Analysis to Determine the Safe Mud Weight Window for Deep Well, Halfaya Oilfield
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Wellbore instability is one of the most common issues encountered during drilling operations. This problem becomes enormous when drilling deep wells that are passing through many different formations. The purpose of this study is to evaluate wellbore failure criteria by constructing a one-dimensional mechanical earth model (1D-MEM) that will help to predict a safe mud-weight window for deep wells. An integrated log measurement has been used to compute MEM components for nine formations along the studied well. Repeated formation pressure and laboratory core testing are used to validate the calculated results. The prediction of mud weight along the nine studied formations shows that for Ahmadi, Nahr Umr, Shuaiba, and Zubair formations

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