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Comparison of ML/DL Approaches for Detecting DDoS Attacks in SDN
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Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an SVM-based DDoS detection model shows superior performance. This comparative analysis offers a valuable insight into the development of efficient and accurate techniques for detecting DDoS attacks in SDN environments with less complexity and time.

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Publication Date
Wed Mar 05 2025
Journal Name
Full Text Book Of Rimarcongress04
Natural and Artificial Radioactivity Estimation for Different types of Pasta Samples in Baghdad City
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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Engineering
Evaluation of ANFIS and Regression Techniques in Estimating Soil Compression Index for Cohesive soils
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Generally, direct measurement of soil compression index (Cc) is expensive and time-consuming. To save time and effort, indirect methods to obtain Cc may be an inexpensive option. Usually, the indirect methods are based on a correlation between some easier measuring descriptive variables such as liquid limit, soil density, and natural water content. This study used the ANFIS and regression methods to obtain Cc indirectly. To achieve the aim of this investigation, 177 undisturbed samples were collected from the cohesive soil in Sulaymaniyah Governorate in Iraq. Results of this study indicated that ANFIS models over-performed the Regression method in estimating Cc with R2 of 0.66 and 0.48 for both ANFIS and Regre

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Publication Date
Thu Apr 01 2021
Journal Name
Applied Soft Computing
Evolutionary multi-objective set cover problem for task allocation in the Internet of Things
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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences( P-issn 1683 - 3597 E-issn 2521 - 3512)
Preparation, In-vitro, and Ex-vivo Evaluation of Ondansetron Loaded Invasomes for Transdermal Delivery
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Invasomes are newly developed types of nanovesicles. A vesicular drug delivery system is considered one of the approaches for transdermal delivery to enhance permeation and improve drug bioavailability. Ondansetron is a serotonin receptor antagonist used for treating vomiting associated with different clinical cases. The study aimed to prepare invasomal dispersions for improving permeation of ondansetron across the skin with a controlled release pattern. Twenty-seven formulas of ondansetron-loaded invasomes were prepared by a modified mechanical dispersion method. These formulas were optimized by studying the effect of variables on entrapment efficiency. Vesicle size, polydispersity, zeta potential, in-vitro release and ex-vivo perm

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Publication Date
Thu Feb 01 2024
Journal Name
Journal Of Engineering
The Economic Evaluation of Various Production Scenarios for Zubair Reservoir in the Kifl Field
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This work evaluates the economic feasibility of various production scenarios for the Zubair reservoir in the Kifl oil field using cash flow and net present value (NPV) calculations. The Kifl field is an exploratory field that has not yet been developed or assessed economically. The first well was drilled in 1960, and three other wells were later drilled to assess the oil accumulation, so in this research, Different production scenarios were evaluated economically. These scenarios were proposed based on the reservoir model of the Zubair formation in the field. The research methodology used QUE$TOR software to estimate capital expenditures (CapEx) and operating expenditures (OpEx) based on field-level data, production prof

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Publication Date
Tue Sep 23 2025
Journal Name
Sensing And Imaging
A Review of Detection, Monitoring, and Analysis Techniques in Terahertz Sensing for Sustainable Agriculture
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Terahertz (THz) technology, which uses radiation lying between microwave and infrared in the electromagnetic spectrum, could revolutionize digital agriculture through terahertz’s ability to assess agricultural materials accurately and non-destructively. The review discusses notable developments in THz applications to digital agriculture: real-time crop monitoring, nutrient and disease detection, soil moisture and contaminant analysis, and supply chain traceability. The developments have emerged from studies in time-domain spectroscopy, imaging, machine learning (ML), and blockchain integration. Despite the promising advances in THz agricultural applications, limitations remain, such as limited penetration depth, high system costs, and ope

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Publication Date
Thu Oct 01 2009
Journal Name
Journal Of The College Of Languages (jcl)
Computer-assisted Programme for the Teaching of the English Syllable in RP Allophonic Pronunciation
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Native speakers of English from different parts of the world have different accents,but the differences of accents are mainly the result of differences in the sound of  vowels  and consonants . The actual use of all these sounds in combination leads the speaker to produce a number of segments which only appear on the production level and realized on the perceptual  one . RP pronunciation represents the teachable variety in all Iraqi universities because it is the most acceptable and understandable accent all over the world and not only in South East London ..The structure of the English syllable in RP  pronunciation is influenced by the appearance of certain allophones especially aspiration and glottalization which ch

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Publication Date
Mon Dec 29 2025
Journal Name
Journal Of Applied Engineering And Technological Science (jaets)
Using Fuzzy Cognitive Maps For Modeling Environmental Aspect of Sustainable Development in Construction Projects
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The pillars of sustainable development are representing the interface between environmental, economic, and social sustainability. Sustainable development is a method of planning and managing construction projects to reduce the effect of the construction process on the environment so that there is a balance between environmental capabilities and the human needs of present and future generations. Usually, Environmental sustainability is most important and effective in construction projects. The environment suffers from significant negative impacts as a result of the implementation of construction projects; therefore, this study aims to identify the effecting factors on environmentally sustainable development. The methodology of this s

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Publication Date
Sat Sep 26 2026
Journal Name
Journal Of Physical Education
A comparative analysis , for some Elkinmetekih variables , in the performance of the skill (Nick shot the front reverse ) , between the players of the Iraqi team and the Egyptian , for young people in squash
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Publication Date
Tue May 16 2023
Journal Name
Journal Of Engineering
Statistical Model for Predicting the Optimum Gypsum Content in Concrete
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The problem of internal sulfate attack in concrete is widespread in Iraq and neighboring countries.This is because of the high sulfate content usually present in sand and gravel used in it. In the present study the total effective sulfate in concrete was used to calculate the optimum SO3 content. Regression models were developed based on linear regression analysis to predict the optimum SO3 content usually referred as (O.G.C) in concrete. The data is separated to 155 for the development of the models and 37 for checking the models. Eight models were built for 28-days age. Then a late age (greater than 28-days) model was developed based on the predicted optimum SO3 content of 28-days and late age. Eight developed models were built for all

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