The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

The importance of the current study  lies in the  importance of the  Tax policy that  being considered one of the most important tools working on fulfilling  the  social,  financial  and economic  goals  and improving  the investment environment  in the country  to become  having the ability to  activate the  national economy. The current study  has  referred  that  (  Has  the  tax planning  practiced by  the Iraqi  contribution  companies  led to increase  the  far-term tax  outcome through  getting  benefit of   the monetary  funds  and expansion in&nbs

ABSTRACT

The research aims to know the reality of a two examined variables at the organization studied identifying the relationship between managerial processes reengineering and organizational citizenship behavior. The research applied on the Electronic Manufacturing Company encompassing a sample of managers and employees consisted of (100) individuals. A questionnaire is the main instrument for data gathering, which has been included (45) questions as well as personal interviews to support the questionnaire's questions and to achieve greater realism for collecting information.

Answers were analyzed to reach the final results through the use of a number of statistical methods via

he planning process is generally aimed at developing the city and making it meet the needs of different citizens. The green areas constitute one of the basic needs of the city and with the rapid and unusual growth in the size of cities, especially in the third world countries, which is often embodied in capitals. Which was achieved as a result of many reasons, including political, economic and social and even enshrined through some of the decisions that were issued and the city of Baghdad, but a clear example of these cities. The city and the environment are inseparable terms. The city is where people spend their lives and their daily experiences, and the environment is the center in w

The design and implementation of an active router architecture that enables flexible network programmability based on so-called "user components" will be presents. This active router is designed to provide maximum flexibility for the development of future network functionality and services. The designed router concentrated mainly on the use of Windows Operating System, enhancing the Active Network Encapsulating Protocol (ANEP). Enhancing ANEP gains a service composition scheme which enables flexible programmability through integration of user components into the router's data path. Also an extended program that creates and then injects data packets into the network stack of the testing machine will be proposed, we will call this program

Socio-scientific issues provide a great platform to both engage students in scientific topics and assess their understanding of scientific concepts. Nancy R. Singer, Amy Lannin, Maha Kareem, William Romine, and Katie Kline report on the STEM Literacy Project, a three-year National Science Foundation grant that aimed to improve STEM teachers’ knowledge and integration of literacy in their classrooms. They describe teachers’ professional learning, scenario-based assessments and other strategies they incorporated in their STEM classrooms, and how writing enables students to understand real-world issues.