Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

Let  be a non-trivial simple graph. A dominating set in a graph is a set of vertices such that every vertex not in the set is adjacent to at least one vertex in the set. A subset  is a minimum neighborhood dominating set if  is a dominating set and if for every  holds. The minimum cardinality of the minimum neighborhood dominating set of a graph  is called as minimum neighborhood dominating number and it is denoted by  . A minimum neighborhood dominating set is a dominating set where the intersection of the neighborhoods of all vertices in the set is as small as possible, (i.e., ). The minimum neighborhood dominating number, denoted by , is the minimum cardinality of a minimum neighborhood dominating set. In other words, it is the

The rapid development of telemedicine services and the requirements for exchanging medical information between physicians, consultants, and health institutions have made the protection of patients’ information an important priority for any future e-health system. The protection of medical information, including the cover (i.e. medical image), has a specificity that slightly differs from the requirements for protecting other information. It is necessary to preserve the cover greatly due to its importance on the reception side as medical staff use this information to provide a diagnosis to save a patient's life. If the cover is tampered with, this leads to failure in achieving the goal of telemedicine. Therefore, this work provides an in

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

The main purpose of this work is to introduce some types of fuzzy convergence sequences of operators defined on a standard fuzzy normed space (SFN-spaces) and investigate some properties and relationships between these concepts. Firstly, the definition of weak fuzzy convergence sequence in terms of fuzzy bounded linear functional is given. Then the notions of weakly and strongly fuzzy convergence sequences of operators  are introduced and essential theorems related to these concepts are proved. In particular, if ( ) is a strongly fuzzy convergent sequence with a limit  where linear operator from complete standard fuzzy normed space  into a standard fuzzy normed space  then  belongs to the set of all fuzzy bounded linear operators

Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

Smart cities have recently undergone a fundamental evolution that has greatly increased their potentials. In reality, recent advances in the Internet of Things (IoT) have created new opportunities by solving a number of critical issues that are allowing innovations for smart cities as well as the creation and computerization of cutting-edge services and applications for the many city partners. In order to further the development of smart cities toward compelling sharing and connection, this study will explore the information innovation in smart cities in light of the Internet of Things (IoT) and cloud computing (CC). IoT data is first collected in the context of smart cities. The data that is gathered is uniform. The Internet of Things,

The research seeks to achieve its goal of demonstrating the impact of applying banking governance variables on the financial performance of Islamic banks, and the independent research variables are represented by (X) by (the number of independent members in the board (X1), the number of directors in the board (X2), the number of committees emanating from the board ( X3), the percentage of shares owned by major shareholders in the board (X4), the number of members of the Sharia supervisory board (X5)), and the dependent variable (Y) is represented by (rate of return on assets (Y1), rate of return on equity (Y2)).

The research sample included (4) Islamic banks, namely (Iraqi Islamic Bank, National Islamic Bank, Jihan Islamic Bank,

With today's rapid and full of dangers the world banking sector is one of the most vital sectors at risk, and on the supervisory bodies responsible for monitoring the work of banks to take an active role in influencing the banks and put on the right track and is compatible with internationally approved curriculum. The lie of the research problem in the weak supervisory role of the Central Bank for banks in general and private banks in particular, limited the process of performance audit carried out by the Federal Office of Financial Supervision in auditing oversight role of the Central Bank control over the banks, according to the methods of performance audit followed by the upper bodies of financial control and accounting, And it was ba

This qualitative study was conducted on eight types of commercial baking yeast which available in local markets to estimate their fermentation activity as affecting the Bread industry and the impact of the salt added to DoughLeavening, The results showed a great variation in the fermentation capacity of yeast samples (their role in swelling the dough), most notably the sample value Y3 and least sample Y7 and reached 80% and 20% respectively, and the value of Leavening by using the two types of yeast with addition of three levels of salt (0 , 1 and 2%) have 20.0 , 19.7 and 15.7 of the sample Y3, compared with 10.5 , 10.3 and 8.8 of the sample Y7 for each of the levels of salt respectively, reflect