Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

Supra nanoparticles (submicron) of Chicken bones fibers were used (before and after treated with citric acid solution) as additives  to dental composite with the weight ratios (1%, 2% and 4%). The main mechanical tests represented by hardness, wear resistance and compression strength was carried out on the improvement dental composites.

The addition of treated supra nanoparticles Chicken thigh bones with particles size (300 nm) by weight ratio (1%) to ordinary dental composite resin , significantly improves all of its mechanical properties, in addition to the increase the value of the its  glass transition temperature from  43^oC  to 45.4 ^oC. The techniques X-ray diffraction (XRD), Energy Dispersive Spectr

Interface bonding between asphalt layers has been a topic of international investigation over the last thirty years. In this condition, a number of researchers have made their own techniques and used them to examine the characteristics of pavement interfaces. It is obvious that test findings won't always be comparable to the lack of a globally standard methodology for interface bonding. Also, several kinds of research have shown that factors like temperature, loading conditions, materials, and others have an impact on surface qualities. This study aims to solve this problem by thoroughly investigating interface bond testing that might serve as a basis for a uniform strategy. First, a general explanation of how

In this paper, analyzing the non-dimensional Magnesium-hydrodynamics problem Using nanoparticles in Jeffrey-Hamel flow (JHF) has been studied. The fundamental equations for this issue are reduced to a three-order ordinary differential equation. The current project investigated the effect of the angles between the plates, Reynolds number, nanoparticles volume fraction parameter, and magnetic number on the velocity distribution by using analytical technique known as a perturbation iteration scheme (PIS). The effect of these parameters is similar in the converging and diverging channels except magnetic number that it is different in the divergent channel. Furthermore, the resulting solutions with good convergence and high accuracy for the d

Interface bonding between asphalt layers has been a topic of international investigation over the last thirty years. In this condition, a number of researchers have made their own techniques and used them to examine the characteristics of pavement interfaces. It is obvious that test findings won't always be comparable to the lack of a globally standard methodology for interface bonding. Also, several kinds of research have shown that factors like temperature, loading conditions, materials, and others have an impact on surface qualities. This study aims to solve this problem by thoroughly investigating interface bond testing that might serve as a basis for a uniform strategy. First, a general explanation of how the bonding strength

Due to the large-scale development in satellite and network communication technologies, there is a significant demand for preserving the secure storage and transmission of the data over the internet and shared network environments. New challenges appeared that are related to the protection of critical and sensitive data
from illegal usage and unauthorized access. In this paper, we address the issues described above and develop new techniques to eliminate the associated problems. To achieve this, we propose a design of a new sensor node for tracking the location of cars and collecting all information and all visited locations by cars, followed by
encryption in a sensor node and saving in the database. A microcontroller of Arduino es

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

Seventy of Klebsiella pneumoniae isolates had been collected from some Hospitals in Baghdad city from October to December 2017. The 70 isolates were taken from diverse clinical specimens. All K. pneumoniae isolates were identified based on API 20 E and Vitek2 compact system. Antibiotics sensitivity test was carried out toward 10 antibiotics using discs diffusion method. The level of antibiotics resistance was 81.42% for Ceftriaxone, whereas the low level of antibiotics resistance was 37.14% for Piperacillin. K. pneumoniae isolates were typed genotypically by using two different methods of amplification, multiplex-PCR and enterobacterial repetitive intergenic consensus (ERIC)-PCR typing methods. Results showed that out of 70 isolates, there