With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

In networking communication systems like vehicular ad hoc networks, the high vehicular mobility leads to rapid shifts in vehicle densities, incoherence in inter-vehicle communications, and challenges for routing algorithms. It is necessary that the routing algorithm avoids transmitting the pockets via segments where the network density is low and the scale of network disconnections is high as this could lead to packet loss, interruptions and increased communication overhead in route recovery. Hence, attention needs to be paid to both segment status and traffic. The aim of this paper is to present an intersection-based segment aware algorithm for geographic routing in vehicular ad hoc networks. This algorithm makes available the best route f

     Optimization is the task of minimizing or maximizing an objective function f(x) parameterized by x. A series of effective numerical optimization methods have become popular for improving the performance and efficiency of other methods characterized by high-quality solutions and high convergence speed. In recent years, there are a lot of interest in hybrid metaheuristics, where more than one method is ideally combined into one new method that has the ability to solve many problems rapidly and efficiently. The basic concept of the proposed method is based on the addition of the acceleration part of the Gravity Search Algorithm (GSA) model in the Firefly Algorithm (FA) model and creating new individuals. Some stan

The influence of different types of plasmonic gold (Au-NPs) and silver (Ag-NPs) nanoparticles as well as aging on the performance of Surface-Enhanced Raman Scattering (SERS) sensors were studied. The average diameters of Au-NPs and Ag-NPs were about 23 nm and 15 nm, respectively, with a number of laser pulses of about 200. plasmonic nanoparticles were synthesized by laser ablation process in distilled water using a fixed energy laser fluence of about 14 J/cm² of Nd-YAG laser, with 1060 nm wavelength and 1 Hz pulse repetition rate. The SERS sensor was carried out by quick drop casting process of plasmonicplasmonic nanoparticles on glass substrates. The morphological aspects and the performance of SERS sensors were investigated

The research aims to demonstrate the impact of TDABC as a strategic technology compatible with the rapid developments and changes in the contemporary business environment) on pricing decisions. As TDABC provides a new philosophy in the process of allocating indirect costs through time directives of resources and activities to the goal of cost, identifying unused energy and associated costs, which provides the management of economic units with financial and non-financial information that helps them in the complex and dangerous decision-making process. Of pricing decisions. To achieve better pricing decisions in light of the endeavor to maintain customers in a highly competitive environment and a variety of alternatives, the resear

Energy efficiency is a significant aspect in designing robust routing protocols for wireless sensor networks (WSNs). A reliable routing protocol has to be energy efficient and adaptive to the network size. To achieve high energy conservation and data aggregation, there are two major techniques, clusters and chains. In clustering technique, sensor networks are often divided into non-overlapping subsets called clusters. In chain technique, sensor nodes will be connected with the closest two neighbors, starting with the farthest node from the base station till the closest node to the base station. Each technique has its own advantages and disadvantages which motivate some researchers to come up with a hybrid routing algorit

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se