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

XML is being incorporated into the foundation of E-business data applications. This paper addresses the problem of the freeform information that stored in any organization and how XML with using this new approach will make the operation of the search very efficient and time consuming. This paper introduces new solution and methodology that has been developed to capture and manage such unstructured freeform information (multi information) depending on the use of XML schema technologies, neural network idea and object oriented relational database, in order to provide a practical solution for efficiently management multi freeform information system.

High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination

In this study, gold nanoparticles were synthesized in a single step biosynthetic method using aqueous leaves extract of thymus vulgaris L. It acts as a reducing and capping agent. The characterizations of nanoparticles were carried out using UV-Visible spectra, X-ray diffraction (XRD) and FTIR. The surface plasmon resonance of the as-prepared gold nanoparticles (GNPs) showed the surface plasmon resonance centered at 550[Formula: see text]nm. The XRD pattern showed that the strong four intense peaks indicated the crystalline nature and the face centered cubic structure of the gold nanoparticles. The average crystallite size of the AuNPs was 14.93[Formula: see text]nm. Field emission scanning electron microscope (FESEM) was used to s

Diamond-like carbon (DLC) homogeneous thin films were deposited from cyclohexane (Ccyclohexane (Ccyclohexane (Ccyclohexane (C cyclohexane (Ccyclohexane (Ccyclohexane (C cyclohexane (Ccyclohexane (C 6H12 ) liquid by using a plasma jet system which operates with alternating high voltage 7.5 which operates with alternating high voltage 7.5which operates with alternating high voltage 7.5which operates with alternating high voltage 7.5 which operates with alternating high voltage 7.5which operates with alternating high voltage 7.5which operates with alternating high voltage 7.5 which operates with alternating high voltage 7.5which operates with alternating high voltage 7.5 which operates with alternating high voltage 7.5which operates with al

<p>Energy and memory limitations are considerable constraints of sensor nodes in wireless sensor networks (WSNs). The limited energy supplied to network nodes causes WSNs to face crucial functional limitations. Therefore, the problem of limited energy resource on sensor nodes can only be addressed by using them efficiently. In this research work, an energy-balancing routing scheme for in-network data aggregation is presented. This scheme is referred to as Energy-aware and load-Balancing Routing scheme for Data Aggregation (hereinafter referred to as EBR-DA). The EBRDA aims to provide an energy efficient multiple-hop routing to the destination on the basis of the quality of the links between the source and destination. In

Ahmed ibn Imad ibn Yusuf al-Aqfhasi (808 AH / 1405 AD) is a small message that speaks about the Nile River in all its sides, despite its limited papers, but it is one of the manuscripts of the important geographical literature for its geographical, historical, religious and grammatical information. it was not limited to the information of the author alore, but taken from many sources below, which added to the importance of the fact that it has saved us the names of the sources that preceded him in mentioning this river with the names of its authors.The method of the Aqfhasi was characterized by scientific methodology in writing and clarity, with reference to some of the myths that people carried in their minds about the Nile River at tha

Dates are considered one of the most important foods consumed in Arab countries. Dates are commonly infested with the sawtoothed grain beetle, Oryzaephilus surinamensis. Consequently, the date yield, quantity, and quality (economic value and seed viability) are negatively affected. This study was designed to investigate the effectiveness of air evacuation as eco-friendly and safe control method against adult O. surinamensis. Insects were obtained from the infested date purchased from a private store in sakaka city, Aljouf region, Saudi Arabia. Air evacuation (using a vacuum pump) and food deprivation were applied to O. surinamensis, and insect mortality was observed daily in comparison with the control group (a

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c