The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

This paper proposes and tests a computerized approach for constructing a 3D model of blood vessels from angiogram images. The approach is divided into two steps, image features extraction and solid model formation. In the first step, image morphological operations and post-processing techniques are used for extracting geometrical entities from the angiogram image. These entities are the middle curve and outer edges of the blood vessel, which are then passed to a computer-aided graphical system for the second phase of processing. The system has embedded programming capabilities and pre-programmed libraries for automating a sequence of events that are exploited to create a solid model of the blood vessel. The gradient of the middle c

Future wireless systems aim to provide higher transmission data rates, improved spectral efficiency and greater capacity. In this paper a spectral efficient two dimensional (2-D) parallel code division multiple access (CDMA) system is proposed for generating and transmitting (2-D CDMA) symbols through 2-D Inter-Symbol Interference (ISI) channel to increase the transmission speed. The 3D-Hadamard matrix is used to generate the 2-D spreading codes required to spread the two-dimensional data for each user row wise and column wise. The quadrature amplitude modulation (QAM) is used as a data mapping technique due to the increased spectral efficiency offered. The new structure simulated using MATLAB and a comparison of performance for ser

The automatic liquid filling system is used in different applications such as production of detergents, liquid soaps, fruit juices, milk products, bottled water, etc. The automatic bottle filling system is highly expensive. Where, the common filling systems required to complex changes in hardware and software in order to modify volume of liquid. There are many important variables in the filling process such as volume of liquid, the filling time, etc. This paper presents a new approach to develop an automatic liquid filling system. The new proposed system consists of a conveyor subsystem, filling stations, and camera to detect the level of the liquid at any instant during the filling process. The camera can detect accurately the leve

In this paper, a discussion of the principles of stereoscopy is presented, and the phases
of 3D image production of which is based on the Waterfall model. Also, the results are based
on one of the 3D technology which is Anaglyph and it's known to be of two colors (red and
cyan).
A 3D anaglyph image and visualization technologies will appear as a threedimensional
by using a classes (red/cyan) as considered part of other technologies used and
implemented for production of 3D videos (movies). And by using model to produce a
software to process anaglyph video, comes very important; for that, our proposed work is
implemented an anaglyph in Waterfall model to produced a 3D image which extracted from a
video.

 The vast majority of EC applications are the web-based deployed in 3-tire Server-Client environment, the data within such application often resides within several heterogeneous data sources. Building a single application that can access each data sources can be a matter of challenging; this paper concerns with developing a software program that runs transparently against heterogeneous environment for an EC-application.
 

The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

Abstract

Zigbee is considered to be one of the wireless sensor networks (WSNs) designed for short-range communications applications. It follows IEEE 802.15.4 specifications that aim to design networks with lowest cost and power consuming in addition to the minimum possible data rate. In this paper, a transmitter Zigbee system is designed based on PHY layer specifications of this standard. The modulation technique applied in this design is the offset quadrature phase shift keying (OQPSK) with half sine pulse-shaping for achieving a minimum possible amount of phase transitions. In addition, the applied spreading technique is direct sequence spread spectrum (DSSS) technique, which has

In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p