Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer

A comprehensive review focuses on 3D network-on-chip (NoC) simulators and plugins while paying attention to the 2D simulators as the baseline is presented. Discussions include the programming languages, installation configuration, platforms and operating systems for the respective simulators. In addition, the simulator’s properties and plugins for design metrics evaluations are addressed. This review is intended for the early career researchers starting in 3D NoC, offering selection guidelines on the right tools for the targeted NoC architecture, design, and requirements.

Volumetric chemical adsorption was done in a volumetric apparatus using hydrogen gas at room temperature on eleven platinum catalyst, commercial catalysts (RG-412,RG-402 ,RG-432, RG-451, RG-482, and PS-10) and prepared platinum catalysts with 0.1, 0.2 , 0.45 , and 0.55% by weight of Pt supported with Y-alumina. The results show that the metal crystallite area increases with increasing platinum content. The dispersion and particle size of metal crystallite located between 48.2-96.1% and 3.85-12.72 nm, respectively. For bimetallic catalysts, the hydrogen intake decrease in the following order : Re < Sn < Ir.

Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le

The advancement of digital technology has increased the deployment of wireless sensor networks (WSNs) in our daily life. However, locating sensor nodes is a challenging task in WSNs. Sensing data without an accurate location is worthless, especially in critical applications. The pioneering technique in range-free localization schemes is a sequential Monte Carlo (SMC) method, which utilizes network connectivity to estimate sensor location without additional hardware. This study presents a comprehensive survey of state-of-the-art SMC localization schemes. We present the schemes as a thematic taxonomy of localization operation in SMC. Moreover, the critical characteristics of each existing scheme are analyzed to identify its advantages

    Identification of complex communities in biological networks is a critical and ongoing challenge since lots of network-related problems correspond to the subgraph isomorphism problem known in the literature as NP-hard. Several optimization algorithms have been dedicated and applied to solve this problem. The main challenge regarding the application of optimization algorithms, specifically to handle large-scale complex networks, is their relatively long execution time. Thus, this paper proposes a parallel extension of the PSO algorithm to detect communities in complex biological networks. The main contribution of this study is summarized in three- fold; Firstly, a modified PSO algorithm with a local search operator is proposed

The creation and characterisation of biodegradable blend films based on chitosan and polyvinyl alcohol for application in a range of packaging is described. The compatibility between the chitosan and PVA polymers was good. Composite films had a compact and homogeneous structure, according to the morphology analysis. The mechanical test result of PVA/CH at concentrations 5% showed, that The higher values of TS recorded in sample (p1, with 40 MPa) while the lower values appeared in sample (p9, with 22.09 MPa), the TS decreased gradually as the amount of PVA increased in blend film. While the blend film of pure Chitosan exhibits a poor mechanical strength which makes it a poor candidate for packaging but Blending CH with PVA together improved