The main aim of this paper is studied the punching shear and behavior of reinforced concrete slabs exposed to fires, the possibility of punching shear failure occurred as a result of the fires and their inability to withstand the loads. Simulation by finite element analysis is made to predict the type of failure, distribution temperature through the thickness of the slabs, deformation and punching strength. Nonlinear finite element transient thermal-structural analysis at fire conditions are analyzed by ANSYS package. The validity of the modeling is performed for the mechanical and thermal properties of materials from earlier works from literature to decrea

Wireless Multimedia Sensor Networks (WMSNs) are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to   produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC). The Modify Spike Neural Network controller (MSNC) can calculate the appropriate traffi

Objectives: This study aims to assess and compare the micro-shear bond strength (μSBS) of a novel resin-modified glass-ionomer luting cement functionalized with a methacrylate co-monomer containing a phosphoric acid group, 30 wt% 2-(methacryloxy) ethyl phosphate (2-MEP), with different substrates (dentin, enamel, zirconia, and base metal alloy). This assessment is conducted in comparison with conventional resin-modified glass ionomer cement and self-adhesive resin cement. Materials and methods: In this in vitro study, ninety-six specimens were prepared and categorized into four groups: enamel (A), dentin (B), zirconia (C), and base metal alloys (D). Enamel (E) and dentin (D) specimens were obtained from 30 human maxillary first premolars e

Objective: To enhance bonding strength between thermoplastic denture base and acrylic soft liner through ethyl acetate surface treatment. Materials and Methods: Modifications of thermoplastic acrylic denture base surface were investigated with SEM. FTIR was used to detect whether there was a chemical bond between thermoplastic acrylic and the organic solvent. A total of 80 samples were prepared and divided into 20 samples for the surface roughness test and 60 samples for the shear bond strength test. Failure type was assessed visually. Results: Shear bond strength and surface roughness values of un treated samples were lower in comparison to surface treated groups; the greatest post thermocycling bond strength value was recorded for the sam

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

In Automatic Speech Recognition (ASR) the non-linear data projection provided by a one hidden layer Multilayer Perceptron (MLP), trained to recognize phonemes, and has previous experiments to provide feature enhancement substantially increased ASR performance, especially in noise. Previous attempts to apply an analogous approach to speaker identification have not succeeded in improving performance, except by combining MLP processed features with other features. We present test results for the TIMIT database which show that the advantage of MLP preprocessing for open set speaker identification increases with the number of speakers used to train the MLP and that improved identification is obtained as this number increases beyond sixty.

The objective of this work is to design and implement a cryptography system that enables the sender to send message through any channel (even if this channel is insecure) and the receiver to decrypt the received message without allowing any intruder to break the system and extracting the secret information. In this work, we implement an interaction between the feedforward neural network and the stream cipher, so the secret message will be encrypted by unsupervised neural network method in addition to the first encryption process which is performed by the stream cipher method. The security of any cipher system depends on the security of the related keys (that are used by the encryption and the decryption processes) and their corresponding le