Preferred Language
Articles
/
bsj-927
Hybrid Cipher System using Neural Network
...Show More Authors

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 lengths. In our work, there are two types of keys; the first type is the keystream that is adopted by the stream cipher stage with optimal length (length of the keystream greater or equal the message length); and the second key type is the final weights that are obtained from the learning process within the neural network stage, So we can represent our work as an update or development for using the neural network to enhance the security of stream cipher. As a result for a powerful hybrid design, the resulted cipher system provides a high degree of security which satisfies the data confidentially which is the main goal of the most cryptography systems.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Bilinear System Identification Using Subspace Method
...Show More Authors

In this paper, a subspace identification method for bilinear systems is used . Wherein a " three-block " and " four-block " subspace algorithms are used. In this algorithms the input signal to the system does not have to be white . Simulation of these algorithms shows that the " four-block " gives fast convergence and the dimensions of the matrices involved are significantly smaller so that the computational complexity is lower as a comparison with " three-block " algorithm .

View Publication Preview PDF
Crossref
Publication Date
Mon Mar 20 2023
Journal Name
2023 International Conference On Information Technology, Applied Mathematics And Statistics (icitams)
Hybrid Color Image Compression Using Signals Decomposition with Lossy and Lossless Coding Schemes
...Show More Authors

View Publication
Scopus (1)
Scopus Crossref
Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
...Show More Authors

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

... Show More
Publication Date
Wed Jun 01 2022
Journal Name
Applied Energy
Novel mathematical modeling, performance analysis, and design charts for the typical hybrid photovoltaic/phase-change material (PV/PCM) system
...Show More Authors

Scopus (41)
Crossref (27)
Scopus Clarivate Crossref
Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Energy Storage
A hybrid solidification enhancement in a latent-heat storage system with nanoparticles, porous foam, and fin-aided foam strips
...Show More Authors

Scopus (29)
Crossref (25)
Scopus Clarivate Crossref
Publication Date
Wed Jun 01 2022
Journal Name
Applied Energy
Novel mathematical modeling, performance analysis, and design charts for the typical hybrid photovoltaic/phase-change material (PV/PCM) system
...Show More Authors

View Publication
Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Using Smart Control System to Enhancement the Split Air Conditioning System Performance
...Show More Authors

In IRAQ, the air conditioners are the principal cause of high electrical demand. In summer, the outer temperature sometimes exceeds 500C which significantly effects on the A/C system performance and power consumed. In the present work, the improvement in mechanical and electrical performance of split A/C system is investigated experimentally and analytically. In this paper, performance and energy saving enhancement of a split-A/C system was experimentally investigated to be efficiently compatible with elevated temperature weathers. This improvement is accomplished via Smart Control System integrate with Proportional-Integral- Differential PID algorithm. The PIC16F877A micro-controller has been programmed with the PID and PWM c

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Recognizing Different Foot Deformities Using FSR Sensors by Static Classification of Neural Networks
...Show More Authors

Sensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar

... Show More
View Publication Preview PDF
Scopus (4)
Crossref (3)
Scopus Crossref
Publication Date
Thu Jan 11 2018
Journal Name
Al-khwarizmi Engineering Journal
Control on a 2-D Wing Flutter Using an Adaptive Nonlinear Neural Controller
...Show More Authors

An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th

... Show More
View Publication Preview PDF
Publication Date
Sun Mar 31 2013
Journal Name
Inventi Impact: Artificial Intelligence
SIMULATION OF IDENTIFICATION AND CONTROL OF SCARA ROBOT USING MODIFIED RECURRENT NEURAL NETWORKS
...Show More Authors

This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

... Show More
View Publication