IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING

Web services send and receive messages over standard Internet protocols such as HTTP. Plaintext messages can be intercepted by an attacker and potentially viewed or even modified for malicious purposes. By using message protection, we can protect sensitive data against threats such as eavesdropping and data tampering. Sensitive data transmitted over the Internet should always be encrypted to avoid potential intruders from eavesdropping on the communication anywhere along the route the data takes between the two machines.
In this paper, we provide a feasible solution to enhance the integrity of sensitive data. Our approach is to use variant encryption algorithms based on session key which is sent with the client page from the server side where it is used to encrypt and decrypt data so that the data will be unreadable from the attacker. The encryption algorithm will be changed to every connection state. Our approach is very complex as we must cryptanalysis and modify the plaintext from attackers and make it applicable to client-server architecture.

Real-Time 3D animation and Real-Time Simulation results are reported for a 3R
underactuated robot moving in a horizontal plane using Virtual Reality Toolbox™™, Real-
Time Windows Target™™,Real-Time Workshop®, and interfaced to Simulink® under the
MATLAB® environment. The reason behind Real-time 3D animation and Real-Time
simulation is to provide animated real-time tools in a realistic fashion to demonstrate the
effectiveness of the controllers in tracking the desired trajectory and to provide a tool for
researchers to test their proposed controllers and observe their behavior using 3-DOF
underactuated manipulator in real-time.

In this paper a fuzzy proportional-Integral (FPI) controller is designed as an
Active Queue Management (AQM) in internet routers to improve the performance of
PI controller for congestion avoidance in computer networks. Firstly the parameters
of FPI controller are selected by trial and error method, but to get the best controller
parameters the Genetic Algorithm (GA) is used as an optimization method for tuning
the FPI parameters. The analytical results for linearized TCP/AQM model are
presented in MATLAB version 7.0. From the obtained results, a faster response time
as well as the regulation of the output to a constant value by the designed FPI
controller is clearly observed and it is noted that the FPI controller provides good
tracking performance under different circumstances for congestion avoidance in
computer networks.

The Braille system is a method that is widely used by blind people to read and
write. Braille generally consists of cells of raised dots arranged in a grid. The presence
or absence of dots can be sensed by the blind people's fingertips to give them the coding
for the symbol.
The electronic revolution is changing the way Braille is produced, stored and
retrieved, making it easier to use in the work place. All kinds of materials can be put
into Braille, from bank statements, bus timetables, maps to music. But it is still difficult
to produce an error-free Braille for complex materials. In this paper, the ability of the
neural networks will be tested to be used for translating scanned text pages, books or
lectures from English language into Grade I Braille; so that blind people can deal with
it.
An artificial neural network is designed with minimum structure and tested to
convert the English characters into grade I literary Braille code. English characters will
be assumed to be affected by noise of mean variant between 0 and 0.4.The output of the
N.N can be stored in a data file that can be sent into a Braille printer or a Braille display.

Mobile robot is a mechanical device capable of moving in an environment with a certain
degree of autonomy. The main goal of this work is to design, and simulate an intelligent
controller for autonomous mobile robot named Fuzzy like PD Controller, as the test bed
for future development of an intelligent vehicle. The fuzzy algorithm was implemented
using a combination of three different units of fuzzy logic systems that controls two
identical DC servo motors to implement the requirements of the safety navigation of the
mobile robot. The paper implies computer simulations in MATLAB platform using a
step input to demonstrate the ability of each controller to accommodate the sudden
changes along the motion of the mobile robot.

Surface electromyography (SEMG) measurement technique for the signal was produced
through the contraction of muscles in a human body. The surface electrode is connected on the
skin of the muscle. This paper presents an off-line design for the estimation of the actual joint
angle of a human leg obtained in performing flexion-extension of the leg at slow and high
speeds movement. The design is composed of two phases. The first is measurement of real
EMG signal of human leg performance by using SEMG technique and processing this signal
with filtering, amplification and then normalized with maximum amplitude. The second phase
is to design an artificial neural network (ANN) and train it to predict the joint angle from the
parameters extracted from the SEMG signal. Three main parameters of EMG signal are used in
the prediction process: Number of turns in a specific time period, duration of signal repetition
and amplitude of signal. The design of ANN includes the identification of a performing human
leg EMG signal with two speed levels (slow-fast) and estimation of knee joint angle by
recognition process depending on the parameters of real measured EMG signal. The real EMG
signal is measured from full leg-extension to full leg-flexion by (3 sec) with slow motion and (1
sec) at fast motion.
Root mean square (RMS) errors were calculated between the actual angle (measured by the
trigonometric formula was applied with any human leg gives real EMG signal measurement)
and the angle predicted by the neural network design. This design is simulated by using
MATLAB Ver. R2010a, and satisfying results are obtained. That explains the ability of
estimation of joint angle for human leg, where the RMS errors are obtained from (0.065) to
(0.015) at fast speed leg flexion -extension and from (0.018) to (0.0026) at slow speed leg
flexion-extension.

A Tuning Model Reference Adaptive Controller (TMRAC) for a synchronous generator is
presented in this paper. The controller performs the function of terminal voltage of the
machine. The proposed controller is used to overcome the problems of nonlinearities and
parametric uncertainties for Synchronous Generator (SG). The results verify improved
performance of TMRAC compared to conventional Automatic Voltage Regulator (AVR)
under various operating conditions.

Orthogonal Frequency Division Multiplexing (OFDM) is a very attractive
technique for high bit rate data transmission in a multipath fading environment that
causes intersymbol interference (ISI). In this paper, two steps are used to improve the
error rate performance of OFDM system. First, we proposed the Slantlet Transform
(SLT) used instead of Fast Fourier Transform (FFT) to obtain high orthogonality
properties between subcarriers and hence reduce (ISI). Second, we proposed the Low
Density Parity Check (LDPC) Codes for the proposed SLT-OFDM system to improve
the Bit Error Rate (BER) and Packet Error Rate(PER) performance.
The goal of the proposed SLT method is to reduce the energy needed to transmit data on
a fading channel and to decrease the number of complex computations(addition and
multiplication) and hence increase the speed of the system in addition to obtaining high
orthogonality between subcarriers. Hence, the proposed LDPC-based SLT-OFDM
system is a promising solution to high efficient data transmission over fading channels.
The proposed system has been tested and validated using MATLAB 7 package.

The aim of this research is to provide a computerized technique to build Entity
Relationship Table (ERT) instead of Entity Relationship Diagram(ERD). The ERT contains
Source Node Type (SNT) and Destination Node Type (DNT) which are either Entity or
Attribute. Also, it contains the source and destination node and their relationship type; Source
Node Relationship Type (SNRT) and Destination Node Relationship Type (DNRT). The verb
presents the relationship name between nodes. The program in this research splits the
relationship from the subject item then the relation will map to relationships dictionary to get real
word presentation to the corresponding relationship words. The same process is repeated with the
Complement group.

In this paper, Particle Swarm Optimization-feedforward Neural Network (PSONN) and Genetic
Algorithm-Neural Network (GANN) are proposed to enhance the learning process of ANN in
term of convergence rate and classification accuracy. They have been tested and compared and
the results applied in pattern classification. The experiments show that both algorithms produce
feasible results in terms of convergence time and classification percentage. At the end of the
evolutionary process of GANN for optimal structure, not only the best network structure for a
particular application but also the trained network with few numbers of epochs is provided. A
Hardware Design of ANN platform (HDANN) is proposed to evolve the architecture of ANN
circuits using FPGA-spartan3 board (XSA-3S1000 Board). The HDANN design platform creates
ANN design files using WebPACKTM ISE 9.2i, and converted into device-dependent
programming files for eventual downloading into an FPGA device by using GXSLOAD program
from the XSTOOLS programs.