IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING

This research deals with the using of correlation measurement that leads to
describing the degree of relationship between variables, quantities or qualities. Therefore,
we implement a simple correlation coefficient and conditional correlation to introduce a
regular vine copula, which gives different tree structures. Two methods to select tree
structures are introduced. The first one adopts the Partial Correlation Constant (PCC)
with constant, while the second method depends on the estimation of summation pathway.
The proposed method makes modification on Diβmann’s algorithm to increase the
dependency on each level of the tree using rank correlation measurement. Both methods
are adopted to construct the best model with more than three dimensions based on the
available label crime dataset in Iraq. The selected model is used for selecting the suitable
tree model and generating a decision with the low dimensionality of variables.

This paper adopted a thermal network method (TNM) based on Motor-CAD
with MATLAB/Simulink software, and finite element method (FEM) based on Motor-
CAD with Flux2D software, to estimate the stator winding temperature of a totally
enclosed fan-cooled (TEFC), squirrel cage, three-phase induction motor. The three
software packages were adopted successfully with a good agreement among their results
resulting in preferring using Motor-CAD in obtaining results, and using Flux2D with
MATLAB to validate these results. The success of triple-software methodology will give
the induction motor designer a well-validated tool in attaining a safe motor operation
without exceeding the maximum allowable stator winding temperature rise, and without
using an experimental test based on an expensive manufacturing motor.

The design and simulation of the Spiking Neural Network (SNN) are
proposed in this paper to control a plant without and with load. The proposed
controller is performed using Spike Response Model. SNNs are more powerful
than conventional artificial neural networks since they use fewer nodes to solve
the same problem. The proposed controller is implemented using SNN to work
with different structures as P, PI, PD or PID like to control linear and
nonlinear models. This controller is designed in discrete form and has three
inputs (error, integral of error and derivative of error) and has one output. The
type of controller, number of hidden nodes, and number of synapses are set
using external inputs. Sampling time is set according to the controlled model.
Social-Spider Optimization algorithm is applied for learning the weights of the
SNN layers. The proposed controller is tested with different linear and
nonlinear models and different reference signals. Simulation results proved the
efficiency of the suggested controller to reach accurate responses with minimum
Mean Squared Error, small structure and minimum number of epochs under no
load and load conditions.

Filter Bank Multicarrier (FBMC) is a multitone modulation
technique that is expected to replace the Orthogonal Frequency Division
Multiplexing (OFDM) due to its inherent characteristics that makes it immune
to channel dispersive effect on the transmitted signal in both time and
frequency. The most effective ingredient in the FBMC is the pulse shaping that
the OFDM symbol lacks. In this paper, a comparative study is presented
between different pulse shapes used in the FBMC like the RRC, PHYDIAS,
IOTA and Hermite function alongside the conventional OFDM.

in this paper, an analytical model is developed to estimate a
nonlinear phase noise (NPN) due to Kerr fiber nonlinearity and its interaction
with amplifier noise in mode division multiplexing (MDM) systems. Our
analysis uses generalized coupled multimode nonlinear Schrödinger equations
(MM- NLSE) that describe the propagation of the mode superimposing in the
optical fiber. The nonlinear phase noise versus channel power and transmission
distance is evaluated by implementing our analytical model for LP01, LP11a,
and LP11b spatial modes. Each mode carries a 4-QAM signal at a symbol rate
of 20 Gsymbol/s. The results reveal that LP11 mode has a lower phase noise
variance than LP01 mode over entire transmission distances. Finally, the error
vector magnitude (EVM) versus channel power is quantified using an analytical
model.

Any work to improve the performance of the solar modules could add to their
economic competitiveness against fossil fuels. In the present work the performance of PV
solar module was improved by using V-Trough concentrator system (CPV) which moved
by two axis tracking system. The concentrator consists of two flat reflectors of area 2 m2
for each one with geometric concentration ratio of 2X. To optimize the performance of the
V-Trough CPV systems, two types of reflector material, Aluminum and mirror (glass coated
by silver nitrate) were used. The results indicated that the temperature of PV reference
module was higher than the ambient temperature by 27oC but there is too small difference
in temperature between the tracking PV module with the reference which ranged to 2oC,
while the temperature of the CPV system was higher than reference by 37oC. The
temperature of the PV module under mirror reflectors was lower than module combined
with Aluminum reflectors by 3oC. As a result of arising of the temperature of CPV system
in compare with PV reference module, the open circuit voltage was droop by 0.7 V, 0.5 V
for PV module under mirror and Aluminum reflectors respectively. The reflectors
increased the short circuit current values by 2.1 A, 2.6 A for PV module combined with
mirror and Aluminum reflectors respectively. Accordingly the performance (as an average
daily gain of output power) of the PV solar module was improved by using V-Trough CPV
system, 44%, 34% by using Aluminum and mirror reflectors respectively.

In this paper, Field Oriented Control (FOC) of 3-phase induction motor is
controlled by using (PI) and (I-P). These controllers are established with the help of
MATLAB/SIMULINK.  The gains value obtained by the trial and error method of PI-
controller and   Particle Swarm Optimization (PSO) technique is used in this paper for
designing I-P controllers that give better performance.  PSO technique was proposed to
tune the optimal gains of I-P controller and state feedback gains. A comparison between
two controllers is presented. From simulation results, the advantages and disadvantages
of both controllers are investigated to explain the characteristic of the two methods. The
operation perforamcnes of the two proposed controller systems have been examined in
terms of the motor torque, current ripples and momentary responses to load toque
variants.

Recently, indoor localization has witnessed an increase in interest,
due to the potential wide range of using in different applications, such as
Internet of Things (IoT). It is also providing a solution for the absence of Global
Positioning System (GPS) signals inside buildings. Different techniques have
been used for performing the indoor localization, such as sensors and wireless
technologies. In this paper, an indoor localization and object tracking system is
proposed based on WiFi transmission technique. It is done by distributing
different WiFi sources around the building to read the data of the tracked
objects. This is to measure the distance between the WiFi receiver and the
object to allocate and track it efficiently. The test results show that the proposed
system is working in an efficient way with low cost.

monitoring the behavior of computer networks is essential for
problem identification and optimal management. Part of this behavior to be
monitored is the utilization of the network bandwidth. Several techniques are
used to model and forecast network traffic such as time series models, modern
data mining techniques, soft computing approaches, and neural networks are
used for network traffic analysis and prediction. Efficient bandwidth utilization
and optimization are very interesting research issues in effective networks
because bandwidth is one of the most required and expensive Internet
components needed today. It is generally known that the higher the bandwidth
available, the better the network performance, thus an essential aid for network
design and bandwidth wastage control and a need for traffic models which can
capture the characteristics is necessary. In this paper, a time series prediction
models were proposed for LAN office network bandwidth utilization. The
proposed prediction models are tested by using evaluation metrics used in time
series such as MSE and performance evaluation plot. Testing results show that
the proposed models can enhance the detection of bandwidth traffic and provide
an efficient tool for bandwidth utilization.

Electrical power systems are different in their sizes because of their amount of
generation power stations, substations, transmission lines and loads. Therefore, these
factors may impact on short circuit levels values. Capacity of power stations and dummy
transmission lines in Extra high voltage grid (400kV) of the Iraqi Electrical power grids
cause high short circuit levels values such that exceed both rating of the peak and breaking
capacity of switchgear equipment's. Reduction of short-circuit levels by using Fast-acting
Flexible Alternating Current Transmission Systems (FACTS) types devices in power grids
maintain the operation of power grids with acceptable value of short circuit levels for their
electrical equipment's and preventing cascading event outages which may lead to
blackouts. This paper mainly studies strategies on how to add Short Circuit Current Limiter
(SCCL) device by determining its number, value and location of connection in power grids
by programing with (PSS™E version 30.3 Package Program). IEEE 25-bus system is used
for testing the adding series SCCL at power transmission lines method procedure. The
results of adding series SCCL with power transmission lines give significant reducing short
circuit levels for the stations have highest short circuit levels in order to prevent the
blackouts of overall power grid.