IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING

Aggregation is a tool used in presenting the multiple instances of an individual attribute in a single value that characterizes the groups represented. However, probabilistic relational models are constructed from relational data base; these data are interrelated with different cardinalities so it is needed for aggregation in some situations in order to convert the relation cardinality from “many” to “one”. This paper will shed light on the role of aggregation in learning probabilistic relational models through presenting two aggregate functions one is conventional and the other is proposed and compare their effects on the produced models. The results produced from practical work assess that the effect of using different aggregate functions is not determined numerically but conceptually that is needed for intervening the expertise in learning probabilistic relational model.

In this paper, a new secret-key block cipher called 512 bits RC6 is proposed which is an evolutionary improvement of the 128 bits RC6 designed to meet the requirements of the Advanced Encryption Standard (AES) to increase security and improve performance. The inner loop is based around the same round found in the 128 bits RC6. The proposed algorithm includes two things the first is doubling the pervious 128 bits RC6 to 256 bits RC6 and the second adapting a Feistal network which is iterated 256 bits RC6 20 times. A desirable property of an encryption algorithm is that a small change in either the plaintext or the key should produce a significant change in the ciphertext. This is so called valanche Effect. An Avalanche Effect of 128 bit RC6 is about 43.25%. If we change the same amount of information in key for 512 bits RC6 then the Avalanche Effect is about 257.27%. The proposed algorithm is resistant to matching and a dictionary attack which increases the security of the previous 128 bits RC6 algorithm by using a block size of 512 bits instead of 128 bits.

In this research, the dynamic response of the electro-hydraulic system was investigated and analyzed based on a developed vision system. An experimental setup, which consist of hydraulic a circuit (tank, supply pump, pressure gauges, hydraulic actuator, and proportional directional valve) was developed and implemented. In addition, an electronic interface circuit used to control the proportional valve via a personal computer was built. The proposed vision system consists of a digital video camera used to monitor the hydraulic actuator base on two types of camera poses; fixed and on-rod poses. Algorithms and computer programs were implemented for acquiring the image data from the gained video frames. Extra processing steps of the obtained image data were applied to achieve actuator position, velocity, and acceleration. The mathematical model of the developed experimental setup was derived and simulated using SIMULINK software, where it consists of two parts; proportional valve model and hydraulic actuator model. Evaluation of the theoretical and experimental results and error analyses were presented, where it can be concluded that the use of the vision system as a feedback unit in hydraulic circuit can give promising results in position and force control problem.

Biometrics, is defined as the since of Human recognition based on his/her physical or behavioral traits, is beginning to used as Human added computer method for determining an individual's identity. The human hand presents the sorce for a numerous of physiological biometric features. Palmprint, hand geometry, finger geometry and the vein pattern on the dorsum of the hand, are mostly used in many fields for different applications. Lines and points are extracted from palms for individual identification in original image or frequency space. In this paper, the normalized energy based spectral eigenpalms is used for human identification. The correlation distance is used as a similarity measure. A threshold value is used to prevent the imposter form being identified. The experimental results point up the effectiveness of the method in varying noisy types.

Induction heating system has a number of inherent benefits compared to traditional heating systems. Many analytical and numerical approaches have been applied to solve the problem of induction heating. Artificial Neural Networks possess many advantages and have the ability to tackle problems that cannot be accomplished by more analytical and numerical methods. This paper involves modeling many artificial neural networks, and training them based on the results of analysis induction heating systems, by using ANSYS package, to enable them to evaluate the heat distribution inside the workpiece of any induction heating system. Also neural networks are used to specify the time and the power supply required for any desired heat distribution inside the workpiece. The neural networks are simulated by using Neural Network Toolbox in MATLAB, and the networks are trained according to supervised scaled conjugate gradient algorithm until the performance function (mean square error) reach the goal (=104). Artificial Neural Networks show a good success in solving the problem of induction heating through obtaining results with high accuracy and very short run time.

The UOTCS (University Of Technology Control System) helicopter system is a laboratory scale experimental platform developed primarily for teaching system dynamics and control engineering principles to undergraduate students. It also provides an excellent research platform for control and mechatronics postgraduate students. This paper is concerned with the modeling and controllers design for the UOTCS helicopter to mimics its motion. The kinematics model was derived following the Denavit-Hartenberg theory while the dynamic model was based on Euler-Lagrange equations of motion. The helicopter mathematical model includes the inertias of the counterweight, the beams and the propeller motors. This model was found competent enough for this application as it describes the dominant behaviors and coupling among the degrees of freedom of the helicopter model. Fuzzy logic controllers for elevation and pitch motion control were designed. The performance of the FLC is compared with the classical PID controller and the results are evaluated. Fuzzy logic controllers are suitable to control the elevation and pitch motions of the UOTCS helicopter.

Cantor fractal linear array, with ‘101' generator from second stage of growth, is analyzed here with two types of current amplitude excitation coefficients (Dolph and Fractal). The Koch fractal dipole element with 2nd iteration and 0=60° will be used here as the array elements. Kaiser-Bessel window will be used as the generating function, to calculate the fractal amplitude excitation coefficients. The benefit from using fractal antenna element in the design of fractal antenna array will be clearly deduced from the results. The radiation pattern and impedance were calculated by using software package MATLAB version 7.6 (R2008a) and software package 4NEC2 respectively.

In this paper we propose a new method of hiding information that produces a stego-image which is totally indistinguishable from the original image to extract the hiding message. GA is used as an efficient method to minimize the number of different bits between the cover image and the stego-image as minimum as possible by embedding the message in random locations of cover image, and then modifying the locations containing changed information in original image (cover) to improve stego-image quality. Το satisfy excellent security we used a crypto-key which contains encrypted locations from hiding process. This key is used to extract the embedded message.

Pneumatic servo system has been applied in many industry fields. The system has many advantages, such as high speed, high flexibility and low price. However, the application of the system is restricted because the physical parameters have strong nonlinearity, inaccuracy and uncertainty, so that it is very difficult to find an optimal controller by means of traditional control theory. Proportional integral derivative (PID) control is one of the earlier control strategies; it has a simple control structure and can be easily tuned. Optimization of PID controller parameters is one of the recent control solutions; especially when the system is of high complexity. In this paper foraging strategy has been adopted to optimize the gains of PID controller for positioning control of a pneumatic system. The foraging theory is based on the assumption that animals search for nutrients in a way that maximize their energy intake per unit time spent for foraging. The bacterial foraging algorithm is a non-gradient and stochastical optimization technique; as no need for measurement and analytical description. In the work, the optimization model of E. coli bacterial foraging has been used and the performance index (cost) is based on Integral Square Error (ISE) for obtaining sub- optimal values of controller parameters. The behavior of bacteria (solutions) over their lifetime has been simulated and the effect of foraging parameters on cost function has been studied.

In this paper two invariant sets are derived for a second order nonlinear affine system using a sliding mode controller. If the state started in these sets, it will not leave it for all future time. The invariant set is found function to the initial condition only, from which the state bound is estimated and used when determining the gain of the sliding mode controller. This step overcomes an arithmetic difficulty that consists of calculating suitable controller gain value that ensures the attractiveness of the switching manifold. Also, by using a differentiable form for the approximate signum function in sliding mode controller formula, the state will converge to a positively invariant set rather than the origin. The size of this set is found function to the parameters that can be chosen by the designer, thus, it enables us to control the size of the steady state error. The sliding mode controller is designed to the servo actuator system with friction where the derived invariant sets are used in the calculation of the sliding mode controller gain. The friction model is represented by the major friction components; Coulomb friction, the Stiction friction, and the viscous friction. The simulation results demonstrate the rightness of the derived sets and the ability of the differentiable sliding mode controller to attenuate the friction effect and regulate the state to the positively invariant set with a prescribed steady state error.