Welcome to Journal of Theoretical and Applied Information Technology

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Classification is one of the most important tasks for different application such as text categorization, tone recognition, image classification, micro-array gene expression, proteins structure predictions, data Classification etc. Most of the existing supervised classification methods are based on traditional statistics, which can provide ideal results when sample size is tending to infinity. However, only finite samples can be acquired in practice. In this paper, a novel learning method, Support Vector Machine (SVM), is applied on different data (Diabetes data, Heart Data, Satellite Data and Shuttle data) which have two or multi class. SVM, a powerful machine method developed from statistical learning and has made significant achievement in some field. Introduced in the early 90’s, they led to an explosion of interest in machine learning. The foundations of SVM have been developed by Vapnik and are gaining popularity in field of machine learning due to many attractive features and promising empirical performance. SVM method does not suffer the limitations of data dimensionality and limited samples [1] & [2].
In our experiment, the support vectors, which are critical for classification, are obtained by learning from the training samples. In this paper we have shown the comparative results using different kernel functions for all data samples.

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As the increasing demand for higher capacity, better coverage and higher transmission quality rises, array antennas are used in mobile communication systems. For WiMAX application different microstrip antenna array configurations such as uniform circular, uniform concentric and modified uniform concentric circular arrays are studied for 3.3 GHz frequency band. Based on the simulation results obtained it is shown that modified concentric circular array outperforms other array configurations in terms of half power beamwidth, number of side lobes and main lobe to side lobe ratio.

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To improve the performance of motor drives, there is a need to improve the quality and reliability of the drive system. With the high power handling capability of the switching device, pulse width modulated AC chopper can be used in high power applications. AC chopper using pulse width modulation provides substantial advantages over conventional line commutated AC controllers. To alleviate the problems associated with the conventional AC voltage controllers, pulse width modulated AC chopper fed induction motor drive is developed and presented in this paper with an appropriate control circuit. The FFT analysis for voltage and current is performed for the developed system. The simulation is done using matlab and the hardware is implemented using an embedded microcontroller. The experimental results are compared with the simulation results.

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This paper deals with simulation of STATCOM used for harmonic reduction with the aid of multilevel VSI circuit. The harmonics in STATCOM due to the voltage ripple are reduced. As a result, the size of inductor and DC capacitor can be reduced. The STATCOM has the great advantage of a fewer number of devices. The VSI is extremely fast in response to reactive power change. The simulation of the STATCOM is performed in the Simulink environment and the results are presented.

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A license plate recognition system is an automatic system that is able to recognize a license plate number, extracted from an image device. Such system is useful in many fields and places: parking lots, private and public entrances, border control, theft and vandalism control. In our paper we designed such a system. First we separated each digit from the license plate using image processing tools. Then we built a classifier, using a training set based on digits extracted from approximately 350 license plates. Once a license plate is detected, its digits are recognized, displayed on the User Interface or checked against a database. The focus is on the design of algorithms used for extracting the license plate from an image of the vehicle, isolating the characters of the plate and identifying characters. Our approach is considered to identify vehicle through recognizing of its license plate using two different types of neural networks: Hopfield and the multi layer perceptron "MLP". A comparative result has shown the ability to recognize the license plate successfully. The experimental results have shown the ability of Hopfield Network to recognize correctly characters on license plate more than MLP architecture which has a weaker performance. A negative point in the case of Hopfield is the processing time.

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This paper demonstrates the design of an AGC scheme for an interconnected power system. The Stochastic Search Technique (SST), involving a Genetic Algorithm (GA) is used to get the optimal AGC feedback gains. A penalty function based strategy is used to satisfy transient response specifications of system frequency and power flow deviations and consequently, area control error (ACE) is minimized to zero. This proposed AGC scheme is tested on a two-area interconnected power system consisting of thermal power plants with reheat turbines. The area interconnections considered are with (i) only AC link and (ii) AC link in parallel with DC link. The dynamic response plots for various system states are obtained considering 1% load perturbation in one of the areas. The response plots achieved with proposed scheme are compared those obtained with optimal AGC regulators designed using Linear Quadratic Regulator (LQR) concept. The investigation of the system dynamic responses under load disturbance conditions reveal that proposed GA based AGC scheme yields appreciably better results as compared to those obtained with LQR concept based optimal AGC scheme. The optimal AGC gains designed using proposed scheme is more globally optimal in comparison to LQR concept based optimal AGC gains.

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Commitment schemes are fundamental bricks for guaranteeing fairness in upper level cryptographic protocols. Most commitment schemes in the literature rely on hash functions, which should be strongly collision free for the scheme to be secure. We present a commitment scheme, which avoids hash functions by using a public-key cryptosystem based on braid conjugator search problem instead

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As the networks improve and new demands for rapid data transfer rates and multimedia services grow, operators are seeking new cellular communication solutions based on technologies like GSM, 3GSM and CDMA2000 to cater to these requirements. The paper points out that the increasing popularity of the GSM equipments globally is driving manufacturers to bring phones to market faster with competitive enhancements increased the quality of service and reduced costs. The paper relates that CDMA, Code Division Multiple Access, alternatively signifies a more powerful digital air interface standard, equating about eight to fifteen times the capacity of conventional analog cellular systems.

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In this paper, a weighted adaptive scalable hierarchical (WASH) tree based video coding algorithm is proposed with low-memory usage. The standard coding uses three separate lists to store and organize tree data structures and their significance, which can grow large at high rate and consume large amounts of memory. In the proposed algorithm, value added adaptive scale down operator discards unnecessary lists and the process length of the sorting phase is shortened to reduce coding time and memory usage. Spatial and temporal scalability can be easily incorporated into the system to meet various types of display parameter requirements and self-adapting rate allocations are automatically achieved. Results show that the proposed method reduces memory usage, run time and improves PSNR.

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The overall goal of this paper is to investigate the scalability of the Fish-eye State Routing (FSR) protocol under different network scenarios in mobile ad hoc networks (MANETs). This performance based study simulates FSR under practical network scenarios typical of MANETs, and measures selected metrics that give an introspective look into the performance of FSR. The FSR protocol is compared against the minimum hop-count based reactive Dynamic Source Routing (DSR) protocol. The implementations of both protocols are simulated for varying conditions of network density, node mobility and traffic load. The following performance metrics are evaluated: packet delivery ratio, average hop count per path, control message overhead and energy consumed per node. Simulation results indicate FSR scales relatively better compared to DSR and consumes less energy when operated with moderate to longer link-state broadcast update time intervals in high density networks with moderate to high node mobility and offered traffic load. FSR successfully delivers packets for a majority of the time with relatively lower energy cost in comparison to DSR.