Welcome to Journal of Theoretical and Applied Information Technology

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Sensitivity and Robustness is the primary issue while designing the controller for non-linear systems. One of the performance objectives for controller design is to keep the error between the controlled output and the set-point as small as possible. A comparison between Evolutionary Algorithms namely GAs (Genetic Algorithms), and Swarm Intelligence i.e. PSO (Particle Swarm Optimization) and BG (Bacterial Foraging) has been carried out on the basis of performance indices: ITAE (Integral Time Absolute Error), ISE (Integral Square Error), IAE (Integral Absolute Error) and MSE (Mean Square Error) and settling time. In this paper, the idea of model generation and optimization is explored for PD-PI controller. Most commonly known, the highly nonlinear Inverted Pendulum system is used as a test system for this approach. The simulations are tabulated in section IV to analyze which technique gives promising results for the system.

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Neural networks are increasingly used to solve highly non linear control problems. The current paper addresses the problem of forecasting the result of general elections in India. The neural network is first made to learn and then the trained network is made to forecast the result of the election. While training the network minimal disturbance principle was followed, which suggests that during training it is advisable to inject new information into the network in such a manner that it disturbs the stored information to the smallest extent possible.

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The Universal Mobile Telecommunication System (UMTS) is a third generation (3G) mobile communications system that provides a range of broadband services to the world of wireless and mobile communications. The UMTS delivers low-cost, mobile communications at data rates of up to 2 Mbps. It preserves the global roaming capability of second generation GSM/GPRS networks and provides new enhanced capabilities. The UMTS is designed to deliver pictures, graphics, video communications, and other multimedia information, as well as voice and data, to mobile wireless subscribers. UMTS also addresses the growing demand of mobile and Internet applications for new capacity in the overcrowded mobile communications sky. The new network increases transmission speed to 2 Mbps per mobile user and establishes a global roaming standard. UMTS allows many more applications to be introduced to a worldwide base of users and provides a vital link between today’s multiple GSM systems and the ultimate single worldwide standard for all mobile telecommunications, International Mobile Telecommunications–2000 (IMT–2000).

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In this paper we present a new iterative method to solve the maximum satisfiability problem (MAX SAT). This one aims to find the best assignment for a set of Boolean variables that gives the maximum of verified clauses in a Boolean formula. Unfortunately, It is shown that the MAX SAT problem is NP complete if the number of variable per clause is higher than 3. Our approach called QHILLSAT is a combination of a Quantum Genetic Algorithm QGA and a Hill Climbing Algorithm. The main features of this algorithm consist in the quantum structure used to represent MAX SAT solutions and the quantum operators defining the overall evolutionary dynamic of the genetic algorithm. The Hill Climbing Search procedure is used in order to increase the efficiency of the exploration process. Experiments on wide range of data sets have shown the effectiveness of the proposed framework and its ability to achieve good quality solutions.

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In digital image classification the conventional statistical approaches for image classification use only the gray values. Different advanced techniques in image classification like Artificial Neural Networks (ANN), Support Vector Machines (SVM), Fuzzy measures, Genetic Algorithms (GA), Fuzzy support Vector Machines (FSVM) and Genetic Algorithms with Neural Networks are being developed for image classification. Artificial neural networks can handle non-convex decisions. The use of textural features in ANN helps to resolve misclassification. SVM was found competitive with the best available machine learning algorithms in classifying high-dimensional data sets. Fuzzy measures show the detection of textures by analyzing the image by stochastic properties. The fundamental stochastic properties of the image are isolated by different kinds of stochastic methods, by non-linear filtering and by non-parametric methods. Fuzzy support vector machines (FSVM) was proposed to overcome the n-class problem in Support Vector Machines. In this using the decision functions obtained by training the SVM, for each class, a truncated polyhedral pyramidal membership function was defined. The genetic algorithm searches a space of image processing operations for a set that can produce suitable feature planes, and a more conventional classifier which uses those feature planes to output a final classification. The use of a hybrid genetic algorithm investigates the effectiveness of the genetic algorithm evolved neural network classifier and its application to the image classification of remotely sensed multispectral imagery. A comparative study of some of these techniques for image classification is made to identify relative merits.

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 Today's wireless subscribers are much more sophisticated telecommunications users than they were five years ago. No longer satisfied with just completing a clear call, today's subscribers demand innovative ways to use the wireless phone. They want multiple services that allow them to handle or select incoming calls in a variety of ways.Wireless Intelligent network is developed to drive intelligent network capabilities such as service independence, separation of basic switching functions from service and application functions and independence of applications from lower-level communication details into wireless networks. The primary weapon for empowering providers to deliver distinctive services with enhanced flexibility is Wireless Intelligent Networks (WINs).

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Matching based on Moiré pattern is a well known method for image recognition. Image recognition is one of the interesting fields of study. There are many methods for image recognition. Some uses images subtraction and others use the wavelet technique which is a new topic used in many fields and applications. This paper, represent a model image recognition by mean of Binary similarity measure. Matching technique used in this model differs from conventional matching, in such a way that the matching points are not compared under a search task, but rather under a circular pattern resulting from superimposing two images under investigation. Results obtained, prove that this technique introduced by the modified Moiré pattern is very useful and can be used in many applications. It is accurate, fast and can be performed in minimum space for storing data. It is applicable in image recognition and it is more secure in image transmission.

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A method for dominant skeleton extraction of textures using different wavelet transforms is proposed in this paper. In the present paper 3×3 masks are used for extraction of skeleton primitives. For a 3×3 skeleton primitive there will be 29 skeleton primitive combinations. But the present paper considered a skeleton primitive for the skeletonization purpose if and only if its center pixel is one. By this, there will be 28 combinations of skeleton primitives. These skeleton primitive are used for evaluating skeleton points. The skeleton of an object has the property that it is reduced to one point when the skeleton primitive used for the skeletonization is exactly homothetic to the object. The dominant skeleton subset is evaluated by counting the skeleton points. The skeleton subset that leads to the least skeleton points will be the resultant skeleton subset. The present paper classified the textures based on two methods. In the first method textures are classified based on skeleton primitive weight, which is nothing but based on skeleton primitive combination. In the second method classification is made based on distance function of skeleton points. These two methods are applied on Brodatz textures with different wavelet transforms which resulted a good classification of textures.

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Multi-carrier code division multiple access (MC-CDMA) systems receive a great deal of attention due to their great potential in achieving high data rates in wireless communication. Nevertheless, when transmission over fading channel multi-cell interference occurs and this degrades the performance of the system. Site diversity technique is applied to the system to overcome this problem. Due to non orthogonality of spreading codes multi-cell interference is not completely eradicated. In this paper space time block code (STBC) site diversity with multiple input multiple output technique (MIMO) is proposed to improve the performance of MC-CDMA systems and is extended to differential space time block codes (DSTBC). Investigation is done with combining techniques under Rayleigh channel conditions. Simulation results shows that DSTBC outperforms STBC site diversity.

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This paper deals with the energy saving potential possible with changing in illumination schemes. The case study in an engineering institute deals with the replacement of existing conventional lighting scheme with LED lighting scheme will have huge energy saving potential, with pay back period of even less than 18 months. The LED lighting scheme provides additional advantages as cool light, decreased maintenance cost, longer life, more flexibility, easier handling
With increase in energy crisis there is a need of looking for additional energy sources or reduce in energy consumption in any form without loosing comfort. It is always preferred over energy conservation over energy generation, as energy generated is many fold energy generated. Energy audition is the new trend in the present scenario. An energy auditor can play a major role in energy saving. Energy saving potential is possible at every part of life. One of the energy saving scheme in illumination is, by using natural light and/or use of LEDs. LEDs are having major advantages of longer life & almost negligible power consumption compared to any type of illuminating source(s).

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This paper proposes and investigates the fast on-line training back propagation algorithm for feed-forward ANN. It presents an ANN based architecture suitable to identify the status of a Switched reluctance motor to minimize the torque ripple. A hardware implementation of this scheme is on the way to testify the results and implement the scheme to other SRM.

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India has emerged as an ‘IT Super power’, especially in the field of software and related services export. The paper is an attempt to discern and delineate the growth performance, challenges and opportunities of such a promising sector of Indian economy. It has been observed that software export has registered an annual compound growth rate of 45 per cent during the last decade and continues to show robust growth even today. Growing respect for Indian software industry in the international market, continued rise in the offshore services, quality services, timely delivery, entry into new markets, Y2K data conversion business, international linkages and also due to various steps taken by the Government to promote software export such as simplifying procedures, tax concessions, establishments of software technology parks, more liberal foreign investment policies, possessement of second largest pool of scientific and skilled manpower which is also English speaking, low cost of labour, locational time difference with the western world enabling round the clock development, pro-active role by Nasscom (the software industry association), etc. are some of the factors that gave fillip to the faster growth of India’s software export. Undoubtedly other developing countries can learn lessons from India’s experience and can develop IT capabilities by mutual cooperation.

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Knowledge creation has become the primary focus in advance research of knowledge management system. There are few fundamental stages one has to reach before moving comfortably into knowledge creation stage. Social learning is an essential environment in ensuring that social interactions within knowledge management system promote mutual understanding and engagement among members. We use community of practice as the social theory to analyze the advance knowledge management system so-called Communicative Social Intelligence. An analysis has shown that CSI has sufficient intelligent features to support the social learning as prescribed in community of practice.

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We present a study of the web based user navigation patterns mining and propose a novel approach for clustering of user navigation patterns. The approach is based on the graph partitioning for modeling user navigation patterns. In order to mining user navigation patterns, we establish an undirected graph based on connectivity between each pair of the web pages. Moreover, we propose novel formula for assigning weights to edges of the graph. The experimental results represent that the approach can improve the
quality of clustering for user navigation pattern in web usage mining systems. These results can be use for predicting user’s next request in the huge web sites.