Welcome to Journal of Theoretical and Applied Information Technology

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The increasing need for information dissemination and the tremendous population growth in today’s organizations calls for the need to migrate most application and their associated data to the network where several millions of people can access concurrently. Several challenges such as security risk and management/maintenance of the database have been posed to such system that operates on the network. In this research paper we have been able to determine some functionality that can be incorporated into a database management system that operates in an open network system environment. These functionalities include: application of open password for open database system, creation of register database, creation and monitoring of activity log file, creation of privacy lock on schema and application of a locking control on file. To demonstrate this, a system was designed using the student arm of the University of Agriculture Abeokuta as a case study. In designing the system, C# as the host programming language was used in designing the front-end while Microsoft SQL Server 2005 was used for the back-end design. With the introduction of these five functionalities, open database is secured to be used by the desired users.

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This paper presents the optimal fuzzy controller design for load frequency control (LFC) of two area power system using Adaptive Particle Swarm Optimization (APSO). Firstly, the controller is designed according to Fuzzy Logic rules such that the systems are fundamentally robust. Secondly, the Fuzzy Logic controller (FLC) used earlier was optimized with PSO so as to obtain optimal adjustment of the membership functions only. Finally, the FLC is completely optimized by Swarm Intelligence Algorithms. Digital simulation results demonstrate that in comparison with the FLC, the designed FLC-APSO speed controller gives better dynamic performance of the LFC, as well as without any overshoot. The proposed controller is compared against other controllers. The results show that the proposed controller outperforms other schemes.

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Functional prediction of human hypothetical proteins remains a major project for biologist to carry out their further research in various life science and healthcare segments. Human chromosome 1 is the one which is very largest and has many hypothetical proteins. So it is attempted to find the function of some of the human chromosome 1 hypothetical proteins, the proteins are clustered based on their sequence similarities and identify the consensus sequence in those proteins. Using various prediction methods their functional annotations are carried out and a domain was predicted which is involved in the pathogenic functionality.

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In many applications, different kinds of moments have been utilized to classify images and object shapes. Moments are important features used in recognition of different types of images. In this paper, three kinds of moments: Geometrical, Zernike and Legendre Moments have been evaluated for classifying 3D object images using Nearest Neighbor classifier. Experiments are conducted using ETH-80 database, which contains 80 objects.

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Human Xq22.1 is a genomic region, which has 20 mammalian rapidly evolving genes and involved in numerous genetic diseases such as XLMR, Fabry disease, pre mature ovarian failure, cancer etc. Many complex diseases may arise from quantitative, rather than qualitative differences in the gene products. Review, characterization and statistical analysis is performed on protein coding genes in human genomic region, Xq22.1. The analysis is based on literature review, molecular weight, molecular class, biological process, gene localization, gene expression, splicing events and mutational study. Role in biological processes, cellular component and molecular class of most of the genes in human genome Xq22.1 is unknown. Tracing the specific genes will help us in understanding the genetics of human disease associated with Xq22.1. Study on splicing events and SNP studies revealed interesting results on APG4A, the gene responsible for autophagy.

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This paper discusses an Artificial Neural Network (ANN) based method for reducing the torque ripple in a Doubly Fed Induction machine (DFIM) in which Direct Torque Control (DTC) scheme is applied. DFIM is gaining popularity as the best alternative for wind energy generation system. Often, wind energy generation demands good torque dynamic performance. ANN is used here to give pulses to the inverter in place of the conventional DTC scheme. The proposed method gives reduced torque ripple as compared to conventional DTC scheme.

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This document describes how Low Cost HF (13.56 MHz) antennas can be built and tuned so that their characteristics match the requirements of the high performance reader and third party RF modules. This third edition places greater emphasis on antennas for the higher power readers. In general, the distance at which a Tag-it™ transponder inlay (tag) can be read is related to the size of the Reader's antenna system and its associated magnetic field strength, the larger the antenna, the greater the range. Depending on the type and make of the long range RFID reader, more gate pedestals can be configured and integrated to a single reader. For a three pedestal gate, its antenna pedestals are spaced at up to 1.2 meter apart. Optionally, each gate pedestal can be equipped with a flasher light

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Handwriting recognition has always been a challenging task in image processing and pattern recognition. There are five major stages in the handwritten character recognition problem: Image processing, segmentation, feature extraction, training and recognition, and preprocessing. India is a multi-lingual multi-script country, where eighteen official scripts are accepted and there are over a hundred regional languages. In this paper we propose a zone-based feature extraction algorithm scheme for the recognition of off-line handwritten numerals of four popular Indian scripts. The character centroid is computed and the character/numeral image (50x50) is further divided into 25 equal zones (10x10). The average distance from the character centroid to the pixels present in the zone column, is computed. This procedure is sequentially repeated for all the zone/grid/box columns present in the zone (10 features). Similarly, the average distance from the character centroid to the pixels present in the zone row is computed. This procedure is sequentially repeated for all the zone rows present in the zone (10 features). There could be some zone column/row that is empty of foreground pixels; then the feature value of that zone column/row in the feature vector is zero. This procedure is sequentially repeated for the entire zone present in the numeral image. Finally, 500 such features are extracted for classification and recognition. The nearest neighbor, feed forward back propagation neural network and support vector machine classifiers are used for subsequent classification and recognition purposes. We obtained a recognition rate of 98.65 % for Kannada numerals, 96.1 % for Tamil numerals, 98.6 % for Telugu numerals and 96.5 % for Malayalam numerals using the support vector machine.

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In this paper, we present a novel high bit rate LSB audio watermarking method that reduces embedding distortion of the host audio. Using the proposed two-step algorithm, watermark bits are embedded into higher LSB layers, resulting in increased robustness against noise addition. In addition, listening tests showed that perceptual quality of watermarked audio is higher in the case of the proposed method than in the standard LSB method. Conventionally, a perceptual limit of three bits per sample is imposed to the basic LSB audio steganography method. The proposed algorithm makes use of minimum error replacement method for LSB adjustment and modified error diffusion method for decreasing SNR value. Subjective listening test proved that high perceptual transparency is accomplished even if four LSBs of host audio signal are used for data hiding. Using the proposed two-step algorithm, hidden bits are embedded into the higher LSB layers, resulting in increased robustness against noise addition. In addition, listening tests showed that perceptual quality of watermarked audio is higher in the case of rite proposed method than the perceptual quality obtained using the standard LSB method. We present a novel high bit rate LSB audio watermarking method. The basic idea of the proposed LSB algorithm is watermark embedding that causes minimal embedding distortion of the host audio.

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Pictures are frequently used as visuals in education to facilitate learning. Pictures should be used in line with their purposes in order to support learning. Mayer classifies pictures as decorative, representational, organizational and explanative pictures with respect to their purpose of use. Among these, decorative pictures and representational pictures are reported not to serve the instructional purpose, while organizational pictures and explanative pictures are claimed to support the transfer of instructional messages. In the present study, the pictures found in the student workbook of fifth grade elementary school students in the course of Information Technologies were examined in terms of their purpose of use in line with expert views. According to the results obtained at the end of the study, it was concluded that the pictures found in the student workbook do not serve the instructional purpose.