Welcome to Journal of Theoretical and Applied Information Technology

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Association rule mining is to find out association rules that satisfy the predefined minimum support and confidence from a given database. End users of association rule mining tools encounter several in practice when data bases come with binary attributes. In this paper, we introduce a new measure, which does not require initially allotted weights .The quality of transactions is considered by link based models and a fast mining algorithm is adopted.

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One of the most common complaints expressed by individuals with hearing loss is the difficulty in understanding speech when listening in background noise. This paper highlights the importance of enhancement of an important acoustic attribute of clear speech -�Consonant-Vowel intensity ratio�. A case for synthetic clear speech in the context of hearing impairment was developed. Consonant recognition in noise free and noisy situations using the Nonsense syllable Test (NST) was investigated in 5 normal hearing subjects under simulated hearing-impairment. The fricative consonants of English language in CV context were being processed for consonant-vowel intensity ratio modifications from 0 to +12 dB at +3 dB step. The Speech Perception In Noise (SPIN) tests were quantified in terms of information transmission analysis measures, in the presence of white noise-masker at three noise levels,0 dB, +12 dB, and +6 dB. C/V intensity ratio modifications of +6, to +12 dBs were found to improve speech intelligibility in simulated low level sensorineural loss. A maximum intelligibility benefit of 21% points was reported for +12 dB C/V modification, also the perception of consonant place of articulation reported better improvement of intelligibility compared to consonant voicing.

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Learning Management System is a process of delivering learning process and tracking learner details. Many very good comprehensive proprietary packages are available. For in-house system, many free, open source solutions are available which can be adapted in any manner needed. This approach however, might require more initial development and different skill sets among staff to ensure the robustness of the system, to provide a higher level of on-going technical support, to prepare documentation and training, and to interface with other systems as necessary. The choice of Learning Management System is based on the needs of the course, without consideration of costs, the availability of qualified staff or any requirement to use existing systems. Content Management Plays an important role to the learner to access the content in a rapid manner.. As Content and storage increases Learning objects offer a new conceptualization of the learning process: rather than the traditional "several hour chunk", they provide smaller, self-contained, re-usable units of learning. Most institutions are less concerned about exact definitions for learning objects and more concerned about whether these objects are being used in a sound pedagogical manner. The educational strengths of a learning object for application might then include a number of characteristics, such as its granularity (can be small, manageable chunks of learning content), its reusability (can be applied to different learning objectives) and its aggregation potential (can be customized).

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Now-a-days due to high availability of computing facilities, large amount of
data in electronic form is generated. The data generated is to be analyzed so as to maximize the benefits, for intelligent decision making. If the data generated is in the structured form then a large amount of work in analyzing such structured data is available. But in case of textual data, which is also termed as unstructured data, the need to analyze such data has become inevitable. This paper attempts in exploring the methods in analyzing the unstructured data.

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Grid computing started as a project to link geographically dispersed supercomputers, but now it has grown far beyond its original intent. The Grid infrastructure can benefit many applications, including collaborative engineering, data exploration, high-throughput computing, and distributed supercomputing. Computing Grids are basically networks that pool resources -- CPU cycles, storage or data from many different machines and apply them to one complex application.
This work explores different features of a grid technology. With focus on data and application sharing on grid, a real time, University Result application that is windows-based and user-friendly was developed using VB.net deployed on an already existing test bed (the AccessGrid) and the observations in terms of Connectivity, Accessibility, Security, Flexibility, and Memory Robustness were recorded. This will enable online real time access to academic records for the purpose of assessing a candidate�s suitability for admission for higher degrees or a transfer to any other institutions in the world among other applications.
It is envisaged that this work will lead to the development of a worldwide Data Grid, enabling universities result (transcripts) sharing thus alleviating the difficulties encountered by inability to verify applicants� results for academic and other purposes.

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A computer graphics card is an additional peripheral that enhances the performance of rendered graphics. Recently, there has been an increasing interest in general purpose computation on graphics hardware. The ability to work independently alongside the CPU as a coprocessor is interesting but not motivating enough to learn how to apply problems to the graphics domain. This paper analyzes the overall architecture of the GPU and its performance.

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The Semantics-based Web Service Matching Model is proposed in this paper to improve the performance of Web Service discovery. Semantics-based Web Service Matching is a two-phase method including semantic similarity matching and qualitative filtering. Function-based semantic similarity matching used of matching algorithm in order to finding the most proper services. And also, used for selecting the best service among results of qualitative filtering.

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This paper presents a new methodology using Fuzzy and Real Coded Genetic Algorithm (RCGA) for the placement of DG units in electrical distribution systems to reduce the power losses and to improve the voltage profile. Electrical energy is vital in every aspect of day-to-day life. Keen interest is taken on all possible sources of energy from which it can be generated and this led to the encouragement of generating electrical power using renewable energy resources such as solar, tidal waves and wind energy. Due to the increasing interest on renewable sources in recent times, the studies on integration of distributed generation to the power grid have rapidly increased. The distributed generation (DG) sources are added to the network mainly to reduce the power losses by supplying a net amount of power. In order to minimize the line losses of power systems, it is equally important to define the size and location of local generation. There have been many studies, to define the optimum location of distributed generation. In this paper, Fuzzy approach is used to find the optimal locations of DG units and Real Coded Genetic Algorithm (RCGA) is used to find the optimal sizes of DG units. The suggested method is programmed under MATLAB software and is tested on 15-bus, 33-bus, 69-bus and 85-bus test systems and the results are presented

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The design of a millimeter wave n x n array antenna at 60 GHz with corporate feed network printed on the same side of the substrate is presented. The antenna is designed using transmission line model and simulated using IE3D software. Simulation and measured results were in good agreement. Analyses were carried out for 2x2, 4x4, 8x8 arrays. The gain and beam width of 8x8 microstrip array is 18.48 dBi and 10.49 deg. The 10 dB return loss bandwidth spans from 59 GHz to about 61 GHz. The proposed array can be integrated with the existing MMIC�s or wireless equipment with suitable selection of the substrate.

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Frequent pattern mining is one of the active research themes in data mining. It plays an important role in all data mining tasks such as clustering, classification, prediction, and association analysis. Identifying all frequent patterns is the most time consuming process due to a massive number of patterns generated. A reasonable solution is identifying maximal frequent patterns which form the smallest representative set of patterns to generate all frequent patterns. In this paper, an efficient numerical method for mining frequent patterns is proposed. This method is based on prime number characteristics to generate all frequent patterns by using maximal frequent ones. There are two new properties introduced in this method; a novel tree structure called PC_Tree and PC_Miner algorithm. The PC_Tree is a simple tree structure but yet capable to capture the whole of transactions information with an efficient data transformation technique that utilizes the prime number theory. The PC_Miner algorithm traverses the PC_Tree by using an efficient pruning technique. The experimental results verify the compactness and the efficiency of mining shown by the proposed method.