Informatics Publishing Limited

Vishakha Agarwal ¹, Akhilesh Tiwari ¹

Affiliations
1 Dept. of CSE & IT, Madhav Institute of Technology and Science, Gwalior, IN

Abstract

Data management has always been a serious issue. The rate at which the data is growing at every time instance, each small and big organization has to incorporate proper repositories and management systems within their organizations to handle such data. New kinds of repositories are being introduced as the demand of analysis of data is generated. Data warehouses are capable to store huge data in multidimensional way and analysis can also be performed over it. But due to certain challenges, this repository is also not the best solution to the problem. To deal with this issue, the concept of pattern warehouses is being introduced. This paper reveals the journey of the management aspect of data from data warehouse to pattern warehouse.

Keywords

Data Management, Data Mining, Data Warehouse, Patterns, Pattern Warehouse.

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Jagrat Gupta ¹, Akhilesh Tiwari ¹

Affiliations
1 Department of Computer Science and Engineering, Madhav Institute of Technology & Science, Gwalior, IN

Abstract

Profitable pattern mining is a captivating research area that accentuates to adjudicate the business objectives. One of the most prominent and unaddressed business objectives regarding this discussion is Profit. The research problem as well as the prominent objective behind this research paper is to extract profitable rules accurately, efficiently as well as in optimized manner. To accomplish the above objective, incorporation of rough set theory followed by conventional association rule mining algorithm and genetic based optimization is used in optimized and efficient manner. The proposed model overcomes the major findings to make model more beneficial for any business organization in the current scenario.

Keywords

Association Rules, Data Mining, Genetic Algorithm, Market Basket Analysis, Profitable Pattern Mining (PPM), Rough Set Theory (RST).

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Shraddha Pandit ¹, Piyush Kumar Shukla ¹, Akhilesh Tiwari ²

Affiliations
1 Department of Computer Science & Engineering, UIT RGPV, Bhopal, IN
2 MITS, Gwalior, IN

Abstract

Transform based function play vital role in video compression. In this paper used two transform functions for video compression one is discrete wavelet transform function and other is fractal transform function. The discrete wavelet transform function is very promising image compression technique. Instead of discrete wavelet transform fractal transform is fast image compression technique. Here both wavelet transform function and fractal transform function used for video compression. The H-V partition technique is used for fast processing of video data in terms of row and column. The process of compressing produce good PSNR value and the compression ratio instead of DWT transform function. The DWT transform function creates group of frames in terms of layer for the processing of lower and higher band data of process video. The major contribution of H-V partition technique in video compression due to represents of domain and range blocks for the processing of video components. The processing of transform generates the similarity property of range and the compression process is fast. The both methods DWT and H-V partition techniques simulated in MATLAB software and measure some standard parameter such as PSNR, Compression ratio, encoding time, and MSE.

Keywords

Video Compression, DWT, Fractal Transform, H-V Partitioning, MATLAB, MSE.

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