Data Structures and Algorithms

1510 Submissions

[6] viXra:1510.0487 [pdf] submitted on 2015-10-28 20:24:58

Secure Data Compression using Chaotic Images

Authors: Sai Venkatesh Balasubramanian
Comments: 10 Pages.

A Chaos based embedding process for textual data offering high capacity and high security simultaneously is designed and implemented. A chaotic image, obtained using a frequency dependant driven chaotic system is used as the data carrier in which textual data is embedded. The decryption and subsequent performance analyses reveal a high fidelity with a mean square error of around 0.0009 percent and a compression ratio increasing nonlinearly with text size, with ratio values more than 150:1 obtained for significantly large texts. Moreover, a very high level of security leading to up to 60 percent of mean square error values even for 1 percent misalignment in the decryption process is observed. The extreme simplicity of implementation coupled with the twin advantages of high compression ratios and high security forms the highlight of the present work.
Category: Data Structures and Algorithms

[5] viXra:1510.0478 [pdf] submitted on 2015-10-28 20:36:00

Genome Data Compression using Digital Chaos

Authors: Sai Venkatesh Balasubramanian
Comments: 7 Pages.

Efficient techniques of Genome Data handling and storage are the need of the hour in the present genetic engineering era. The present work purports to the design and implementation of a Genome Sequence Data Compression Technique without the use of references and lookup. This is achieved by first generating a digital chaotic bit stream, formed by performing XOR operations on three square waves with mismatched frequencies. The generated bit stream is XORed with the Genome Sequence bit stream after necessary data conditioning, and the result is stored as a 2D array (image). The png format is chosen, owing to its inherent lossless properties. It is seen that the perfectly reversible operations of compression and decompression result in compression ratios of around 2.6-3.5 being achieved with absolute zero error. The use of digital chaos provides an additional layer of security, since the frequencies of the input square wave signals form a secure key, which when mismatched during decompression even by 1 percent, can result in error rates of upto 60 percent.
Category: Data Structures and Algorithms

[4] viXra:1510.0473 [pdf] replaced on 2016-06-15 06:17:06

A Still Simpler Way of Introducing Interior-Point Method for Linear Programming

Authors: Kurt Mehlhorn, Sanjeev Saxena
Comments: 18 Pages.

Linear programming is now included in algorithm undergraduate and postgraduate courses for computer science majors. We give a self-contained treatment of an interior-point method which is particularly tailored to the typical mathematical background of CS students. In particular, only limited knowledge of linear algebra and calculus is assumed.
Category: Data Structures and Algorithms

[3] viXra:1510.0417 [pdf] submitted on 2015-10-27 09:23:57

A Secure Technique for Data Compression and Supercompression using Frequency Dependent Chaos

Authors: Sai Venkatesh Balasubramanian
Comments: 15 Pages.

A Chaos based compression technique offering high capacity and high security simultaneously is designed and implemented. A chaotic image, obtained by reshaping the signal representing a frequency dependant driven chaotic system is used as the data carrier in which data from the file to be compressed is embedded. Implementation of the algorithm is carried out in MATLAB and Python platforms for various filetypes such as txt, png, pdf, mp3, 3gp and rar formats. A comparative performance analysis reveals a high fidelity with a mean square errors of less than 0.0009 percent as well as a relatively high compression ratio value of 5-6. A very high level of security leading to up to 60 percent of mean square error values even for 1 percent misalignment in the decryption process is observed. The execution times for the implementations are obtained reasonably at around 5 seconds. A new compression technique, termed ‘supercompression’ consisting of repeated application of the compression technique is proposed. A proof-of-concept implementation achieved extremely high compression ratios of around 40000. The extreme simplicity of implementation coupled with the twin advantages of high compression ratios and high security forms the highlight of the present work.
Category: Data Structures and Algorithms

[2] viXra:1510.0360 [pdf] submitted on 2015-10-23 09:24:11

Transformation Through Information – Secure Big Data for Men and Machines

Authors: Sai Venkatesh Balasubramanian, T. Venkata Subba Reddy, B. Madhava Reddy
Comments: 14 Pages.

The current era of data explosion entails the necessity of high efficiency in terms of data capacity and data security. This scenario of Big Data inevitably leads to the technology of Internet of Things (IoT) in the future. The present project purports to the effective harnessing of nonlinear signal processing principles leading to enhanced security of data without compromising on capacity. The advantage of using nonlinear signal processing lies in the fact that the nonlinearity of a single NMOS transistor is able to provide robust security by generation of chaotic signals. This results in low power dissipation and simplicity of circuitry. The enhanced secure communication techniques are then studied giving importance to the phase variations in the signal and are then applied to real world information systems. Also, the possibility of introducing such techniques in conventional big data systems such as RDBMS and Hadoop are considered. After significantly demonstrating the capabilities of the nonlinear signal processing approach in terms of fidelity, capacity and robustness, the techniques are extended even further to include an Internet of Things (IoT) based environment. The implementation of nonlinear signal processing techniques to IoT based systems such as RFID are explored. At the final stage, the change in the managerial perspective required to handle the IoT dominated environment is discussed. The business level implications of such a technology shift are studied. This study of IoT is termed as “Management of Things” (MoT). The principal aim of this project is to provide a feasible, efficient, innovative yet costeffective solution to the biggest problems of the telecommunication world today – data capacity and data security. This project thus follows from the motto “Transformation through Information” and leads us gently to become effective citizens of a smarter planet.
Category: Data Structures and Algorithms

[1] viXra:1510.0325 [pdf] replaced on 2016-09-26 07:00:37

Multi-label Methods for Prediction with Sequential Data

Authors: Jesse Read, Luca Martino Jaakko Hollmén
Comments: 29 Pages. (accepted: to appear) Pattern Recognition

The number of methods available for classification of multi-label data has increased rapidly over recent years, yet relatively few links have been made with the related task of classification of sequential data. If labels indices are considered as time indices, the problems can often be seen as equivalent. In this paper we detect and elaborate on connections between multi-label methods and Markovian models, and study the suitability of multi-label methods for prediction in sequential data. From this study we draw upon the most suitable techniques from the area and develop two novel competitive approaches which can be applied to either kind of data. We carry out an empirical evaluation investigating performance on real-world sequential-prediction tasks: electricity demand, and route prediction. As well as showing that several popular multi-label algorithms are in fact easily applicable to sequencing tasks, our novel approaches, which benefit from a unified view of these areas, prove very competitive against established methods.
Category: Data Structures and Algorithms