Archives of Information Science and Technology

Archives of Information Science and Technology

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Table of Content: Volume 1, Issue 1

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Research Article Pages 20-41

Applying Deep Learning Techniques for Big Data Analytics: A Systematic Literature Review

Authors: Memudu Tunde Muhammed, Obidallah Waeal J and Raahemi Bijan

Abstract: Data are being generated from numerous sources and applications and are thereby becoming increasingly complex. The increase in the use of technologies-such as phones, machines, vehicles, sports activities, and academic activities to carry out social and economic functions has also led to various forms of data being generated. The complexity, velocity, versatility, and volume of these data have introduced "big data", which is also called "large data". Because big data analysis is becoming a challenge to the exponential growth of data, deep learning, which is an aspect of machine learning, is considered a method of analyzing big data due to its use of excellent and advanced classification techniques and the hierarchical layer techniques. In this paper, we analyze how deep learning techniques and algorithms have been applied to big data, the types of datasets, the algorithms used, and the trend toward this area of study.

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Original Research Pages 10-19

Multidimensional Chaotic Dynamics and Entropies

Authors: Arturo Tozzi, James F Peters, Colin James III and Eva Deli

Abstract: The possible presence of further dimensions hidden in our three-dimensional-plus time world might help to elucidate countless physical and biological systems’ behaviors, from quantum entanglement to brain function.

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Research Article Pages 1-9

Exploration of Multiscale Geometric Analysis for Enhancement and Structure Detection in MRCP Images

Authors: Rajasvaran Logeswaran

Abstract: Magnetic Resonance Cholangiopancreatography (MRCP) images are used in the diagnosis and treatment planning of the bile ducts and the liver. The ability to diagnose and treat such diseases in recent times has increased with greater importance placed on the effective use of non-invasive medical imaging. However, MRCP images are often noisy (low signal-to-noise ratio) and suffer from the influence of artifacts, partial volume and large inter-image variations.

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