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Annals of Data Science OnlineFirst articles

17.11.2017

Research and Application of GPS Trajectory Data Visualization

Taxi trajectory data is a kind of massive traffic data with spatial–temporal dimensions, and plays a key role in traffic management, travel analysis and route recommendation for residents. Analyzing trajectory data with traditional methods is …

14.11.2017

The Improved EWMA Chart for Heteroscedasticity Process

It is doubtful of the validity of the EWMA chart that the observations from heteroscedasticity processes violate the assumption of identical distribution. In this paper, we discuss the effect of heteroscedasticity on the performance of the …

06.09.2017

Equalization and Carrier Frequency Offset Compensation for Underwater Acoustic OFDM Systems

Due to noise enhancement, conventional Zero Forcing (ZF) equalizers are not suitable for wireless Underwater Acoustic (UWA) Orthogonal Frequency Division Multiplexing (OFDM) communication systems. Furthermore, these systems suffer from increasing …

17.08.2017

Exponentiated Generalized Kumaraswamy Distribution with Applications

In this article, we introduced and studied exponentiated generalized Kumaraswamy distribution. We derived mathematical properties including quantile function, moment generating function, ordinary moments, probability weighted moments, incomplete …

01.08.2017

Big Data and Causality

Causality analysis continues to remain one of the fundamental research questions and the ultimate objective for a tremendous amount of scientific studies. In line with the rapid progress of science and technology, the age of big data has …

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Annals of Data Science (AODS) is a new academic journal focusing on Big Data analytics and applications. It not only promotes how to use interdisciplinary techniques, including statistics, artificial intelligence and optimization, to process Big Data and conduct data mining, but also how to use the knowledge gleaned from Big Data for real-life applications. AODS accepts high-quality contributions on the foundations of data science, technical papers on various challenging problems in Big Data and meaningful case studies concerning business analytics in the context of Big Data.

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