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Annals of Data Science OnlineFirst articles

23.03.2017

Three Decades of Business Activity Evolution in Curitiba: A Case Study

Recent concepts such as Smart Cities, Urban Computing, and Geographic Information Systems are being discussed in various international forums, using themes such as sustainability and efficient use of the city infrastructures. One important aspect …

20.03.2017 Open Access

Modeling Determinants of Time-To-Death in Premature Infants Admitted to Neonatal Intensive Care Unit in Jimma University Specialized Hospital

Preterm birth is the term used to define births that occur before 37 completed weeks or 259 days of gestation. The aim of this study is to model survival probability of premature infants who were under follow-up and identify significant risk …

13.03.2017

A New Family of Distributions: The Additive Modified Weibull Odd Log-logistic-G Poisson Family, Properties and Applications

In this paper, a new family of distributions, called the additive modified Weibull odd log-logistic-G Poisson distribution, is proposed and studied. Some mathematical properties are presented and special models are discussed. We derive a power …

11.03.2017

A Rough Based Hybrid Binary PSO Algorithm for Flat Feature Selection and Classification in Gene Expression Data

Feature selection in high dimensional data, particularly, in gene expression data, is one of the challenging task in bioinformatics due to the curse of dimensionality, data redundancy and noise values. In gene expression data, insignificant …

10.03.2017

Influencing Factors of Online P2P Lending Success Rate in China

The low success rate of lending is the main drawback of development of online P2P lending platforms in China. Based on the theory of social capital, this study analysed the influence factors of success rate of P2P lending platform in China, using …

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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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