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Social and Behavioral Sciences Commons™
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Articles 1 - 5 of 5
Full-Text Articles in Social and Behavioral Sciences
Vivambc: Estimating Viral Sequence Variation In Complex Populations From Illumina Deep-Sequencing Data Using Model-Based Clustering, Bie M. P Verbist, Lieven Clement, Joke Reumers, Kim Thys, Alexander Vapirev, Willem Talloen, Yves Wetzels, Joris Meys, Jeroen Aerssens, Luc Bijnens, Olivier Thas
Vivambc: Estimating Viral Sequence Variation In Complex Populations From Illumina Deep-Sequencing Data Using Model-Based Clustering, Bie M. P Verbist, Lieven Clement, Joke Reumers, Kim Thys, Alexander Vapirev, Willem Talloen, Yves Wetzels, Joris Meys, Jeroen Aerssens, Luc Bijnens, Olivier Thas
Faculty of Engineering and Information Sciences - Papers: Part A
Background: Deep-sequencing allows for an in-depth characterization of sequence variation in complex populations. However, technology associated errors may impede a powerful assessment of low-frequency mutations. Fortunately, base calls are complemented with quality scores which are derived from a quadruplet of intensities, one channel for each nucleotide type for Illumina sequencing. The highest intensity of the four channels determines the base that is called. Mismatch bases can often be corrected by the second best base, i.e. the base with the second highest intensity in the quadruplet. A virus variant model-based clustering method, ViVaMBC, is presented that explores quality scores and second …
Recent Advances In Security And Privacy In Big Data, Yong Yu, Yi Mu, Giuseppe Ateniese
Recent Advances In Security And Privacy In Big Data, Yong Yu, Yi Mu, Giuseppe Ateniese
Faculty of Engineering and Information Sciences - Papers: Part A
Big data has become an important topic in science, engineering, medicine, healthcare, finance, business and ultimately society itself. Big data refers to the massive amount of digital information stored or transmitted in computer systems. Approximately, 2.5 quintillion bytes of data are created every day. Almost 90% of data in the world today are created in the last two years alone. Security and privacy issues becomes more critical due to large volumes and variety, due to data hosted in large-scale cloud infrastructures, diversity of data sources and formats, streaming nature of data acquisition and high volume inter-cloud migration. In large-scale cloud …
Tour-Based Travel Mode Choice Estimation Based On Data Mining And Fuzzy Techniques, Nagesh Shukla, Jun Ma, Rohan Wickramasuriya, Nam N. Huynh, Pascal Perez
Tour-Based Travel Mode Choice Estimation Based On Data Mining And Fuzzy Techniques, Nagesh Shukla, Jun Ma, Rohan Wickramasuriya, Nam N. Huynh, Pascal Perez
Faculty of Engineering and Information Sciences - Papers: Part A
No abstract provided.
Searchable Atribute-Based Mechanism With Efficiient Data Sharing For Secure Cloud Storage, Kaitai Liang, Willy Susilo
Searchable Atribute-Based Mechanism With Efficiient Data Sharing For Secure Cloud Storage, Kaitai Liang, Willy Susilo
Faculty of Engineering and Information Sciences - Papers: Part A
To date, the growth of electronic personal data leads to a trend that data owners prefer to remotely outsource their data to clouds for the enjoyment of the high-quality retrieval and storage service without worrying the burden of local data management and maintenance. However, secure share and search for the outsourced data is a formidable task, which may easily incur the leakage of sensitive personal information. Efficient data sharing and searching with security is of critical importance. This paper, for the first time, proposes a searchable attribute-based proxy re-encryption system. When compared to existing systems only supporting either searchable attribute-based …
Arcgis V.10 Landslide Susceptibility Data Mining Add-In Tool Integrating Data Mining And Gis Techniques To Model Landslide Susceptibility, Darshika Palamakumbure, David Stirling, Phillip N. Flentje, Robin N. Chowdhury
Arcgis V.10 Landslide Susceptibility Data Mining Add-In Tool Integrating Data Mining And Gis Techniques To Model Landslide Susceptibility, Darshika Palamakumbure, David Stirling, Phillip N. Flentje, Robin N. Chowdhury
Faculty of Engineering and Information Sciences - Papers: Part A
Landslide susceptibility modeling is an essential early step towards managing landslide risk. A minimum of $4.8 million is lost due to landslide related damages every year in Illawara region of Australia. At present, Data mining and knowledge discovery techniques are becoming popular in building landslide susceptibility models due to their enhanced predictive performances. Until now, the lack of tools to undertake data extraction and making the predictions have limited the applicability of this novel technique in landslide model building. This paper discusses the development of the LSDM (Landslide Susceptibility Data Mining) toolbar which was designed to utilize machine learning techniques …