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Articles 1 - 8 of 8
Full-Text Articles in Social and Behavioral Sciences
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
Nagesh Shukla
No abstract provided.
Identity Awareness And Re-Use Of Research Data In Veillance And Social Computing, Alexander Hayes, Stephen Mann, Amir Aryani, Susannah Sabine, Leigh Blackall, Pia Waugh, Stephan Ridgway
Identity Awareness And Re-Use Of Research Data In Veillance And Social Computing, Alexander Hayes, Stephen Mann, Amir Aryani, Susannah Sabine, Leigh Blackall, Pia Waugh, Stephan Ridgway
Alexander Hayes Mr.
Identity awareness of research data has been introduced as a requirement for open research, transparency and reusability of research data in the context of eScience. This requirement includes the capability of linking research data to researchers, research projects and publications, and identifying the license for the data. This connectivity between research data and other elements in research ecosystems is required in order to make the data available and reusable beyond the initial research. In this paper, we examine these capabilities in the domains of veillance and social computing. The dataset cases presented in this paper articulate the challenges that researchers …
A Comparative Analysis Of Multichannel Data Acquisition Systems For Quality Assurance In External Beam Radiation Therapy, Iolanda Fuduli, Claudiu Porumb, Anthony Espinoza, Abdullah Aldosari, Martin Carolan, Michael Lf Lerch, Peter E. Metcalfe, Anatoly Rosenfeld, Marco Petasecca
A Comparative Analysis Of Multichannel Data Acquisition Systems For Quality Assurance In External Beam Radiation Therapy, Iolanda Fuduli, Claudiu Porumb, Anthony Espinoza, Abdullah Aldosari, Martin Carolan, Michael Lf Lerch, Peter E. Metcalfe, Anatoly Rosenfeld, Marco Petasecca
Anthony A Espinoza Mr
The paper presents a comparative study performed by the Centre of Medical Radiation Physics (CMRP) on three multichannel Data Acquisition Systems (DAQ) based on different analogue front-ends to suit a wide range of radiotherapy applications. The three front-ends are: a charge-to-frequency converter developed by INFN Torino, an electrometer and a charge-to-digital converter (both commercial devices from Texas Instruments). For the first two (named DAQ A and B), the CMRP has designed the read-out systems whilst the third one (DAQ C) comes with its own evaluation board. For the purpose of the characterization DAQ A and DAQ B have been equipped …
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 …