Big data: From beginning to future

I Yaqoob, IAT Hashem, A Gani, S Mokhtar… - International Journal of …, 2016 - Elsevier
Big data is a potential research area receiving considerable attention from academia and IT
communities. In the digital world, the amounts of data generated and stored have expanded …

Big data: challenges, opportunities, and realities

AK Bhadani, D Jothimani - Effective big data management and …, 2016 - igi-global.com
With the advent of Internet of Things (IoT) and Web 2.0 technologies, there has been a
tremendous growth in the amount of data generated. This chapter emphasizes on the need …

Joint analysis of eco-efficiency and eco-innovation with common weights in two-stage network DEA: A big data approach

RK Mavi, RF Saen, M Goh - Technological Forecasting and Social Change, 2019 - Elsevier
The joint investigation of economic growth and environmental impact has led research to
develop evaluation models on environmental and economic changes, especially on eco …

Food recognition using statistics of pairwise local features

S Yang, M Chen, D Pomerleau… - 2010 IEEE computer …, 2010 - ieeexplore.ieee.org
Food recognition is difficult because food items are de-formable objects that exhibit
significant variations in appearance. We believe the key to recognizing food is to exploit the …

Performance evaluation of an independent time optimized infrastructure for big data analytics that maintains symmetry

S Vats, BB Sagar, K Singh, A Ahmadian, BA Pansera - Symmetry, 2020 - mdpi.com
Traditional data analytics tools are designed to deal with the asymmetrical type of data ie,
structured, semi-structured, and unstructured. The diverse behavior of data produced by …

Evaluation on China's forestry resources efficiency based on big data

L Li, T Hao, T Chi - Journal of Cleaner Production, 2017 - Elsevier
The development of China's forestry resources has never been more challenging due to
serious problems such as shortage, inferiority and uneven distribution of forestry resources …

Elastic extreme learning machine for big data classification

J Xin, Z Wang, L Qu, G Wang - Neurocomputing, 2015 - Elsevier
Abstract Extreme Learning Machine (ELM) and its variants have been widely used for many
applications due to its fast convergence and good generalization performance. Though the …

Real-time distributed architecture for remote acoustic elderly monitoring in residential-scale ambient assisted living scenarios

J Navarro, E Vidaña-Vila, RM Alsina-Pagès, M Hervás - Sensors, 2018 - mdpi.com
Ambient Assisted Living (AAL) has become a powerful alternative to improving the life
quality of elderly and partially dependent people in their own living environments. In this …

[PDF][PDF] A study of the determinants affecting adoption of big data using integrated Technology Acceptance Model (TAM) and diffusion of innovation (DOI) in Malaysia

KWK Soon, CA Lee, P Boursier - International journal of applied …, 2016 - researchgate.net
Large private companies had shown interest in adopting big data technologies. The review
of literature and report from international industry analyst were being analyzed on the trends …

The impact of intention of use on the success of big data adoption via organization readiness factor

A Haddad, AA Ameen, M Mukred - International Journal of …, 2018 - ejournal.lucp.net
Big data is one of the most contemporary issues. It is innovative processing solutions for a
variety of new and existing data to provide real business benefits. Unless it is tied to …