Search results for "Big data"
showing 10 items of 311 documents
sPlotOpen – An environmentally balanced, open‐access, global dataset of vegetation plots
2021
Datos disponibles en https://github.com/fmsabatini/sPlotOpen_Code
Individual-Based Tracking Systems in Ornithology: Welcome to the Era of Big Data
2016
Technological innovations have led to exciting fast-moving developments in science. Today, we are living in a technology-driven era of biological discovery. Consequently, tracking technologies have facilitated dramatic advances in the fundamental understanding of ecology and animal behaviour. Major technological improvements, such as the development of GPS dataloggers, geolocators and other bio-logging technologies, provide a volume of data that were hitherto unconceivable. Hence we can claim that ornithology has entered the era of big data. In this paper, which is particularly addressed to undergraduate students and starting researchers in the emerging field of movement ecology, I summaris…
TOWARDS SMART MANUFACTURING WITH VIRTUAL FACTORY AND DATA ANALYTICS
2017
International audience; Virtual factory models can help improve manufacturing decision making when augmented with data analytics applications. Virtual factory models provide the capability of simulating real factories and generating realistic data streams at the desired level of resolution. Deeper insights can be gained and underlying relationships quantified by channeling the simulation output data to an external analytics tool. This paper describes integration of a virtual factory prototype with a neural network analytics application. The combined capability is used to create a neural network capable of predicting the expected cycle times for a small job shop. The capability can adapt by …
Big Data in operations and supply chain management: a systematic literature review and future research agenda
2021
In the era of digitalisation, the role of Big Data is proliferating, receiving considerable attention in all sectors and domains. The domain of operations and supply chain management (OSCM) is no different since it offers multiple opportunities to generate a large magnitude of data in real-time. Such extensive opportunities for data generation have attracted academics and practitioners alike who are eager to tap different elements of Big Data application in OSCM. Despite the richness of prior studies, there is limited research that extensively reviews the extant findings to present an overview of the different facets of this area. The current study addresses this gap by conducting a systema…
Opportunities for the Use of Business Data Analysis Technologies
2016
Abstract The paper analyses the business data analysis technologies, provides their classification and considers relevant terminology. The feasibility of business data analysis technologies handling big data sources is overviewed. The paper shows the results of examination of the online big data source analytics technologies, data mining and predictive modelling technologies and their trends.
Industry 4.0 Technologies for Manufacturing Sustainability: A Systematic Review and Future Research Directions
2021
Recent developments in manufacturing processes and automation have led to the new industrial revolution termed “Industry 4.0”. Industry 4.0 can be considered as a broad domain which includes: data management, manufacturing competitiveness, production processes and efficiency. The term Industry 4.0 includes a variety of key enabling technologies i.e., cyber physical systems, Internet of Things, artificial intelligence, big data analytics and digital twins which can be considered as the major contributors to automated and digital manufacturing environments. Sustainability can be considered as the core of business strategy which is highlighted in the United Nations (UN) Sustainability 2030 age…
Towards Shipping 4.0. A preliminary gap analysis
2020
Abstract The paradigm of Industry 4.0 involves a substantial innovation to the value creation approach thought the supply chain and the application of digital enabling technologies like the Internet of Things (IoT), Big Data Analytics (BDA) and cloud computing. The fourth industrial revolution is thus expected to have a disruptive impact on maritime transport and shipping sectors, where smart ships and autonomous vessels well be part of a new and fully interconnected maritime ecosystem. Specific hardware components, such as sensors, actuators, or processors will be embedded in the ship’s key systems in order to provide valuable information to increase the efficiency, sustainability and safe…
Recentrifuge: Robust comparative analysis and contamination removal for metagenomics
2017
Metagenomic sequencing is becoming widespread in biomedical and environmental research, and the pace is increasing even more thanks to nanopore sequencing. With a rising number of samples and data per sample, the challenge of efficiently comparing results within a specimen and between specimens arises. Reagents, laboratory, and host related contaminants complicate such analysis. Contamination is particularly critical in low microbial biomass body sites and environments, where it can comprise most of a sample if not all. Recentrifuge implements a robust method for the removal of negative-control and crossover taxa from the rest of samples. With Recentrifuge, researchers can analyze results f…
Innovation in cardiovascular disease in Europe with focus on arrhythmias: current status, opportunities, roadblocks, and the role of multiple stakeho…
2018
The European Heart Rhythm Association (EHRA) held an Innovation Forum in February 2016, to consider issues around innovation. The objective of the forum was to extend the innovation debate outside of the narrow world of arrhythmia specialists and cardiology in general, and seek input from all stakeholders including regulators, strategists, technologists, industry, academia, health providers, medical societies, payers, and patients. Innovation is indispensable for a continuing improvement in health care, preferably at higher efficacy and lower costs. It requires people who have been trained in a good scientific environment, high-quality research for achieving ground breaking inventions and t…
Making sense of big data in health research: {T}owards an {EU} action plan
2016
Genome medicine 8(1), 71 (2016). doi:10.1186/s13073-016-0323-y