Search results for "Data Science"

showing 10 items of 495 documents

An Ontology-Based Approach for the Reconstruction and Analysis of Digital Incidents Timelines

2015

International audience; Due to the democratisation of new technologies, computer forensics investigators have to deal with volumes of data which are becoming increasingly large and heterogeneous. Indeed, in a single machine, hundred of events occur per minute, produced and logged by the operating system and various software. Therefore, the identification of evidence, and more generally, the reconstruction of past events is a tedious and time-consuming task for the investigators. Our work aims at reconstructing and analysing automatically the events related to a digital incident, while respecting legal requirements. To tackle those three main problems (volume, heterogeneity and legal require…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-WB] Computer Science [cs]/WebComputer scienceOntology PopulationDigital forensics[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH][ INFO.INFO-WB ] Computer Science [cs]/Web02 engineering and technologyEvent ReconstructionOntology (information science)[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]SoftwareKnowledge extraction[INFO.INFO-CY]Computer Science [cs]/Computers and Society [cs.CY]020204 information systemsForensic OntologyTimeline Analysis0202 electrical engineering electronic engineering information engineering[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]Event reconstructionKnowledge Extractionbusiness.industry[INFO.INFO-WB]Computer Science [cs]/WebTimelineComputer forensicsData scienceComputer Science Applications[ INFO.INFO-CY ] Computer Science [cs]/Computers and Society [cs.CY][INFO.INFO-OH] Computer Science [cs]/Other [cs.OH]Medical Laboratory TechnologyIdentification (information)Digital Forensics[INFO.INFO-CY] Computer Science [cs]/Computers and Society [cs.CY][ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH]020201 artificial intelligence & image processingbusinessLaw
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Systèmes imageurs 3D pour des applications agricoles : caractérisation de cultures et phénotypage de racines

2016

The development of the concepts of precision agriculture and viticulture since the last three decades has shown the need to use first 2D image acquisition techniques and dedicated image processing. More and more needs concern now 3D images and information. The main ideas of this chapter is thus to present some innovations of the 3D tools and methods in the agronomic domain. This chapter will particularly focus on two main subjects such as the 3D characterization of crop using Shape from Focus or Structure from Motion techniques and the 3D use for root phenotyping using rhizotron system. Results presented show that 3D information allows to better characterize crucial crop morphometric parame…

[SDE] Environmental Sciences0106 biological sciences2. Zero hungerRoot (linguistics)Focus (computing)SHAPE FROM FOCUSComputer scienceMachine vision3D reconstructionImage processing04 agricultural and veterinary sciencesPHENOTYPAGE15. Life on land01 natural sciencesData scienceDomain (software engineering)Agricultural science[SDE]Environmental Sciences040103 agronomy & agriculture0401 agriculture forestry and fisheriesStructure from motionSTRUCTURE FROM MOTIONPrecision agriculture010606 plant biology & botany
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Hypotheses engineering : first essential steps of experiment-driven software development

2019

Recent studies have proposed the use of experiments to guide software development in order to build features that the user really wants. Some authors argue that this approach represents a new way to develop software that is different from the traditional requirement-driven one. In this position paper, we propose the discipline of Hypotheses Engineering in comparison to Requirements Engineering, highlighting the importance of proper handling hypotheses that guide experiments. We derive a set of practices within this discipline and present how the literature has tackled them up to now. Finally, we propose a set of research questions that could guide future work towards helping practitioners. …

assumptionsRequirements engineeringComputer sciencebusiness.industrySoftware developmenttietokoneohjelmatvaatimusmäärittelytData scienceexperimentationhypoteesitSoftwareWork (electrical)Order (exchange)hypothesesexperiment driven software developmentPosition paperkokeet (tutkimustoiminta)Research questionsrequirements engineeringhypotheses engineeringbusinessSet (psychology)ohjelmistokehitys
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The Future of Antibiotic: From the Magic Bullet to the Smart Bullet

2014

business.industryAntibiotic resistance antivirulence drugsBiologySettore BIO/19 - Microbiologia GeneralebusinessMagic bulletApplied Microbiology and BiotechnologyBiochemistryMicrobiologyData scienceBiotechnologyBiotechnologyJournal of Microbial & Biochemical Technology
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A Trust-Based Crowdfunding Campaign Marketing Framework: Theoretical Underpinnings and Big-Data Analytics Practice

2021

business.industryBig dataGeneral MedicineBusinessData scienceVDP::Samfunnsvitenskap: 200::Statsvitenskap og organisasjonsteori: 240International Journal of Big Data Management
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How to start with big data - a multiple case study

2018

business.industryBig dataMultiple casebusinessData scienceInnovation adoptionDigital Transformation – Meeting the challenges
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Data lakes in business intelligence: reporting from the trenches

2018

Abstract The data lake approach has emerged as a promising way to handle large volumes of structured and unstructured data. This big data technology enables enterprises to profoundly improve their Business Intelligence. However, there is a lack of empirical studies on the use of the data lake approach in enterprises. This paper provides the results of an exploratory study designed to improve the understanding of the use of the data lake approach in enterprises. I interviewed 12 experts who had implemented this approach in various enterprises and identified three important purposes of implementing data lakes: (1) as staging areas or sources for data warehouses, (2) as a platform for experime…

business.industryComputer science05 social sciencesBig dataExploratory researchUnstructured data02 engineering and technologyData scienceData warehouseEmpirical research0502 economics and businessBusiness intelligence0202 electrical engineering electronic engineering information engineeringGeneral Earth and Planetary Sciences020201 artificial intelligence & image processingbusiness050203 business & managementGeneral Environmental ScienceProcedia Computer Science
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An Ontology Model for Interoperability and Multi-organization Data Exchange

2020

Progress in the uptake and use of technologies such as Artificial Intelligence and the Internet of Things seems to be stalled by the colossal fragmentation of information and data standards. This complexity is compounded by issues of inter-organisational differences, hindering effective collaboration. There is a growing demand for cross-organizational integrations in regulated but decentralized environments. This paper introduces an ontology architecture where information is sliced into independent semantic layers, each focusing on a specific aspect of the data. By dissolving traditional monolithic data structures into layered, light semantic components, the necessity to maintain contextual…

business.industryComputer science05 social sciencesInteroperability050301 education02 engineering and technologyOntology (information science)Data structureData scienceMarket fragmentationMetadataData exchange0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArchitectureInternet of Thingsbusiness0503 educationArtificial Intelligence and Bioinspired Computational Methods - Proceedings of the 9th Computer Science On-line Conference 2020, Vol. 2
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Towards the definitive evaluation framework for cross-platform app development approaches

2019

Abstract Mobile app development is hindered by device fragmentation and vendor-specific modifications. Boundaries between devices blur with PC-tablet hybrids on the one side and wearables on the other. Future apps need to support a host of app-enabled devices with differing capabilities, along with their software ecosystems. Prior work on cross-platform app development concerned concepts and prototypes, and compared approaches that target smartphones. To aid choosing an appropriate framework and to support the scientific assessment of approaches, an up-to-date comparison framework is needed. Extending work on a holistic, weighted set of assessment criteria, we propose what could become the …

business.industryComputer science05 social sciencesWearable computer020207 software engineering02 engineering and technologyData scienceVDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420Variety (cybernetics)Market fragmentationSoftwareHardware and Architecture0502 economics and businessCross-platform0202 electrical engineering electronic engineering information engineeringWeb applicationbusinessSet (psychology)Host (network)050203 business & managementSoftwareInformation Systems
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Big Data Metadata Management in Smart Grids

2014

Smart home, smart grids, smart museum, smart cities, etc. are making the vision for living in smart environments come true. These smart environments are built based upon the Internet of Things paradigm where many devices and applications are involved. In these environments, data are collected from various sources in diverse formats. The data are then processed by different intelligent systems with the purpose of providing efficient system planning, power delivery, and customer operations. Even though there are known technologies for most of these smart environments, putting them together to make intelligent and context-aware systems is not an easy task. The reason is that there are semantic…

business.industryComputer scienceBig dataIntelligent decision support systemcomputer.file_formatData scienceWorld Wide WebMetadataSmart gridHome automationMetadata managementSmart environmentRDFbusinessInternet of Thingscomputer
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