Search results for "FRAM"

showing 10 items of 2142 documents

Amidst Uncertainty–or Not? : Decision-Making in Early-Stage Software Startups

2019

It is commonly claimed that the initial stages of any startup business are dominated by continuous, extended uncertainty, in an environment that has even been described as chaotic. Consequently, decisions are made in uncertain circumstances, so making the right decision is crucial to successful business. However, little currently exists in the way of empirical studies into this supposed uncertainty. In this paper, we study decision-making in early-stage software startups by means of a single, in-depth case study. Based on our data, we argue that software startups do not work in a chaotic environment, nor are they characterized by unique uncertainty unlike that experienced by other firms. pe…

FOS: Computer and information sciencesComputer sciencepäätöksentekoeducation02 engineering and technologyentrepreneurshipstartup-yrityksetComputer Science - Software EngineeringSoftwareEmpirical researchohjelmistoala0202 electrical engineering electronic engineering information engineeringcynefin frameworkliiketoimintaympäristöbusiness.industry020207 software engineeringdecision-makingyrittäjyys113 Computer and information sciencesin-depth case studyepävarmuusIndustrial engineeringSoftware Engineering (cs.SE)Work (electrical)020201 artificial intelligence & image processingsoftware startupsStage (hydrology)business

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Factors and actors leading to the adoption of a JavaScript framework

2018

The increasing popularity of JavaScript has led to a variety of JavaScript frameworks that aim to help developers to address programming tasks. However, the number of JavaScript frameworks has risen rapidly to thousands of versions. It is challenging for practitioners to identify the frameworks that best fit their needs and to develop new ones which fit such needs. Furthermore, there is a lack of knowledge regarding what drives developers towards the choice. This paper explores the factors and actors that lead to the choice of a JavaScript framework. We conducted a qualitative interpretive study of semi-structured interviews. We interviewed 18 decision makers regarding the JavaScript framew…

FOS: Computer and information sciencesJavaScriptKnowledge managementComputer sciencehuman aspects of software developmentpäätöksentekotulkintalaadullinen tutkimus02 engineering and technologyUnified theory of acceptance and use of technologyJavaScriptohjelmointikieletWorld Wide WebBody of knowledgeComputer Science - Software Engineeringinterpretivism0202 electrical engineering electronic engineering information engineeringomaksuminenSocial influencecomputer.programming_languageExpectancy theoryLearnabilitybusiness.industry020207 software engineeringCompetitor analysisprogramming frameworkstechnology adoptionPopularitySoftware Engineering (cs.SE)teknologia020201 artificial intelligence & image processingohjelmistokehityskvalitatiivinen tutkimusbusinesscomputerSoftwareEmpirical Software Engineering

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Multispectral image denoising with optimized vector non-local mean filter

2016

Nowadays, many applications rely on images of high quality to ensure good performance in conducting their tasks. However, noise goes against this objective as it is an unavoidable issue in most applications. Therefore, it is essential to develop techniques to attenuate the impact of noise, while maintaining the integrity of relevant information in images. We propose in this work to extend the application of the Non-Local Means filter (NLM) to the vector case and apply it for denoising multispectral images. The objective is to benefit from the additional information brought by multispectral imaging systems. The NLM filter exploits the redundancy of information in an image to remove noise. A …

FOS: Computer and information sciencesMulti-spectral imaging systemsComputer Vision and Pattern Recognition (cs.CV)Optimization frameworkMultispectral imageComputer Science - Computer Vision and Pattern Recognition02 engineering and technologyWhite noisePixels[SPI]Engineering Sciences [physics][ SPI ] Engineering Sciences [physics]0202 electrical engineering electronic engineering information engineeringComputer visionUnbiased risk estimatorMultispectral imageMathematicsMultispectral imagesApplied MathematicsBilateral FilterNumerical Analysis (math.NA)Non-local meansAdditive White Gaussian noiseStein's unbiased risk estimatorIlluminationComputational Theory and MathematicsRestorationImage denoisingsymbols020201 artificial intelligence & image processingNon-local mean filtersComputer Vision and Pattern RecognitionStatistics Probability and UncertaintyGaussian noise (electronic)Non- local means filtersAlgorithmsNoise reductionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONFace Recognitionsymbols.namesakeNoise RemovalArtificial IntelligenceFOS: MathematicsParameter estimationMedian filterMathematics - Numerical AnalysisElectrical and Electronic EngineeringFusionPixelbusiness.industryVector non-local mean filter020206 networking & telecommunicationsPattern recognitionFilter (signal processing)Bandpass filters[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsStein's unbiased risk estimators (SURE)NoiseAdditive white Gaussian noiseComputer Science::Computer Vision and Pattern RecognitionSignal ProcessingArtificial intelligenceReconstructionbusinessModel

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PageRank model of opinion formation on Ulam networks

2013

We consider a PageRank model of opinion formation on Ulam networks, generated by the intermittency map and the typical Chirikov map. The Ulam networks generated by these maps have certain similarities with such scale-free networks as the World Wide Web (WWW), showing an algebraic decay of the PageRank probability. We find that the opinion formation process on Ulam networks have certain similarities but also distinct features comparing to the WWW. We attribute these distinctions to internal differences in network structure of the Ulam and WWW networks. We also analyze the process of opinion formation in the frame of generalized Sznajd model which protects opinion of small communities.

FOS: Computer and information sciencesPageRankPhysics - Physics and SocietyTheoretical computer scienceSznajd model[ NLIN.NLIN-CD ] Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD]FOS: Physical sciencesGeneral Physics and AstronomyNetwork structurePhysics and Society (physics.soc-ph)[ PHYS.PHYS.PHYS-SOC-PH ] Physics [physics]/Physics [physics]/Physics and Society [physics.soc-ph]01 natural sciencesopinion formation010305 fluids & plasmaslaw.inventionPageRanklawIntermittency0103 physical sciencesAlgebraic number010306 general physicsSocial and Information Networks (cs.SI)Physicsvoting models[PHYS.PHYS.PHYS-SOC-PH]Physics [physics]/Physics [physics]/Physics and Society [physics.soc-ph]Frame (networking)Process (computing)Computer Science - Social and Information NetworksNonlinear Sciences - Chaotic Dynamics[NLIN.NLIN-CD]Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD]Chaotic Dynamics (nlin.CD)Opinion formation

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Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

2018

Context: Startups are disrupting traditional markets and replacing well-established actors with their innovative products.To compete in this age of disruption, large and established companies cannot rely on traditional ways of advancement, which focus on cost efficiency, lead time reduction and quality improvement. Corporate management is now looking for possibilities to innovate like startups. Along with it, the awareness and the use of the Lean startup approach have grown rapidly amongst the software startup community and large companies in recent years. Objective: The aim of this study is to investigate how Lean internal startup facilitates software product innovation in large companies.…