Urval Senaste Alla publikationer 16 Alves, R., Ros, A., Black

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By extracting a set of common features and principles of integra-tive levels of granularity, the triarchic theory of granular computing is developed. 1. Introduction Granularity is the relative size, scale, level of detail, or depth of penetration that characterizes an object or activity. It may help to think of it as: which type of "granule" are we looking at? This term is used in astronomy, photography, physics, linguistics, and fairly often in … time is modeled at a ﬁxed granularity, gener-ally selected based on the rate at which the fastest component evolves. Inference must then be performed at this fastest granularity, poten-tially at signiﬁcant computational cost. Contin-uous Time Bayesian Networks (CTBNs) avoid time-slicing in the representation by modeling School of Computer Science University of Magdeburg, Germany mkuhlema@ovgu.de ABSTRACT Building software product lines (SPLs) with features is a challeng-ing task.

questions of granularity, and general constraints applying to verbal semantics. Abstract : Autonomic computing aims at making computing systems Dynamic Adaptations of Synchronization Granularity in Concurrent Data Structures Programming Model and Protocols for Reconfigurable Distributed Systems. On one hand, research focused on the creation and application of new data science approaches, like deep learning and cognitive computing, can inform different Coverage at a more granular level. • Service parameters technical training in computer/data science and engineering. It should also include av M Johannesson · 2002 · Citerat av 14 — publisher: Department of Computer Science, Lund University; defense location: Sal 104, Kungshuset; defense date: 2002-05-29 10:00:00; external identifiers.

Particle Methods for Modelling Granular Material Flow - DiVA

Therefore, we present different metrics to evaluate and compare Department of Computer Science University of of data mining is searching for the right level of granularity in in many branches of social sciences.23 I don't know what they mean in my assignment refering to granularity in question 3)e) of the assignment found below. 3) [5 marks] A radio station broadcasts at a frequency of 2MHz with a total radiated power of 1000W. a.

[PDF] Predictions of train delays using machine learning

Though many SPLs can and have been implemented with the coarse granularity of existing approaches, of granularity as a basis of granular computing.

Consider a finite number of photons falling on an array of detectors.
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The term comes from the fact that in conventional photography a high noise content image appears grainy to the viewer. Zero granularity is, of course, impossible. Consider a finite number of photons falling on an array of detectors. In computer science, granularity refers to a ratio of computation to communication – and also, in the classical sense, to the breaking down of larger holistic tasks into smaller, more finely delegated tasks.

The extent to which a system contains separate components (like granules). The more components in a system — or the greater the granularity — the more flexible it is.
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Investigation of Step Granularity for Adaptive Learning - DiVA

1. Introduction Some popular types of traditional machine learning are presented in terms of their key features and limitations in the context of big data. Further, the book discusses why granular-computing-based machine learning is called for, and demonstrates how granular computing concepts can be used in different ways to advance machine learning for big data processing.

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‪Guorun Yang‬ - ‪Google Scholar‬

This technical report has been published as Relaxed Consistency and Coherence Granularity in DSM Systems: A Performance Evaluation. Y. Zhou, L 2020-12-09 · In this letter, we propose a conceptually simple and effective dual-granularity triplet loss for visible-thermal person re-identification (VT-ReID). In general, ReID models are always trained with the sample-based triplet loss and identification loss from the fine granularity level.