نتایج جستجو برای: hot start

تعداد نتایج: 171359  

2007
Zhixing Liu Chunming Fan Shoichiro Asano Nobuhiro Kishimoto Harumasa Hojo Akio Yasuda

A function of automatic location identification from an emergency call is required in Japan and many other countries. How to give a reliable position promptly is a problem in places where the GPS signal is extremely weak. We propose an acquisition scheme for the Assisted GPS (AGPS) architecture based on a timing-synchronized mobile network. With this method, the C/A code search and frequency se...

Journal: :Transactions of the Institute of Systems, Control and Information Engineers 2000

Journal: :Journal of Fluid Mechanics 2012

Journal: :Energies 2022

Plug-in hybrid electric vehicles (PHEVs) are a promising technology for reducing the tailpipe emissions of CO2 as well air pollutants, especially in urban environments. However, several studies raise questions over their after-treatment exhaust efficiency when internal combustion engine (ICE) ignites. The rationale is high ICE load during cold start combination with conditions devices. In this ...

2016
Enrico Daga Mathieu d'Aquin Aldo Gangemi Enrico Motta

Workflow formalisations are often focused on the representation of a process with the primary objective to support execution. However, there are scenarios where what needs to be represented is the effect of the process on the data artefacts involved, for example when reasoning over the corresponding data policies. This can be achieved by annotating the workflow with the semantic relations that ...

2011
Shaghayegh Sahebi William W. Cohen

The “Cold-Start” problem is a well-known issue in recommendation systems: there is relatively little information about each user, which results in an inability to draw inferences to recommend items to users. In this paper, we try to give a solution to this problem based on homophily in social networks: we can use social networks’ information in order to fill the gap existing in cold-start probl...

2014
Matthew Rowe

Matrix Factorisation is a recommendation approach that tries to understand what factors interest a user, based on his past ratings for items (products, movies, songs), and then use this factor information to predict future item ratings. A central limitation of this approach however is that it cannot capture how a user’s tastes have evolved beforehand; thereby ignoring if a user’s preference for...

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