Œuvre libre | EPFL Graph Search

thumb|150px|Logo œuvres culturelles libres Une œuvre libre, ou contenu libre, est une œuvre de l'esprit (ce qui implique sa soumission au droit d'auteur) dont la diffusion et la modification sont libres. Ces œuvres sont notamment des s, des textes, de la musique et des logiciels dont chacun peut distribuer autant de copies qu'il le souhaite, et aussi les modifier pour les améliorer. Cela ne signifie pas pour autant que ces œuvres ne sont pas soumises au droit d’auteur. Ces droits sont accordés par les auteurs dans une licence dite licence libre ou licence de libre diffusion, ces dernières étant également appelées licence ouverte, en fonction des droits cédés. Ces libertés données aux utilisateurs dans la réutilisation des œuvres (usage, étude, modification, diffusion ou non à but commercial) sont souvent associées à des obligations (citer l'auteur original, maintenir la licence originale du contenu réutilisé) ou des restrictions (pas d'usage commercial, interdiction de certains médias

Synthetic calibrators for the analysis of sulfoconjugated metanephrines in urine: hydrolysis conditions revisited

Sandrine Gerber, Jonathan Simonin

Background: The quantification of total (free + sulfated) metanephrines in urine is recommended to diagnose pheochromocytoma. Urinary metanephrines include metanephrine itself, normetanephrine and methoxytyramine, mainly in the form of sulfate conjugates (60-80%). Their determination requires the hydrolysis of the sulfate ester moiety to allow electrochemical oxidation of the phenolic group. Commercially available urine calibrators and controls contain essentially free, unhydrolysable metanephrines which are not representative of native urines. The lack of appropriate calibrators may lead to uncertainty regarding the completion of the hydrolysis of sulfated metanephrines, resulting in incorrect quantification.

Elsevier2012

Adaptive video delivery using semantics

Olivier Steiger

The diffusion of network appliances such as cellular phones, personal digital assistants and hand-held computers has created the need to personalize the way media content is delivered to the end user. Moreover, recent devices, such as digital radio receivers with graphics displays, and new applications, such as intelligent visual surveillance, require novel forms of video analysis for content adaptation and summarization. To cope with these challenges, we propose an automatic method for the extraction of semantics from video, and we present a framework that exploits these semantics in order to provide adaptive video delivery. First, an algorithm that relies on motion information to extract multiple semantic video objects is proposed. The algorithm operates in two stages. In the first stage, a statistical change detector produces the segmentation of moving objects from the background. This process is robust with regard to camera noise and does not need manual tuning along a sequence or for different sequences. In the second stage, feedbacks between an object partition and a region partition are used to track individual objects along the frames. These interactions allow us to cope with multiple, deformable objects, occlusions, splitting, appearance and disappearance of objects, and complex motion. Subsequently, semantics are used to prioritize visual data in order to improve the performance of adaptive video delivery. The idea behind this approach is to organize the content so that a particular network or device does not inhibit the main content message. Specifically, we propose two new video adaptation strategies. The first strategy combines semantic analysis with a traditional frame-based video encoder. Background simplifications resulting from this approach do not penalize overall quality at low bitrates. The second strategy uses metadata to efficiently encode the main content message. The metadata-based representation of object's shape and motion suffices to convey the meaning and action of a scene when the objects are familiar. The impact of different video adaptation strategies is then quantified with subjective experiments. We ask a panel of human observers to rate the quality of adapted video sequences on a normalized scale. From these results, we further derive an objective quality metric, the semantic peak signal-to-noise ratio (SPSNR), that accounts for different image areas and for their relevance to the observer in order to reflect the focus of attention of the human visual system. At last, we determine the adaptation strategy that provides maximum value for the end user by maximizing the SPSNR for given client resources at the time of delivery. By combining semantic video analysis and adaptive delivery, the solution presented in this dissertation permits the distribution of video in complex media environments and supports a large variety of content-based applications.

EPFL2005

User Profiling Using Submitted Review Content

Boi Faltings, Yizhong Liang, Claudiu-Cristian Musat

A computer-implemented method for generating a user profile of a user of an online platform, a computer-implemented method for providing a first user with targeted information and a computer-implemented method for providing a user of an online platform with targeted advertisements.

2014

Adaptive video delivery using semantics

Olivier Steiger

EPFL2005