Orange S.A.

About: Orange S.A. is a company organization based out in Paris, France. It is known for research contribution in the topics: Terminal (electronics) & Signal. The organization has 6735 authors who have published 9190 publications receiving 156440 citations. The organization is also known as: Orange SA & France Télécom.

Active matrix, high definition, liquid crystal display structure

Abstract: This color display structure for color display purposes has a first and second spaced, transparent substrates, between which is interposed a liquid crystal film (6), the first substrate (2) essentially supporting color filters (124) resistant to high temperatures and separated by black matrixes (126), a first transparent, passivating layer (128) deposited on the entire surface occupied by the filters and the black matrixes, thin film transistors (8, 9), formed on the first passivating layer facing the black matrixes so as to be protected from the ambient light, first transparent capacitor plates (10) formed on the first passivating layer facing the color filters and connected to the transistors, electrode rows (14) and columns (12) for controlling these transistors and a second transparent passivating layer (20) covering the transistors, the first plates, the rows and the columns, the second substrate (4) essentially having the second transparent capacitor plate.

Spatio-Temporal Convolutional Sparse Auto-Encoder for Sequence Classification.

Abstract: We present in this paper a novel learning-based approach for video sequence classification Contrary to the dominant methodology, which relies on hand-crafted features that are manually engineered to be optimal for a specific task, our neural model automatically learns a sparse shift-invariant representation of the local 2D+t salient information, without any use of prior knowledge To that aim, a spatio-temporal convolutional sparse auto-encoder is trained to project a given input in a feature space, and to reconstruct it from its projection coordinates Learning is performed in an unsupervised manner by minimizing a global parametrized objective function The sparsity is ensured by adding a sparsifying logistic between the encoder and the decoder, while the shift-invariance is handled by including an additional hidden variable to the objective function The temporal evolution of the obtained sparse features is learned by a long short-term memory recurrent neural network trained to classify each sequence We show that, since the feature learning process is problem-independent, the model achieves outstanding performances when applied to two different problems, namely human action and facial expression recognition Obtained results are superior to the state of the art on the GEMEP-FERA dataset and among the very best on the KTH dataset

A Semantic Overlay for Self- Peer-to-Peer Publish/Subscribe

Abstract: Publish/Subscribe systems provide a useful platform for delivering data (events) from publishers to subscribers in an anonymous fashion in distributed networks. In this paper, we promote a novel design principle for self-. dynamic and reliable content-based publish/subscribe systems and perform a comparative analysis of its probabilistic and deterministic implementations. More specifically, we present a generic content-based publish/subscribe system, called DPS (Dynamic Publish/Subscribe). DPS combines classical content-based filtering with self-. (self-organizing, selfconfiguring, and self-healing) subscription-driven clustering of subscribers. DPS gracefully adapts to failures and changes in the system while achieving scalable events delivery. DPS includes a variety of fault-tolerant deterministic and probabilistic content-based publication/subscription schemes. These schemes are targeted toward scalability, and aim at reducing and distributing the number of messages exchanged. Reliability and scalability of our system are shown through analytical and experimental evaluation.

System, method, device, and computer program product for a sender to send a personalized notification to a recipient of a communication

Abstract: In a communication network, a caller selects a personalized notification to be sent together with his call. The personalized notification, for example a personalized ringtone, is sent as a message together with the call. The switching center sends the message to the recipient of the call when the call is routed. The recipient's device determines that the incoming caller matches the sender of the message, and the message is opened, causing the caller's personalized notification to be played on the recipient's device.