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.

Process for making a payment using an account manager

Abstract: The present invention relates to a process for making a payment using an account manager or kiosk, the process guaranteeing the payment of the supplier and the anonymity of the customer. A customer (U) withdraws from his bank (B) a sum in the form of "blind" electronic coins or cash, deposits the latter in one or more anonymous accounts in a kiosk (K) and finally uses said account or accounts for paying suppliers of goods or services (SA). The invention has application to streamline and voice telepayment.

Automated Diagnosis for UMTS Networks Using Bayesian Network Approach

Abstract: This paper presents an automated diagnosis in troubleshooting (TS) for Universal Mobile Telecommunications System (UMTS) networks using a Bayesian network (BN) approach. An automated diagnosis model is first described using the Naive Bayesian Classifier. To increase the performance of the diagnosis model, the entropy minimization discretization (EMD) method is incorporated into the model to select optimal segments for the discretization of the input symptoms. In the first phase, the diagnosis model is constructed using a dynamic simulator. The simulator TS platform allows generation of a large amount of data required to study the relations between faults and symptoms. In the second phase, the diagnosis model is adapted to a real UMTS network using counters and key performance indicators (KPIs) recovered from an Operations and Maintenance Center (OMC). Results for the automated diagnosis using both network simulator and real UMTS network measurements illustrate the efficiency of the proposed TS approach and its importance to mobile network operators.

Hand gesture recognition using input-output hidden Markov models

Abstract: A new hand gesture recognition method based on input-output hidden Markov models is presented. This method deals with the dynamic aspects of gestures. Gestures are extracted from a sequence of video images by tracking the skin-color blobs corresponding to the hand into a body-face space centered on the face of the user. Our goal is to recognize two classes of gestures: deictic and symbolic.

Efficient image or video encryption based on spatiotemporal chaos system

Abstract: In this paper, an efficient image/video encryption scheme is constructed based on spatiotemporal chaos system. The chaotic lattices are used to generate pseudorandom sequences and then encrypt image blocks one by one. By iterating chaotic maps for certain times, the generated pseudorandom sequences obtain high initial-value sensitivity and good randomness. The pseudorandom-bits in each lattice are used to encrypt the Direct Current coefficient (DC) and the signs of the Alternating Current coefficients (ACs). Theoretical analysis and experimental results show that the scheme has good cryptographic security and perceptual security, and it does not affect the compression efficiency apparently. These properties make the scheme a suitable choice for practical applications.