University of Avignon

About: University of Avignon is a education organization based out in Avignon, Provence-Alpes-Côte-d'Azur, France. It is known for research contribution in the topics: Population & Speaker recognition. The organization has 1526 authors who have published 3766 publications receiving 88928 citations.

Probabilistic analysis of buffer starvation in Markovian queues

Abstract: Our purpose in this paper is to obtain the exact distribution of the number of buffer starvations within a sequence of N consecutive packet arrivals. The buffer is modeled as an M/M/1 queue. When the buffer is empty, the service restarts after a certain amount of packets are prefetched. With this goal, we propose two approaches, one of which is based on Ballot theorem, and the other uses recursive equations. The Ballot theorem approach gives an explicit solution, but at the cost of the high complexity order in certain circumstances. The recursive approach, though not offering an explicit result, needs fewer computations. We further propose a fluid analysis of starvation probability on the file level, given the distribution of file size and the traffic intensity. The starvation probabilities of this paper have many potential applications. We apply them to optimize the quality of experience (QoE) of media streaming service, by exploiting the tradeoff between the start-up delay and the starvation.

Generalized Analysis of a Distributed Energy Efficient Algorithm for Change Detection

Abstract: We propose an energy efficient distributed cooperative Change Detection scheme called DualCUSUM based on Page's CUSUM algorithm. In the algorithm, each sensor runs a CUSUM and transmits only when the CUSUM is above some threshold. The transmissions from the sensors are fused at the physical layer. The channel is modeled as a Multiple Access Channel (MAC) corrupted with noise. The fusion center performs another CUSUM to detect the change. The algorithm performs better than several existing schemes when energy is at a premium. We generalize the algorithm to also include nonparametric CUSUM and provide a unified analysis. Our results show that while the false alarm probability is smaller for observation distribution with a lighter tail, the detection delay is asymptotically the same for any distribution. Consequently, we provide a new viewpoint on why parametric CUSUM performs better than nonparametric CUSUM. In the process, we also develop new results on a reflected random walk which can be of independent interest.

A review through recovery, purification and identification of genipin

Abstract: Genipin is a secoiridoid that may be obtained directly from Genipa americana and after geniposide hydrolysis from Gardenia jasminoides fruits. It is well known that genipin is a high added value product which has a great potential for its application in different fields, such as medicine and food industry. A lack of information and research about the development of novel methods for the environmental friendly recovery and purification of genipin exists, focused on the green recovery of genipin through emerging technologies that lead to the sustainable extraction. In the present review, the available methods for recovery of genipin and geniposide are enlisted and described, as well as the reaction mechanism of genipin, and the developed methods for genipin and geniposide identification and quantification based on HPLC analysis. Moreover, this work reveals the scarcity of available identification methods for genipin, that should be taken into account to fulfill the recovery and quantification process of genipin.

The influence of acylation, metal binding and natural antioxidants on the thermal stability of red cabbage anthocyanins in neutral solution.

Abstract: The main red cabbage anthocyanins (pigments) are cyanidin glycosides bearing one or two acyl groups derived from hydroxycinnamic acids (HCAs). Through π-stacking interactions with the cyanidin chromophore, the HCA residues have a deep influence on the color expressed and its stability. In this work, a series of non-, mono- and diacylated anthocyanins were investigated in neutral solution (pH 7 and 8), where the pigments exhibit purple to blue colors. Under such conditions, the gradual color loss observed is a combination of two distinct processes involving the cyanidin nucleus: reversible water addition and irreversible autoxidation. By acidification to pH < 2, the colorless forms stemming from water addition (hemiketal and chalcones) are converted to the red flavylium ion, thereby permitting the selective monitoring of the irreversible contribution. The kinetics of color loss and of true pigment degradation could thus be recorded for each pigment. The influence of iron – cyanidin binding and of antioxidants (caffeic acid, N-acetylcysteine) was also investigated. A complete kinetic analysis combining the anthocyanin colored and colorless forms and the degradation products is provided. Overall, it appears that acylation is critical to color stability. For instance, the nonacylated pigment is rapidly bleached as a result of fast water addition and its iron complex is too unstable to provide protection. By contrast, the diacylated pigments are efficiently protected against hydration but much more moderately against autoxidation, which on the other hand is inhibited by efficient iron binding and addition of N-acetylcysteine. Finally, the diacylated pigments are much more resistant to bleaching by hydrogen peroxide (possibly produced by cyanidin autoxidation) and bisulfite (a common food preservative).

Conceptual decoding from word lattices: application to the spoken dialogue corpus MEDIA

Abstract: Within the framework of the French evaluation program MEDIA on spoken dialogue systems, this paper presents the methods proposed at the LIA for the robust extraction of basic conceptual constituents (or concepts) from an audio message. The conceptual decoding model proposed follows a stochastic paradigm and is directly integrated into the Automatic Speech Recognition (ASR) process. This approach allows us to keep the probabilistic search space on sequences of words produced by the ASR module and to project it to a probabilistic search space of sequences of concepts. This paper presents the first ASR results on the French spoken dialogue corpus MEDIA, available through ELDA. The experiments made on this corpus show that the performance reached by our approach is better than the traditional sequential approach that looks first for the best sequence of words before looking for the best sequence of concepts. Index Terms: Automatic Speech Recognition, Spoken Dialogue, Spoken Language Understanding.