Incremental and hierarchical classification of a personal image collection on mobile devices

International audienceBrowsing multimedia collection on mobile devices raises the needs for new multimedia indexing solutions. In this paper, we focus on the management of personal image collections. We propose a method to simplify the browsing task on such a collection. The contributions reside in an incremental hierarchical algorithm, a method to provide a textual representation of the groups obtained and an algorithm to build a geo-temporal view of the collection. The proposed incremental hierarchical algorithm builds a temporal tree from the time stamp of each image. We opt here for a combination of a supervised clustering and an incremental algorithm based on mixture model. Good properties of the hierarchy are determined automatically thanks to the Integrated Likelihood Criterion (ICL). Based on the events obtained, a textual representation is proposed and then used to improve our temporal classification, combining geographical and temporal information. Results are validated on several real user collections with our prototype MyOwnLife

Scalable manufacture of pluripotent stem cell derived therapeutics

Human pluripotent stem cells (PSC) hold great promise as a source of starting material for the further production of therapeutic cell products. However, PSC are typically cultivated in planar formats that severely constrain scalability and hence restrict the quantities of cells that can be generated. Such formats are largely uncontrolled, require open processing, are labour intensive, and have an unfavourable risk profile. Manufacture of PSC in a suspension bioreactor format would alleviate scale-up constraints and simultaneously provide the benefits of sophisticated process monitoring and control, labour reduction, and process closure. We have developed a platform process for the expansion of PSC as aggregates in stirred tank reactors (STR’s), and demonstrated scale-up to a 10 L single-use Xcellerex XDR10 bioreactor system. PSC themselves are of no value as a cell therapy, and it is the differentiated progeny that are desired. We have demonstrated scalable differentiation of suspension cultured PSC to cardiomyocytes, as aggregates in STR’s. PSC expanded to the 10 L scale differentiated to cardiomyocytes with an efficiency of 97% and yield (cardiomyocyte:PSC) of \u3e 5

Building and Tracking Hierarchical Geographical & Temporal Partitions for Image Collection Management on Mobile Devices

International audienceUsage of mobile devices (phones, digital cameras) raises the need for organizing large personal image collections. In accordance with studies on user needs, we propose a statistical criterion and an associated optimization technique, relying on geo-temporal image metadata, for building and tracking a hierarchical structure on the image collection. In a mixture model framework, particularities of the application and typical data sets are taken into account in the design of the scheme (incrementality, ability to cope with non-Gaussian data, with both small and large samples). Results are reported on real data sets

Synchronizing the dynamics of a single NV spin qubit on a parametrically coupled radio-frequency field through microwave dressing

A hybrid spin-oscillator system in parametric interaction is experimentally emulated using a single NV spin qubit immersed in a radio frequency (RF) field and probed with a quasi resonant microwave (MW) field. We report on the MW mediated locking of the NV spin dynamics onto the RF field, appearing when the MW driven Rabi precession frequency approaches the RF frequency and for sufficiently large RF amplitudes. These signatures are analog to a phononic Mollow triplet in the MW rotating frame for the parametric interaction and promise to have impact in spin-dependent force detection strategies

Observation of a phononic Mollow triplet in a hybrid spin-nanomechanical system

Reminiscent of the bound character of a qubit's dynamics confined on the Bloch sphere, the observation of a Mollow triplet in the resonantly driven qubit fluorescence spectrum represents one of the founding signatures of Quantum Electrodynamics. Here we report on its observation in a hybrid spin-nanomechanical system, where a Nitro-gen Vacancy spin qubit is magnetically coupled to the vibrations of a Silicon Carbide nanowire. A resonant microwave field turns the originally parametric hybrid interac-tion into a resonant process, where acoustic phonons are now able to induce transitions between the dressed qubit states, leading to synchronized spin-oscillator dynamics. We further explore the vectorial character of the hybrid coupling to the bidimensional de-formations of the nanowire. The demonstrated microwave assisted synchronization of the spin-oscillator dynamics opens novel perspectives for the exploration of spin-dependent forces, the key-ingredient for quantum state transfer

A decentralized and robust approach to estimating a probabilistic mixture model for structuring distributed data

International audienceData sharing services on the web host huge amounts of resources supplied and accessed by millions of users around the world. While the classical approach is a central control over the data set, even if this data set is distributed, there is growing interesting in decentralized solutions, because of good properties (in particularity, privacy and scaling up). In this paper, we explore a machine learning side of this work direction. We propose a novel technique for decentralized estimation of probabilistic mixture models, which are among the most versatile generative models for understanding data sets. More precisely, we demonstrate how to estimate a global mixture model from a set of local models. Our approach accommodates dynamic topology and data sources and is statistically robust, i.e. resilient to the presence of unreliable local models. Such outlier models may arise from local data which are outliers, compared to the global trend, or poor mixture estimation. We report experiments on synthetic data and real geo-location data from Flickr

Fast aggregation of Student mixture models

International audienceThis paper deals with probabilistic models, that take the form of mixtures of Student distributions. Student distributions are known to be more statistically robust than Gaussian distributions, with regard to outliers (i.e. data that cannot be reasonnably explained by any component in the mixture and that do not justifiy an extra component. Our contribution is as follows : we show how several mixtures of Student distributions may be agregated into a single mixture, without resorting to sampling. The trick is that, as is well known, a Student distribution may be expressed as an infinite mixture of Gaussians, where the variances follow a Gamma distribution

Deviation from the normal mode expansion in a coupled graphene-nanomechanical system

We optomechanically measure the vibrations of a nanomechanical system made of a graphene membrane suspended on a silicon nitride nanoresonator. When probing the thermal noise of the coupled nanomechanical device, we observe a significant deviation from the normal mode expansion. It originates from the heterogeneous character of mechanical dissipation over the spatial extension of coupled eigenmodes, which violates one of the fundamental prerequisite for employing this commonly used description of the nanoresonators' thermal noise. We subsequently measure the local mechanical susceptibility and demonstrate that the fluctuation-dissipation theorem still holds and permits a proper evaluation of the thermal noise of the nanomechanical system. Since it naturally becomes delicate to ensure a good spatial homogeneity at the nanoscale, this approach is fundamental to correctly describe the thermal noise of nanomechanical systems which ultimately impact their sensing capacity