Search results for "NETWORKS"
showing 10 items of 3260 documents
Multicast delivery of file download services in 3G mobile networks with MBMS
2008
This article investigates the efficient transmission of file download services to several users simultaneously in 3G mobile networks with HSDPA (High-Speed Downlink Packet Access) and MBMS (Multimedia Broadcast Multicast Services). HSDPA supports high speed point-to-point (p-t-p) transmissions (up to several Mb/s), whereas with MBMS the same content can be transmitted with a point-to-multipoint (p-t-m) connection to multiple users in a unidirectional fashion. Multicast delivery can be implemented through only p-t-p transmissions with HSDPA, a single p-t-m transmission with MBMS, or using both jointly in a hybrid approach by employing HSDPA for error repair of the MBMS p-t-m transmission. We…
Studying the evolution of neural activation patterns during training of feed-forward ReLU networks
2021
The ability of deep neural networks to form powerful emergent representations of complex statistical patterns in data is as remarkable as imperfectly understood. For deep ReLU networks, these are encoded in the mixed discrete–continuous structure of linear weight matrices and non-linear binary activations. Our article develops a new technique for instrumenting such networks to efficiently record activation statistics, such as information content (entropy) and similarity of patterns, in real-world training runs. We then study the evolution of activation patterns during training for networks of different architecture using different training and initialization strategies. As a result, we see …
Consistency Analysis of Genome-Scale Models of Bacterial Metabolism: A Metamodel Approach.
2015
Genome-scale metabolic models usually contain inconsistencies that manifest as blocked reactions and gap metabolites. With the purpose to detect recurrent inconsistencies in metabolic models, a large-scale analysis was performed using a previously published dataset of 130 genome-scale models. The results showed that a large number of reactions (~22%) are blocked in all the models where they are present. To unravel the nature of such inconsistencies a metamodel was construed by joining the 130 models in a single network. This metamodel was manually curated using the unconnected modules approach, and then, it was used as a reference network to perform a gap-filling on each individual genome-s…
Estimation techniques to measure subjective quality on live video streaming in Cloud Mobile Media services
2018
Abstract The adoption of smart phones, the increased access to mobile broadband networks and the availability of public cloud infrastructures are aligning to the next generation of truly ubiquitous multimedia services, known as Cloud Mobile Media (CMM) services offering mobile video. Nevertheless, due to an inherit higher and variable end to end delay mainly as a result of the virtualization process, new challenges appear. One challenge is given by live video streaming applications when trying to keep a good Quality of Experience of the delivered video, measured in terms of a subjective video quality metric, named Mean Opinion Score (MOS). Our goal is to estimate and predict this subjective…
Multimedia application to support distance learning and other social interactions in real-time
2000
Supporting social interactions, in distance learning situations for example, with modern technology is very difficult. Generally Internet, networked PC, document handling and communication services and applications are not designed from a multiple user perspective but to support a one-person-one-device (or tool) interaction. This approach creates problems for supporting awareness of, and communication with other people while simultaneously working on documents. Such simultaneous activities have been identified as essential by CSCW and CHI studies, where users are reported to move promiscuously between media and devices, and combine applications and media intuitively, while maintaining aware…
Applying a web-based training to foster self-regulated learning — Effects of an intervention for large numbers of participants
2016
Trainings on self-regulated learning (SRL) have been shown to be effective in improving both competence of self-regulated learning and objective measures of performance. However, human trainers can reach only a limited number of people at a time. Web-based trainings (WBT) could improve efficiency, as they can be distributed to potentially unlimited numbers of participants. We developed a WBT based on the process model of SRL by Schmitz and Wiese (2006) and tested it with 211 university students in a randomized control evaluation study including additional process analyses of learning diaries. Results showed that the training had significant effects on SRL knowledge, SRL behavior measured by…
Scalable Virtual Network Video-Optimizer for Adaptive Real-Time Video Transmission in 5G Networks
2020
The increasing popularity of video applications and ever-growing high-quality video transmissions (e.g., 4K resolutions), has encouraged other sectors to explore the growth of opportunities. In the case of health sector, mobile Health services are becoming increasingly relevant in real-time emergency video communication scenarios where a remote medical experts’ support is paramount to a successful and early disease diagnosis. To minimize the negative effects that could affect critical services in a heavily loaded network, it is essential for 5G video providers to deploy highly scalable and priorizable in-network video optimization schemes to meet the expectations of a large quantity of vide…
Stochastic Nonlinear Time Series Forecasting Using Time-Delay Reservoir Computers: Performance and Universality
2014
International audience; Reservoir computing is a recently introduced machine learning paradigm that has already shown excellent performances in the processing of empirical data. We study a particular kind of reservoir computers called time-delay reservoirs that are constructed out of the sampling of the solution of a time-delay diFFerential equation and show their good performance in the forecasting of the conditional covariances associated to multivariate discrete-time nonlinear stochastic processes of VEC-GARCH type as well as in the prediction of factual daily market realized volatilities computed with intraday quotes, using as training input daily log-return series of moderate size. We …
Multivariate correlation measures reveal structure and strength of brain–body physiological networks at rest and during mental stress
2021
In this work, we extend to the multivariate case the classical correlation analysis used in the field of network physiology to probe dynamic interactions between organ systems in the human body. To this end, we define different correlation-based measures of the multivariate interaction (MI) within and between the brain and body subnetworks of the human physiological network, represented, respectively, by the time series of delta, theta, alpha, and beta electroencephalographic (EEG) wave amplitudes, and of heart rate, respiration amplitude, and pulse arrival time (PAT) variability. MI is computed: (i) considering all variables in the two subnetworks to evaluate overall brain–body interaction…
Extended causal modeling to assess Partial Directed Coherence in multiple time series with significant instantaneous interactions.
2010
The Partial Directed Coherence (PDC) and its generalized formulation (gPDC) are popular tools for investigating, in the frequency domain, the concept of Granger causality among multivariate (MV) time series. PDC and gPDC are formalized in terms of the coefficients of an MV autoregressive (MVAR) model which describes only the lagged effects among the time series and forsakes instantaneous effects. However, instantaneous effects are known to affect linear parametric modeling, and are likely to occur in experimental time series. In this study, we investigate the impact on the assessment of frequency domain causality of excluding instantaneous effects from the model underlying PDC evaluation. M…