Modeling and analysis of a deep learning pipeline for cloud based video analytics.

Video analytics systems based on deep learning approaches are becoming the basis of many widespread applications including smart cities to aid people and traffic monitoring. These systems necessitate massive amounts of labeled data and training time to perform fine tuning of hyper-parameters for object classification. We propose a cloud based video analytics system built upon an optimally tuned deep learning model to classify objects from video streams. The tuning of the hyper-parameters including learning rate, momentum, activation function and optimization algorithm is optimized through a mathematical model for efficient analysis of video streams. The system is capable of enhancing its own training data by performing transformations including rotation, flip and skew on the input dataset making it more robust and self-adaptive. The use of in-memory distributed training mechanism rapidly incorporates large number of distinguishing features from the training dataset - enabling the system to perform object classification with least human assistance and external support. The validation of the system is performed by means of an object classification case-study using a dataset of 100GB in size comprising of 88,432 video frames on an 8 node cloud. The extensive experimentation reveals an accuracy and precision of 0.97 and 0.96 respectively after a training of 6.8 hours. The system is scalable, robust to classification errors and can be customized for any real-life situation.N/

Biological effects of naturally occurring and man-made fibres: in vitro cytotoxicity and mutagenesis in mammalian cells

Cytotoxicity and mutagenicity of tremolite, erionite and the man-made ceramic (RCF-1) fibre were studied using the human– hamster hybrid A L cells. Results from these fibres were compared with those of UICC Rhodesian chrysotile fibres. The A L cell mutation assay, based on the S1 gene marker located on human chromosome 11, the only human chromosome contained in the hybrid cell, has been shown to be more sensitive than conventional assays in detecting deletion mutations. Tremolite, erionite and RCF-1 fibres were significantly less cytotoxic to A L cells than chrysotile. Mutagenesis studies at the HPRT locus revealed no significant mutant yield with any of these fibres. In contrast, both erionite and tremolite induced dose-dependent S1− mutations in fibre-exposed cells, with the former inducing a significantly higher mutant yield than the latter fibre type. On the other hand, RCF-1 fibres were largely non-mutagenic. At equitoxic doses (cell survival at ∼ 0.7), erionite was found to be the most potent mutagen among the three fibres tested and at a level comparable to that of chrysotile fibres. These results indicate that RCF-1 fibres are non-genotoxic under the conditions used in the studies and suggest that the high mesothelioma incidence previously observed in hamster may either be a result of selective sensitivity of hamster pleura to fibre-induced chronic irritation or as a result of prolonged fibre treatment. Furthermore, the relatively high mutagenic potential for erionite is consistent with its documented carcinogenicity. © 1999 Cancer Research Campaig

Inhibition of Ataxia Telangiectasia Mutated Kinase Activity Enhances TRAIL-Mediated Apoptosis in Human Melanoma Cells

L’ouvrage de Giuseppina Battista sur l’éducation des enfants dans la Regola del governo di cura familiare de Jean Dominici est, comme l’écrit Christiane Klapisch-Zuber, le résultat d’une rencontre entre deux auteurs qui ne se sont jamais connus : le dominicain florentin Jean Dominici (1355/6-1419), qui devint cardinal et fut béatifié en 1832, et la célèbre pédagogue italienne Maria Montessori (1870-1952). Bien que la seconde n’ait pas lu les écrits du premier, la comparaison de leurs œuvres i..

Peer-to-peer live video streaming with rateless codes for massively multiplayer online games

International audienc

Quality of spirometry and related diagnosis in primary care with a focus on clinical use

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