1,209 research outputs found

    MultiNet: Multi-Modal Multi-Task Learning for Autonomous Driving

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    Autonomous driving requires operation in different behavioral modes ranging from lane following and intersection crossing to turning and stopping. However, most existing deep learning approaches to autonomous driving do not consider the behavioral mode in the training strategy. This paper describes a technique for learning multiple distinct behavioral modes in a single deep neural network through the use of multi-modal multi-task learning. We study the effectiveness of this approach, denoted MultiNet, using self-driving model cars for driving in unstructured environments such as sidewalks and unpaved roads. Using labeled data from over one hundred hours of driving our fleet of 1/10th scale model cars, we trained different neural networks to predict the steering angle and driving speed of the vehicle in different behavioral modes. We show that in each case, MultiNet networks outperform networks trained on individual modes while using a fraction of the total number of parameters.Comment: Published in IEEE WACV 201

    Persistence analysis of velocity and temperature fluctuations in convective surface layer turbulence

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    Persistence is defined as the probability that the local value of a fluctuating field remains at a particular state for a certain amount of time, before being switched to another state. The concept of persistence has been found to have many diverse practical applications, ranging from non-equilibrium statistical mechanics to financial dynamics to distribution of time scales in turbulent flows and many more. In this study, we carry out a detailed analysis of the statistical characteristics of the persistence probability density functions (PDFs) of velocity and temperature fluctuations in the surface layer of a convective boundary layer, using a field-experimental dataset. Our results demonstrate that for the time scales smaller than the integral scales, the persistence PDFs of turbulent velocity and temperature fluctuations display a clear power-law behaviour, associated with self-similar eddy cascading mechanism. Moreover, we also show that the effects of non-Gaussian temperature fluctuations act only at those scales which are larger than the integral scales, where the persistence PDFs deviate from the power-law and drop exponentially. Furthermore, the mean time scales of the negative temperature fluctuation events persisting longer than the integral scales are found to be approximately equal to twice the integral scale in highly convective conditions. However, with stability this mean time scale gradually decreases to almost being equal to the integral scale in the near neutral conditions. Contrarily, for the long positive temperature fluctuation events, the mean time scales remain roughly equal to the integral scales, irrespective of stability

    An International Standard : ISO Quality

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    An International Standard – ISO 9000 quality management system as applicable to service centre is discusse

    Boitawl: Soil, Lost and Left

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    Boitawl ( Boi - lack, devoid of, Tawl - bottom/ ground/ foundation), the word in one of the Bengali dialects refers to one without a ground beneath her feet. The thesis, a hybrid collection of prose and verse including narratives and graphic vignettes, flash, fabulist and short stories, prose poems and free verse imagines the inside worlds of such un-settled existences. In the process, the pieces connect migration, memory, childhood and lost towns with fractured humans caught in between - to reveal what lies under pillars of desires, the shapes of unsaid longings and recurrent images in their dreams

    Taxonomic study of Silene and related genera

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    Exploring modes of engagement within reform-oriented primary mathematics textbooks in India

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    In India, a curriculum reform inspired by critical perspectives has sought to transform primary mathematics teaching and learning. It is aimed at strengthening socio-cultural-political connections between school mathematics and students’ life experiences, thereby challenging traditional textbook culture. At the same time, this initiative has retained the textbook as a vehicle of reform while seeking to subvert many of its established conventions. Guided by Remillard’s idea of modes of engagement, this paper analyses the innovative Math-Magic textbooks associated with the Indian National Curriculum Framework. It investigates how these textbooks represent and communicate the framework ideas, focusing on key curricular elements and on the teacher as reader. Analysing the ‘voice’ and ‘structure’ of the textbooks as well as the ‘contexts’ used, it is revealed that they use a radically unique voice to introduce school mathematics while also attempting to use authentic and socially relevant contexts within their tasks. However, they have limited structural support to communicate these ideas clearly to the teacher-reader. The paper has implications for studying reformed textbooks in primary school mathematics in the Global South, where they remain the main teaching resource for teachers. Further, by focusing on ‘context’, the notion of modes of engagement within textbooks is extended through socio-cultural perspectives

    Impact of the Primary Science Capital Teaching Approach

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    Developing a justice-oriented science teaching approach for primary schools

    Level-crossings reveal organized coherent structures in a turbulent time series

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    In turbulent flows, energy production is associated with highly organized structures, known as coherent structures. Since these structures are three-dimensional, their detection remains challenging in the most common situation, when single-point temporal measurements are considered. While previous research on coherent structure detection from time series employs a thresholding approach, the thresholds are ad-hoc and vary significantly from one study to another. To eliminate this subjective bias, we introduce the level-crossing method and show how specific features of a turbulent time series associated with coherent structures can be objectively identified, without assigning a prior any arbitrary threshold. By using two wall-bounded turbulence time series datasets, we successfully extract through level-crossing analysis the impacts of coherent structures on turbulent dynamics, and therefore, open an alternative avenue in experimental turbulence research. By utilizing this framework further we identify a new metric, characterized by a statistical asymmetry between peaks and troughs of a turbulent signal, to quantify inner-outer interaction in wall turbulence. Moreover, a connection is established between extreme value statistics and level-crossing analysis, thereby allowing additional possibilities to study extreme events in other dynamical systems.Comment: This manuscript has 9 figures and 3 supplementary figure
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