115,860 research outputs found

    Exploring sensor data management

    Get PDF
    The increasing availability of cheap, small, low-power sensor hardware and the ubiquity of wired and wireless networks has led to the prediction that `smart evironments' will emerge in the near future. The sensors in these environments collect detailed information about the situation people are in, which is used to enhance information-processing applications that are present on their mobile and `ambient' devices.\ud \ud Bridging the gap between sensor data and application information poses new requirements to data management. This report discusses what these requirements are and documents ongoing research that explores ways of thinking about data management suited to these new requirements: a more sophisticated control flow model, data models that incorporate time, and ways to deal with the uncertainty in sensor data

    Bridging the Gap: 21st Century Media Meets Theoretical Pedagogical Literacy Practices

    Full text link
    In this chapter, the researchers used an ethnographic stance to demonstrate how conversation evolved within a social media platform. They investigated the online discussions and face-to-face dialogues between teacher educators and pre-service teachers. They compared the participants’ reciprocal conversations within this case study to analyze patterns in the language used in each forum in order to identify the affordances and constraints of perceived understanding. Through this discourse analysis the authors sought to identify indicators of each participant’s metacognitive development while engaging in an online book discussion through a social media platform. Data analysis indicated that there was metacognitive growth when comparing the initial reciprocal conversations with the final conversations

    Improving perceptual multimedia quality with an adaptable communication protocol

    Get PDF
    Copyrights @ 2005 University Computing Centre ZagrebInnovations and developments in networking technology have been driven by technical considerations with little analysis of the benefit to the user. In this paper we argue that network parameters that define the network Quality of Service (QoS) must be driven by user-centric parameters such as user expectations and requirements for multimedia transmitted over a network. To this end a mechanism for mapping user-oriented parameters to network QoS parameters is outlined. The paper surveys existing methods for mapping user requirements to the network. An adaptable communication system is implemented to validate the mapping. The architecture adapts to varying network conditions caused by congestion so as to maintain user expectations and requirements. The paper also surveys research in the area of adaptable communications architectures and protocols. Our results show that such a user-biased approach to networking does bring tangible benefits to the user

    Bridging the Gap Between Training and Inference for Spatio-Temporal Forecasting

    Get PDF
    Spatio-temporal sequence forecasting is one of the fundamental tasks in spatio-temporal data mining. It facilitates many real world applications such as precipitation nowcasting, citywide crowd flow prediction and air pollution forecasting. Recently, a few Seq2Seq based approaches have been proposed, but one of the drawbacks of Seq2Seq models is that, small errors can accumulate quickly along the generated sequence at the inference stage due to the different distributions of training and inference phase. That is because Seq2Seq models minimise single step errors only during training, however the entire sequence has to be generated during the inference phase which generates a discrepancy between training and inference. In this work, we propose a novel curriculum learning based strategy named Temporal Progressive Growing Sampling to effectively bridge the gap between training and inference for spatio-temporal sequence forecasting, by transforming the training process from a fully-supervised manner which utilises all available previous ground-truth values to a less-supervised manner which replaces some of the ground-truth context with generated predictions. To do that we sample the target sequence from midway outputs from intermediate models trained with bigger timescales through a carefully designed decaying strategy. Experimental results demonstrate that our proposed method better models long term dependencies and outperforms baseline approaches on two competitive datasets.Comment: ECAI 2020 Accepted, preprin

    Stochastic assembly of sublithographic nanoscale interfaces

    Get PDF
    We describe a technique for addressing individual nanoscale wires with microscale control wires without using lithographic-scale processing to define nanoscale dimensions. Such a scheme is necessary to exploit sublithographic nanoscale storage and computational devices. Our technique uses modulation doping to address individual nanowires and self-assembly to organize them into nanoscale-pitch decoder arrays. We show that if coded nanowires are chosen at random from a sufficiently large population, we can ensure that a large fraction of the selected nanowires have unique addresses. For example, we show that N lines can be uniquely addressed over 99% of the time using no more than /spl lceil/2.2log/sub 2/(N)/spl rceil/+11 address wires. We further show a hybrid decoder scheme that only needs to address N=O(W/sub litho-pitch//W/sub nano-pitch/) wires at a time through this stochastic scheme; as a result, the number of unique codes required for the nanowires does not grow with decoder size. We give an O(N/sup 2/) procedure to discover the addresses which are present. We also demonstrate schemes that tolerate the misalignment of nanowires which can occur during the self-assembly process

    Bridging the Gap

    Get PDF
    School districts across the country are increasingly seeking out digital tools to support the work of educators, in the hopes of improving students' academic achievement. With the rapid emergence of this new market, many districts have been challenged by the task of identifying and procuring educational technology (ed-tech) products that match the needs of their educators and students.The NYC Department of Education's "Innovate NYC Schools" division, supported by a U.S. DOE Investing in Innovation (i3) grant, aims to address this problem, in part by promoting "user-centered design," an approach that puts the needs and preferences of products' intended users (in this case, teachers, students, and parents) front and center in the development and procurement of new technology.Bridging the Gap describes the design and implementation of three Innovate NYC Schools initiatives grounded in user-centered design theory:School Choice Design Challenge (SCDC),an effort to develop apps that would help students explore and narrow down their choices of high school.#SharkTankEDU events, during which ed-tech developers present a product to a panel of educators who provide feedback on the tool.Short-Cycle Evaluation Challenges (SCEC), a classroom-based, semester-long pilot of ed-tech tools intended to inform product development, as well as the ultimate procurement decisions of school staff.The report focuses on four phases of work involved in bringing ed-tech companies and the users of their products together: defining a problem; selecting users and ed-tech companies; implementing pilot-based initiatives; and evaluating products. It describes strategies used and challenges faced, and offers practical lessons gleaned from the experiences of the individuals who designed and participated in these efforts.
    • 

    corecore