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Determinants of participants' follow-up and characterization of representativeness in flu near you, a participatory disease surveillance system

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JMIR Public Health and Surveillance 2017年第2期3卷 e18页

作者： Baltrusaitis, Kristin Santillana, Mauricio Crawley, Adam W. Chunara, Rumi Smolinski, Mark Brownstein, John S. Computational Health Informatics Program Boston Children's Hospital Boston MA United States Department of Biostatistics Boston University School of Public Health Boston MA United States Harvard Medical School Boston MA United States Harvard School of Engineering and Applied Sciences Cambridge MA United States Skoll Global Threats Fund San Francisco CA United States Global Institute of Public Health New York University New York NY United States Computer Science and Engineering New York University New York NY United States

Background: Flu Near You (FNY) is an Internet-based participatory surveillance system in the United States and Canada that allows volunteers to report influenza-like symptoms using a brief weekly symptom report. Objective: Our objective was to evaluate the representativeness of the FNY population compared with the general population of the United States, explore the demographic and behavioral characteristics associated with FNY's high-participation users, and summarize results from a user survey of a cohort of FNY participants. Methods: We compared (1) the representativeness of sex and age groups of FNY participants during the 2014-2015 flu season versus the general US population and (2) the distribution of Human Development Index (HDI) scores of FNY participants versus that of the general US population. We analyzed associations between demographic and behavioral factors and the level of participant follow-up (ie, high vs low). Finally, descriptive statistics of responses from FNY's 2015 and 2016 end-of-season user surveys were calculated. Results: During the 2014-2015 influenza season, 47,234 unique participants had at least one FNY symptom report that was either self-reported (users) or submitted on their behalf (household members). The proportion of female FNY participants was significantly higher than that of the general US population (n=28,906, 61.2% vs 51.1%, P<.001). Although each age group was represented in the FNY population, the age distribution was significantly different from that of the US population (P<.001). Compared with the US population, FNY had a greater proportion of individuals with HDI >5.0, signaling that the FNY user distribution was more affluent and educated than the US population baseline. We found that high-participation use (ie, higher participation in follow-up symptom reports) was associated with sex (females were 25% less likely than men to be high-participation users), higher HDI, not reporting an influenza-like illness at the first

关键词： Community-based participatory research Crowdsourcing Digital disease detection Human Influenza Public health informatics Public health surveillance

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Unsupervised learning of depth during coordinated head/eye movements

Unsupervised learning of depth during coordinated head/eye m...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Marco Antonelli Michele Rucci Bertram Shi Department of Electronic and Computer Engineering at the Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Department of Psychological and Brain Sciences and the Graduate Program in Neuroscience Boston University MA 02215 USA

ISBN: (纸本)9781509037636

Autonomous robots and humans need to create a coherent 3D representation of their peripersonal space in order to interact with nearby objects. Recent studies in visual neuroscience suggest that the small coordinated head/eye movements that humans continually perform during fixation provides useful depth information. In this work, we mimic such a behavior on a humanoid robot and propose a computational model that extracts depth information without requiring the kinematic model of the robot. First, we show that, during fixational head/eye movements, proprioceptive cues and optic flow lie on a low dimensional subspace that is a function of the depth of the target. Then, we use the generative adaptive subspace self-organizing map (GASSOM) to learn these depth-dependent subspaces. The depth of the target is eventually decoded using a winner-take-all strategy. The proposed model is validated on a simulated model of the iCub robot.

关键词： Cameras Robot vision systems Optical imaging Robot kinematics Integrated optics Three-dimensional displays

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Parallel Solution of Diagonally Dominant Banded Triangular Toeplitz Systems Using Taylor Polynomials

Parallel Solution of Diagonally Dominant Banded Triangular T...

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IEEE International Conference on High Performance Computing and Communications

作者： Michael Kapralos Aron Wolinetz Brian J. Murphy Department of Electrical and Computer Engineering University of Connecticut Storrs CT 06269 The Graduate Center of the City University of New York Ph.D. Program in Computer Science NY NY 10016 Lehman College of the City University of New York Bronx NY 10468

ISBN: (纸本)9781509042982

We present a new numerical and inherently parallel algorithm for solving banded (strictly) diagonally dominant triangular and banded Toeplitz (BDDTT) systems of linear equations. A Taylor polynomial, derived from the matrix analog of the Taylor Series for evaluating (1-x) ~(-1)where |χ| < 1, is applied, in conjunction with other techniques, to compute an approximate solution to a BDDTT-type system. This method requires O(n log_2n) arithmetic operations (ops) and O(log_2n) parallel steps (steps). Two FFTs and an IFFT of order 2n are the main contributors to the workload. This matches the FFT count for a triangular Toeplitz-matrix-vector multiplication. Clearly then, our method improves on the many algebraic FFT based processes that first determine the triangular Toeplitz matrix that is the inverse of a BDDTT matrix in order to then solve the associated BDDTT system.

关键词： Banded Triangular Toeplitz Diagonally Dominant Linear System FFT

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User-adaptive fall detection for patients using wristband

User-adaptive fall detection for patients using wristband

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2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Young-Hoon Nho Jong Gwan Lim Dae-Eon Kim Dong-Soo Kwon Robotics Program and Human-Robot Interaction research center Korea Advanced Institute of Science and Technology Daejeon Republic of Korea Department of Information Engineering Computer Science and University of Trento Italy KAIST Human-Robot Interaction Research Center Daejeon Republic of Korea Department of Mechanical Engineering Human-Robot Interaction research center Daejeon Republic of Korea

Fall detection systems have been proposed to prevent additional injuries following fall accidents. This paper introduces an easily learnable fall detection system based on the data of an individual patient in a hospital room. The improvement of low performance using a single accelerometer at wrists and the inconvenience of sensor attached to a waist in the conventional approach was concentrated on by integrating heart rate signals to the conventional acceleration approach and changing the sensor location from a waist to wrists. As for the optimal heart rate feature selection, we proposed a four-feature vector combination (root mean square of successive differences, standard deviation of successive differences, normal to normal 50, normal to normal 20) with correlation and mutual information analysis in addition to mean absolute deviation selected as an accelerometer feature. To easily acquire and train the patients' fall data, our system was based on unsupervised learning approaches using Gaussian mixture models for optimal classifiers with the optimal cluster number decided by cluster validation index of square error sum. A 10-fold cross validation was applied for a final performance evaluation where each threshold for separating fall state from non-fall state was automatically decided in several comparison groups, which were created on the basis of fusion timing and used sensors. As a result, despite sensors attached to the wrist, the wearable inconvenience of the conventional is overcome using the feature-level fused approach between heart rates and accelerations with the accuracy up to 98.39 %, which is closest to 99.34 % of the case using a single accelerometer located at the waist.

关键词： Accelerometers Heart rate Wrist Training data Hospitals Robot sensing systems Unsupervised learning

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Context transfer and Q-Transferable tasks 29

Context transfer and Q-Transferable tasks

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29th AAAI Conference on Artificial Intelligence, AAAI 2015

作者： Mousavi, Amin Araabi, Babak Nadjar Ahmadabadi, Majid Nili Robotics and AI Lab Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Iran School of Cognitive Science Tehran Iran

ISBN: (纸本)9781577357209

This article discusses the notion of context transfer in reinforcement learning tasks. Context transfer, as defined in this article, implies knowledge transfer between tasks that share the same environment's dynamics and reward function, but have different state and action spaces. For example, we have a working mobile robot in an environment. At some point, we decide to upgrade its sensors and/or actuators. Any change in these modules will result in a different description of the agent- environment model, and the trained knowledge is no longer applicable. We consider the tasks of the old and new robots, as the source and target tasks, respectively. The Markov decision process (MDP) of these tasks, under certain conditions, are called Q-transferable tasks, and the problem of knowledge transfer between them is called context transfer. We investigate the relation of the MDPs of these tasks. Copyright © 2015, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Markov processes

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An automatic calibration framework applied on a metaheuristic fuzzy model for the CIF competition

An automatic calibration framework applied on a metaheuristi...

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International Joint Conference on Neural Networks

作者： Vitor N. Coelho Igor M. Coelho Ivan R. Meneghini Marcone J. F. Souza Frederico G. Guimaraes Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Av. Ant?nio Carlos 6627 31270-901 Belo Horizonte Brazil Department of Computer Science State University of Rio de Janeiro Brazil Department of Computer Science Universidade Federal de Ouro Preto MG Brazil Departament of Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte Brazil

ISBN: (纸本)9781509006212

The challenging problem of forecasting a given time series as accurately as possible is reality in different areas of expertise. The requirement of achieving reliable forecasts, for assisting the new generation of soft sensors, requests the development of novel smart mechanisms to be integrated into the available forecasting models. This current paper improves the previous work of Coelho et al. [1], [2], introduced in the 2014 WCCI, which introduced a Hybrid Self-adaptive Forecasting Model (HFM), calibrated using an evolutionary metaheuristic. Here, an expert input selection assisted by the use of Neighborhood Structures is used for learning the dataset provide in the CIF 2016 forecasting competition. Two different metaheuristic algorithms are used for training the HFM, computational experiments are conducted for optimizing both models. By selecting the maximum lag to be used by our model and, consequently, defining a rate of training cycles, we calibrate the HFM in order to minimize Symmetric Mean Absolute Percentage Errors. Blind forecasts generated by the model will be submit to the competition.

关键词： Forecasting Time series analysis Predictive models Training Computational modeling Electronic mail Prediction algorithms

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Optical manipulation of shape-morphing elastomeric liquid crystal microparticles doped with gold nanocrystals

arXiv

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arXiv 2017年

作者： Sun, Yaoran Evans, Julian S. Lee, Taewoo Senyuk, Bohdan Keller, Patrick He, Sailing Smalyukh, Ivan I. Department of Physics Material Science and Engineering Program Department of Electrical Computer & Energy Engineering and Liquid Crystal Materials Research Center University of Colorado BoulderCO80309 United States Centre for Optical and Electromagnetic Research Zhejiang University Hangzhou310058 China Institut Curie Centre de Recherche CNRS UMR 168 Université Pierre et Marie Curie Paris cedex 0575248 France Department of Chemistry and Biochemistry and Liquid Crystal Materials Research Center University of Colorado BoulderCO80309 United States Department of Electromagnetic Engineering Royal Institute of Technology StockholmS-100 44 Sweden Renewable and Sustainable Energy Institute National Renewable Energy Laboratory University of Colorado BoulderCO80309 United States

We demonstrate facile optical manipulation of shape of birefringent colloidal microparticles made from liquid crystal elastomers. Using soft lithography and polymerization, we fabricate elastomeric microcylinders with weakly undulating director oriented on average along their long axes. These particles are infiltrated with gold nanospheres acting as heat transducers that allow for an efficient localized transfer of heat from a focused infrared laser beam to a submicrometer region within a microparticle. Photothermal control of ordering in the liquid crystal elastomer using scanned beams allows for a robust control of colloidal particles, enabling both reversible and irreversible changes of shape. Possible applications include optomechanics, microfluidics, and reconfigurable colloidal composites with shape-dependent self-assembly. Copyright © 2017, The Authors. All rights reserved.

关键词： Liquid crystals

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Region-based fault-tolerant distributed file storage system design in networks

Region-based fault-tolerant distributed file storage system ...

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作者： Sen, Arunabha Mazumder, Anisha Banerjee, Sujogya Das, Arun Zhou, Chenyang Shirazipourazad, Shahrzad Computer Science and Engineering Program School of Computing Informatics and Decision System Engineering Arizona State University TempeAZ85287 United States

Distributed storage of data files in different nodes of a network enhances its fault tolerance capability by offering protection against node and link failures. Reliability is often achieved through redundancy in one of the following two ways: (i) storage of multiple copies of the entire file at different locations (nodes) or (ii) storage of file segments (not entire files) at different node locations. In the (N, K) file distribution scheme, N file segments from a file F are created in such a way that it is possible to reconstruct the entire file, just by accessing any K ≤ N segments. For the reconstruction scheme to work, it is essential that the K segments of the file are stored in nodes that are connected in the network. However, in the event of node/link failures, the network might become disconnected (i.e., split into several connected components). We focus on node failures that are spatially correlated or region based. Such failures are often encountered in disaster situations or natural calamities where only the nodes in the disaster zone are affected. The first goal of this research is to design a least cost file storage scheme to ensure that no matter which region is destroyed;resulting in fragmentation of the network, a largest connected component of the residual network will have enough file segments with which to reconstruct the entire file. In case the least cost to ensure this objective is within the allocated budget, the storage design will be all region fault-tolerant (ARFT). In case the least cost exceeds the allocated budget, design of an ARFT file storage system design is impossible. The second goal of this research is to design file storage schemes that will be maximum region fault-tolerant within the allocated budget. The third goal of this research is to investigate the impact of the coding parameters N and K on storage requirements for ensuring all region or \textit{maximum region} fault-tolerant design. We provide maximum region fault-toleran

关键词： Approximation algorithms

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Dilute-nitride GaNP planar and core/shell microwire solar cells

Dilute-nitride GaNP planar and core/shell microwire solar ce...

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Indium Phosphide and Related Materials Conference

作者： Supanee Sukrittanon Ren Liu Janet L Pan Katherine L Jungjohann Shadi A Dayeh Charles W Tu Graduate Program of Materials Science and Engineering University of California San Diego United States of America Department of Electrical and Computer Engineering University of California San Diego United States of America Center for Integrated Nanotechnologies Sandia National Laboratories United States of America

ISBN: (纸本)9781509019656

Dilute nitride GaNP is potentially useful as the top junction in dual-junction solar cells on Si because it has a tunable direct-bandgap and small lattice mismatch with Si. Investigations on GaP are the first step toward this goal. Our best GaNP solar cell on GaP ([N] = 1.8%, Eg = 2.05 eV) achieves an efficiency of 7.9%, which is 3 times higher than the most efficient GaP solar cell to date and higher than other solar cells with similar direct bandgap (InGaP, GaAsP). We also report GaP/GaNP core/shell microwire solar cells utilizing top-down reactiveion etching to create the GaP cores and molecular beam epitaxy to create the GaNP shells. Systematic studies of cell performance over a series of microwire lengths, array periods, and sidewall morphologies, examined by transmission electron microscopy, were conducted to shed light on performance-limiting factors and to optimize the cell efficiency.

关键词： Photovoltaic cells Silicon Compounds computers Laboratories Junctions Lattices

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Data-driven analysis of kinaesthetic and tactile information for shape classification

Data-driven analysis of kinaesthetic and tactile information...

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2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015

作者： De Oliveira, Thiago Eustaquio Alves Prado Da Fonseca, Vinicius Huluta, Emanuil Rosa, Paulo F. F. Petriu, Emil M. School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil

ISBN: (纸本)9781479960910

Humans sense of touch consists in a complexity of sensors and nervous system. The information inferred by this system enables the daily dexterous manipulation tasks. In biological systems, there is no conscious prioritization of sensors while performing tactile exploration and the selection of exploratory movements is driven by learning instincts and data gathered by previous movements. The development of artificial systems tries to mimic such systems with engineered sensors and strategies for movement selection. This paper presents a data-driven analysis to the problem of sensor selection in the contour following for shape discrimination task. This task consists of a 4-DOF robotic finger exploring a set of 7 synthetic shapes. The data collected from the motors, inertial measurement unit, and magnetometer was analyzed applying principal component analysis and a multilayer perceptron neural network. Results show the variation of classification rate depending on the fingertip material and sensor considered. It is worth to observe that the magnetometer was the most robust in both cases. © 2015 IEEE.

关键词： Magnetometers

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