1,465,378 research outputs found

    Online Visual Robot Tracking and Identification using Deep LSTM Networks

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    Collaborative robots working on a common task are necessary for many applications. One of the challenges for achieving collaboration in a team of robots is mutual tracking and identification. We present a novel pipeline for online visionbased detection, tracking and identification of robots with a known and identical appearance. Our method runs in realtime on the limited hardware of the observer robot. Unlike previous works addressing robot tracking and identification, we use a data-driven approach based on recurrent neural networks to learn relations between sequential inputs and outputs. We formulate the data association problem as multiple classification problems. A deep LSTM network was trained on a simulated dataset and fine-tuned on small set of real data. Experiments on two challenging datasets, one synthetic and one real, which include long-term occlusions, show promising results.Comment: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada, 2017. IROS RoboCup Best Paper Awar

    Symmetrical Observability of Kinematic Parameters in Symmetrical Parallel Mechanisms

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    This article presents an application of symmetry group theory in kinematic identification of parallel mechanisms of nlegs legs -- Kinematic Identification implies the estimation of the actual geometrical parameters (as opposed to nominal ones) of a physical mechanism -- For a symmetric mechanism, KI requires configuring sets of leg positions with symmetrical observability ā€“ This article presents as main contributions: (i) a conjecture that allows mapping the symmetries of the mechanism into the active-joint workspace, (ii) a set of necessary conditions to express leg parameters in coordinate systems which allow symmetrical observability, and (iii) a procedure for exploiting symmetries in pose selection for kinematic identification of symmetrical parallel mechanisms -- For the kinematic identification itself, we adopt a divide-and-conquer (DC) identification protocol -discussed by us in another publication- in which each leg of the mechanism is independently identified by using the inverse calibration method -- In this article we emphasize how to exploit the symmetries existent in (nlegs āˆ’ 1) legs of the parallel mechanism allowing to apply to other legs the symmetry-transformed sample protocol used for the kinematic identification of a reference leg -- The symmetrical observability of sets of leg parameters allows to reduce the costs of the pose selection procedure by a factor of (1/nlegs) compared to a complete DC procedure in which the poses of each leg are selected independently -- The pose selection is carried out only for the reference leg -- For the (nlegsāˆ’1) remaining legs the poses are dictated by symmetry operations performed onto the poses of the reference leg -- An application of the symmetrical observability is presented through the simulated kinematic identification of a 3RRR symmetrical parallel mechanismPolytechnic School of the University of SĆ£o PauloSitio webIndicaciones, AssociaĆ§Ć£o Brasileira de MĆ©todos Computacionais em Engenharia, International Association for Computational Mechanics, International Congress and Convention Association, ConheƧa o SĆ£o Paulo Ć© Tudo de Bom, Embratur, PETROBRA

    Demand for Redistribution, Support for the Welfare State, and Party Identification in Austria

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    This paper describes subjective wage inequality and the demand for redistribution in Austria using individuals' estimates of occupational wages from the International Social Survey Program. Although these estimates differ widely across individuals, the data clearly show that most individuals would like to decrease wage inequality, relative to the level of inequality which they perceive to exist. The empirical analysis also shows that the demand for redistribution is strongly associated not only with variables describing self-interested motives for redistribution, but also with perceptions of and social norms with respect to inequality. Further, the demand for redistribution is a strong predictor for whether an individual is supportive of redistribution by the state. On the other hand, however, I find almost no evidence for an empirical association between the demand for redistribution and individuals' party identification.subjective inequality measures, demand for redistribution, support for the welfare state, party identification

    Demand for Redistribution, Support for the Welfare State, and Party Identification in Austria

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    This paper describes subjective wage inequality and the demand for redistribution in Austria using individuals' estimates of occupational wages from the International Social Survey Program. Although these estimates differ widely across individuals, the data clearly show that most individuals would like to decrease wage inequality, relative to the level of inequality which they perceive to exist. The empirical analysis also shows that the demand for redistribution is strongly associated not only with variables describing self-interested motives for redistribution, but also with perceptions of and social norms with respect to inequality. Further, the demand for redistribution is a strong predictor for whether an individual is supportive of redistribution by the state. On the other hand, however, I find almost no evidence for an empirical association between the demand for redistribution and individuals' party identification.subjective inequality measures, demand for redistribution, support for the welfare state, party identification

    Loran-C performance assurance assessment program

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    The Federal Aviation Administration (FAA) has accepted the Loran-C navigation system as a supplemental navigation aid for enroute use. Extension of Loran-C utilization to instrument approaches requires establishment of a process by which the current level of performance of the system is always known by the pilot. This system 'integrity' translates into confidence that, if the system is made available to the pilot, the guidance will be correct. Early in the consideration of Loran-C for instrument approaches, the Loran-C Planning Work-Group (LPW) was formed with membership from the FAA, the US Coast Guard, various state governments, aviation users, equipment manufacturers and technical experts. The group was hosted and co-chaired by the National Association of State Aviation Officials (NASAO). This forum was ideal for identification of system integrity issues and for finding the correct process for their resolution. Additionally, the Wild Goose Association (WGA), which is the international Loran-C technical and user forum, regularly brings together members of the FAA, Coast Guard, and the scientific community. Papers and discussions from WGA meetings have been helpful. Given here is a collection of the issues in which Ohio University became involved. Issues definition and resolution are included along with the recommendations in those areas where resolution is not yet complete

    The role of forensic dentist following mass disaster

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    This review article focuses on mass disaster situations that may arise from natural or manmade circumstances and the significant role of forensic dental personnel in human identification following such occurrences. The various forensic dental modalities of identification that include matching techniques, postmortem profiling, genetic fingerprinting, dental fossil assessment and dental biometrics with digital subtraction were considered. The varying extent of use of forensic dental techniques and the resulting positive impact on human identification were considered. The importance of preparation by way of special training for forensic dental personnel, mock disaster rehearsal, and use of modern day technology was stressed. The need for international standardization of identification through the use of Interpol Disaster Victim Identification (DVI) for ms was further emphasized. Recommendations for improved human identification in Nigerian situation include reform of the National Emergency Management Association (NEMA), incorporation of dental care in primary health care to facilitate proper ante mortem database of the populace and commencement of identification at site of disaster

    A Genome-Wide Screening and SNPs-to-Genes Approach to Identify Novel Genetic Risk Factors Associated with Frontotemporal Dementia

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    Frontotemporal dementia (FTD) is the second most prevalent form of early onset dementia after Alzheimerā€™s disease (AD). We performed a case-control association study in an Italian FTD cohort (n = 530) followed by the novel SNPs-to-genes approach and functional annotation analysis. We identified two novel potential loci for FTD. Suggestive SNPs reached p-values ~10-7 and OR > 2.5 (2p16.3) and 1.5 (17q25.3). Suggestive alleles at 17q25.3 identified a disease-associated haplotype causing decreased expression of -cis genes such as RFNG and AATK involved in neuronal genesis and differentiation, and axon outgrowth, respectively. We replicated this locus through the SNPs-to-genes approach. Our functional annotation analysis indicated significant enrichment for functions of the brain (neuronal genesis, differentiation and maturation), the synapse (neurotransmission and synapse plasticity), and elements of the immune system, the latter supporting our recent international FTD-GWAS. This is the largest genome-wide study in Italian FTD to date. Although our results are not conclusive, we set the basis for future replication studies and identification of susceptible molecular mechanisms involved in FTD pathogenesis

    Early antenatal prediction of gestational diabetes in obese women: development of prediction tools for targeted intervention

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    All obese women are categorised as being of equally high risk of gestational diabetes (GDM) whereas the majority do not develop the disorder. Lifestyle and pharmacological interventions in unselected obese pregnant women have been unsuccessful in preventing GDM. Our aim was to develop a prediction tool for early identification of obese women at high risk of GDM to facilitate targeted interventions in those most likely to benefit. Clinical and anthropometric data and non-fasting blood samples were obtained at 15+0ā€“18+6 weeksā€™ gestation in 1303 obese pregnant women from UPBEAT, a randomised controlled trial of a behavioural intervention. Twenty one candidate biomarkers associated with insulin resistance, and a targeted nuclear magnetic resonance (NMR) metabolome were measured. Prediction models were constructed using stepwise logistic regression. Twenty six percent of women (n = 337) developed GDM (International Association of Diabetes and Pregnancy Study Groups criteria). A model based on clinical and anthropometric variables (age, previous GDM, family history of type 2 diabetes, systolic blood pressure, sum of skinfold thicknesses, waist:height and neck:thigh ratios) provided an area under the curve of 0.71 (95%CI 0.68ā€“0.74). This increased to 0.77 (95%CI 0.73ā€“0.80) with addition of candidate biomarkers (random glucose, haemoglobin A1c (HbA1c), fructosamine, adiponectin, sex hormone binding globulin, triglycerides), but was not improved by addition of NMR metabolites (0.77; 95%CI 0.74ā€“0.81). Clinically translatable models for GDM prediction including readily measurable variables e.g. mid-arm circumference, age, systolic blood pressure, HbA1c and adiponectin are described. Using a ā‰„35% risk threshold, all models identified a group of high risk obese women of whom approximately 50% (positive predictive value) later developed GDM, with a negative predictive value of 80%. Tools for early pregnancy identification of obese women at risk of GDM are described which could enable targeted interventions for GDM prevention in women who will benefit the most

    Nurse staffing levels revisited: a consideration of key issues in nurse staffing levels and skill mix research.

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    AIM: This paper revisits the published evidence relating to how nurse staffing levels impact on patient, nurse and service outcomes and considers the implications of this body of research for nurse managers in their quest to determine optimum nursing numbers. BACKGROUND: Within the context of the recognized global nursing shortage and particular local pressures within international health services, questions of appropriate nurse staffing levels and skill mix are once again becoming increasingly important. It would seem that the determination of optimum nurse staffing levels and skill mix is a central issue in relation to health service governance, service user involvement, as well as in the recruitment, retention and well-being of nursing staff across the service sectors. METHODS: A review of published evidence was carried out, applying key principles of the systematic method, in order to facilitate the identification of current factors and issues in nurse staffing levels research. The review did not seek to address a specific research question. The search covered 10 years from 1998 to 2008 and identified more than 500 relevant papers, giving a wide international perspective. KEY ISSUES: The majority of research in the field relates to the acute service sector and there are considerable similarities in issues that transcend international boundaries. Much of the research focuses on the impact on patients and nurses of 'poor' nurse staffing levels. More recent studies have explored the impact of nurse staffing levels on the service organization itself. However, while there may be an association between models of nurse staffing and outcomes, there is insufficient evidence to establish a causal relationship between these factors. In this context it is perhaps time to reconsider how nursing outcomes are defined and measured. IMPLICATIONS FOR NURSING MANAGEMENT AND CONCLUSION: Nurse managers, commissioners of services and workforce planners need to be cognisant of key issues and analyses in the consideration of nurse staffing levels. Not least of these is the need for a healthy degree of caution regarding the supposed objectivity, scientific basis, or evidence base, for rational calculation of optimum nurse staffing levels
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