Visual place recognition (VPR) is critical in not only localization and mapping for autonomous driving vehicles, but also assistive navigation for the visually impaired population. To enable a long-term VPR system on ...
详细信息
ISBN:
(纸本)9781665417143
Visual place recognition (VPR) is critical in not only localization and mapping for autonomous driving vehicles, but also assistive navigation for the visually impaired population. To enable a long-term VPR system on a large scale, several challenges need to be addressed. First, different applications could require different image view directions, such as front views for self-driving cars while side views for the low vision people. Second, VPR in metropolitan scenes can often cause privacy concerns due to the imaging of pedestrian and vehicle identity information, calling for the need for data anonymization before VPR queries and database construction. Both factors could lead to VPR performance variations that are not well understood yet. To study their influences, we present the nyu-VPR dataset that contains more than 200,000 images over a 2km x2km area near the New York University campus, taken within the whole year of 2016. We present benchmark results on several popular VPR algorithms showing that side views are significantly more challenging for current VPR methods while the influence of data anonymization is almost negligible, together with our hypothetical explanations and in-depth analysis.
The aims of the nyu Children's Health and Environment Study (CHES) are to evaluate influences of prenatal non-persistent chemical exposures on fetal and postnatal growth and pool our data with the US National Inst...
详细信息
The aims of the nyu Children's Health and Environment Study (CHES) are to evaluate influences of prenatal non-persistent chemical exposures on fetal and postnatal growth and pool our data with the US National Institutes of Health Environmental influences on Child Health Outcomes (ECHO) Program to answer collaborative research questions on the impact of the preconceptual, prenatal, and postnatal environment on childhood obesity, neurodevelopment, pre/peri/postnatal outcomes, upper and lower airway outcomes, and positive health. Eligible women were >= 18 years old, < 18 weeks pregnant, had a pregnancy that is not medically threatened, and planned to deliver at nyu Langone Hospital-Manhattan, Bellevue Hospital, or nyu Langone Hospital-Brooklyn. Between March 22, 2016 and April 15, 2019, we recruited 2469 pregnant women, from whom 2193 completed an initial questionnaire and continued into nyu CHES. Of the 2193, 88 miscarried, 28 terminated, and 20 experienced stillbirth, while 57 were lost to follow up. We report here demographic and other characteristics of the 2000 live deliveries (2037 children), from whom 1624 (80%) consented to postnatal follow-up. Data collection in pregnancy was nested in clinical care, with questionnaire and specimen collection conducted during routine prenatal visits at < 18, 18-25, and > 25 weeks gestation. These have been followed by questionnaire and specimen collection at birth and regular postpartum intervals.
As the world grapples with the COVID-19 pandemic, we as health care professionals thrive to continue to help our patients, and as orthopedic surgeons, this goal is ever more challenging. As part of a major academic te...
详细信息
As the world grapples with the COVID-19 pandemic, we as health care professionals thrive to continue to help our patients, and as orthopedic surgeons, this goal is ever more challenging. As part of a major academic tertiary medical center in New York City, the orthopedic department at New York University (nyu) Langone Health has evolved and adapted to meet the challenges of the COVID pandemic. In our report, we will detail the different aspects and actions taken by nyu Langone Health as well as nyu Langone Orthopedic Hospital and the orthopedic department in particular. Among the steps taken, the department has reconfigured its staff's assignments to help both with the institution's efforts and our patients' needs from reassigning operating room nurses to medical COVID floors to having attending surgeons cover urgent care locations. We have reorganized our residency and fellowship rotations and assignments as well as adapting our educational programs to online learning. While constantly evolving to meet the institution's and our patient demands, our leadership starts planning for the return to a new "normal". (C) 2020 Elsevier Inc. All rights reserved.
The next generation of wireless networks will use sub-THz frequencies alongside mmWave frequencies to enable multi-Gbps and low latency applications. To enable different verticals and use cases, engineers must take a ...
详细信息
ISBN:
(纸本)9798400707476
The next generation of wireless networks will use sub-THz frequencies alongside mmWave frequencies to enable multi-Gbps and low latency applications. To enable different verticals and use cases, engineers must take a holistic approach to build, analyze, and study different parts of the network and the interplay among the lower and higher layers of the protocol stack. It is of paramount importance to accurately characterize the radio propagation in diverse scenarios such as urban microcell (UMi), urban macrocell (UMa), rural macrocell (RMa), indoor hotspot (InH), and indoor factory (InF) for a wide range of frequencies. The 3GPP statistical channel model (SCM) is oversimplified and restricted to the frequency range of 0.5-100 GHz. Thus, to overcome these limitations, this paper presents a detailed implementation of the drop-based nyu channel model (nyuSIM) for the frequency range of 0.5-150 GHz for the UMi, UMa, RMa, InH, and InF scenarios. nyuSIM allows researchers to design and evaluate new algorithms and protocols for future sub-THz wireless networks in ns-3.
The coronavirus disease 2019 (COVID-19) pandemic has accelerated the drive of health-care delivery towards virtual-care platforms. While the potential of virtual care is significant, there are challenges to the implem...
详细信息
The coronavirus disease 2019 (COVID-19) pandemic has accelerated the drive of health-care delivery towards virtual-care platforms. While the potential of virtual care is significant, there are challenges to the implementation and scalability of virtual care as a platform, and health-care organisations are at risk of building and deploying non-strategic, costly or unsustainable virtual-health systems. In this article, we share the nyu Langone Health enterprise approach to building and scaling an integrated virtual-health platform prior to and during the COVID-19 pandemic, and offer lessons learned and recommendations for health systems that need to undertake or are currently undertaking the transition to virtual-care delivery.
作者：
Djukic, MajaFulmer, TerryAdams, Jennifer G.Lee, SabrinaTriola, Marc M.NYU
Coll Nursing New York NY 10003 USA Northeastern Univ
Bouve Coll Hlth Sci Behrakis Hlth Sci Ctr 215 Boston MA 02115 USA NYU
Sch Med Bellevue Hosp Ctr New York NY 10016 USA NYU
Dept Med Primary Care Residency Program Div Internal Med New York NY 10016 USA NYU
Sect Med Informat Div Educ Informat Sch Med New York NY 10016 USA
Interprofessional education is a critical precursor to effective teamwork and the collaboration of health care professionals in clinical settings. Numerous barriers have been identified that preclude scalable and sust...
详细信息
Interprofessional education is a critical precursor to effective teamwork and the collaboration of health care professionals in clinical settings. Numerous barriers have been identified that preclude scalable and sustainable interprofessional education (IPE) efforts. This article describes nyu3T: Teaching, Technology, Teamwork, a model that uses novel technologies such as Web-based learning, virtual patients, and high-fidelity simulation to overcome some of the common barriers and drive implementation of evidence-based teamwork curricula. It outlines the program's curricular components, implementation strategy, evaluation methods, and lessons learned from the first year of delivery and describes implications for future large-scale IPE initiatives.
Background/Objectives Excessive gestational weight gain (GWG) and pre-pregnancy obesity affect a significant portion of the US pregnant population and are linked with negative maternal and child health outcomes. The o...
详细信息
Background/Objectives Excessive gestational weight gain (GWG) and pre-pregnancy obesity affect a significant portion of the US pregnant population and are linked with negative maternal and child health outcomes. The objective of this study was to explore associations of pre-pregnancy body mass index (pBMI) and GWG with longitudinally measured maternal urinary metabolites throughout pregnancy. Subjects/Methods Among 652 participants in the New York University Children's Health and Environment Study, a longitudinal pregnancy cohort, targeted metabolomics were measured in serially collected urine samples throughout pregnancy. Metabolites were measured at median 10 (T1), 21 (T2), and 29 (T3) weeks gestation using the Biocrates AbsoluteIDQ (R) p180 Urine Extension kit. Acylcarnitine, amino acid, biogenic amine, phosphatidylcholine, lysophosphatidylcholine, sphingolipid, and sugar levels were quantified. Pregnant people 18 years or older, without type 1 or 2 diabetes and with singleton live births and valid pBMI and metabolomics data were included. GWG and pBMI were calculated using weight and height data obtained from electronic health records. Linear mixed effects models with interactions with time were fit to determine the gestational age-specific associations of categorical pBMI and continuous interval-specific GWG with urinary metabolites. All analyses were corrected for false discovery rate. Results Participants with obesity had lower long-chain acylcarnitine levels throughout pregnancy and lower phosphatidylcholine and glucogenic amino acids and higher phenylethylamine concentrations in T2 and T3 compared with participants with normal/underweight pBMI. GWG was associated with taurine in T2 and T3 and C5 acylcarnitine species, C5:1, C5-DC, and C5-M-DC, in T2. Conclusions pBMI and GWG were associated with the metabolic environment of pregnant individuals, particularly in relation to mid-pregnancy. These results highlight the importance of both preconception and prena
Site-specific wireless channel simulations via ray tracers can be used to effectively study wireless network deployments, decreasing the need for extensive site-specific radio propagation measurements. To ensure that ...
详细信息
Site-specific wireless channel simulations via ray tracers can be used to effectively study wireless network deployments, decreasing the need for extensive site-specific radio propagation measurements. To ensure that ray tracer simulations faithfully reproduce wireless channels, calibration of simulation results against real-world measurements is required. In this study, we introduce nyuRay, a 3-D ray tracer specifically tailored for mmWave and sub-THz frequencies. To reliably generate site-specific wireless channel parameters, nyuRay is calibrated using radio propagation measurements conducted at 28, 73, and 142 GHz in diverse scenarios such as outdoor areas, indoor offices, and factories. Traditional ray tracing calibration assumes angle-dependent reflection, requiring slow iterative optimization techniques with no closed-form solution. We propose a simpler and quicker novel calibration method that assumes angle-independent reflection. The effectiveness of the proposed calibration approach is demonstrated using nyuRay. When comparing the directional multipath power predicted by nyuRay to the actual measured power, the standard deviation in error was less than 3 dB in indoor office environments and less than 2 dB in outdoor and factory environments. The root mean square (rms) delay spread and angular spread were underpredicted by nyuRay due to incomplete environmental maps available for calibration;however, an overall agreement between the measured and simulated values was observed. These results highlight the high level of accuracy nyuRay provides in generating the site-specific real-world wireless channel, that could be used to generate synthetic data for machine learning.
暂无评论