•A car crash detection system based on an ensemble deep learning model is proposed.•An ensemble deep learning model uses video and audio data from dashboard cameras.•A GRU-and-CNN-based base ...classifier is developed for video data.•A GRU-based and a CNN-based base classifiers are developed for audio data.•The proposed system establishes state-of-the-art classification performances.
Due to the increase in motor vehicle accidents, there is a growing need for high-performance car crash detection systems. The authors of this research propose a car crash detection system that uses both video data and audio data from dashboard cameras in order to improve car crash detection performance. While most existing car crash detection systems depend on single modal data (i.e., video data or audio data only), the proposed car crash detection system uses an ensemble deep learning model based on multimodal data (i.e., both video and audio data), because different types of data extracted from one information source (e.g., dashboard cameras) can be regarded as different views of the same source. These different views complement one another and improve detection performance, because one view may have information that the other view does not contain. In this research, deep learning techniques, gated recurrent unit (GRU) and convolutional neural network (CNN), are used to develop a car crash detection system. A weighted average ensemble is used as an ensemble technique. The proposed car crash detection system, which is based on multiple classifiers that use both video and audio data from dashboard cameras, is validated using a comparison with single classifiers that use video data or audio data only. Car accident YouTube clips are used to validate this research. The experimental results indicate that the proposed car crash detection system performs significantly better than single classifiers. It is expected that the proposed car crash detection system can be used as part of an emergency road call service that recognizes traffic accidents automatically and allows immediate rescue after transmission to emergency recovery agencies.
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DAX is a library of functions and operators that can be combined to build formulas and expressions in Power BI Desktop, Azure Analysis Services, SQL Server Analysis Services, and Power Pivot in ...Excel. This book is a desk reference for people who want to leverage DAX's functionality and flexibility in BI and data analytics domains.
In recent years, new types of interactive analytical dashboard features have emerged for operational decision support systems (DSS). Analytical components of such features solve optimization problems ...hidden from the human eye, whereas interactive components involve the individual in the optimization process via graphical user interfaces (GUIs). Despite their expected value for organizations, little is known about the effectiveness of interactive analytical dashboards in operational DSS or their influences on human cognitive abilities. This paper contributes to the closing of this gap by exploring and empirically testing the effects of interactive analytical dashboard features on situation awareness (SA) and task performance in operational DSS. Using the theoretical lens of SA, we develop hypotheses about the effects of a what-if analysis as an interactive analytical dashboard feature on operational decision-makers' SA and task performance. The resulting research model is studied with a laboratory experiment, including eye-tracking data of 83 participants. Our findings show that although a what-if analysis leads to higher task performance, it may also reduce SA, nourishing a potential out-of-the-loop problem. Thus, designers and users of interactive analytical dashboards have to carefully mitigate these effects in the implementation and application of operational DSS. In this article, we translate our findings into implications for designing dashboards within operational DSS to help practitioners in their efforts to address the danger of the out-of-the-loop syndrome.
•A what-if analysis positively impacts the task performance•A what-if analysis is not cost-free and can trigger an out-of-the-loop problem•Using the SAGAT seems most promising to measure SA in production planning
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We need to rapidly detect and respond to public rumours, perceptions, attitudes and behaviours around COVID-19 and control measures. The creation of an interactive platform and dashboard to provide ...real-time alerts of rumours and concerns about coronavirus spreading globally would enable public health officials and relevant stakeholders to respond rapidly with a proactive and engaging narrative that can mitigate misinformation.
The COVID-19 pandemic is unlikely to end until there is global roll-out of vaccines that protect against severe disease and preferably drive herd immunity. Regulators in numerous countries have ...authorised or approved COVID-19 vaccines for human use, with more expected to be licensed in 2021. Yet having licensed vaccines is not enough to achieve global control of COVID-19: they also need to be produced at scale, priced affordably, allocated globally so that they are available where needed, and widely deployed in local communities. In this Health Policy paper, we review potential challenges to success in each of these dimensions and discuss policy implications. To guide our review, we developed a dashboard to highlight key characteristics of 26 leading vaccine candidates, including efficacy levels, dosing regimens, storage requirements, prices, production capacities in 2021, and stocks reserved for low-income and middle-income countries. We use a traffic-light system to signal the potential contributions of each candidate to achieving global vaccine immunity, highlighting important trade-offs that policy makers need to consider when developing and implementing vaccination programmes. Although specific datapoints are subject to change as the pandemic response progresses, the dashboard will continue to provide a useful lens through which to analyse the key issues affecting the use of COVID-19 vaccines. We also present original data from a 32-country survey (n=26 758) on potential acceptance of COVID-19 vaccines, conducted from October to December, 2020. Vaccine acceptance was highest in Vietnam (98%), India (91%), China (91%), Denmark (87%), and South Korea (87%), and lowest in Serbia (38%), Croatia (41%), France (44%), Lebanon (44%), and Paraguay (51%).
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Recent statistics show that almost 1/4 of a million people have died and four million people are affected either with mild or serious health problems caused by coronavirus (COVID‐19). These numbers ...are rapidly increasing (World Health Organization, May 3, 2020c). There is much concern during this pandemic about the spread of misleading or inaccurate information. This article reports on a small study which attempted to identify the types and sources of COVID‐19 misinformation. The authors identified and analysed 1225 pieces of COVID‐19 fake news stories taken from fact‐checkers, myth‐busters and COVID‐19 dashboards. The study is significant given the concern raised by the WHO Director‐General that ‘we are not just fighting the pandemic, we are also fighting infodemic’. The study concludes that the COVID‐19 infodemic is full of false claims, half backed conspiracy theories and pseudoscientific therapies, regarding the diagnosis, treatment, prevention, origin and spread of the virus. Fake news is pervasive in social media, putting public health at risk. The scale of the crisis and ubiquity of the misleading information require that scientists, health information professionals and journalists exercise their professional responsibility to help the general public identify fake news stories. They should ensure that accurate information is published and disseminated.J.M.
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Since the mid-1990s a plethora of indicator projects have been developed and adopted by cities seeking to measure and monitor various aspects of urban systems. These have been accompanied by city ...benchmarking endeavours that seek to compare intra- and inter-urban performance. More recently, the data underpinning such projects have started to become more open to citizens, more real-time in nature generated through sensors and locative/social media, and displayed via interactive visualisations and dashboards that can be accessed via the internet. In this paper, we examine such initiatives arguing that they advance a narrowly conceived but powerful realist epistemology - the city as visualised facts - that is reshaping how managers and citizens come to know and govern cities. We set out how and to what ends indicator, benchmarking and dashboard initiatives are being employed by cities. We argue that whilst these initiatives often seek to make urban processes and performance more transparent and to improve decision making, they are also underpinned by a naive instrumental rationality, are open to manipulation by vested interests, and suffer from often unacknowledged methodological and technical issues. Drawing on our own experience of working on indicator and dashboard projects, we argue for a conceptual re-imaging of such projects as data assemblages - complex, politically-infused, socio-technical systems that, rather than reflecting cities, actively frame and produce them.
To describe the creation of an interactive dashboard to advance the understanding of the COVID-19 pandemic from an equity and urban health perspective across 30 large US cities that are members of ...the Big Cities Health Coalition (BCHC).
We leveraged the Drexel‒BCHC partnership to define the objectives and audience for the dashboard and developed an equity framework to conceptualize COVID-19 inequities across social groups, neighborhoods, and cities. We compiled data on COVID-19 trends and inequities by race/ethnicity, neighborhood, and city, along with neighborhood- and city-level demographic and socioeconomic characteristics, and built an interactive dashboard and Web platform to allow interactive comparisons of these inequities across cities.
We launched the dashboard on January 21, 2021, and conducted several dissemination activities. As of September 2021, the dashboard included data on COVID-19 trends for the 30 cities, on inequities by race/ethnicity in 21 cities, and on inequities by neighborhood in 15 cities.
This dashboard allows public health practitioners to contextualize racial/ethnic and spatial inequities in COVID-19 across large US cities, providing valuable insights for policymakers. (
. 2022;112(6):904-912. https://doi.org/10.2105/AJPH.2021.306708).
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The book will help you build effective business intelligence dashboards using the latest features of QlikView. You will create different types of visualizations such as bar charts, interactive plots, ...and more. With this book, you will learn how to gain actionable insights from your data and communicate them across to relevant stakeholders in.
As the COVID-19 pandemic has clearly demonstrated, the role of local data in guiding public health action cannot be overstated. Government agencies, frontline community organizations, health care ...institutions, policymakers, researchers, and advocates all depend on data to guide their work and, especially during COVID-19, take swift action. Much has been written about gaps in the nation's surveillance capacity and the need to improve reporting timeliness.1 Less has been written about an ever-growing array of health-related data aggregation dashboards that have stepped in to address some of these gaps. These resources build on surveillance tenets (to provide data to assess burden and distribution of adverse health events and prioritize public health actions) and share the premise that data draw power and value from being placed in context and compared across jurisdictions and geographies, overtime, between population groups, and by community characteristics. Indeed, one of the driving forces behind data dashboards has been an effort to reframe how we think about health and its many determinants. Another driving force has been the goal of making data available to wider and more diverse audiences, often with visualizations intended to catalyze change. But are these data dashboards meeting their intended promise? Are they useful to public health stakeholders? We believe the answer is rapidly trending toward "yes." The introduction of data dashboards by nongovernmental entities is relatively recent. One of the first, the County Health Rankings & Roadmaps (CHRR), was released in 2010 by the University of Wisconsin in partnership with the Robert Wood Johnson Foundation.2 By parsing data from multiple data sources, CHRR provided the public with ready access to county-level data on a host of metrics. Since then, foundations and federal agencies have supported the development of other dashboards to expand access to data on health and its drivers.1 The purposes of dashboards can vary. Some analyze health and health equity data to distinct geographic boundaries.3 Others present and disseminate a new metric.4 Still others aggregate local policies and laws that affect population health to guide research and advocacy.5 During the rapidly unfolding COVID-19 pandemic, many state and local health departments struggled to make data publicly available, and the Johns Hopkins University COVID Tracker quickly became the "go-to" data source for by-the-day counts of COVID-19 cases, deaths, tests, and vaccinations.6 Other COVID-19 dashboards have since drawn explicit attention to COVID-19 inequities7-9 (see Table 1 for examples).
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