相关论文: Making Public Safety Data Accessible in the Westsi…
Increasingly available high-frequency location datasets derived from smartphones provide unprecedented insight into trajectories of human mobility. These datasets can play a significant and growing role in informing preparedness and…
Recently, pedestrian behavior research has shifted towards machine learning based methods and converged on the topic of modeling pedestrian interactions. For this, a large-scale dataset that contains rich information is needed. We propose a…
A large amount of data is produced every second from modern information systems such as mobile devices, the world wide web, Internet of Things, social media, etc. Analysis and mining of this massive data requires a lot of advanced tools and…
This paper introduces a strategic planning tool for master-planned communities designed specifically to quantify residents' subjective preferences about large investments in amenities and infrastructure projects. Drawing on data obtained…
Monitoring of the large-scale data processing of the ATLAS experiment includes monitoring of production and user analysis jobs. The Experiment Dashboard provides a common job monitoring solution, which is shared by ATLAS and CMS…
Business intelligence (BI) tools for database analytics have come a long way and nowadays also provide ready insights or visual query explorations, e.g. QuickInsights by Microsoft Power BI, SpotIQ by ThoughtSpot, Zenvisage, etc. In this…
Ambient air pollution is a pervasive issue with wide-ranging effects on human health, ecosystem vitality, and economic structures. Utilizing data on ambient air pollution concentrations, researchers can perform comprehensive analyses to…
Making data visualizations accessible for people with disabilities remains a significant challenge in current practitioner efforts. Existing visualizations often lack an underlying navigable structure, fail to engage necessary input…
Coastal communities are confronted with a growing incidence of climate-induced flooding, necessitating adaptation measures for resilience. In this paper, we introduce a framework that integrates an urban digital twin with a geospatial…
California is challenged by its worst drought in 600 years and faces future water uncertainty. Pioneering new data infrastructure to integrate water use data across California's more than a thousand water providers will support water…
The capability afforded by Vehicle-to-Vehicle communication improves situational awareness and provides advantages for many of the traffic problems caused by reduced visibility or No-Line-of-Sight situations, being useful for both…
Any data analysis, especially the data sets that may be changing often or in real-time, consists of at least three important synchronized components: i) figuring out what to infer (objectives), ii) analysis or computation of objectives, and…
Crime prevention measures, aiming for the effective and efficient spending of public resources, rely on the empirical analysis of spatial and temporal data for public safety outcomes. We perform a variable-density cluster analysis on crime…
Autonomous vehicles require accurate and reliable short-term trajectory predictions for safe and efficient driving. While most commercial automated vehicles currently use state machine-based algorithms for trajectory forecasting, recent…
An explorative data analysis system should be aware of what the user already knows and what the user wants to know of the data: otherwise the system cannot provide the user with the most informative and useful views of the data. We propose…
The use of social media is ubiquitous and nowadays well-established in our everyday life, but increasingly also before, during or after emergencies. The produced data is spread across several types of social media and can be used by…
As transportation technology advances, the demand for connected vehicle infrastructure has greatly increased to improve their efficiency and safety. One area of advancement, Cooperative Driving Automation (CDA) still relies on expensive…
As the population of world is increasing, and even more concentrated in urban areas, ensuring public safety is becoming a taunting job for security personnel and crowd managers. Mass events like sports, festivals, concerts, political…
Data spaces represent an emerging paradigm that facilitates secure and trusted data exchange through foundational elements of data interoperability, sovereignty, and trust. Within a data space, data items, potentially owned by different…
Case records on victims of human trafficking are highly sensitive, yet the ability to share such data is critical to evidence-based practice and policy development across government, business, and civil society. We present new methods to…