相关论文: Understanding Public Safety Trends in Calgary thro…

We use high resolution data to investigate the association between crime incidence and proximity to different types of public schools over the past fifteen years in the city of Philadelphia. We employ two statistical methods, regression…

Understanding human mobility patterns is important in applications as diverse as urban planning, public health, and political organizing. One rich source of data on human mobility is taxi ride data. Using the city of Chicago as a case…

The objective of this work is to take advantage of deep neural networks in order to make next day crime count predictions in a fine-grain city partition. We make predictions using Chicago and Portland crime data, which is augmented with…

To what extent can the strength of a local urban community impact neighborhood safety? We construct measures of community vibrancy based on a unique dataset of block party permit approvals from the City of Philadelphia. Our first measure…

We apply spectral clustering and multislice modularity optimization to a Los Angeles Police Department field interview card data set. To detect communities (i.e., cohesive groups of vertices), we use both geographic and social information…

More than 80 civic tech communities in Japan are developing information technology (IT) systems to solve their regional issues. Collaboration among such communities across different regions assists in solving their problems because some…

The pattern of pedestrian crashes varies greatly depending on lighting circumstances, emphasizing the need of examining pedestrian crashes in various lighting conditions. Using Louisiana pedestrian fatal and injury crash data (2010-2019),…

We report on a quantitative analysis of relationships between the number of homicides, population size and other ten urban metrics. By using data from Brazilian cities, we show that well defined average scaling laws with the population size…

This paper focuses on finding spatial and temporal criminal hotspots. It analyses two different real-world crimes datasets for Denver, CO and Los Angeles, CA and provides a comparison between the two datasets through a statistical analysis…

The explosive growth of cyber attacks nowadays, such as malware, spam, and intrusions, caused severe consequences on society. Securing cyberspace has become an utmost concern for organizations and governments. Traditional Machine Learning…

Car sharing is one the pillars of a smart transportation infrastructure, as it is expected to reduce traffic congestion, parking demands and pollution in our cities. From the point of view of demand modelling, car sharing is a weak signal…

We intend to identify relationships between cancer cases and pollutant emissions and attempt to understand whether cancer in children is typically located together with some specific chemical combinations or is independent. Co-location…

In public health, various data are rigorously collected and published with open access. These data reflect the environmental and non-environmental characteristics of heterogeneous neighborhoods in cities. In the present study, we aimed to…

Precise knowledge about the size of a crowd, its density and flow can provide valuable information for safety and security applications, event planning, architectural design and to analyze consumer behavior. Creating a powerful machine…

Ensuring urban safety is an essential part of developing sustainable cities. An urban safety map can assist cities to prevent future crimes. However, mapping is costly in terms of both time and money due to the need for manual data…

Community detection and edge prediction are both forms of link mining: they are concerned with discovering the relations between vertices in networks. Some of the vertex similarity measures used in edge prediction are closely related to the…

Researchers regard crime as a social phenomenon that is influenced by several physical, social, and economic factors. Different types of crimes are said to have different motivations. Theft, for instance, is a crime that is based on…

Association Rule Mining is a machine learning method for discovering the interesting relations between the attributes in a huge transaction database. Typically, algorithms for Association Rule Mining generate a huge number of association…

With the focus that cities around the world have put on sustainable transportation during the past few years, biking has become one of the foci for local governments around the world. Cities all over the world invest in bike infrastructure,…

Analyses of occurrences of residential burglary in urban areas have shown that crime rates are not spatially homogeneous: rates vary across the network of city streets, resulting in some areas being far more susceptible to crime than…