empathi: An ontology for Emergency Managing and Planning about Hazard Crisis

In the domain of emergency management during hazard crises, having sufficient situational awareness information is critical. It requires capturing and integrating information from sources such as satellite images, local sensors and social media content generated by local people. A bold obstacle to capturing, representing and integrating such heterogeneous and diverse information is lack of a proper ontology which properly conceptualizes this domain, aggregates and unifies datasets. Thus, in this paper, we introduce empathi ontology which conceptualizes the core concepts concerning with the domain of emergency managing and planning of hazard crises. Although empathi has a coarse-grained view, it considers the necessary concepts and relations being essential in this domain. This ontology is available at https://w3id.org/empathi/

Problems of methodology and explanation in word order universals research

Ever since the publication of Greenberg 1963, word order typologists have attempted to formulate and refine implicational universals of word order so as to characterize the restricted distribution of certain word order patterns, and in some cases have also attempted to develop general principles to explain the existence of those universals

Probabilistic modelling and inference of human behaviour from mobile phone time series

With an estimated 4.1 billion subscribers around the world, the mobile phone offers a unique opportunity to sense and understand human behaviour from location, co-presence and communication data. While the benefit of modelling this unprecedented amount of data is widely recognised, a number of challenges impede the development of accurate behaviour models. In this thesis, we identify and address two modelling problems and show that their consideration improves the accuracy of behaviour inference. We first examine the modelling of long-range dependencies in human behaviour. Human behaviour models only take into account short-range dependencies in mobile phone time series. Using information theory, we quantify long-range dependencies in mobile phone time series for the first time, demonstrate that they exhibit periodic oscillations and introduce novel tools to analyse them. We further show that considering what the user did 24 hours earlier improves accuracy when predicting user behaviour five hours or longer in advance. The second problem that we address is the modelling of temporal variations in human behaviour. The time spent by a user on an activity varies from one day to the next. In order to recognise behaviour patterns despite temporal variations, we establish a methodological connection between human behaviour modelling and biological sequence alignment. This connection allows us to compare, cluster and model behaviour sequences and introduce novel features for behaviour recognition which improve its accuracy. The experiments presented in this thesis have been conducted on the largest publicly available mobile phone dataset labelled in an unsupervised fashion and are entirely repeatable. Furthermore, our techniques only require cellular data which can easily be recorded by today's mobile phones and could benefit a wide range of applications including life logging, health monitoring, customer profiling and large-scale surveillance

Using crowdsourced geospatial data to aid in nuclear proliferation monitoring

In 2014, a Defense Science Board Task Force was convened in order to assess and explore new technologies that would aid in nuclear proliferation monitoring. One of their recommendations was for the director of National Intelligence to explore ways that crowdsourced geospatial imagery technologies could aid existing governmental efforts. Our research builds directly on this recommendation and provides feedback on some of the most successful examples of crowdsourced geospatial data (CGD). As of 2016, Special Operations Command (SOCOM) has assumed the new role of becoming the primary U.S. agency responsible for counter-proliferation. Historically, this institution has always been reliant upon other organizations for the execution of its myriad of mission sets. SOCOM's unique ability to build relationships makes it particularly suited to the task of harnessing CGD technologies and employing them in the capacity that our research recommends. Furthermore, CGD is a low cost, high impact tool that is already being employed by commercial companies and non-profit groups around the world. By employing CGD, a wider whole-of-government effort can be created that provides a long term, cohesive engagement plan for facilitating a multi-faceted nuclear proliferation monitoring process.http://archive.org/details/usingcrowdsource1094551570Major, United States ArmyMajor, United States ArmyApproved for public release; distribution is unlimited

Political decision processes, transportation investment, and changes in urban land use: a selective bibliography with particular reference to airports and highways

See this work in the Center for Transportation Research Library catalog: https://library.ctr.utexas.edu/Presto/catalogid=31630The purpose of this Bibliography is to assist with the revision and extension of intra-urban location theory, so as to explain and predict how decision making by different persons and groups affects change in intra-urban land use. Special attention is paid to the generation and resolution of conflicts over urban land in the vicinity of new transportation facilities. In particular the Bibliography focuses on new airports on rural-urban fringes and the conflicts generat.ed between politicians, citizens' and business groups, and planners over land use in their vicinity. Existing literature is sparse on this topicThe Department of Transportation, Office of University ResearchCenter for Transportation Researc