Maritime data integration and analysis: Recent progress and research challenges

The correlated exploitation of heterogeneous data sources offering very large historical as well as streaming data is important to increasing the accuracy of computations when analysing and predicting future states of moving entities. This is particularly critical in the maritime domain, where online tracking, early recognition of events, and real-time forecast of anticipated trajectories of vessels are crucial to safety and operations at sea. The objective of this paper is to review current research challenges and trends tied to the integration, management, analysis, and visualization of objects moving at sea as well as a few suggestions for a successful development of maritime forecasting and decision-support systems

MARITIME DATA INTEGRATION AND ANALYSIS: RECENT PROGRESS AND RESEARCH CHALLENGES

The correlated exploitation of heterogeneous data sources offering very large historical as well as streaming data is important to increasing the accuracy of computations when analysing and predicting future states of moving entities. This is particularly critical in the maritime domain, where online tracking, early recognition of events, and real-time forecast of anticipated trajectories of vessels are crucial to safety and operations at sea. The objective of this paper is to review current research challenges and trends tied to the integration, management, analysis, and visualization of objects moving at sea as well as a few suggestions for a successful development of maritime forecasting and decision-support systems. Document type: Articl

Increasing maritime situation awareness via trajectory detection, enrichment and recognition of events

The research presented in this paper aims to show the deployment and use of advanced technologies towards processing surveillance data for the detection of events, contributing to maritime situation awareness via trajectories’ detection, synopses generation and semantic enrichment of trajectories. We first introduce the context of the maritime domain and then the main principles of the big data architecture developed so far within the European funded H2020 datAcron project. From the integration of large maritime trajectory datasets, to the generation of synopses and the detection of events, the main functions of the datAcron architecture are developed and discussed. The potential for detection and forecasting of complex events at sea is illustrated by preliminary experimental results

MARITIME DATA INTEGRATION AND ANALYSIS: RECENT PROGRESS AND RESEARCH CHALLENGES

The correlated exploitation of heterogeneous data sources offering very large historical as well as streaming data is important to increasing the accuracy of computations when analysing and predicting future states of moving entities. This is particularly critical in the maritime domain, where online tracking, early recognition of events, and real-time forecast of anticipated trajectories of vessels are crucial to safety and operations at sea. The objective of this paper is to review current research challenges and trends tied to the integration, management, analysis, and visualization of objects moving at sea as well as a few suggestions for a successful development of maritime forecasting and decision-support systems. Document type: Articl

Big data analytics for time critical maritime and aerial mobility forecasting

The correlated exploitation of heterogeneous data sources offering very large archival and streaming data is important to increase the accuracy of computations when analysing and predicting future states of moving entities. Aiming to significantly advance the capacities of systems to improve safety and effectiveness of critical operations involving a large number of moving entities in large geographical areas, this paper describes progress achieved towards time critical big data analytics solutions to user-defined challenges in the air-traffic management and maritime domains. Besides, this paper presents further research challenges concerning data integration and management, predictive analytics for trajectory and events forecasting, and visual analytics

Visual exploration of movement and event data with interactive time masks

We introduce the concept of time mask, which is a type of temporal filter suitable for selection of multiple disjoint time intervals in which some query conditions fulfil. Such a filter can be applied to time-referenced objects, such as events and trajectories, for selecting those objects or segments of trajectories that fit in one of the selected time intervals. The selected subsets of objects or segments are dynamically summarized in various ways, and the summaries are represented visually on maps and/or other displays to enable exploration. The time mask filtering can be especially helpful in analysis of disparate data (e.g., event records, positions of moving objects, and time series of measurements), which may come from different sources. To detect relationships between such data, the analyst may set query conditions on the basis of one dataset and investigate the subsets of objects and values in the other datasets that co-occurred in time with these conditions. We describe the desired features of an interactive tool for time mask filtering and present a possible implementation of such a tool. By example of analysing two real world data collections related to aviation and maritime traffic, we show the way of using time masks in combination with other types of filters and demonstrate the utility of the time mask filtering

Role of uncertainties on time dependent behavior of prestressed and cable stayed concrete bridges

The behavior of pre-stressed and of cable stayed concrete bridges may be strongly affected by the time dependent response due to the creep and shrinkage of concrete. The assessment of safety and serviceability performance of these structures during their whole service life requires a reliable estimation of the influence of these phenomena. The conventional design of pre-stress losses and, in general, of the time dependent behavior of non homogeneous structures, like cable stayed bridges, uses tools of analysis which involve many uncertain quantities, such as environmental factors, the material characteristics and the intensities of the tension in cables. Also construction imperfections may strongly influence the final structural response. After some brief recalls regarding the time dependent analysis in presence of creep and shrinkage, this paper studies, through a probabilistic approach, the effects due to a large variations of the basic variables. Two cases are studied: the first one is less sensitive to uncertain data, while the second is strongly affected by them. In the case of a cable stayed bridge, made of a concrete deck, subjected to creep effects and suspended to a set of pretensioned cables, the role of uncertainties in the pretensioning forces, in the relative humidity and in the concrete strength do not influence the time dependent behavior sensibly. The standard deviation with respect to the mean tension in the cables is relatively small and, most of all, it progressively reduces. Hence the system seems to be self-stabilizing over time. On the contrary, in the case of a prestressed cantilever beam, the effects of uncertainties in the pretensioning forces and in the concrete strength cause a significant variance of the tip deflections. Both deflections and their variance increase over time and, speaking about bridges, they may strongly modify the vertical attitude of the structure. These effects are emphasized when the prestressing is applied a few days after curing. Such results outline the limits of the traditional deterministic analyses and suggest the need of further studies on this topic

Inquérito sorológico para toxoplasmose em equinos na região de Botucatu-SP

The frequency of anti-T.gondii IgG antibodies was evaluated and compared in 253 sera samples of equines by modified agglutination test (MAT) and indirect immunofluorescent antibody test (IFAT). Fifteen samples (5.9%) were positive by IFAT and 32 (12.6%) by MAT. Significant difference between the two methods was found when a cutoff titer of 16 was established. There was no correlation with breed, gender, and age of horses examined

Adaptive Management of Multigranular Spatio-Temporal Object Attributes

In applications involving spatio-temporal modelling, granularities of data may have to adapt according to the evolving semantics and significance of data. In this paper we define ST 2_ODMGe, a multigranular spatio-temporal model supporting evolutions , which encompass the dynamic adaptation of attribute granularities, and the deletion of attribute values. Evolutions are specified as Event - Condition - Action rules and are executed at run-time. The event, the condition, and the action may refer to a period of time and a geographical area. The evolution may also be constrained by the attribute values. The ability of dynamically evolving the object attributes results in a more flexible management of multigranular spatio-temporal data but it requires revisiting the notion of object consistency with respect to class definitions and access to multigranular object values. Both issues are formally investigated in the paper