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EN
The Sinai Peninsula is a subplate located between the African and Arabian plates. It is an important subplate in the world; however, this region is poorly understood because of the shortage of geophysical data. Thus, this study focuses on built a three-dimensional (3D) high-resolution forward model of the crustal thickness with a new tectonic model and structural evaluation of the Sinai Peninsula to understand this area tectonically and determine its lithospheric and crustal thicknesses. Qualitative and quantitative interpretations of Bouguer gravity, reduced-to-the-pole (RTP) aeromagnetic, and earthquake data are explained to achieve the goals of this study. Two-dimensional (2D) interactive sequential modeling of gravity data is performed along with some well-selected profiles with existing crustal layer depth points from previous works in the studied region. Seventeen 2D models are constructed and used to determine the basement, Conrad (lower crust boundary), and Moho (upper mantle boundary) depths and to build a 3D model. Accuracy of the 3D built model is evaluated by extracting observed, calculated, and residual gravity anomaly maps. The results show that the basement rocks appear on the surface in the South of Sinai and deepen (down to 4.5 km) toward the North. The Conrad surface varies approximately from 16 km (in the northeast and southwest of Sinai) to 22.8 km (in the southeast). The Moho surface depth (i.e., crustal thickness) varies approximately from 28.8 to 34.2 km, and it deepens toward the northeastern and southwestern parts of Sinai. A tentative basement structure map is constructed from the horizontal gradient (H-gradient) filter and the 3D Euler deconvolution of the Bouguer gravity and RTP aeromagnetic data. Correlation between the geological background of the study area and the obtained results suggests that the Sinai Peninsula is tectonically active, mainly in its southern portion due to the tectonic movements along the Gulf of Suez and the Gulf of Aqaba. The crustal thickness increases southward and thins northward.
EN
In this paper, we introduce a method for survival analysis on data streams. Survival analysis (also known as event history analysis) is an established statistical method for the study of temporal “events” or, more specifically, questions regarding the temporal distribution of the occurrence of events and their dependence on covariates of the data sources. To make this method applicable in the setting of data streams, we propose an adaptive variant of a model that is closely related to the well-known Cox proportional hazard model. Adopting a sliding window approach, our method continuously updates its parameters based on the event data in the current time window. As a proof of concept, we present two case studies in which our method is used for different types of spatio-temporal data analysis, namely, the analysis of earthquake data and Twitter data. In an attempt to explain the frequency of events by the spatial location of the data source, both studies use the location as covariates of the sources.
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