The trade-off between spatial and temporal resolution limits the acquisition of dense time series of Landsat images, and limits the ability to properly monitor land surface dynamics in time. Spatiotemporal image fusion methods provide a cost-efficient alternative to generate dense time series of Landsat-like images for applications that require both high spatial and temporal resolution images. The ...

Cloud providers offering Software-as-a-Service (SaaS) are increasingly being trusted by customers to store sensitive data. Companies often monetize such personal data through curation and analysis, providing customers with personalized application experiences and targeted advertisements. Personal data is often accompanied by strict privacy and security policies, requiring data processing to be ...

Human-model data are very valuable and important in biomedical research. Ethical and economical constraints limit the access to such data, and consequently these datasets rarely comprise more than a few hundred observations. As measurements are comparatively cheap, the tendency is to measure as many things as possible for the few, valuable participants in a study. With -omics technologies it is cheap ...

PCMSolver is an open‐source library for continuum electrostatic solvation. It can be combined with any quantum chemistry code and requires a minimal interface with the host program, greatly reducing programming effort. As input, PCMSolver needs only the molecular geometry to generate the cavity and the expectation value of the molecular electrostatic potential on the cavity surface. It then returns ...

Neural networks, in the context of deep learning, show much promise in becoming an important tool with the purpose assisting medical doctors in disease detection during patient examinations. However, the current state of deep learning is something of a "black box", making it very difficult to understand what internal processes lead to a given result. This is not only true for non-technical users but ...

The objective of this paper is to investigate the dependency of oil spill observations in polarimetric SAR data on imaging geometry, i.e., on incidence angle and look direction relative to the wind. The study is based on quad-polarization data acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar over experimental oil slicks under relatively high winds of 10–12 m/s over an 8-hour period. ...

Icebergs can cause a significant danger for shipping, offshore oil exploration, and undersea or subsea pipelines and production facilities. Synthetic aperture radar (SAR) is very valuable tool of detecting and monitoring icebergs in the often dark and cloud-covered polar regions. Detection of small icebergs floating in nonhomegeous sea clutter environments is a challenging task in remote sensing. ...

This dissertation argues that we can develop unified systems for reproducible exploration and analysis of high-throughput biological datasets. We propose an approach, Small Modular Entities (SME), that orchestrates the execution of analysis pipelines and data exploration applications. We realize SMEs using software container technologies together with well-defined interfaces, configuration, and ...

Starting with Lie’s classification of finite-dimensional transitive Lie algebras of vector fields on <b>C²</b> we construct transitive Lie algebras of vector fields on the bundle <b>C² x C</b> by lifting the Lie algebras from the base. There are essentially three types of transitive lifts and we compute all of them for the Lie algebras from Lie’s classification. The simplest ...

The wetting behavior of homogeneous systems is now well understood at the macroscopic scale. However, this understanding offers little predictive power regarding wettability when mesoscopic chemical and morphological heterogeneities come into play. The fundamental interest in the effect of heterogeneity on wettability is derived from its high technological relevance in several industries, including ...