Just-In-Time Data Virtualization: Lightweight Data Management with ViDa
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Database systems access memory either sequentially or randomly. Contrary to sequential access and despite the extensive efforts of
computer architects, compiler writers, and system builders, random access to data larger than the processor cache has been s ...
Advances in data acquisition technologies and supercomputing for large-scale simulations have led to an exponential growth in the volume of spatial data. This growth is accompanied by an increase in data complexity, such as spatial density, but also by mor ...
Modern applications accumulate data at an exponentially increasing rate and traditional database systems struggle to keep up.
Decision support systems used in industry, rely heavily on data analysis, and require real-time responses irrespective of data siz ...
We study user interaction with touchscreens based on swipe gestures for personal authentication. This approach has been analyzed only recently in the last few years in a series of disconnected and limited works. We summarize those recent efforts and then c ...
Deletion is a core facet of Online Social Networks (OSNs). For users, deletion is a tool to remove what they have shared and control their data. For OSNs, robust deletion is both an obligation to their users and a risk when developer mistakes inevitably oc ...
Medical data are often scattered among multiple clinics, hospitals, insurance companies, pharmacies, and research institutions that store and process personal healthcare information. The use of information and communication technologies for health (eHealth ...
Despite an increasing interest in speaker recognition technologies, a significant obstacle still hinders their wide deployment --- their high vulnerability to spoofing or presentation attacks. These attacks can be easy to perform. For instance, if an attac ...
In the past two decades, the use of ontologies has been proven to be an effective tool for enriching existing information systems in the digital data modelling domain and exploiting those assets for semantic interoperability. With the rise of Industry 4.0, ...
Modern server hardware is increasingly heterogeneous as hardware accelerators, such as GPUs, are used together with multicore CPUs to meet the computational demands of modern data analytics workloads. Unfortunately, query parallelization techniques used by ...
Data models capture the structure and characteristic properties of data entities, e.g., in terms of a database schema or an ontology. They are the backbone of diverse applications, reaching from information integration, through peer-to-peer systems and ele ...