Welcome to our book review site www.go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Symbolic model generation for graph properties
Graphs are ubiquitous in Computer Science. For this reason, in many areas, it is very important to have the means to express and reason about graph properties. In particular, we want to be able to check automatically if a given graph property is satisfiable. Actually, in most application scenarios it is desirable to be able to explore graphs satisfying the graph property if they exist or even to get a complete and compact overview of the graphs satisfying the graph property. We show that the tableau-based reasoning method for graph properties as introduced by Lambers and Orejas paves the way for a symbolic model generation algorithm for graph properties. Graph properties are formulated in a ...
Deep learning for computer vision in the art domain
In recent years, computer vision algorithms based on machine learning have seen rapid development. In the past, research mostly focused on solving computer vision problems such as image classification or object detection on images displaying natural scenes. Nowadays other fields such as the field of cultural heritage, where an abundance of data is available, also get into the focus of research. In the line of current research endeavours, we collaborated with the Getty Research Institute which provided us with a challenging dataset, containing images of paintings and drawings. In this technical report, we present the results of the seminar "Deep Learning for Computer Vision". In this seminar,...
On the operationalization of graph queries with generalized discrimination networks
Graph queries have lately gained increased interest due to application areas such as social networks, biological networks, or model queries. For the relational database case the relational algebra and generalized discrimination networks have been studied to find appropriate decompositions into subqueries and ordering of these subqueries for query evaluation or incremental updates of query results. For graph database queries however there is no formal underpinning yet that allows us to find such suitable operationalizations. Consequently, we suggest a simple operational concept for the decomposition of arbitrary complex queries into simpler subqueries and the ordering of these subqueries in form of generalized discrimination networks for graph queries inspired by the relational case. The approach employs graph transformation rules for the nodes of the network and thus we can employ the underlying theory. We further show that the proposed generalized discrimination networks have the same expressive power as nested graph conditions.
Automatic verification of behavior preservation at the transformation level for relational model transformation
The correctness of model transformations is a crucial element for model-driven engineering of high quality software. In particular, behavior preservation is the most important correctness property avoiding the introduction of semantic errors during the model-driven engineering process. Behavior preservation verification techniques either show that specific properties are preserved, or more generally and complex, they show some kind of behavioral equivalence or refinement between source and target model of the transformation. Both kinds of behavior preservation verification goals have been presented with automatic tool support for the instance level, i.e. for a given source and target model s...
Die Cloud für Schulen in Deutschland
Die digitale Entwicklung durchdringt unser Bildungssystem, doch Schulen sind auf die Veränderungen kaum vorbereitet: Überforderte Lehrer/innen, infrastrukturell schwach ausgestattete Unterrichtsräume und unzureichend gewartete Computernetzwerke sind keine Seltenheit. Veraltete Hard- und Software erschweren digitale Bildung in Schulen eher, als dass sie diese ermöglichen: Ein zukunftssicherer Ansatz ist es, die Rechner weitgehend aus den Schulen zu entfernen und Bildungsinhalte in eine Cloud zu überführen. Zeitgemäßer Unterricht benötigt moderne Technologie und eine zukunftsorientierte Infrastruktur. Eine Schul-Cloud (https://hpi.de/schul-cloud) kann dabei helfen, die digitale Transf...
HPI Future SOC Lab
The “HPI Future SOC Lab” is a cooperation of the Hasso-Plattner-Institut (HPI) and industrial partners. Its mission is to enable and promote exchange and interaction between the research community and the industrial partners. The HPI Future SOC Lab provides researchers with free of charge access to a complete infrastructure of state of the art hard- and software. This infrastructure includes components, which might be too expensive for an ordinary research environment, such as servers with up to 64 cores. The offerings address researchers particularly from but not limited to the areas of computer science and business information systems. Main areas of research include cloud computing, parallelization, and In-Memory technologies. This technical report presents results of research projects executed in 2013. Selected projects have presented their results on April 10th and September 24th 2013 at the Future SOC Lab Day events.
Operating systems II - student projects
EN This technical report presents the results of student projects which were prepared during the lecture “Operating Systems II” offered by the “Operating Systems and Middleware” group at HPI in the Summer term of 2020. The lecture covered ad- vanced aspects of operating system implementation and architecture on topics such as Virtualization, File Systems and Input/Output Systems. In addition to attending the lecture, the participating students were encouraged to gather practical experience by completing a project on a closely related topic over the course of the semester. The results of 10 selected exceptional projects are covered in this report. The students have completed hands-on ...
HPI Future SOC Lab: Proceedings 2012
The “HPI Future SOC Lab” is a cooperation of the Hasso-Plattner-Institut (HPI) and industrial partners. Its mission is to enable and promote exchange and interaction between the research community and the industrial partners. The HPI Future SOC Lab provides researchers with free of charge access to a complete infrastructure of state of the art hard- and software. This infrastructure includes components, which might be too expensive for an ordinary research environment, such as servers with up to 64 cores. The offerings address researchers particularly from but not limited to the areas of computer science and business information systems. Main areas of research include cloud computing, parallelization, and In-Memory technologies. This technical report presents results of research projects executed in 2012. Selected projects have presented their results on June 18th and November 26th 2012 at the Future SOC Lab Day events.
Batch regions
Business process automation improves organizations’ efficiency to perform work. In existing business process management systems, process instances run independently from each other. However, synchronizing instances carrying similar characteristics, i.e., sharing the same data, can reduce process execution costs. For example, if an online retailer receives two orders from one customer, there is a chance that they can be packed and shipped together to save shipment costs. In this paper, we use concepts from the database domain and introduce data views to business processes to identify instances which can be synchronized. Based on data views, we introduce the concept of batch regions for a context-aware instance synchronization over a set of connected activities. We also evaluate the concepts introduced in this paper with a case study comparing costs for normal and batch processing.
