Dagstuhl Annual Report January - December 2011

The International Conference and Research Center for Computer Science is a non-profit organization. Its objective is to promote world-class research in computer science and to host research seminars which enable new ideas to be showcased, problems to be discussed and the course to be set for future development in this field. The work being done to run this informatics center is documented in this report for the business year 2011

Lightning Talk:"I solemnly pledge" A Manifesto for Personal Responsibility in the Engineering of Academic Software

International audienceSoftware is fundamental to academic research work, both as part of the method and as the result of research. In June 2016 25 people gathered at Schloss Dagstuhl for a week-long Perspectives Workshop and began to develop a manifesto which places emphasis on the scholarly value of academic software and on personal responsibility. Twenty pledges cover the recognition of academic software, the academic software process and the intellectual content of academic software. This is still work in progress. Through this lightning talk, we aim to get feedback and hone these further, as well as to inspire the WSSSPE audience to think about actions they can take themselves rather than actions they want others to take. We aim to publish a more fully developed Dagstuhl Manifesto by December 2016

Finite difference methods fengshui: alignment through a mathematics of arrays

Numerous scientific-computational domains make use of array data. The core computing of the numerical methods and the algorithms involved is related to multi-dimensional array manipulation. Memory layout and the access patterns of that data are crucial to the optimal performance of the array-based computations. As we move towards exascale computing, writing portable code for efficient data parallel computations is increasingly requiring an abstract productive working environment. To that end, we present the design of a framework for optimizing scientific array-based computations, building a case study for a Partial Differential Equations solver. By embedding the Mathematics of Arrays formalism in the Magnolia programming language, we assemble a software stack capable of abstracting the continuous high-level application layer from the discrete formulation of the collective array-based numerical methods and algorithms and the final detailed low-level code. The case study lays the groundwork for achieving optimized memory layout and efficient computations while preserving a stable abstraction layer independent of underlying algorithms and changes in the architecture.Peer ReviewedPostprint (author's final draft

Model pathway diagrams for the representation of mathematical models

Mathematical models are the foundation of numerical simulation of optoelectronic devices. We present a concept for a machine-actionable as well as human-understandable representation of the mathematical knowledge they contain and the domain-specific knowledge they are based on. We propose to use theory graphs to formalize mathematical models and model pathway diagrams to visualize them. We illustrate our approach by application to the van Roosbroeck system describing the carrier transport in semiconductors by drift and diffusion. We introduce an approach for the block-based composition of models from simpler components

Intrusion detection using machine learning-hardened domain generation algorithms

Machine learning has recently been applied in a variety of areas in information technology due to its superiority over the typical computer algorithms. The machine learning approaches are being integrated into cybersecurity detection approaches with the primary aim of supporting or providing an alternative to the first line of defense in networks. Although the automation of these detection and analysis systems is potent in today’s changing technological environment, the usefulness of machine learning in cybersecurity requires evaluation. In this research, we present an analysis and address cybersecurity concerns of machine learning techniques used in the detection of intrusion, spam, and malware. The analysis will entail the evaluation of the current maturity of the machine learning solutions when identifying their primary limitations, which has prevented the immediate adoption of machine learning in cybersecurity

Integration of SPOC courses in the subjects of degree. A practical experience

Los cursos SPOC (del inglés Small Private Online Course) son cursos de formación a distancia con una metodología participativa y colaborativa, características que comparten con los MOOC, aunque en este caso, los SPOC están destinados a grupos reducidos de estudiantes de perfil bien definido. La combinación de la enseñanza virtual y la enseñanza presencial es un recurso positivo para la comunidad universitaria que es importante analizar. En este estudio se elabora una comparación de dos grupos de estudiantes universitarios que realizan dos experiencias de aprendizaje, desarrolladas en contextos de aprendizaje muy diferentes, uno online a través de un curso SPOC insertado en una asignatura de Grado y otro presencial, en la que el alumnado hace el mismo curso pero dentro del contexto del aula.The SPOC (Small Private Online Course) courses are distance learning courses with am participatory and collaborative methodology, characteristics that they share with the MOOCs, although in this case, the SPOCs are aimed at small groups of well-defined students. The combination of virtual teaching and face-to-face teaching is a positive resource for the university community that is important to analyze. This study compiles a comparison of two groups of university students who carry out two learning experiences, developed in very different learning contexts, one online through an SPOC course inserted in a subject of Degree and one face-to-face, in which the Students do the same course but within the context of the classroom