Who watches the watchers: Validating the ProB Validation Tool

Over the years, ProB has moved from a tool that complemented proving, to a development environment that is now sometimes used instead of proving for applications, such as exhaustive model checking or data validation. This has led to much more stringent requirements on the integrity of ProB. In this paper we present a summary of our validation efforts for ProB, in particular within the context of the norm EN 50128 and safety critical applications in the railway domain.Comment: In Proceedings F-IDE 2014, arXiv:1404.578

Writing a Model Checker in 80 Days: Reusable Libraries and Custom Implementation

During a course on model checking we developed BMoth, a full-stack model checker for classical B, featuring both explicit-state and symbolic model checking. Given that we only had a single university term to finish the project, a particular focus was on reusing existing libraries to reduce implementation workload.In the following, we report on a selection of reusable libraries, which can be combined into a prototypical model checker relatively easily. Additionally, we discuss where custom code depending on the specification language to be checked is needed and where further optimization can take place. To conclude, we compare to other model checkers for classical B

Differential limit on the extremely-high-energy cosmic neutrino flux in the presence of astrophysical background from nine years of IceCube data

We report a quasi-differential upper limit on the extremely-high-energy (EHE) neutrino flux above $5\times 10^{6}$ GeV based on an analysis of nine years of IceCube data. The astrophysical neutrino flux measured by IceCube extends to PeV energies, and it is a background flux when searching for an independent signal flux at higher energies, such as the cosmogenic neutrino signal. We have developed a new method to place robust limits on the EHE neutrino flux in the presence of an astrophysical background, whose spectrum has yet to be understood with high precision at PeV energies. A distinct event with a deposited energy above $10^{6}$ GeV was found in the new two-year sample, in addition to the one event previously found in the seven-year EHE neutrino search. These two events represent a neutrino flux that is incompatible with predictions for a cosmogenic neutrino flux and are considered to be an astrophysical background in the current study. The obtained limit is the most stringent to date in the energy range between $5 \times 10^{6}$ and $5 \times 10^{10}$ GeV. This result constrains neutrino models predicting a three-flavor neutrino flux of $E_\nu^2\phi_{\nu_e+\nu_\mu+\nu_\tau}\simeq2\times 10^{-8}\ {\rm GeV}/{\rm cm}^2\ \sec\ {\rm sr}$at$10^9\ {\rm GeV}$. A significant part of the parameter-space for EHE neutrino production scenarios assuming a proton-dominated composition of ultra-high-energy cosmic rays is excluded.Comment: The version accepted for publication in Physical Review

Ranking in evolving complex networks

Complex networks have emerged as a simple yet powerful framework to represent and analyze a wide range of complex systems. The problem of ranking the nodes and the edges in complex networks is critical for a broad range of real-world problems because it affects how we access online information and products, how success and talent are evaluated in human activities, and how scarce resources are allocated by companies and policymakers, among others. This calls for a deep understanding of how existing ranking algorithms perform, and which are their possible biases that may impair their effectiveness. Many popular ranking algorithms (such as Google’s PageRank) are static in nature and, as a consequence, they exhibit important shortcomings when applied to real networks that rapidly evolve in time. At the same time, recent advances in the understanding and modeling of evolving networks have enabled the development of a wide and diverse range of ranking algorithms that take the temporal dimension into account. The aim of this review is to survey the existing ranking algorithms, both static and time-aware, and their applications to evolving networks. We emphasize both the impact of network evolution on well-established static algorithms and the benefits from including the temporal dimension for tasks such as prediction of network traffic, prediction of future links, and identification of significant nodes

Simulation of SVPWM Based Multivariable Control Method for a DFIG Wind Energy System

This paper deals with a variable speed device toproduce electrical energy on a power network based on adoubly-fed induction machine used in generating mode(DFIG) in wind energy system by using SVPWM powertransfer matrix. This paper presents a modeling and controlapproach which uses instantaneous real and reactive powerinstead of dq components of currents in a vector controlscheme. The main features of the proposed model comparedto conventional models in the dq frame of reference arerobustness and simplicity of realization. The sequential loopclosing technique is adopted to design a multivariable controlsystem including six compensators for a DFIG wind energysystem to capture the maximum wind power and to inject therequired reactive power to the generator. In this paperSVPWM method is used for better controlling of converters.It also provides fault ride through method to protect theconverter during a fault. The time-domain simulation of thestudy system is presented by using MATLAB Simulink to testthe system robustness, to validate the proposed model and toshow the enhanced tracking capability