Prepare for Citizen Science Challenges at CERN

Abstract: To inspire more people to contribute to science, and educate the public about science, two Citizen Science "challenges" were prepared during summer 2013: the CERN Summer Webfest 2013 and the Virtual LHC Challenge. The first part of this report summarizes how to organize a Webfest at CERN and the outcome of the CERN Summer Webfest 2013.The second part gives an introduction to the current state of the Virtual LHC Challenge: a development of the LHC@Home Test4Theory project planned to attract many unskilled volunteers. This work was supported by a grant from the EU Citizen Cyberlab project, with assistance from the Citizen Cyberscience Centre (CCC)

Solution of AntiSeepage for Mengxi River Based on Numerical Simulation of Unsaturated Seepage

Lessening the leakage of surface water can reduce the waste of water resources and ground water pollution. To solve the problem that Mengxi River could not store water enduringly, geology investigation, theoretical analysis, experiment research, and numerical simulation analysis were carried out. Firstly, the seepage mathematical model was established based on unsaturated seepage theory; secondly, the experimental equipment for testing hydraulic conductivity of unsaturated soil was developed to obtain the curve of two-phase flow. The numerical simulation of leakage in natural conditions proves the previous inference and leakage mechanism of river. At last, the seepage control capacities of different impervious materials were compared by numerical simulations. According to the engineering actuality, the impervious material was selected. The impervious measure in this paper has been proved to be effectible by hydrogeological research today

Relation-Centric Task Identification for Policy-Based Process Mining

Many organizations use business policies to govern their business processes. For complex business processes, this results in huge amount of policy documents. Given the large volume of policies, manually analyzing policy documents to discover process information imposes excessive cognitive load. In order to provide a solution to this problem, we have proposed previously a novel approach named Policy-based Process Mining (PBPM) to automatically extracting process models from policy documents using information extraction techniques. In this paper, we report our recent findings in an important PBPM step called task identification. Our investigation indicates that task identification from policy documents is quite challenging because it is not a typical information extraction problem. The novelty of our approach is to formalize task identification as a problem of extracting relations among three process components, i.e., resource, action, and data while using sequence kernel techniques. Our initial experiment produced very promising results