High Performance Computations for Decision Support in Critical Situations: Introduction to the Third Workshop on Urgent Computing

AbstractThis paper is the preface to the Third Workshop on Urgent Computing.The Urgent Computing workshops have been traditionally embedded in frame of International Conference of Computational Science (ICCS) since 2012. They are aimed to develop a dialogue on the present and future ofresearch and applications associated with the large-scale computations for decision support in critical situations. The key workshop topics in 2014 are: methods and principles of urgent computing, middleware, platforms and infrastructures, simulation-based decision support for complex systems control, interactive visualization and virtual reality for decision support in emergency situations, domain-area applications to emergency situations, including natural and man-made disasters, e.g.transportation problems, epidemics, criminal acts, etc

Urgent Computing for Operational Storm Surge Forecasting in Saint-Petersburg

AbstractThe accurate forecasting of storm surges and decision support for gates maneuvering is an important issue in Saint-Petersburg. The evolution of the numerical hydrodynamic models, hardware performance and computer technologies allow to make Flood Warning System (FWS) in Saint-Petersburg more reliable and appropriate to the real needs. This article describes the key solutions of the development and the present operational set-up of FWS with emphasis on computational issues and decision support on the basis of urgent computing paradigm. It includes a brief description data-assimilation techniques, such as Kalman filtering, the probabilistic real-data forecasting model, forecast quality control, distributed computing of different scenarios and decision support for gates maneuvering

Data-driven Travel Demand Modelling and Agent-based Traffic Simulation in Amsterdam Urban Area

AbstractThe goal of this project is the development of a large-scale agent-based traffic simulation system for Amsterdam urban area, validated on sensor data and adjusted for decision support in critical situations and for policy making in sustainable city development, emission control and electric car research. In this paper we briefly describe the agent-based simulation workflow and give the details of our data- driven approach for (1) modeling the road network of Amsterdam metropolitan area extended by major national roads, (2) recreating the car owners population distribution from municipality demographic data, (3) modeling the agent activity based on travel survey, and (4) modeling the inflow and outflow boundary conditions based on the traffic sensor data. The models are implemented in scientific Python and MATSim agent-based freeware. Simulation results of 46.5 thousand agents -with travel plans sampled from the model distributions- show that travel demand model is consistent, but should be improved to correspond with sensor data. The next steps in our project are: extensive validation, calibration and testing of large-scale scenarios, including critical events like the major power outage in the Netherlands (doi:10.1016/j.procs.2015.11.039), and modelling emissions and heat islands caused by traffic jams

Knowledge-based Expressive Technologies within Cloud Computing Environments

Presented paper describes the development of comprehensive approach for knowledge processing within e-Sceince tasks. Considering the task solving within a simulation-driven approach a set of knowledge-based procedures for task definition and composite application processing can be identified. This procedures could be supported by the use of domain-specific knowledge being formalized and used for automation purpose. Within this work the developed conceptual and technological knowledge-based toolbox for complex multidisciplinary task solv-ing support is proposed. Using CLAVIRE cloud computing environment as a core platform a set of interconnected expressive technologies were developed.Comment: Proceedings of the 8th International Conference on Intelligent Systems and Knowledge Engineering (ISKE2013). 201

Workflow-based Collaborative Decision Support for Flood Management Systems

AbstractSimulation-based decision making is the one of prospective applications of computational sciences which is central to advances in many scientific fields. The complexity and interdisciplinarity of scientific problems lead to the new technologies of simulation software implementation based on cloud computing, workflow tools and close interaction between experts and decision-makers. The important challenge in this field is to combine simulation scenarios, expert decisions and distributed environment to solve the complex interdisciplinary problems. In this paper, we describe a way to organize the collaborative decision support on the basis of e-Science platform CLAVIRE with the emphasis on urgency. A case study on decision making is the gates maneuvering for the flood prevention in Saint-Petersburg as a part of flood management system

Inference of the Russian drug community from one of the largest social networks in the Russian Federation

The criminal nature of narcotics complicates the direct assessment of a drug community, while having a good understanding of the type of people drawn or currently using drugs is vital for finding effective intervening strategies. Especially for the Russian Federation this is of immediate concern given the dramatic increase it has seen in drug abuse since the fall of the Soviet Union in the early nineties. Using unique data from the Russian social network 'LiveJournal' with over 39 million registered users worldwide, we were able for the first time to identify the on-line drug community by context sensitive text mining of the users' blogs using a dictionary of known drug-related official and 'slang' terminology. By comparing the interests of the users that most actively spread information on narcotics over the network with the interests of the individuals outside the on-line drug community, we found that the 'average' drug user in the Russian Federation is generally mostly interested in topics such as Russian rock, non-traditional medicine, UFOs, Buddhism, yoga and the occult. We identify three distinct scale-free sub-networks of users which can be uniquely classified as being either 'infectious', 'susceptible' or 'immune'.Comment: 12 pages, 11 figure