Using Vocal-Based Sounds to Represent Sentiment in Complex Event Processing

Presented at the 20th International Conference on Auditory Display (ICAD2014), June 22-25, 2014, New York, NY.There is an intricate and evolving relationship between sonification and Complex Event Processing (CEP) for improved situational awareness. In a paper presented at ICAD 2013 [1], we introduced a series of techniques using CEP for simultaneous sonification of both quantitative “hard” data and human-derived “soft” data in the context of assistive technology. The connection of CEP and sonification was explored further in the context of a severe weather tracker that relies on fusion of quantitative (sensor-based) weather data along with human observations about storms and related conditions [2]. An area of shortcoming in both of these earlier works was the difficulty in creating sounds that represented human sentiment about observed conditions (e.g. unanticipated obstacles for a blind person crossing a busy street, or impending dangerous weather conditions) in a format that enabled intuitive listening for improved situational awareness. This extended abstract provides an update on that continuing research by representing human sentiment data, via the use of vocal synthesis that is driven by Complex Event Processing

Application of the Complex Event Processing system for anomaly detection and network monitoring

Protection of infrastructures for e-science, including grid environments and NREN facilities, requires the use of novel techniques for anomaly detection and network monitoring. The aim is to raise situational awareness and provide early warning capabilities. The main operational problem that most network operators face is integrating and processing data from multiple sensors and systems placed at critical points of the infrastructure. From a scientific point of view, there is a need for the efficient analysis of large data volumes and automatic reasoning while minimizing detection errors. In this article, we describe two approaches to Complex Event Processing used for network monitoring and anomaly detection and introduce the ongoing SECOR project (Sensor Data Correlation Engine for Attack Detection and Support of Decision Process), supported by examples and test results. The aim is to develop methodology that allows for the construction of next-generation IDS systems with artificial intelligence, capable of performing signature-less intrusion detection

Development of a generic activities model of command and control

This paper reports on five different models of command and control. Four different models are reviewed: a process model, a contextual control model, a decision ladder model and a functional model. Further to this, command and control activities are analysed in three distinct domains: armed forces, emergency services and civilian services. From this analysis, taxonomies of command and control activities are developed that give rise to an activities model of command and control. This model will be used to guide further research into technological support of command and control activities

A Hilbert Space Geometric Representation of Shared Awareness and Joint Decision Making

Two people in the same situation may ascribe very different meanings to their experiences. They will form different awareness, reacting differently to shared information. Various factors can give rise to this behavior. These factors include, but are not limited to, prior knowledge, training, biases, cultural factors, social factors, team vs. individual context, time, resources, and technology. At the individual level, the differences in attaining separate actions by accessing shared information may not be considered as an anomaly from the perspective of rational decision-making. But for group behavior, reacting differently to the shared information can give rise to conflicts and deviations from an expected behavior, and are categorized as an anomaly or irrational behavior. The lack of proper recognition of the reasons for differences can even impede the shared action towards attaining a common objective. The manifestation of differences becomes noticeable in complex situations. The shared awareness approaches that originate from available situational awareness models fail to recognize the reasons of an unexpected decision in these situations. One reason for this is that in complex situations, incompatible events can become dominant. Human information processing is sensitive to the compatibility of the events. This, and various other human psychological characteristics, require models to be developed that include comprehensive formalisms for both compatible and incompatible events in complex situations. Quantum probability provides a geometrical probabilistic formalism to study the decision and the dynamic cognitive systems in complex situations. The event representation in Hilbert space provides the necessary foundation to represent an individual\u27s knowledge of a situation. Hilbert space allows representing awareness as a superposition of indefinite states. These states form a complete N-dimensional Hilbert space. Within the space generated, events are represented as a subspace. By using these characteristics of Hilbert space and quantum geometrical probabilities, this study introduces a representation of self and other-than-self in a situation. An area of awareness with the possibility of projection onto the same event allows representing shared awareness geometrically. This formalism provides a coherent explanation of shared awareness for both compatible and incompatible events. Also, by using the superposition principles, the dissertation introduces spooky action at a distance concept in studying shared awareness

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio