Hossein Rahnama

Urban search and rescue with canine augmentation technology

The agility, sense of smell, hearing and speed of dogs is put to good use by dedicated canine teams involved in search and rescue operations. Perhaps the weakest link in the human-dog team is the human. In comparison to dogs, humans hear less, cannot effectively follow a scent and actually slow the dog down when involved in area searches. To mitigate this problem the Network-Centric Applied Research Team has been working with the Ontario Provincial Police to augment SAR dogs with a suite of supporting technologies to extend the dogs potential area of operation and allow a greater distance between dog and handler. Through canine augmentation technology we hope to allow canine handlers to see what the dog sees, hear what the dog hears, know where the dog is and be able to communicate with the dog at extended distances

Rubble Search with Canine Augmentation Technology

We have been working to augment trained search and rescue canines with technological components to allow them to be monitored and controlled from greater distances in rubble caused by a disaster. Such rubble often precludes close interaction between a dog and its handler. In this paper we report the results of a set of trials involving augmented canines searching for simulated casualties in rubble. Two trials are reported on two different rubble piles.

Adaptive context for generic pattern matching in ad hoc social networks

Efficient pattern matching algorithms in ad hoc networks can have significant benefits in generating real-time context and eliminate the need for a centralized arbiter. In our paper we demonstrate a generic and customizable architecture for achieving efficient pattern matching in mobile ad hoc networks. A major limitation of current ad hoc matching algorithms is that they are tailored for a specific design scenario and are unable to adapt to new scenarios. In this paper we present a novel architecture for the development of an ad hoc generic matching engine which is customizable to varying scenarios through a web service. We show how customizable semantics can play an important role in decision making, selection of a desired attribute and notifying a message in a volatile network. We also show how our system is adaptable to various scenarios, and focus on social interaction to verify our results.

Social Context Awareness in Ad Hoc System of Systems

In this project we describe a generic framework that can be used as a basis for building mobile ad hoc social networks. By modifying Bluetooth authentication scheme, we provide a real time ad hoc matching environment where the strength of match is calculated based on the search s criteria and the users profile. We enhance current matching algorithms used in asynchronous transmission mode protocol and provide priority matching algorithms which are more suitable for the volatile ad hoc networks. We also propose a new measurement of conceptual distance, as compared to physical distance in an ad hoc social network. In this paper we focus on increasing the users available relevant information on the system, and express an architecture that can be applied to a system of systems.

Canine as Robot in Directed Search

One of the goals of rescue robotics has been to allow machines to sense and act where people cannot go. Deployed with various sensors and under the guidance of trained operators these systems have shown great potential for finding victims in rubble. However, the current state of mobility of all deployed rescue robots is such that they can only be employed in very constrained circumstances where surfaces are mostly regular and acceptable for various modes of tracked and wheeled mobility. We have been exploring an alternative employing the existing abilities of trained US.4R canines to search nibble both quickly and effectively. This paper discusses one of the potential areas where canines might be augmented to deliver the desired sensing and remote control of a robot.

“CANthings”(Context Aware Network for the Design of Connected Things) service modeling based on Timed CPN

In the past few years, the advances in context-aware systems and sensor technologies, has elevated the Internet of Things (IoT) development greatly and rather quickly. Services of IoT systems must be reasonably designed to provide not only the users requirements and requests, but also perceive the environmental context and customized services to get users satisfaction. Systematic modeling methodologies are essential to control the correctness of the services and the systems behaviors among dynamic changing contexts. The presented solution will be a novel IoT framework, “CANthings” (Context-Aware Networks for the Design of Connected Things) to identify IoT needs.This paper mainly promotes and analyzes an IoT system modeling methodology based on Timed Colored Petri Net (TCPN) to check the effectiveness of the provided services in the CANthings framework. Our goal is to present a standard solution that can be used in high-technical research and industrial projects.

CAMPUS: context aware mobile platform for uniformed security

The Context Aware Mobile Platform for Uniformed Security (CAMPUS) system was developed with the aim of using ambient intelligence and mobile communications to information sources as an aid to field security and law enforcement personnel. The system is centered on a context aware information distribution framework and a client operating on a head mounted display. The system allows field service personnel to receive information relevant to their current operations, review information from sensors, and communicate with colleagues while remaining vigilant during security and law enforcement operations. Sensor integration and mapping technologies are the key elements in provisioning of appropriate information services.

Building Human Infrastructure for the Digital Economy: Ryerson’s Digital Media Zone

Drawing upon the policy literature and empirical work, this paper proposes an ecological model in which entrepreneurial skills are a critical part of the human infrastructure needed to fuel national Digital Economy and Innovation strategies. While many countries around the world reference the importance of building a “culture of innovation” and some countries, such as Israel, are seen as having this deeply embedded, there are few definitions and fewer empirical studies assessing this. We suggest that the prevalence of individuals with entrepreneurial mindsets and a willingness to take risks will drive economic growth and development but that developing this is easier said than done, as complex factors shape values and aspirations. While University-based incubators have long been seen as important parts of the innovation ecosystem, we provide a case study of a unique incubator, Ryerson University’s Digital Media Zone (Toronto, Canada), and suggest that it not only offers short term outcomes but also offers a model that is critical to fostering a culture of innovation. We conclude that more needs to be done in Canada to promote this culture of innovation and that it needs to begin long before students reach university.

Synthesizing social context for making Internet of Things environments more immersive

The growth in context-aware systems and smart devices elevates another technology in ubiquitous computing - Internet of Things (IoT), where all objects are connected. The integration of Smart objects and social networking play an important role in todays life. This paper mainly promotes the management and architecture for adaptive social services within IoT, where objects interact based on social behavior. We proposed social context-aware and ontology as the major keys for this study. Our main goal is to make the presented framework CANthings a standard social framework that can be used both in research and industry projects.

Fuzzy Bayesian models for Classification and Diagnosis in Generalized Cardiology Discipline

There has been a steady progress in creating expert systems capable of diagnosis; however, there exists no generic expert system structure capable of accurately representing medical knowledge and extracting diagnosis in a specific multi-disease medical discipline. This paper aims to justify a standard methodology that can be used in creating a generic expert system model for generic medical domains.