Muhammad Imran

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Microblogging sites such as Twitter can play a vital role in spreading information during “natural” or man-made disasters. But the volume and velocity of tweets posted during crises today tend to be extremely high, making it hard for disaster-affected communities and professional emergency responders to process the information in a timely manner.(More)
We present AIDR (Artificial Intelligence for Disaster Response), a platform designed to perform automatic classification of crisis-related microblog communications. AIDR enables humans and machines to work together to apply human intelligence to large-scale data at high speed. The objective of AIDR is to classify messages that people post during disasters(More)
Social media platforms provide active communication channels during mass convergence and emergency events such as disasters caused by natural hazards. As a result, first responders, decision makers, and the public can use this information to gain insight into the situation as it unfolds. In particular, many social media messages communicated during(More)
In wireless sensor and actor networks maintaining inter-actor connectivity is very important in mission-critical applications where actors have to quickly plan optimal coordinated response to detected events. Failure of one or multiple actors may partition the inter-actor network into disjoint segments, and thus hinders the network operation. Autonomous(More)
Prion diseases are transmissible, progressive and invariably fatal neurodegenerative conditions associated with misfolding and aggregation of a host-encoded cellular prion protein, PrPC. They have occurred in a wide range of mammalian species including human. Human prion diseases can arise sporadically, be hereditary or be acquired. Sporadic human prion(More)
Simulators, emulators and testbeds are invaluable tools for performance evaluation of algorithms and protocols in wireless sensor networks (WSNs). It is extremely difficult to choose an appropriate tool for performance testing without the horizontal and vertical analysis of existing tools. This paper presents a survey of thirty five performance evaluation(More)
During times of disasters online users generate a significant amount of data, some of which are extremely valuable for relief efforts. In this paper, we study the nature of social-media content generated during two different natural disasters. We also train a model based on conditional random fields to extract valuable information from such content. We(More)
Recently, Wireless Sensor and Actor Networks have been receiving a growing attention from the research community because of their suitability for critical applications. Maintaining inter-actor connectivity becomes extremely crucial in such situations where actors have to quickly plan optimal coordinated response to detected events. Failure of critical actor(More)