Abstract We describe a gold standard corpus of protest events that comprise various local and international English language sources from countries. The contains document-, sentence-, token-level annotations. This facilitates creating machine learning models automatically classify news articles extract event-related information, constructing knowledge bases enable comparative social political s...

BACKGROUND United States Army Soldiers regularly use dietary supplements (DS) to promote general health, enhance muscle strength, and increase energy, but limited scientific evidence supports the use of many DS for these benefits. This study investigated factors associated with Soldiers' confidence in the efficacy and safety of DS, and assessed Soldiers' knowledge of federal DS regulatory requi...

Tweets provide a continuous update on current events. However, Tweets are short, personalized and noisy, thus raises more challenges for event extraction and representation. Extracting events out of Arabic tweets is a new research domain where few examples – if any – of previous work can be found. This paper describes a knowledge-based approach for fostering event extraction out of Arabic tweet...

We describe work aimed at building commonsense knowledge by reading word definitions using deep understanding techniques. The end result is a knowledge base allowing complex concepts to be reasoned about using OWL-DL reasoners. We show that we can use this system to automatically create a mid-level ontology for WordNet verbs that has good agreement with human intuition with respect to both the ...

Event detection is a central component in numerous wireless sensor network (WSN) applications. Nevertheless, the area of event description has not received enough attention. The majority of current event description and detection approaches rely on using precise values to specify event thresholds. However, we believe that crisp values cannot adequately handle the often imprecise sensor readings...

This paper develops solutions for efficient transfer of sporadic (event-triggered) data over a time-triggered communication channel. We present novel and efficient techniques for composite provisioning of the event triggered (ET) and time triggered (TT) paradigms to achieve both the predictability and flexibility inherent in TT and ET systems respectively. As a tangible demonstration of the tec...

fault tree analysis (fta) as a probabilistic risk assessment (pra) method is used to identify basic causes leading to an undesired event, to represent logical relation of these basic causes in leading to the event, and finally to calculate the probability of occurrence of this event. to conduct a quantitative fta, one needs a fault tree along with failure data of the basic events (bes). someti...

Event detection is a central component in numerous wireless sensor network (WSN) applications. In spite of this, the area of event description has not received enough attention. The majority of current event description approaches rely on using precise values to specify event thresholds. However, we believe that crisp values cannot adequately handle the often imprecise sensor readings. In this ...