Description: In this paper, the authors describe the SemEval-2010 Cross-Lingual Lexical Substitution task, where given an English target word in context, participating systems had to find an alternative substitute word or phrase in Spanish. The task is based on the English Lexical Substitution task run at SemEval-2007. In this article, the authors provide background and motivation for the task, the authors describe the data annotation process and the scoring system, and present the results of the participating systems.

Description: This paper introduces SenseLearner - a minimally supervised sense tagger that attempts to disambiguate all content words in a text using the sense from WordNet. SenseLearner participated in the SENSEVAL-3 English all words task, and achieved an average accuracy of 64.6%.

Description: This paper presents the task definition, resources, participating systems, and comparative results for the English lexical sample task, which was organized as part of the SENSEVAL-3 evaluation exercise. The task drew the participation of 27 teams from around the world, with a total of 47 systems.

Description: This poster discusses transportation, carbon footprinting and ridesharing. The focus of this research project was to analyze and collect travel trajectories to calculate carbon footprints under different travel modes and identify ways to reduce it.

Description: The authors design and implement a local session admission control (SAC) algorithm for third-generation wireless networks which allows for the simulation of network throughput for different spreading factors and various mobility scenarios. The design of the SAC algorithm uses global information; it incorporates the session arrival rates and the user mobilities across the network and guarantees the users' quality of service as well as pre-specified blocking probabilities. On the other hand, its implementation in each cell uses local information; it only requires the number of sessions currently active in that cell. A global SAC algorithm is also implemented and used as a benchmark since it is inherently optimized and uses global information in making every session admission decision; it yields the best possible performance but has an intensive computational complexity. Using simulation, we determine the network throughput, and show that our optimized local SAC algorithm achieves almost the same performance as our global SAC algorithm at a fraction of the computational cost for pre-specified blocking probabilities and quality of service r4equirements and spreading factor values of 256, 64, 16, and 4.