In this paper, we present the JUCSE system, designed for the TempEval-3 shared task. The system extracts events and temporal information from natural text in English. We have participated in all the tasks of TempEval-3, namely Task A, Task B & Task C. We have primarily utilized the Conditional Random Field (CRF) based machine learning technique, for all the above tasks. Our system seems to perf...

There is an extensive literature on task modelling related to the design of computer systems. Task analysis and task modelling have been widely recognized as central components in human-centred approaches. The aim of this paper is to report on some results of a worldwide survey about actual practices of task descriptions languages (TDL) in SIGCHI community. Results suggest that academic TDL are...

Although discriminating between all efficient decision making units (DMUs) with identical efficiency is a very important subject in data envelopment analysis (DEA), it may not be an easy task, particularly when the decision maker wants to select one and only one efficient DMU among all. There are some papers that have proposed methods for finding an efficient DMU as the most efficient one but h...

This paper presents a computational model of integrated introspective learning, which is a deliberative learning process in which a rea-soner introspects about its own performance on a reasoning task, identiies what it needs to learn to improve its performance, formulates learning goals to acquire the required knowledge, and pursues its learning goals using multiple learning strategies. We disc...

A Fault-Tolerant Control (FTC) methodology has been presented for nonlinear processes being imposed by control input constraints. The proposed methodology uses a combination of Feedback Linearization and Model Predictive Control (FLMPC) schemes. The resulting constraints in the transformed process will be dependent on the actual evolving states, making their incorporation in the de...