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...

Model checking is a well developed verification technique still it is not widely adopted. One of the reasons is that defining formal specification is an error-prone and time-consuming task. This paper gives an overview of the ongoing research which focuses on expressing verifiable requirements in controlled natural language in the framework of automata-based programming.

EEG recording is a time consuming operation during which the subject is expected to stay still for a long time performing tasks. It is reasonable to expect some fluctuation in the level of focus toward the performed task during the task period. This study is focused on investigating various approaches for emphasizing regions of interest during the task period. Dividing the task period into thre...

Although there have been regular improvements in speech recognition technology over the past decade, speech recognition is far from being a solved problem. Recognition systems are usually tuned to a particular task and porting the system to a new task (or language) is both time-consuming and expensive. In this paper, issues in speech recognizer portability are addressed through the development ...

When our attention is engaged in a visual task, we can be blind to events which would otherwise not be missed. In three experiments, 97 out of the 165 observers performing a visual attention task failed to notice an unexpected, irrelevant object moving across the display. Surprisingly, this object significantly lowered accuracy in the primary task when, and only when, it failed to reach awarene...

As it is well known the rough set a beneficial method for data uncertainty analysis. However, this time- consuming task many big sets. So we utilized concept of local sets in analysis children addicted to social media handle efficiently and give some properties. With results, proved that gave more concrete clear information than

It is vital to select an appropriate distance metric for many learning algorithm. Cosine distance is an efficient metric for measuring the similarity of descriptors in classification task. However, the cosine similarity metric learning (CSML)[1] is not widely used due to the complexity of its formulation and time consuming. In this paper, a Quasi Cosine Similarity Metric Learning (QCSML) is pro...

Many-Task Computing (MTC) is a widely used computing paradigm for large-scale task-parallel processing. One of the key issues in MTC is to schedule a large number of independent tasks onto heterogeneous resources. Traditional task-level scheduling heuristics, like Min-Min, Sufferage and MaxStd, cannot readily be applied in this scenario. As most of MTC tasks are usually fine-grained, the resour...