This study sought to probe the role of input flooding through listening tasks on the uptake of simple present tense and the present progressive tense among pre - intermediate English a s Foreign Language ( EFL ) learners. To comply with the objective, an experimental design was adopted. 55 pre - intermediate learners participated in the study. They were randomly divided into one control group, ...

This paper presents a comprehensive design methodology for guaranteeing end-to-end requirements of real-time systems. Applications are structured as a set of process components connected by asynchronous channels, in which the endpoints are the system's external inputs and outputs. Timing constraints are then postulated between these inputs and outputs; they express properties such as end-to-end...

the present study assessed the construct validity and reliability of a researcher-constructed psycho-motor mechanism scale based on the communicative theory of translation proposed by pacte (2003). in doing so, the necessary criteria for designing the scale were obtained by a thorough review of related literature on previously constructed scales in error analysis or holistic ones. moreover, in ...

The past decade has seen a revolution in genomic technologies that enable a flood of genome-wide profiling of chromatin marks. Recent literature tried to understand gene regulation by predicting gene expression from large-scale chromatin measurements. Two fundamental challenges exist for such learning tasks: (1) genome-wide chromatin signals are spatially structured, high-dimensional and highly...

Many learning tasks can be viewed as sequence prediction problems. For example, online classification can be converted to sequence prediction with the sequence being pairs of input/target data and where the goal is to correctly predict the target data given input data and previous input/target pairs. Solomonoff induction is known to solve the general sequence prediction problem, but only if the...

In a warehouse environment, tasks appear dynamically. Consequently, task management system that matches them with the workforce too early (e.g., weeks in advance) is necessarily sub-optimal. Also, rapidly increasing size of action space such consists significant problem for traditional schedulers. Reinforcement learning, however, suited to deal issues requiring making sequential decisions towar...