BACKGROUND Mounting evidence demonstrates that individuals with stroke benefit from sleep to enhance learning of a motor task. While stage NREM2 sleep and REM sleep have been associated with offline motor skill learning in neurologically intact individuals, it remains unknown which sleep parameters or specific sleep stages are associated with offline motor skill learning in individuals with str...

Major comments: 1) In this study, the authors try to compare an offline-couple model and an online-coupled model. However, the meteorological evaluation only focuses on WRF results which are only used for the offline model. Due to the feedbacks of air pollutants and complex interactions between meteorological variables with pollutants, the online-coupled model should have different meteorologic...

[1] The purpose of this study is to compare two methods of correcting the bias of a GCM; namely statistical correction performed a posteriori (offline) as a function of forecast length, and correction done within the model integration (online). The model errors of a low resolution GCM are estimated by the 6-hour forecast residual averaged over several years and used to correct the model. Both t...

We analyse online learning from finite training sets at noninfinitesimal learning rates TJ. By an extension of statistical mechanics methods, we obtain exact results for the time-dependent generalization error of a linear network with a large number of weights N. We find, for example, that for small training sets of size p ~ N, larger learning rates can be used without compromising asymptotic g...

TORCS car racing bots have improved significantly in the last years. We show that accurate curvature information for the upcoming corners enables offline learning a near-optimal driving style that consistently beats an expert human player (and the fastest currently known bots). Generalization to other tracks often, but not always succeeds, so that the method is extended by an online error corre...

ÐThis paper presents an integrated approach for both built-in online and offline testing of embedded DRAMs. It is based on a new technique for output data compression which offers the same benefits as signature analysis during offline test, but also supports efficient online consistency checking. The initial fault-free memory contents are compressed to a reference characteristic and compared to...

The model order reduction methodology of reduced basis (RB) techniques offers efficient treatment of parametrized partial differential equations (PDEs) by providing both approximate solution procedures and efficient error estimates. RB-methods have so far mainly been applied to finite element schemes for elliptic and parabolic problems. In the current study we extend the methodology to general ...

An adaptive reduced basis finite element heterogeneous multiscale method (RB-FE-HMM) is proposed for elliptic problems with multiple scales. The multiscale method is based on the RB-FE-HMM introduced in [A. Abdulle and Y. Bai, J. Comput. Phys, 2012, in press]. It couples a macroscopic solver with effective data recovered from the solution of micro problems solved on sampling domains. Unlike cla...

We employ the reduced basis method as a surrogate model for the solution of optimal control problems governed by parametrized partial differential equations (PDEs) and develop rigorous a posteriori error bounds for the error in the optimal control and the associated error in the cost functional. The proposed bounds can be efficiently evaluated in an offline-online computational procedure. We pr...

The simultaneous use of the state and the output of the offline controller in bumpless transfer design for the multi-input-multi-output (MIMO) systems is proposed. Under the large online/offline controller mismatch, the recently introduced MIMO bumpless transfer design based on the feedback of the offline controller state and the online controller input and output is found to produce significan...