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These findings have critical implications in our current understanding of the rate effects on MLR characteristics which may inspire further studies to explore the characteristics of evoked responses at high rates and deconvolution paradigms.

With the development of Computerized Business Application, the amount of data is increasing exponentially. Cloud computing provides high performance computing resources and mass storage resources for massive data processing. In distributed cloud computing systems, data intensive computing can lead to data scheduling between data centers. Reasonable data placement can reduce data scheduling between the data centers effectively, and improve the data acquisition efficiency of users. In this paper, the mathematical model of data scheduling between data centers is built. By means of the global optimization ability of the genetic algorithm, generational evolution produces better approximate solution, and gets the best approximation of the data placement at last. The experimental results show that genetic algorithm can effectively work out the approximate optimal data placement, and minimize data scheduling between data centers.

To obtain reliable transient auditory evoked potentials (AEPs) from EEGs recorded using high stimulus rate (HSR) paradigm, it is critical to design the stimulus sequences of appropriate frequency properties. Traditionally, the individual stimulus events in a stimulus sequence occur only at discrete time points dependent on the sampling frequency of the recording system and the duration of stimulus sequence. This dependency likely causes the implementation of suboptimal stimulus sequences, sacrificing the reliability of resulting AEPs. In this paper, we explicate the use of continuous-time stimulus sequence for HSR paradigm, which is independent of the discrete electroencephalogram (EEG) recording system. We employ simulation studies to examine the applicability of the continuous-time stimulus sequences and the impacts of sampling frequency on AEPs in traditional studies using discrete-time design. Results from these studies show that the continuous-time sequences can offer better frequency properties and improve the reliability of recovered AEPs. Furthermore, we find that the errors in the recovered AEPs depend critically on the sampling frequencies of experimental systems, and their relationship can be fitted using a reciprocal function. As such, our study contributes to the literature by demonstrating the applicability and advantages of continuous-time stimulus sequences for HSR paradigm and by revealing the relationship between the reliability of AEPs and sampling frequencies of the experimental systems when discrete-time stimulus sequences are used in traditional manner for the HSR paradigm.

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This study investigates the effects of stimulus rate on the recording efficiency of evoked-response scenario using a computer generated data simulating auditory evoked potentials (AEPs). We examine AEPs derived from three paradigms: 1) Conventional stimuli for ensemble averaging; 2) continuous loop averaging deconvolution (CLAD); and 3) maximum length sequence (MLS) stimuli, in which deconvolution techniques are incorporated to retrieve the overlapped responses. The performance is evaluated by correlation coefficients between the ideal and the derived responses. The results show that there is no distinct improvement of SNR for high rate stimulation paradigms, suggesting that the techniques of deconvolution in high rate will not provide more efficient recording approach. Further, responses from the CLAD paradigm tend to deteriorate compared to the other two methods due to the lower jittering arrangement of the sequence.

The use of maximum length sequence (m-sequence) has been found beneficial for recovering both linear and nonlinear components at rapid stimulation. Since m-sequence is fully characterized by a primitive polynomial of different orders, the selection of polynomial order can be problematic in practice. Usually, the m-sequence is repetitively delivered in a looped fashion. Ensemble averaging is carried out as the first step and followed by the cross-correlation analysis to deconvolve linear/nonlinear responses. According to the classical noise reduction property based on additive noise model, theoretical equations have been derived in measuring noise attenuation ratios (NARs) after the averaging and correlation processes in the present study. A computer simulation experiment was conducted to test the derived equations, and a nonlinear deconvolution experiment was also conducted using order 7 and 9 m-sequences to address this issue with real data. Both theoretical and experimental results show that the NAR is essentially independent of the m-sequence order and is decided by the total length of valid data, as well as stimulation rate. The present study offers a guideline for m-sequence selections, which can be used to estimate required recording time and signal-to-noise ratio in designing m-sequence experiments.

The generation of auditory-evoked steady-state responses (SSRs) is associated with the linear superposition of transient auditory-evoked potentials (AEPs) that cannot be directly observed. A straightforward way to justify the superposition hypothesis is the use of synthesized SSRs by a transient AEP under a predefined condition based on the forward process of this hypothesis. However, little is known about the inverse relation between the transient AEP and its synthetic SSR, which makes the interpretation of the latter less convincible because it may not necessarily underlie the true solution. In this study, we chose two pairs of AEPs from the conventional and deconvolution paradigms, which represent the homo-AEPs from a homogenous group and the hetero-AEPs from two heterogeneous groups. Both pairs of AEPs were used as templates to synthesize SSRs at rates of 20–120 Hz. The peak-peak amplitudes and the differences between the paired waves were measured. Although amplitude enhancement occurred at ~40 Hz, comparisons between the available waves demonstrated that the relative differences of the synthetic SSRs could be dramatically larger at other rates. Moreover, two virtually identical SSRs may come from clearly different AEPs. These results suggested inconsistent relationships between the AEPs and their corresponding SSRs over the tested rates.