This article describes how stateful data analytic frameworks have emerged to provide fresh and low-latency results for big data processing. At present, it is desired to achieve the fine-grained data model in Spark data processing framework. However, Spark adopts coarse-grained data model in...

Fuzzy rule interpolation offers a useful means for enhancing the robustness of fuzzy models by making inference possible in systems of only a sparse rule base. However in practical applications, as the application domain of fuzzy systems expand to more complex ones, the curse of dimensionality...

Currently, big data and its applications have become one of the emergent topics. In practice, MapReduce framework and its different extensions are the most popular approaches for big data. Fuzzy system based models stand out for many applications. However, when a given observation has no overlap...

Music emotion recognition (MER) is a challenging field of studies that has been addressed in multiple disciplines such as cognitive science, physiology, psychology, musicology, and arts. In this paper, music emotions are modeled as a set of continuous variables composed of valence and arousal...

Big data are pervasively generated by human cognitive processes, formal inferences, and system quantifications. This paper presents the cognitive foundations of big data systems towards big data science. The key perceptual model of big data systems is the recursively typed hyperstructure (RTHS)....

The research of the communication between implanted Cardiac Pacemaker and external devices is a focus. In this paper, a data communications model based Volume Conduction is creatively presented, in this way the human body conductive ability will been utilized to transmit current, which is more...