Cumulon: Simplified Matrix-Based Data Analytics in the Cloud

Cumulon is a system aimed at simplifying the development and deployment of statistical analysis of big data in public clouds. Cumulon allows users to program in their familiar language of matrices and linear algebra, without worrying about how to map data and computation to specific hardware and cloud software platforms. Given user-specified requirements in terms of time, monetary cost, and risk tolerance, Cumulon automatically makes intelligent decisions on implementation alternatives, execution parameters, as well as hardware provisioning and configuration settings -- such as what type of machines and how many of them to acquire. Cumulon also supports clouds with auction-based markets: it effectively utilizes computing resources whose availability varies according to market conditions, and suggests best bidding strategies for them. Cumulon explores two alternative approaches toward supporting such markets, with different trade-offs between system and optimization complexity. Experimental study is conducted to show the efficiency of Cumulon's execution engine, as well as the optimizer's effectiveness in finding the optimal plan in the vast plan space.

Introduction of novel video-based tasks to clinical fMRI: Comparing traditional fMRI tasks with novel video-based tasks for mapping brain language areas

Recently, blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has become a routine clinical procedure for localization of language and motor brain regions and has been replacing more invasive preoperative procedures. However, the fMRI results from these tasks are not always reproducible even from the same patient. Evaluating the reproducibility of language and speech mapping is especially complicated due to the complex brain circuitry that may become activated during the functional task. Non-language areas such as sensory, attention, decision-making, and motor brain regions may also be activated in addition to the specific language regions during a traditional sentence-completion task. In this study, I test a new approach, which utilizes 4-minute video-based tasks, to map language and speech brain regions for patients undergoing brain surgery. Results from 35 subjects have shown that the video-based task activates Wernicke’s area, as well as Broca’s area in most subjects. The computed laterality indices, which indicate the dominant hemisphere from that functional task, have indicated left dominance from the video-based tasks. This study has shown that the video-based task may be an alternative method for localization of language and speech brain regions for patients who are unable to complete the sentence-completion task.