Serverless architectures organized around looselycoupled function invocations represent an emerging design for many applications. Recent work mostly focuses on user-facing products and event-driven processing pipelines. In this paper, we explore a completely different part of the application space and examine the feasibility of analytical processing on big data using a serverless architecture. ...

the intension in this work is to investigate the effect of different bending manifold pipes on engine performance for different engine speed. Power, Torque, and BSFC were calculated and presented to show the effect of varying bending pipes angles on them for all cases considered. A special program used to carry out the calculations. A simulation model for 4-cylinders spark ignition engine with ...

This paper is about a new framework called DeduPlication (DduP). DduP aims to solve large scale deduplication problems on arbitrary data tuples. DduP tries to bridge the gap between big data, high performance and duplicate detection. At the moment a first prototype exists but the overall project status is work in progress. DduP utilises the promising successor of Apache Hadoop MapReduce [Had14]...

Java 8 has introduced new capabilities such as lambda expressions and streams which simplify data-parallel computing. However, as a base language for Big Data systems, it still lacks a number of important capabilities such as processing very large datasets and distributing the computation over multiple machines. This paper gives an overview of the Java 8 Streams API and proposes extensions to a...

Many systems run rich analytics on sensitive data in the cloud, but are prone to data breaches. Hardware enclaves promise data confidentiality and secure execution of arbitrary computation, yet still suffer from access pattern leakage. We propose Opaque, a distributed data analytics platform supporting a wide range of queries while providing strong security guarantees. Opaque introduces new dis...

Spark is a new promising platform for scalable data-parallel computation. It provides several high-level application programming interfaces (APIs) to perform parallel data aggregation. Since execution of parallel aggregation in Spark is inherently non-deterministic, a natural requirement for Spark programs is to give the same result for any execution on the same data set. We present PURESPARK, ...

Ca(+) sparks are vascular smooth muscle cell (VSMC) Ca(2+)-release events that are mediated by ryanodine receptors (RyR) and promote vasodilation by activating large-conductance Ca(2+)-activated potassium channels and inhibiting myogenic tone. We have previously reported that exposing rats to intermittent hypoxia (IH) to simulate sleep apnea augments myogenic tone in mesenteric arteries through...

Distributed data processing platforms for cloud computing are important tools for large-scale data analytics. Apache Hadoop MapReduce has become the de facto standard in this space, though its programming interface is relatively low-level, requiring many implementation steps even for simple analysis tasks. This has led to the development of advanced dataflow oriented platforms, most prominently...

The concept of minimum ignition energy (MIE) has traditionally formed the basis for studying ignition hazards of fuels. However, the viewpoint of ignition as a statistical phenomenon appears to be more consistent with the inherent variability in engineering test data. We have developed a very low-energy capacitive spark ignition system to produce short sparks with fixed lengths of 1 to 2 mm, an...