In this work, the features of phase composition, structures, and properties coatings obtained on a high-speed steel substrate (steel R6M5) were studied. The prepared using ESA method (electro-spark alloying). Electrode materials through self-propagating high-temperature synthesis (SHS) based (Ti-B-Fe)xAlN with addition nanosized AlN particles in amount x = 0.5, 10, 15 wt % used as electrodes. s...

In this article, the electrode erosion and the gap growth of spark plugs were measured on of a CNG fueled engine after durability tests. Then, the required ignition voltage and the spark quality were investigated by a spark plug test rig. Considering results of measurements, the gap growth increased as the running time increased. Thus, the gap growth of spark plugs with 200 and 280 hours runnin...

The role of components in an Electrostatic Precipitator (EP) for a spark and both the phenomenon and mechanism of a spark are elaborated and then the type of spark is classified by the condition of shortage between the discharge and collecting electrodes. The secondary voltage and current waveforms of a spark are discussed in order to address the severe effect of the secondary and primary curre...

The aim of this project is to introduce Spark Clouds, which integrate spark lines into a tag cloud to convey trends between multiple tag clouds. Spark Clouds ability is to show trends compares favorably to the alternative visualizations. In the Existing System, Tag clouds are used to display the relative tag frequency, popularity, or importance by font size. They serve as a visual summary of do...

Decision tree is one of the most widely used classification methods. For massive data processing, MapReduce is a good choice. Whereas, MapReduce is not suitable for iterative algorithms. The programming model of Spark is proposed as a memory-based framework that is fit for iterative algorithms and interactive data mining. In this paper, C4.5 is implemented on both MapReduce and Spark. The resul...

Apache Spark is a popular framework for writing large scale data processing applications. Our long term goal is to develop automatic tools for reasoning about Spark programs. This is challenging because Spark programs combine database-like relational algebraic operations and aggregate operations, corresponding to (nested) loops, with User Defined Functions (UDFs). In this paper, we present a no...

Spark is a popular framework for writing large scale data processing applications. Our goal is to develop tools for reasoning about Spark programs. This is challenging because Spark programs combine database-like relational algebraic operations and aggregate operations with User Defined Functions (UDF s). We present the first technique for verifying the equivalence of Spark programs. We model S...

We introduce SparkCL, an open source unified programming framework based on Java, OpenCL and the Apache Spark framework. The motivation behind this work is to bring unconventional compute cores such as FPGAs/GPUs/APUs/DSPs and future core types into mainstream programming use. The framework allows equal treatment of different computing devices under the Spark framework and introduces the abilit...

Apache Spark is a popular framework for data analytics with attractive features such as fault tolerance and interoperability with the Hadoop ecosystem. Unfortunately, many analytics operations in Spark are an order of magnitude or more slower compared to native implementations written with high performance computing tools such as MPI. There is a need to bridge the performance gap while retainin...