Numerical simulation of a wind excited quasi-periodic regime of a stochastic van der Pol-type equation

The contribution regards a mathematical single-degree-of-freedom model of a slender structure vibrating in an air flow. Based on an experimental investigation, movement of such structures can be expressed by van der PolDuffing-type equations. Several particular configuration parameter settings for a white and non-white Gaussian random excitation together with deterministic harmonic forcing are considered and numerically analysed. The results support recently published analytic formulas.

Towards machine learning-based self-tuning of Hadoop-Spark system

Apache Spark is an open source distributed platform which uses the concept of distributed memory for processing big data. Spark has more than 180 predominant configuration parameter. Configuration settings directly control the efficiency of Apache spark while processing big data, to get the best outcome yet a challenging task as it has many configuration parameters. Currently, these predominant parameters are tuned manually by trial and error. To overcome this manual tuning problem in this paper proposed and developed a self-tuning approach using machine learning. This approach can tune the parameter value when it’s required. The approach was implemented on Dell server and experiment was done on five different sizes of the dataset and parameter. A comparison is provided to highlight the experimented result of the proposed approach with default Spark configuration system. The results demonstrate that the execution is speeded-up by about 33% (on an average) compared to the default configuration.

Vibration isolation using a bar and an Euler beam as negative stiffness for vehicle seat comfort

In this article, the behavior and the efficiency of a nonlinear passive vibration isolator based on a bar and an Euler beam are investigated analytically. The proposed isolator is specifically for isolating vehicle seat from unwanted disturbances in the low frequency range, thereby making the seat comfortable for the driver. The static characteristics of the negative stiffness as well as the nonlinear mathematical model are presented, and its dynamic characteristics are investigated using the harmonic balance method. In addition, the effect of the initial geometric imperfection of the Euler beam is included in the study. The study shows that the performance of the negative isolator has a large isolation frequency range than that of the linear isolator. The configuration parameter choice for the seat base will be vital for the suitable application of this isolator.

Hadoop Configuration Tuning for Performance Optimization

Configuration parameter tuning is an essential part of the implementation of Hadoop clusters. Each parameter in a configuration plays a role that impacts the ov erall performance of the cluster. Therefore, we need to learn the characteristics of said parameter and understand the impact in hardware utilization in order to achieve optimal configuration. In this paper, we conducted experiments that includes modifying configuration and performed benchmark to find out if there is any performance gain. TeraSort is the program that runs the benchmark, we measure the time needed to complete the sort of the set of data and the CPU utilization during the benchmark. We conclu de that from our experiments we can see significant performance improvements by tuning with the configurations. However, the results may vary between different cluster configuration.