Parallel String Sample Sort

We discuss how string sorting algorithms can be parallelized on modern multi-core shared memory machines. As a synthesis of the best sequential string sorting algorithms and successful parallel sorting algorithms for atomic objects, we propose string sample sort. The algorithm makes effective use of the memory hierarchy, uses additional word level parallelism, and largely avoids branch mispredictions. Additionally, we parallelize variants of multikey quicksort and radix sort that are also useful in certain situations.Comment: 34 pages, 7 figures and 12 table

Normalised Root Mean Square and Amplitude of Sidebands of Vibration Response as Tools for Gearbox Diagnosis

Quick assessment of the condition of gearboxes used in helicopters is a safety requirement. One of the most widely used helicopter on-board-mounted condition monitoring system these days is the Health and Usage Monitoring System. It has been specifically designed to monitor the condition of all safety-critical components operating in the helicopter through calculation of so-called condition indicators (CIs) - signal processing routines designed to output a single number that represents the condition of the monitored component. Among number of available parameters, there is a couple of CIs that over the years of testing have earned a reputation of being the most reliable measures of the gear tooth condition. At the same time, however, it has been observed that in some cases, those techniques do not properly indicate the deteriorating condition with the propagation of a gear tooth fault with the period of operation. Hence, three more robust methods have been suggested, which are discussed in this article

Non-universal dependence of spatiotemporal regularity on randomness in coupling connections

We investigate the spatiotemporal dynamics of a network of coupled nonlinear oscillators, modeled by sine circle maps, with varying degrees of randomness in coupling connections. We show that the change in the basin of attraction of the spatiotemporal fixed point due to varying fraction of random links $p$, is crucially related to the nature of the local dynamics. Even the qualitative dependence of spatiotemporal regularity on $p$ changes drastically as the angular frequency of the oscillators change, ranging from monotonic increase or monotonic decrease, to non-monotonic variation. Thus it is evident here that the influence of random coupling connections on spatiotemporal order is highly non-universal, and depends very strongly on the nodal dynamics.Comment: 9 pages, 4 figure

Response to sub-threshold stimulus is enhanced by spatially heterogeneous activity

Sub-threshold stimuli cannot initiate excitations in active media, but surprisingly as we show in this paper, they can alter the time-evolution of spatially heterogeneous activity by modifying the recovery dynamics. This results in significant reduction of waveback velocity which may lead to spatial coherence, terminating all activity in the medium including spatiotemporal chaos. We analytically derive model-independent conditions for which such behavior can be observed.Comment: 5 pages, 5 figure

Modified Technique for Measuring Dielectric Constants Using a Rectangular Cavity Resonator

Technique for measuring dielectric constants using rectangular cavity resonato

Privacy Preserving Clustering In Data Mining

Huge volume of detailed personal data is regularly collected and sharing of these data is proved to be beneficial for data mining application. Such data include shopping habits, criminal records, medical history, credit records etc .On one hand such data is an important asset to business organization and governments for decision making by analyzing it .On the other hand privacy regulations and other privacy concerns may prevent data owners from sharing information for data analysis. In order to share data while preserving privacy data owner must come up with a solution which achieves the dual goal of privacy preservation as well as accurate clustering result. Trying to give solution for this we implemented vector quantization approach piecewise on the datasets which segmentize each row of datasets and quantization approach is performed on each segment using K means which later are again united to form a transformed data set. Some experimental results are presented which tries to finds the optimum value of segment size and quantization parameter which gives optimum in the tradeoff between clustering utility and data privacy in the input dataset