Best network chirplet-chain: Near-optimal coherent detection of unmodeled gravitation wave chirps with a network of detectors

The searches of impulsive gravitational waves (GW) in the data of the ground-based interferometers focus essentially on two types of waveforms: short unmodeled bursts and chirps from inspiralling compact binaries. There is room for other types of searches based on different models. Our objective is to fill this gap. More specifically, we are interested in GW chirps with an arbitrary phase/frequency vs. time evolution. These unmodeled GW chirps may be considered as the generic signature of orbiting/spinning sources. We expect quasi-periodic nature of the waveform to be preserved independent of the physics which governs the source motion. Several methods have been introduced to address the detection of unmodeled chirps using the data of a single detector. Those include the best chirplet chain (BCC) algorithm introduced by the authors. In the next years, several detectors will be in operation. The joint coherent analysis of GW by multiple detectors can improve the sight horizon, the estimation of the source location and the wave polarization angles. Here, we extend the BCC search to the multiple detector case. The method amounts to searching for salient paths in the combined time-frequency representation of two synthetic streams. The latter are time-series which combine the data from each detector linearly in such a way that all the GW signatures received are added constructively. We give a proof of principle for the full sky blind search in a simplified situation which shows that the joint estimation of the source sky location and chirp frequency is possible.Comment: 22 pages, revtex4, 6 figure

The Discovery and Nature of Optical Transient CSS100217:102913+404220

We report on the discovery and observations of the extremely luminous optical transient CSS100217:102913+404220 (CSS100217 hereafter). Spectroscopic observations show this transient was coincident with a galaxy at redshift z=0.147, and reached an apparent magnitude of V ~ 16.3. After correcting for foreground Galactic extinction we determine the absolute magnitude to be M_V =-22.7 approximately 45 days after maximum light. Based on our unfiltered optical photometry the peak optical emission was L = 1.3 x 10^45 erg s^-1, and over a period of 287 rest-frame days had an integrated bolometric luminosity of 1.2 x 10^52 erg. Analysis of the pre-outburst SDSS spectrum of the source shows features consistent with a Narrow-line Seyfert1 (NLS1) galaxy. High-resolution HST and Keck followup observations show the event occurred within 150pc of nucleus of the galaxy, suggesting a possible link to the active nuclear region. However, the rapid outburst along with photometric and spectroscopic evolution are much more consistent with a luminous supernova. Line diagnostics suggest that the host galaxy is undergoing significant star formation. We use extensive follow-up of the event along with archival CSS and SDSS data to investigate the three most likely sources of such an event; 1) an extremely luminous supernova; 2) the tidal disruption of a star by the massive nuclear black hole; 3) variability of the central AGN. We find that CSS100217 was likely an extremely luminous type IIn supernova that occurred within range of the narrow-line region of an AGN. We discuss how similar events may have been missed in past supernova surveys because of confusion with AGN activity.Comment: submitted to Ap

Cuckoo Search-Driven Feature Selection for Decision Tree Modelling

Features are fundamental components of decision tree modeling, and their relevance, quality, and selection are crucial determinants of the model's effectiveness and performance. However, decision trees can be computationally expensive, requiring a significant amount of memory to store the trees and their associated data structures. To address this limitation, we present a novel approach that utilizes a Cuckoo Search-based feature selection algorithm to construct efficient and optimal decision trees. The Cuckoo Search algorithm, inspired by the behavior of cuckoo birds, is a powerful metaheuristic algorithm that effectively selects high-quality features and creates accurate decision trees in the subforest. We evaluate the proposed method on a variety of datasets from the standard UCI learning repository with different domains and sizes, and our results demonstrate that the algorithm creates optimal decision trees with high performance

An Investigation towards Effectiveness in Image Enhancement Process in MPSoC

Image enhancement has a primitive role in the vision-based applications. It involves the processing of the input image by boosting its visualization for various applications. The primary objective is to filter the unwanted noises, clutters, sharpening or blur. The characteristics such as resolution and contrast are constructively altered to obtain an outcome of an enhanced image in the bio-medical field. The paper highlights the different techniques proposed for the digital enhancement of images. After surveying these methods that utilize Multiprocessor System-on-Chip (MPSoC), it is concluded that these methodologies have little accuracy and hence none of them are efficiently capable of enhancing the digital biomedical images

Electrolytes for sodium ion batteries: A short review

113-119Synthesis routes and ion conduction phenomenon in sodium ion conducting solid electrolytes have been reported in the present chapter. The different experimental and theoretical tools have been explained for preparation and ion conduction mechanism of solid electrolytes. The working principle of some polymer electrolyte based conductors has been explained