Description: This paper discusses anchor nodes placement for effective passive localization. Abstract: In many applications, the exact location of the sensor nodes is unknown after deployment. Localization is a process used to locate sensor nodes' positional coordinates, which is vital information. The localization is generally assisted by anchor nodes that are also sensor nodes but with known locations. Anchor nodes generally are expensive and need to be optimally placed for effective localization. Passive localization is one of the localization techniques where the sensor nodes silently listen to the global events like thunder sounds, seismic waves, lighting, etc. According to previous studies, the ideal location to place anchor nodes was on the perimeter of the sensor network. This may not be the case in passive localization, since the function of anchor nodes here is different than the anchor nodes used in other localization systems. The authors do extensive studies on positioning anchor nodes for effective localization. Several simulations are run in dense and sparse networks for proper positioning of anchor nodes. The authors show that, for effective passive localization, the optimal placement of the anchor nodes is at the center of the network in such a way that no three anchor nodes ...

Description: This article discusses classifying genes to the correct Gene Ontology Slim term in Saccharomyces cerevisiae using neighbouring genes with classification learning. Abstract: Background: There is increasing evidence that gene location and surrounding genes influence the functionality of genes in the eukaryotic genome. Knowing the Gene Ontology Slim terms associated with a gene gives the authors insight into a gene's functionality by informing the authors how its gene product behaves in a cellular context using three different ontologies: molecular function, biological process, and cellular component. In this study, the authors analyzed if they could classify a gene in Saccharomyces cerevisiae to its correct Gene Ontology Slim term using information about its location in the genome and information from its nearest-neighbouring genes using classification learning. Results: The authors performed experiments to establish that the MultiBoostAB algorithm using the J48 classifier could correctly classify Gene Ontology Slim terms of a gene given information regarding the gene's location and information from its nearest-neighbouring genes for training. Different neighbourhood sizes were examined to determine how many nearest neighbours should be included around each gene to provide better classification rules. The authors' results show that by just incorporating neighbour information from each gene's two-nearest neighbours, the ...

Description: This paper discusses multilingual subjectivity. While subjectivity related research in other languages has increased, most of the work focuses on single languages. This paper explores the integration of features originating from multiple languages into a machine learning approach to subjectivity analysis, and aims to show that this enriched feature set provides for more effective modeling for the source as well as the target languages. The authors show not only that they are able to achieve over 75% macro accuracy in all of the six languages they experiment with, but also that by using features drawn from multiple languages they can construct high-precision meta-classifiers with a precision of over 83%.

Description: This article discusses temperature-dependent structural heterogeneity in calcium silicate liquids. X-ray diffraction measurements performed on aerodynamically levitated CaSiO3 droplets have been interpreted using a structurally heterogeneous liquid-state model. When cooled, the high-temperature liquid shows evidence of the polymerization of edge shared Ca octahedra. Diffraction isosbestic points are used to characterize the polymerization process in the pair-distribution function. This behavior is linear in the high-temperature melt but exhibits rapid growth just above the glass transition temperature around 1.2Tg. The heterogeneous liquid interpretation is supported by molecular-dynamics simulations which show the CaSiO3 glass has more edge-shared polyhedra and fewer corner shared polyhedra than the liquid model.

Description: This poster discusses bringing real world applications for wireless sensor networks into the classroom. This research covers the use of a wireless sensor network (WSN) using the ZigBee protocol to remotely monitor an artificial aquatic ecosystem.