Peer-to-peer bichromatic reverse nearest neighbours in mobile ad-hoc networks

The increasing use of mobile communications has raised many issues of decision support and resource allocation. A crucial problem is how to solve queries of Reverse Nearest Neighbour (RNN). An RNN query returns all objects that consider the query object as their nearest neighbour. Existing methods mostly rely on a centralised base station. However, mobile P2P systems offer many benefits, including self-organisation, fault-tolerance and load-balancing. In this study, we propose and evaluate 3 distinct P2P algorithms focusing on bichromatic RNN queries, in which mobile query peers and static objects of interest are of two different categories, based on a time-out mechanism and a boundary polygon around the mobile query peers. The Brute-Force Search Algorithm provides a naive approach to exploit shared information among peers whereas two other Boundary Search Algorithms filter a number of peers involved in query processing. The algorithms are evaluated in the MiXiM simulation framework with both real and synthetic datasets. The results show the practical feasibility of the P2P approach for solving bichromatic RNN queries for mobile networks.     

Fuzzy Conditional Probability Relations and their Applications in Fuzzy Information Systems

In our real-world applications, data may be imprecise in which levels or degrees of preciseness of data are intuitively different. In this case, fuzzy set expressions are considered as an alternative to represent the imprecise data. In general, the degree of similarity relationship between two fuzzy (imprecise) data in real-world applications may not necessarily be symmetric or transitive. In order to provide such a degree of similarity between two fuzzy data, we introduced the fuzzy conditional probability relation. The concept of a fuzzy conditional probability relation may be considered as a concrete example of weak similarity relation which in turn is a special type of fuzzy binary relation generalizing similarity relation. Two important applications concerning the application of Knowledge Discovery and Data Mining (KDD) in the presence of a fuzzy data table (usually called fuzzy information system), namely removing redundant objects and recognizing partial or total dependency of (domain) attributes, are considered induced by the fuzzy conditional probability relation. Here, the fuzzy information system contains precise as well as imprecise data (fuzzy values) about objects of interest characterized by some attributes. Related to the dependency of attributes, we introduce the fuzzy functional dependency that satisfies Armstrongs Axioms. In addition, we also discuss some interesting applications such as approximate data reduction and projection, approximate data querying and approximate joining in order to extend the query system.     

Optical and topological characterization of gold nanoparticle dimers linked by a single DNA double strand

We demonstrate that symmetric or asymmetric gold nanoparticle dimers with substantial scattering cross sections and plasmon coupling can be produced with a perfectly controlled chemical environment and a high purity using a single DNA linker as short as 7 nm. A statistical analysis of the optical properties and morphology of single dimers is performed using darkfield and cryo-electron microscopies. These results, correlated to Mie theory calculations, indicate that the particle dimers are stretched in water by electrostatic interactions.     

New EXAFS Measurements by XEOL and TEY on Porous Silicon

Results of an EXAFS investigation on porous Silicon carried out by X-ray Excited Optical Luminescence (XEOL) and Total Electron Yield (TEY) techniques, at the Si K absorption edge, are reported. For the first time XEOL spectra of porous silicon have been recorded in a wide energy range (1800–2500 eV) and EXAFS signals have been singled out from them. Simultaneous TEY and XEOL measurements yield to different results: in particular TEY-EXAFS is sensitive up to the third coordination shell of Si, while XEOL-EXAFS reveals only the contributions of the first two coordination shells; moreover they show a different dependence on changes of the etching parameters. This evidences the sensitivity of XEOL technique to the local structure of the quantum confined luminescent sites. The dependence of the light emission properties on the main preparation parameters and their influence on the short-range structure of red and yellow porous silicon samples are also investigated.     

Electron energy-loss spectroscopy investigation of Y2O3 films on Si (001) substrate

Electron energy -loss spectroscopy has been used to investigate the interface between a Y₂O₃ film and the silicon substrate. The chemical composition of the interface layer is revealed to be nearly pure amorphous SiO₂. Yttrium silicates are found at the Y₂O₃/SiO₂ interface region. The formation of the interfacial yttrium silicates has been interpreted by the direct chemical reaction between the deposited Y₂O₃ film and the SiO₂ interface layer. The Si L₂₃ and O K edges of yttrium silicates (Y₂SiO₅ and Y₂Si₂O₇) have been calculated by the first-principle full multiple - scattering method. The theoretical results are consistent with the experimental spectra, which confirms the formation of yttrium silicates.     

HSIR: hybrid architecture for sensor identification and registration for IoT applications

Internet of things is the backbone of the smart applications, which attracts many types of research on the state-of-the-art network applications. Enormous research on sensor networks left more devices that are sensible in the day-to-day life. Hence, implementing new sensor networks for smart applications is not necessary. Many researchers have accepted and utilized existing networks for their request. In this case, techniques for identifying and registering existing sensible things are on demand. This paper proposed a hybrid framework for sensor identification and registration (HSIR) for new IoT applications. This research proposing HSIR as a framework aimed for user-friendliness in the IoT as well as addressed toward the scalability requirement of IoT applications. This model uses content- and context-based multicast communication instead of broadcast to reduce energy and time consumption in sensor identification. HSIR also proposed a public key to register the new network for application requirements. The behaviour of the proposed model has been assayed in realistic with simulations and proved by comparing other models.