In present study, the thermal conductivity of silver/water nanofluid was investigated experimentally. Four different volume concentrations of nanofluids (2, 3, 5 and 10%) were prepared by dispersing silver nanoparticles in water. The properties of nanofluids were measured by varying the temperature from 20ºC to 100ºC and also, different sizes of nanoparticles dispersed in water (20-30, 50-60 an...

To ensure that social networks (e.g. opinion consensus, cooperative estimation, distributed learning and adaptation etc.) proliferate and efficiently operate, the participating agents need to collaborate with each other by repeatedly sharing information. However, sharing information is often costly for the agents while resulting in no direct immediate benefit for them. Hence, lacking incentives...

There has been much research on network flows over time due to their important role in real world applications. This has led to many results, but the more challenging continuous time model still lacks some of the key concepts and techniques that are the cornerstones of static network flows. The aim of this paper is to advance the state of the art for dynamic network flows by developing the cont...

OVER AN ARBITRARILY VARYING CHANNEL Rudolf Ahlswede and Ning Cai Abstract It is well{known that the deterministic code capacity (for the average error probability criterion) of an arbitrarily varying channel (AVC) either equals its random code capacity or zero. Here it is shown that if two components of a correlated source are additionally available to the sender and receiver, respectively, the...

{ With the fast growing uses of GPS-equipments, mobile users can more easily determine where they are located. These physical location information may play an important role in a wireless ad hoc network formed by a collection of wireless mobile hosts, in the absence of any xed infrastructure. Performance overhead considerations are more important for ad hoc network environments because of the t...

In this paper, we present a new method for modeling timeevolving correlation networks, using a Mean Reversion Autoregressive Model, and apply this to stock market data. The work is motivated by the assumption that the price and return of a stock eventually regresses back towards their mean or average. This allows us to model the stock correlation time-series as an autoregressive process with a ...

Relational data—like graphs, networks, and matrices—is often dynamic, where the relational structure evolves over time. A fundamental problem in the analysis of time-varying network data is to extract a summary of the common structure and the dynamics of the underlying relations between the entities. Here we build on the intuition that changes in the network structure are driven by dynamics at ...

We propose several econometric measures of connectedness based on principal-components analysis and Granger-causality networks, and apply them to the monthly returns of hedge funds, banks, broker/dealers, and insurance companies. We find that all four sectors have become highly interrelated over the past decade, likely increasing the level of systemic risk in the finance and insurance industrie...