Volume 43 (2018): Edition 3 (September 2018)

The fifth generation (5G) cellular wireless networks are heterogeneous networks that will provide higher data rates, enhanced quality-of-experience (QoE) and reduced latency. Interference is one of the main problems in such systems. In this paper, a proposed cross-tier uplink interference alignment algorithm for coexisting two-tier networks is introduced. First at each receiver, the sum of the square of the channel gains from each macro user to this receiver is calculated and the average of these values is taken as a threshold. Macro users whose sum values are greater than this threshold are selected and aligned at the femto receiver. This alignment is performed by using precoders at the transmitters. Then, Zero Forcing technique is applied at the receivers in order to null the aligned interference signals. Numerical results demonstrate the superior performance of the proposed algorithm.

The rapid development of technology has allowed computer simulations to become routinely used in an increasing number of fields of science. These simulations become more and more realistic, and their energetic efficiency grows due to progress in computer hardware and software. As humans merge with machines via implants, brain-computer interfaces and increased activity involving information instead of material objects, philosophical concepts and theoretical considerations on the nature of reality are beginning to concern practical, working models and testable virtual environments. This article discusses how simulation is understood and employed in computer science today, how software, hardware and the physical universe unify, how simulated realities are embedded one in another, how complicated it can get in application, practical scenarios, and the possible consequences of these situations. A number of basic properties of universes and simulations in such multiply nested structures are reviewed, and the relationship of these properties with a level of civilizational development is explored.

In this paper, we make use of a Bayesian (supervised learning) approach in pricing American options via Monte Carlo simulations. We first present Gaussian process regression (Kriging) approach for American options pricing and compare its performance in estimating the continuation value with the Longstaff and Schwartz algorithm. Secondly, we explore the control variates technique in combination with Kriging to further improve the estimation of the continuation value. This method allows to reduce dramatically the standard errors and to improve the stability of the Kriging approach. For illustrative purposes, we use American put options on a stock whose dynamics is given by Heston model, and use European options on the same stock as control variates.

Crowdsourcing is a very effective technique for outsourcing work to a vast network usually comprising anonymous people. In this study, we review the application of crowdsourcing to modeling systems originating from systems biology. We consider a variety of verified approaches, including well-known projects such as EyeWire, FoldIt, and DREAM Challenges, as well as novel projects conducted at the European Center for Bioinformatics and Genomics. The latter projects utilized crowdsourced serious games to design models of dynamic biological systems, and it was demonstrated that these models could be used successfully to involve players without domain knowledge. We conclude the review of these systems by providing 10 guidelines to facilitate the efficient use of crowdsourcing.