The A, C, G, and T of Genome Assembly

Genome assembly in its two decades of history has produced significant research, in terms of both biotechnology and computational biology. This contribution delineates sequencing platforms and their characteristics, examines key steps involved in filtering and processing raw data, explains assembly frameworks, and discusses quality statistics for the assessment of the assembled sequence. Furthermore, the paper explores recent Ubuntu-based software environments oriented towards genome assembly as well as some avenues for future research

Non-Parametric Statistical Analysis of Current Waveforms through Power System Sensors

The protection, control, and monitoring of the power grid is not possible without accurate measurement devices. As the percentage of renewable energy sources penetrating the existing grid infrastructure increases, so do uncertainties surrounding their effects on the everyday operation of the power system. Many of these devices are sources of high-frequency transients. These transients may be useful for identifying certain events or behaviors otherwise not seen in traditional analysis techniques. Therefore, the ability of sensors to accurately capture these phenomena is paramount. In this work, two commercial-grade power system distribution sensors are investigated in terms of their ability to replicate high-frequency phenomena by studying their responses to three events: a current inrush, a microgrid “close-in”, and a fault on the terminals of a wind turbine. Kernel density estimation is used to derive the non-parametric probability density functions of these error distributions and their adequateness is quantified utilizing the commonly used root mean square error (RMSE) metric. It is demonstrated that both sensors exhibit characteristics in the high harmonic range that go against the assumption that measurement error is normally distributed

K-Tier Heterogeneous Small-Cell Networks: Towards Balancing the Spectrum Usage and Power Consumption with Aggressive Frequency Reuse

Heterogeneous small-cell networks (HetSNets) are considered as a standard part of the future mobile networks where multiple low-power, low-cost base stations (e.g., femtocells) complement the existing macrocell infrastructure. In this paper, we propose a heterogeneous network where multiple tiers of small-cells are deployed which in turn expand the network coverage and increase the frequency reuse distance without compromising the frequency reuse factor. The resultant network is referred to as K-tier HetSNets, where small-cells are padded between the macrocells such that each of the macrocells in the network employs aggressive frequency reuse scheme, i.e., same set of frequencies is used in each macrocell. It has been shown that the co-channel interference due to neighboring macrocells has been reduced significantly without increasing the frequency reuse factor. The large scale deployment of the small-cells may increase the downlink power consumption of the considered HetSNet. Therefore, we show that the population of small-cells in each of the K-tiers is probabilistically dependent on the traffic load due to active mobile users, such that the small-cells in the network turn on their sleep mode under low and medium traffic load during the day. Several simulation results are included to illustrate the impact of the aggressive frequency reuse scheme and traffic load dependent population of small-cells on the system interference and downlink power consumption of the small-cell base stations