50,717 research outputs found
A cell outage management framework for dense heterogeneous networks
In this paper, we present a novel cell outage management (COM) framework for heterogeneous networks with split control and data planes-a candidate architecture for meeting future capacity, quality-of-service, and energy efficiency demands. In such an architecture, the control and data functionalities are not necessarily handled by the same node. The control base stations (BSs) manage the transmission of control information and user equipment (UE) mobility, whereas the data BSs handle UE data. An implication of this split architecture is that an outage to a BS in one plane has to be compensated by other BSs in the same plane. Our COM framework addresses this challenge by incorporating two distinct cell outage detection (COD) algorithms to cope with the idiosyncrasies of both data and control planes. The COD algorithm for control cells leverages the relatively larger number of UEs in the control cell to gather large-scale minimization-of-drive-test report data and detects an outage by applying machine learning and anomaly detection techniques. To improve outage detection accuracy, we also investigate and compare the performance of two anomaly-detecting algorithms, i.e., k-nearest-neighbor- and local-outlier-factor-based anomaly detectors, within the control COD. On the other hand, for data cell COD, we propose a heuristic Grey-prediction-based approach, which can work with the small number of UE in the data cell, by exploiting the fact that the control BS manages UE-data BS connectivity and by receiving a periodic update of the received signal reference power statistic between the UEs and data BSs in its coverage. The detection accuracy of the heuristic data COD algorithm is further improved by exploiting the Fourier series of the residual error that is inherent to a Grey prediction model. Our COM framework integrates these two COD algorithms with a cell outage compensation (COC) algorithm that can be applied to both planes. Our COC solution utilizes an actor-critic-based reinforcement learning algorithm, which optimizes the capacity and coverage of the identified outage zone in a plane, by adjusting the antenna gain and transmission power of the surrounding BSs in that plane. The simulation results show that the proposed framework can detect both data and control cell outage and compensate for the detected outage in a reliable manner
Complex dynamics of elementary cellular automata emerging from chaotic rules
We show techniques of analyzing complex dynamics of cellular automata (CA)
with chaotic behaviour. CA are well known computational substrates for studying
emergent collective behaviour, complexity, randomness and interaction between
order and chaotic systems. A number of attempts have been made to classify CA
functions on their space-time dynamics and to predict behaviour of any given
function. Examples include mechanical computation, \lambda{} and Z-parameters,
mean field theory, differential equations and number conserving features. We
aim to classify CA based on their behaviour when they act in a historical mode,
i.e. as CA with memory. We demonstrate that cell-state transition rules
enriched with memory quickly transform a chaotic system converging to a complex
global behaviour from almost any initial condition. Thus just in few steps we
can select chaotic rules without exhaustive computational experiments or
recurring to additional parameters. We provide analysis of well-known chaotic
functions in one-dimensional CA, and decompose dynamics of the automata using
majority memory exploring glider dynamics and reactions
An end-to-end software solution for the analysis of high-throughput single-cell migration data
The systematic study of single-cell migration requires the availability of software for assisting data inspection, quality control and analysis. This is especially important for high-throughput experiments, where multiple biological conditions are tested in parallel. Although the field of cell migration can count on different computational tools for cell segmentation and tracking, downstream data visualization, parameter extraction and statistical analysis are still left to the user and are currently not possible within a single tool. This article presents a completely new module for the open-source, cross-platform CellMissy software for cell migration data management. This module is the first tool to focus specifically on single-cell migration data downstream of image processing. It allows fast comparison across all tested conditions, providing automated data visualization, assisted data filtering and quality control, extraction of various commonly used cell migration parameters, and non-parametric statistical analysis. Importantly, the module enables parameters computation both at the trajectory-and at the step-level. Moreover, this single-cell analysis module is complemented by a new data import module that accommodates multiwell plate data obtained from high-throughput experiments, and is easily extensible through a plugin architecture. In conclusion, the end-to-end software solution presented here tackles a key bioinformatics challenge in the cell migration field, assisting researchers in their highthroughput data processing
Unsteady wake modelling for tidal current turbines
The authors present a numerical model for three-dimensional unsteady wake calculations for tidal turbines. Since wakes are characterised by the shedding of a vortex sheet from the rotor blades, the model is based on the vorticity transport equations. A vortex sheet may be considered a jump contact discontinuity in tangential velocity with, in inviscid hydrodynamic terms, certain kinematic and dynamic conditions across the sheet. The kinematic condition is that the sheet is a stream surface with zero normal fluid velocity; the dynamic condition is that the pressure is equal on either side of the sheet. The dynamic condition is explicitly satisfied at the trailing edge only, via an approximation of the Kutta condition. The shed vorticity is the span-wise derivative of bound circulation, and the trailed vorticity is the time derivative of bound circulation, and is convected downstream from the rotors using a finite-volume solution of vorticity transport equations thus satisfying the kinematic conditions. Owing to an absence in the literature of pressure data for marine turbines, results from the code are presented for the NREL-UAE Phase IV turbine. Axial flow cases show a close match in pressure coefficients at various spanwise stations; however, yawed flow cases demonstrate the shortcomings of a modelling strategy lacking viscosity
How a well-adapting immune system remembers
An adaptive agent predicting the future state of an environment must weigh
trust in new observations against prior experiences. In this light, we propose
a view of the adaptive immune system as a dynamic Bayesian machinery that
updates its memory repertoire by balancing evidence from new pathogen
encounters against past experience of infection to predict and prepare for
future threats. This framework links the observed initial rapid increase of the
memory pool early in life followed by a mid-life plateau to the ease of
learning salient features of sparse environments. We also derive a modulated
memory pool update rule in agreement with current vaccine response experiments.
Our results suggest that pathogenic environments are sparse and that memory
repertoires significantly decrease infection costs even with moderate sampling.
The predicted optimal update scheme maps onto commonly considered competitive
dynamics for antigen receptors
Lateral migration of a 2D vesicle in unbounded Poiseuille flow
The migration of a suspended vesicle in an unbounded Poiseuille flow is
investigated numerically in the low Reynolds number limit. We consider the
situation without viscosity contrast between the interior of the vesicle and
the exterior. Using the boundary integral method we solve the corresponding
hydrodynamic flow equations and track explicitly the vesicle dynamics in two
dimensions. We find that the interplay between the nonlinear character of the
Poiseuille flow and the vesicle deformation causes a cross-streamline migration
of vesicles towards the center of the Poiseuille flow. This is in a marked
contrast with a result [L.G. Leal, Ann. Rev. Fluid Mech. 12,
435(1980)]according to which the droplet moves away from the center (provided
there is no viscosity contrast between the internal and the external fluids).
The migration velocity is found to increase with the local capillary number
(defined by the time scale of the vesicle relaxation towards its equilibrium
shape times the local shear rate), but reaches a plateau above a certain value
of the capillary number. This plateau value increases with the curvature of the
parabolic flow profile. We present scaling laws for the migration velocity.Comment: 11 pages with 4 figure
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