33,234 research outputs found
Aspects of Unstructured Grids and Finite-Volume Solvers for the Euler and Navier-Stokes Equations
One of the major achievements in engineering science has been the development of computer algorithms for solving nonlinear differential equations such as the Navier-Stokes equations. In the past, limited computer resources have motivated the development of efficient numerical schemes in computational fluid dynamics (CFD) utilizing structured meshes. The use of structured meshes greatly simplifies the implementation of CFD algorithms on conventional computers. Unstructured grids on the other hand offer an alternative to modeling complex geometries. Unstructured meshes have irregular connectivity and usually contain combinations of triangles, quadrilaterals, tetrahedra, and hexahedra. The generation and use of unstructured grids poses new challenges in CFD. The purpose of this note is to present recent developments in the unstructured grid generation and flow solution technology
Requirements for implementing real-time control functional modules on a hierarchical parallel pipelined system
Analysis of a robot control system leads to a broad range of processing requirements. One fundamental requirement of a robot control system is the necessity of a microcomputer system in order to provide sufficient processing capability.The use of multiple processors in a parallel architecture is beneficial for a number of reasons, including better cost performance, modular growth, increased reliability through replication, and flexibility for testing alternate control strategies via different partitioning. A survey of the progression from low level control synchronizing primitives to higher level communication tools is presented. The system communication and control mechanisms of existing robot control systems are compared to the hierarchical control model. The impact of this design methodology on the current robot control systems is explored
Space-Time Signal Design for Multilevel Polar Coding in Slow Fading Broadcast Channels
Slow fading broadcast channels can model a wide range of applications in
wireless networks. Due to delay requirements and the unavailability of the
channel state information at the transmitter (CSIT), these channels for many
applications are non-ergodic. The appropriate measure for designing signals in
non-ergodic channels is the outage probability. In this paper, we provide a
method to optimize STBCs based on the outage probability at moderate SNRs.
Multilevel polar coded-modulation is a new class of coded-modulation techniques
that benefits from low complexity decoders and simple rate matching. In this
paper, we derive the outage optimality condition for multistage decoding and
propose a rule for determining component code rates. We also derive an upper
bound on the outage probability of STBCs for designing the
set-partitioning-based labelling. Finally, due to the optimality of the
outage-minimized STBCs for long codes, we introduce a novel method for the
joint optimization of short-to-moderate length polar codes and STBCs
Designing Fair Ranking Schemes
Items from a database are often ranked based on a combination of multiple
criteria. A user may have the flexibility to accept combinations that weigh
these criteria differently, within limits. On the other hand, this choice of
weights can greatly affect the fairness of the produced ranking. In this paper,
we develop a system that helps users choose criterion weights that lead to
greater fairness.
We consider ranking functions that compute the score of each item as a
weighted sum of (numeric) attribute values, and then sort items on their score.
Each ranking function can be expressed as a vector of weights, or as a point in
a multi-dimensional space. For a broad range of fairness criteria, we show how
to efficiently identify regions in this space that satisfy these criteria.
Using this identification method, our system is able to tell users whether
their proposed ranking function satisfies the desired fairness criteria and, if
it does not, to suggest the smallest modification that does. We develop
user-controllable approximation that and indexing techniques that are applied
during preprocessing, and support sub-second response times during the online
phase. Our extensive experiments on real datasets demonstrate that our methods
are able to find solutions that satisfy fairness criteria effectively and
efficiently
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