2,128 research outputs found
Quasi-cyclic Generalized LDPC codes with low error floors
No full textIn this paper, a novel methodology for designing structured generalized LDPC (G-LDPC) codes is presented. The proposed design results in quasi-cyclic G-LDPC codes for which efficient encoding is feasible through shift-register-based circuits. The structure imposed on the bipartite graphs, together with the choice of simple component codes, leads to a class of codes suitable for fast iterative decoding. A pragmatic approach to the construction of G-LDPC codes is proposed. The approach is based on the substitution of check nodes in the protograph of a low-density parity-check code with stronger nodes based, for instance, on Hamming codes. Such a design approach, which we call LDPC code doping, leads to low-rate quasi-cyclic G-LDPC codes with excellent performance in both the error floor and waterfall regions on the additive white Gaussian noise channel
The Same Old New Normal
No full textJournal #14 from Media Rise's Quarantined Across Borders Collection by Ryan Arron D'Souza. From United Arab Emirates. Quarantined in United States, Florida.Media Rise Publications. Quarantined Across Borders Collection. Edited by Dr. Srividya "Srivi" Ramasubramanian.The author tries to make sense of the ideas and practices normalized during quarantine
A Bayesian hierarchical model for risk assessment of methylmercury
No full textThis article uses a Bayesian hierarchical model to quantify the adverse health effects associated with in-utero exposure to methylmercury. By allowing for study-to-study as well as outcome-to-outcome variability, the approach provides a useful meta-analytic tool for multi-outcome, multi-study environmental risk assessments. The analysis presented here expands on the findings of a National Academy of Sciences (NAS) committee, charged with advising the United States Environmental Protection Agency (EPA) on an appropriate approach to conducting a risk assessment for methylmercury. The NAS committee, for which the senior author (Ryan) was a committee member, reviewed the findings from several conflicting studies and reported the results from a Bayesian hierarchical model that synthesized information across several studies and for several outcomes. Although the NAS committee did not suggest that the hierarchical model be used as the actual basis for a methylmercury risk assessment, the results from the model were used to justify and support the final recommendation that the risk analysis be based on data from a study conducted in the Faroe Islands, which had found an association between in-utero exposure to methylmercury and impaired neurological development. We consider a variety of statistical issues, but particularly sensitivity to model specification. © 2003 American Statistical Association and the International Biometric Society
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