Generalized low-density codes with BCH constituents for full-diversity near-outage performance

A new graph-based construction of generalized low density codes (GLD-Tanner) with binary BCH constituents is described. The proposed family of GLD codes is optimal on block erasure channels and quasi-optimal on block fading channels. Optimality is considered in the outage probability sense. Aclassical GLD code for ergodic channels (e.g., the AWGN channel,the i.i.d. Rayleigh fading channel, and the i.i.d. binary erasure channel) is built by connecting bitnodes and subcode nodes via a unique random edge permutation. In the proposed construction of full-diversity GLD codes (referred to as root GLD), bitnodes are divided into 4 classes, subcodes are divided into 2 classes, and finally both sides of the Tanner graph are linked via 4 random edge permutations. The study focuses on non-ergodic channels with two states and can be easily extended to channels with 3 states or more.

Full diversity product codes for block erasure and block fading channels

We show how to build full-diversity product codes under both iterative encoding and decoding over non-ergodic channels, in presence of block erasure and block fading. The concept of a rootcheck or a root subcode is introduced by generalizing the same principle recently invented for low-density parity-check codes. We also describe some channel related graphical properties of the new family of product codes, a familyreferred to as root product codes.

A comparison of full-rate full-diversity 2x2 space-time codes for WiMAX systems

Multiple-input multiple-output (MIMO) techniques have become an essential part of broadband wireless communications systems. For example, the recently developed IEEE 802.16e specifications for broadband wireless access include three MIMOprofiles employing 2×2 space-time codes (STCs), and two of these MIMO schemes are mandatory on the downlink of Mobile WiMAX systems. One of these has full rate, and the other has full diversity, but neither of them has both of the desired features. The third profile, namely, Matrix C, which is not mandatory, is both a full rate and a full diversity code, but it has a high decoder complexity. Recently, the attention was turned to the decodercomplexity issue and including this in the design criteria, several full-rate STCs were proposed as alternatives to Matrix C. In this paper, we review these different alternatives and compare them to Matrix C in terms of performances and the correspondingreceiver complexities.

Outage thresholds of LDPC codes over nonergodic block-fading channels

This paper derives approximations allowing the estimation of outage probability for standard irregular LDPC codes and full-diversity Root-LDPC codes used over nonergodic block-fading channels. Two separate approaches are discussed: a numerical approximation, obtained by curve fitting, for both code ensembles, and an analytical approximation for Root-LDPC codes, obtained under the assumption that the slope of the iterative threshold curve of a given code ensemble matches the slope of the outage capacity curve in the high-SNR regime.

On iterative performance of LDPC and Root-LDPC codes over block-fading channels

This paper presents our investigation on iterativedecoding performances of some sparse-graph codes on block-fading Rayleigh channels. The considered code ensembles are standard LDPC codes and Root-LDPC codes, first proposed in and shown to be able to attain the full transmission diversity. We study the iterative threshold performance of those codes as a function of fading gains of the transmission channel and propose a numerical approximation of the iterative threshold versus fading gains, both both LDPC and Root-LDPC codes.Also, we show analytically that, in the case of 2 fading blocks,the iterative threshold root of Root-LDPC codes is proportional to (α1 α2)1, where α1 and α2 are corresponding fading gains.From this result, the full diversity property of Root-LDPC codes immediately follows.

Imaging for clarification of accusation of treatment error

In the assessment of medical malpractice imaging methods can be used for the documentation of crucial morphological findings which are indicative for or against an iatrogenically caused injury. The clarification of deaths in this context can be usefully supported by postmortem imaging (primarily native computed tomography, angiography, magnetic resonance imaging). Postmortem imaging offers significant additional information compared to an autopsy in the detection of iatrogenic air embolisms and documentation of misplaced medical aids before dissection with an inherent danger of relocation. Additional information is supplied by postmortem imaging in the search for sources of bleeding as well as the documentation of perfusion after cardiovascular surgery. Key criteria for the decision to perform postmortem imaging can be obtained from the necessary preliminary inspection of clinical documentation.

Error and attack tolerance of layered complex networks.

Many complex systems may be described by not one but a number of complex networks mapped on each other in a multi-layer structure. Because of the interactions and dependencies between these layers, the state of a single layer does not necessarily reflect well the state of the entire system. In this paper we study the robustness of five examples of two-layer complex systems: three real-life data sets in the fields of communication (the Internet), transportation (the European railway system), and biology (the human brain), and two models based on random graphs. In order to cover the whole range of features specific to these systems, we focus on two extreme policies of system's response to failures, no rerouting and full rerouting. Our main finding is that multi-layer systems are much more vulnerable to errors and intentional attacks than they appear from a single layer perspective.

L'erreur en médecine ambulatoire: comment l'aborder. [Error in ambulatory medicine: how to deal with it?]

Medical errors compromise patient safety in ambulatory practice. These errors must be faced in a framework that reduces to a minimum their consequences for the patients. This approach relies on the implementation of a new culture without stigmatization and where errors are disclosed to the patients; this culture implies the build up of a system for reporting errors associated to an in-depth analysis of the system, looking for root causes and insufficient barriers with the aim to fix them. A useful education tool is the "critical situations" meeting during which physicians are encouraged to openly present adverse events and "near misses". Their analysis, with supportive attitude towards involved staff members, allows to reveal systems failures within the institution or the private practice.

Model selection and error estimation

We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalization: any good error estimate may be converted into a data-based penalty function and the performance of the estimate is governed by the quality of the error estimate. We consider several penalty functions, involving error estimates on independent test data, empirical {\sc vc} dimension, empirical {\sc vc} entropy, andmargin-based quantities. We also consider the maximal difference between the error on the first half of the training data and the second half, and the expected maximal discrepancy, a closely related capacity estimate that can be calculated by Monte Carlo integration. Maximal discrepancy penalty functions are appealing for pattern classification problems, since their computation is equivalent to empirical risk minimization over the training data with some labels flipped.

Random measurement error and regression dilution bias.

Summary points: - The bias introduced by random measurement error will be different depending on whether the error is in an exposure variable (risk factor) or outcome variable (disease) - Random measurement error in an exposure variable will bias the estimates of regression slope coefficients towards the null - Random measurement error in an outcome variable will instead increase the standard error of the estimates and widen the corresponding confidence intervals, making results less likely to be statistically significant - Increasing sample size will help minimise the impact of measurement error in an outcome variable but will only make estimates more precisely wrong when the error is in an exposure variable

The KAI Cognitive Style Inventory: Was it personality all along?

Kirton's Adaption-Innovation Inventory (KAI) is a widely-used measure of "cognitive style." Surprisingly, there is very little research investigating the discriminant and incremental validity of the KAI. In two studies (n = 213), we examined whether (a) we could predict KAI scores with the "big five" personality dimensions and (b) the KAI scores predicted leadership behavior when controlling for personality and ability. Correcting for measurement error, we found that KAI scores were predicted mostly by personality and gender (multiple R = 0.82). KAI scores did not predict variance in leadership while controlling for established predictors. Our findings add to recent literature that questions the uniqueness and utility of cognitive style or similar "style" constructs; researchers using such measures must control for the big five factors and correct for measurement error to avoid confounded interpretations.