Robust decoding of variable-length encoded Markov sources using a three-dimensional trellis

In this letter, we present an improved index-based a-posteriori probability (APP) decoding approach for the error-resilient transmission of packetized variable-length encoded Markov sources. The proposed algorithm is based on a novel two-dimensional (2D) state representation which leads to a three-dimensional trellis with unique state transitions. APP decoding on this trellis is realized by employing a 2D version of the BCJR algorithm where all available source statistics can be fully exploited in the source decoder. For an additional use of channel codes the proposed approach leads to an increased error-correction performance compared to a one-dimensional state representation.     

An Efficient Variable-Length Code Construction for Iterative Source-Channel Decoding

We present a novel variable-length code (VLC) construction which exhibits an inherent error correcting capability due to the exclusive presence of codewords with even Hamming weight. Besides error robustness, the proposed code construction features a similar codeword length distribution as Golomb-Rice codes, and therefore, in particular for sources with exponentially distributed symbols, has good source compression properties at the same time. We show that in a source channel coding framework with outer source encoding, inner channel encoding with a recursive convolutional code, and iterative decoding the proposed VLC construction can lead to significant performance improvements compared to fixed-length source encoding with optimized mappings. In particular, simulation results for the AWGN channel verify that for Gauss-Markov sources a performance close to the theoretical limit can be achieved.     

Iterative joint source-channel decoding of variable-length codes using residual source redundancy

We present a novel symbol-based soft-input a posteriori probability (APP) decoder for packetized variable-length encoded source indexes transmitted over wireless channels where the residual redundancy after source encoding is exploited for error protection. In combination with a mean-square or maximum APP estimation of the reconstructed source data, the whole decoding process is close to optimal. Furthermore, solutions for the proposed APP decoder with reduced complexity are discussed and compared to the near-optimal solution. When, in addition, channel codes are employed for protecting the variable-length encoded data, an iterative source-channel decoder can be obtained in the same way as for serially concatenated codes, where the proposed APP source decoder then represents one of the two constituent decoders. The simulation results show that this iterative decoding technique leads to substantial error protection for variable-length encoded correlated source signals, especially, when they are transmitted over highly corrupted channels.     

Suicide myths and health care provider bias

Four cases of carotid body tumor are reported, and the diagnosis and treatment are also discussed. We consider that color Doppler flow image and carotid angiography, especially digital subtraction angiography, are of great value to the diagnosis of carotid body tumor. In addition, the collateral cerebral cross-flow was promoted preoperatively with the use of compressing exercises of the carotid artery, and controlled by transcranial Doppler. This means to provide the basis for choosing the operative opportunity and for managing the carotid artery. The operative method was dependent on preoperative color Doppler flow image, carotid angiography, and relationship between the tumor and the carotid artery during operation.     

Common phobias

Mrs. Brown, a 65-year-old woman, was terrified of being alone at night and suffered from nyctophobia. Her husband had been dead for several years, and her 40-year-old son lived in another state with his family. She often called him in the middle of the night in a state of panic, and he felt helpless about her situation. She lived in a senior housing community that never had any problems with crime. Nonetheless, she lived in a continual stage of anxiety.     

Low-complexity iterative joint source-channel decoding for variable-length encoded Markov sources

In this paper, we present a novel packetized bit-level decoding algorithm for variable-length encoded Markov sources, which calculates reliability information for the decoded bits in the form of a posteriori probabilities (APPs). An interesting feature of the proposed approach is that symbol-based source statistics in the form of the transition probabilities of the Markov source are exploited as a priori information on a bit-level trellis. This method is especially well-suited for long input blocks, since in contrast to other symbol-based APP decoding approaches, the number of trellis states does not depend on the packet length. When additionally the variable-length encoded source data is protected by channel codes, an iterative source-channel decoding scheme can be obtained in the same way as for serially concatenated codes. Furthermore, based on an analysis of the iterative decoder via extrinsic information transfer charts, it can be shown that by using reversible variable-length codes with a free distance of two, in combination with rate-1 channel codes and residual source redundancy, a reliable transmission is possible even for highly corrupted channels. This justifies a new source-channel encoding technique where explicit redundancy for error protection is only added in the source encoder.     

Caring for interpersonal violence survivors

Interpersonal violence is a serious public health problem in the United States. Millions of violent injuries occur each year, but the magnitude of the problem can only be estimated. The National Child Abuse and Neglect Data System reported that 3,140,000 abused or neglected children were reported in 1994 to child protective services agencies.