The next generation optical network demands unprecedented performance due to ultra-high aggregate bandwidth and the many channels transported by a single fiber. In dense wavelength division multiplexing (DWDM) networks, optical channels travel for hundreds of kilometers and thus they suffer from attenuation, noise, jitter, dispersion and other degradations due to photon-matter interactions. Amo...

Shortage of available training data is holding back progress in the area of automated error detection. This paper investigates two alternative methods for artificially generating writing errors, in order to create additional resources. We propose treating error generation as a machine translation task, where grammatically correct text is translated to contain errors. In addition, we explore a s...

Berreu et. al. in their landmark paper first introduced turbo codes (TC), which could achieve energy efficiencies within 0.7 dB of Shannon’s limit. Now TC is one of the main options for error correcting codes (ECC) in third generation mobile standards as in UMTS (Universal Mobile Telecommunications System) and cdma2000. UMTS and cdma2000 standards use two types of ECC; Convolutional coding and ...

We demonstrate that the bidirectionality of deep grammars, allowing them to generate as well as parse sentences, can be used to automatically and effectively identify errors in the grammars. The system is tested on two implemented HPSG grammars: Jacy for Japanese, and the ERG for English. Using this system, we were able to increase generation coverage in Jacy by 18% (45% to 63%) with only four ...

Motivation Next-generation sequencing platforms have produced huge amounts of sequence data. This is revolutionizing every aspect of genetic and genomic research. However, these sequence datasets contain quite a number of machine-induced errors-e.g. errors due to substitution can be as high as 2.5%. Existing error-correction methods are still far from perfect. In fact, more errors are sometimes...

In any real–world application scenario, natural language generation (NLG) systems have to employ grammars consisting of tremendous amounts of rules. Detecting and fixing errors in such grammars is therefore a highly tedious task. In this work we present a data mining algorithm which deduces incorrect grammar rules by abductive reasoning out of positive and negative training examples. More speci...

Error tolerant backbone resonance assignment is the cornerstone of the NMR structure determination process. Although a variety of assignment approaches have been developed, none works sufficiently well on noisy fully automatically picked peaks to enable the subsequent automatic structure determination steps. We have designed an integer linear programming (ILP) based assignment system (IPASS) th...

Hyperarticulate speech to computers remains a poorly understood phenomenon, in spite of its association with elevated recognition errors. The present research analyzes the type and magnitude of linguistic adaptations that occur when people engage in error resolution with computers. A semi-automatic simulation method incorporating a novel error generation capability was used to collect speech da...

Viterbi Algorithm Decoder Enhanced with Non-transmittable Codewords is one of the best decoding algorithm which effectively improves forward error correction performance. HoweverViterbi decoder enhanced with NTCs is not yet designed to work in storage media devices. Currently Reed Solomon (RS) Algorithm is almost the dominant algorithm used in correcting error in storage media. Conversely, rece...