Spatial Diffuseness Features for DNN-Based Speech Recognition in Noisy and Reverberant Environments

We propose a spatial diffuseness feature for deep neural network (DNN)-based automatic speech recognition to improve recognition accuracy in reverberant and noisy environments. The feature is computed in real-time from multiple microphone signals without requiring knowledge or estimation of the direction of arrival, and represents the relative amount of diffuse noise in each time and frequency bin. It is shown that using the diffuseness feature as an additional input to a DNN-based acoustic model leads to a reduced word error rate for the REVERB challenge corpus, both compared to logmelspec features extracted from noisy signals, and features enhanced by spectral subtraction.Comment: accepted for ICASSP201

A Framework for the Systematic Evaluation of Data and Analytics Use Cases at an Early Stage

Due to the immense growth of collected data and advancing big data technologies, there are countless potential use cases of data and analytics. But most data initiatives fail and do not bring the desired outcome. One essential reason for this situation is the lack of a systematic approach to evaluate and select promising analytics use cases. This study presents an evaluation framework that enables the systematic screening at an early stage by assessing nine criteria with the help of a scoring model. It also supports a prioritization among several use cases and facilitates the communication to decision makers. The action design research approach was followed to build, test, and evaluate the framework in three iterative design cycles. It was developed in close collaboration with Bundesdruckerei GmbH, an IT-security company owned by the German government that offers products and services for secure identities, data, and infrastructures

Development of a Laser Double-wire Directed Energy Deposition Process for Functionally Graded Materials and In-situ alloying

Development of a Laser Double-wire Directed Energy Deposition process (LD-DED). Utilizing high material efficiency of the laser wire process for multi-material additive manufacturing. Enabling omnidirectional wire based build up of in-situ fabricated alloys and Functionally Graded Material

Pancreatoduodenectomy with or without Pyloric Preservation: A Clinical Outcomes Comparison

Pyloric preservation (PP) can frequently be performed at the time of pancreatoduodenectomy (PD), although some reports have linked it to inferior outcomes such as delayed gastric emptying (DGE). We reviewed records in a single-surgeon practice to assess outcomes after PD with or without PP. There were 133 PDs with 67 PPPDs and 66 PDs. Differences between PPPD and PD groups included cancer frequency, tumor size, OR time, blood loss, and transfusion rate. However, postoperative morbidity rate and grade, NG tube duration, NGT reinsertion rate, DGE, and length of stay were similar. There was no difference among patients with pancreatic cancer. No detrimental outcomes are associated with pyloric preservation during PD. Greater intraoperative ease and superior survival in the PPPD group are due to confounding, tumor-related variables in this nonrandomized comparison. Nevertheless, we intend to continue the use of PP with our technique in patients who meet the stated criteria

Phylogenetic quantification of intra-tumour heterogeneity.

Intra-tumour genetic heterogeneity is the result of ongoing evolutionary change within each cancer. The expansion of genetically distinct sub-clonal populations may explain the emergence of drug resistance, and if so, would have prognostic and predictive utility. However, methods for objectively quantifying tumour heterogeneity have been missing and are particularly difficult to establish in cancers where predominant copy number variation prevents accurate phylogenetic reconstruction owing to horizontal dependencies caused by long and cascading genomic rearrangements. To address these challenges, we present MEDICC, a method for phylogenetic reconstruction and heterogeneity quantification based on a Minimum Event Distance for Intra-tumour Copy-number Comparisons. Using a transducer-based pairwise comparison function, we determine optimal phasing of major and minor alleles, as well as evolutionary distances between samples, and are able to reconstruct ancestral genomes. Rigorous simulations and an extensive clinical study show the power of our method, which outperforms state-of-the-art competitors in reconstruction accuracy, and additionally allows unbiased numerical quantification of tumour heterogeneity. Accurate quantification and evolutionary inference are essential to understand the functional consequences of tumour heterogeneity. The MEDICC algorithms are independent of the experimental techniques used and are applicable to both next-generation sequencing and array CGH data.This is the final published version. It was originally published by PLoS in PLoS Computational Biology here: http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1003535