Application of a three-step approach for prediction of combustion instabilities in industrial gas turbine burners

Abstract Recently, because of environmental regulations, gas turbine manufacturers are restricted to produce machines that work in the lean combustion regime. Gas turbines operating in this regime are prone to combustion-driven acoustic oscillations referred as combustion instabilities. These oscillations could have such high amplitude that they can damage gas turbine hardware. In this study, the three-step approach for combustion instabilities prediction is applied to an industrial test rig. As the first step, the flame transfer function (FTF) of the burner is obtained performing unsteady computational fluid dynamics (CFD) simulations. As the second step, the obtained FTF is approximated with an analytical time-lag-distributed model. The third step is the time-domain simulations using a network model. The obtained results are compared against the experimental data. The obtained results show a good agreement with the experimental ones and the developed approach is able to predict thermoacoustic instabilities in gas turbines combustion chambers

Visual Prosody: Facial Movements Accompanying Speech

As we articulate speech, we usually move the head and exhibit various facial expressions. This visual aspect of speech aids understanding and helps communicating additional information, such as the speaker's mood. We analyze quantitatively head and facial movements that accompany speech and investigate how they relate to the text's prosodic structure. We recorded several hours of speech and measured the locations of the speakers' main facial features as well as their head poses. The text was evaluated with a prosody prediction tool, identifying phrase boundaries and pitch accents. Characteristic for most speakers are simple motion patterns that are repeatedly applied in synchrony with the main prosodic events. Direction and strength of head movements vary widely from one speaker to another, yet their timing is typically well synchronized with the spoken text. Understanding quantitatively the correlations between head movements and spoken text is important for synthesizing photo-realistic talking heads. Talking heads appear much more engaging when they exhibit realistic motion pattern

Mitotic figure recognition: Agreement among pathologists and computerized detector

Abstract. Despite the prognostic importance of mitotic count as one of the components of the Bloom -Richardson grad

Do Pregnant Women and Those at Risk of Developing Post-Natal Depression Consume Lower Amounts of Long Chain Omega-3 Polyunsaturated Fatty Acids?

The aims were to compare intakes of long chain omega-3 polyunsaturated fatty acid (LC n-3 PUFA) in pregnant and non-pregnant women in Australia and to compare these intakes to the Australian National Nutrition Survey of 1995 (NNS95) [1] and to determine if the LC n-3 PUFA intakes differed in women who may be ‘at risk’ compared with women ‘not at risk’ of developing post-natal depression (PND). A validated LC n-3 PUFA food frequency questionnaire and pregnant women’s Edinburgh Postnatal Depression Scale (EPDS) scores were used. LC n-3 PUFA intakes were comparable to the NNS95 but did not differ due to pregnancy or whether or not a woman is at risk of developing PND

Mitotic Figure Recognition: Agreement among Pathologists and Computerized Detector

Despite the prognostic importance of mitotic count as one of the components of the Bloom – Richardson grade [3], several studies ([2, 9, 10]) have found that pathologists’ agreement on the mitotic grade is fairly modest. Collecting a set of more than 4,200 candidate mitotic figures, we evaluate pathologists' agreement on individual figures, and train a computerized system for mitosis detection, comparing its performance to the classifications of three pathologists. The system’s and the pathologists’ classifications are based on evaluation of digital micrographs of hematoxylin and eosin stained breast tissue. On figures where the majority of pathologists agree on a classification, we compare the performance of the trained system to that of the individual pathologists. We find that the level of agreement of the pathologists ranges from slight to moderate, with strong biases, and that the system performs competitively in rating the ground truth set. This study is a step towards automatic mitosis count to accelerate a pathologist's work and improve reproducibility