Abstract: Systems and methods are disclosed for estimating aesthetic quality of digital images using deep learning. In particular, the disclosed systems and methods describe training a neural network to generate an aesthetic quality score digital images. In particular, the neural network includes a training structure that compares relative rankings of pairs of training images to accurately predict a relative ranking of a digital image. Additionally, in training the neural network, an image rating system can utilize content-aware and user-aware sampling techniques to identify pairs of training images that have similar content and/or that have been rated by the same or different users. Using content-aware and user-aware sampling techniques, the neural network can be trained to accurately predict aesthetic quality ratings that reflect subjective opinions of most users as well as provide aesthetic scores for digital images that represent the wide spectrum of aesthetic preferences of various users.

Abstract: The present invention relates to the provision of an organic compound or compounds containing a fluorenone derivative structure or its substituted derivatives to enhance the thermal stability of organic solar cells.

Abstract: Systems and methods for predicting usage based lifing and low cycle fatigue consumption are provided. In one example embodiment, a method can include obtaining historical flight data associated with one or more gas turbine engines of an aerial vehicle; obtaining data indicative of one or more operational conditions of the aerial vehicle during an operating period; determining whether the flight data is indicative of a usable flight; and constructing a model correlating low cycle fatigue consumption with flight data using a machine learning technique.

Abstract: Systems and methods are disclosed for estimating aesthetic quality of digital images using deep learning. In particular, the disclosed systems and methods describe training a neural network to generate an aesthetic quality score digital images. In particular, the neural network includes a training structure that compares relative rankings of pairs of training images to accurately predict a relative ranking of a digital image. Additionally, in training the neural network, an image rating system can utilize content-aware and user-aware sampling techniques to identify pairs of training images that have similar content and/or that have been rated by the same or different users. Using content-aware and user-aware sampling techniques, the neural network can be trained to accurately predict aesthetic quality ratings that reflect subjective opinions of most users as well as provide aesthetic scores for digital images that represent the wide spectrum of aesthetic preferences of various users.

Abstract: Systems and methods are disclosed for estimating aesthetic quality of digital images using deep learning. In particular, the disclosed systems and methods describe training a neural network to generate an aesthetic quality score digital images. In particular, the neural network includes a training structure that compares relative rankings of pairs of training images to accurately predict a relative ranking of a digital image. Additionally, in training the neural network, an image rating system can utilize content-aware and user-aware sampling techniques to identify pairs of training images that have similar content and/or that have been rated by the same or different users. Using content-aware and user-aware sampling techniques, the neural network can be trained to accurately predict aesthetic quality ratings that reflect subjective opinions of most users as well as provide aesthetic scores for digital images that represent the wide spectrum of aesthetic preferences of various users.

Abstract: Systems and methods for predicting usage based lifing and low cycle fatigue consumption are provided. In one example embodiment, a method can include obtaining historical flight data associated with one or more gas turbine engines of an aerial vehicle; obtaining data indicative of one or more operational conditions of the aerial vehicle during an operating period; determining whether the flight data is indicative of a usable flight; and constructing a model correlating low cycle fatigue consumption with flight data using a machine learning technique.

Abstract: Systems and methods are disclosed for estimating aesthetic quality of digital images using deep learning. In particular, the disclosed systems and methods describe training a neural network to generate an aesthetic quality score digital images. In particular, the neural network includes a training structure that compares relative rankings of pairs of training images to accurately predict a relative ranking of a digital image. Additionally, in training the neural network, an image rating system can utilize content-aware and user-aware sampling techniques to identify pairs of training images that have similar content and/or that have been rated by the same or different users. Using content-aware and user-aware sampling techniques, the neural network can be trained to accurately predict aesthetic quality ratings that reflect subjective opinions of most users as well as provide aesthetic scores for digital images that represent the wide spectrum of aesthetic preferences of various users.

Abstract: Systems and methods are disclosed for estimating aesthetic quality of digital images using deep learning. In particular, the disclosed systems and methods describe training a neural network to generate an aesthetic quality score digital images. In particular, the neural network includes a training structure that compares relative rankings of pairs of training images to accurately predict a relative ranking of a digital image. Additionally, in training the neural network, an image rating system can utilize content-aware and user-aware sampling techniques to identify pairs of training images that have similar content and/or that have been rated by the same or different users. Using content-aware and user-aware sampling techniques, the neural network can be trained to accurately predict aesthetic quality ratings that reflect subjective opinions of most users as well as provide aesthetic scores for digital images that represent the wide spectrum of aesthetic preferences of various users.

Abstract: The present invention relates to the provision of an organic compound or compounds containing a fluorenone derivative structure or its substituted derivatives to enhance the thermal stability of organic solar cells.

Abstract: Systems and methods are disclosed for estimating aesthetic quality of digital images using deep learning. In particular, the disclosed systems and methods describe training a neural network to generate an aesthetic quality score digital images. In particular, the neural network includes a training structure that compares relative rankings of pairs of training images to accurately predict a relative ranking of a digital image. Additionally, in training the neural network, an image rating system can utilize content-aware and user-aware sampling techniques to identify pairs of training images that have similar content and/or that have been rated by the same or different users. Using content-aware and user-aware sampling techniques, the neural network can be trained to accurately predict aesthetic quality ratings that reflect subjective opinions of most users as well as provide aesthetic scores for digital images that represent the wide spectrum of aesthetic preferences of various users.

Abstract: Methods for compression of sonic log data include STC processing, sorting peak components in the sonic data; filtering the sorted peak components to remove high-frequency portions in the peak components; and decimating the filtered peak components according to a selected ratio to produce compressed data. One method for telemetry transmission of downhole sonic log data includes sorting peak components in the sonic log data; compressing the sorted peak components to produce compressed data; packing the compressed data to produce data packets for telemetry transmission; and sending the data packets using telemetry.

Abstract: Techniques for displaying sonic logging data that provide highly reliable, visual quality-control (QC) indicators. One aspect herein is directed to a display of sonic logging data corresponding to a slowness frequency analysis (SFA) projection log.

Abstract: A method for acquiring and analyzing time-series data using singularities is described. This method allows for the analysis of data over a wide spectrum of frequencies. Once the data is acquired in an oil field, singularities of the data are extracted; and the extracted singularities are utilized to interpret the formation properties related to the data.

Abstract: The present invention relates to a detection method to differentiate between egg-derived ingredients and chicken-derived ingredients (chicken parts/tissues, excluding eggs) in foods or other products and primer pairs and probes used for specifically detecting chicken in foods or products.

Abstract: A method for in-situ calibrating acoustic receivers while the tool is in an open or cased borehole or during a logging run in a borehole. The method and system facilitate calibrating the acoustic receivers while they are mounted to a downhole acoustic tool. Calibrating the acoustic receivers in situ provides more accurate results than previously available. The method and system provide separate compensation factors for the acoustic receivers at different frequencies and for different transmission sources. The separate compensation factors facilitate more accurate signal acquisition over a wider range of conditions.

Abstract: A method for acquiring and analyzing time-series data using singularities is described. This method allows for the analysis of data over a wide spectrum of frequencies. Once the data is acquired in an oil field, singularities of the data are extracted; and the extracted singularities are utilized to interpret the formation properties related to the data.

Abstract: The present invention relates to a detection method to differentiate between egg-derived ingredients and chicken-derived ingredients (chicken parts/tissues, excluding eggs) in foods or other products and primer pairs and probes used for specifically detecting chicken in foods or products.

Abstract: Techniques for displaying sonic logging data that provide highly reliable, visual quality-control (QC) indicators. One aspect herein is directed to a display of sonic logging data corresponding to a slowness frequency analysis (SFA) projection log.

Abstract: A method and system for calibrating acoustic receivers. The method and system facilitate calibrating the acoustic receivers while they are mounted to a downhole acoustic tool. Calibrating the acoustic receivers in situ provides more accurate results than previously available. The method and system provide separate compensation factors for the acoustic receivers at different frequencies and for different transmission sources. The separate compensation factors facilitate more accurate signal acquisition over a wider range of conditions.

Abstract: Methods for compression of sonic log data include STC processing, sorting peak components in the sonic data; filtering the sorted peak components to remove high-frequency portions in the peak components; and decimating the filtered peak components according to a selected ratio to produce compressed data. One method for telemetry transmission of downhole sonic log data includes sorting peak components in the sonic log data; compressing the sorted peak components to produce compressed data; packing the compressed data to produce data packets for telemetry transmission; and sending the data packets using telemetry.