Abstract: A system and a method generate a recommendation on a mobile device. The system and the method may use a time, a location, a venue and/or an event to generate the recommendation. Further, the system and the method may use an event database to determine current interests of the user. Still further, the system and the method for generating a recommendation on a mobile device may use a transactional history of the user and/or behavior of other users to generate the recommendation. The system and the method may recommend, for example, digital media, news and event information, editorial content and/or physical or digital merchandise. As a result, the system and the method may generate a recommendation that corresponds to the current interests of the user.

Abstract: A system for simplified generation of systems for analysis of satellite images to geolocate one or more objects of interest. A plurality of training images labeled for a study object or objects with irrelevant features loaded into a preexisting feature identification subsystem causes automated generation of models for the study object. This model is used to parameterize pre-engineered machine learning elements that are running a preprogrammed machine learning protocol. Training images with the study are used to train object recognition filters. This filter is used to identify the study object in unanalyzed images. The system reports results in a requestor's preferred format.

Abstract: Disclosed are methods of treating a disorder or disease associated with myotonic dystrophy. Methods of treating a CNS dysfunction and/or cognitive impairment associated with myotonic dystrophy in a subject comprising administering a therapeutically effective amount of a GABAA receptor antagonist or inverse agonist to the subject are disclosed. Methods of treating a myotonic dystrophy associated disease or disorder caused by mis-splicing of GABRG2 in a subject comprising administering a therapeutically effective amount of a GABAA receptor antagonist or inverse agonist to the subject are disclosed. Methods of improving cognitive function or alertness in a subject having myotonic dystrophy comprising administering a therapeutically effective amount of a GABAA receptor antagonist or inverse agonist to the subject are disclosed.

Abstract: A method of cleaning a component within a turbine that includes disassembling the turbine engine to provide a flow path to an interior passageway of the component from an access point. The component has coked hydrocarbons formed thereon. The method further includes discharging a flow of cleaning solution towards the interior passageway from the access point, wherein the cleaning solution is configured to remove the coked hydrocarbons from the component.

Abstract: Techniques for recommending a prediction model from among a number of different prediction models are provided. Each of these prediction models has been trained based on a respective training data set, and each performs in accordance with a respective theoretical performance manifold. An indication of a region definable in relation to the theoretical performance manifolds of the different prediction models is received as input. For each of the different prediction models, the indication of the region is linked to features parameterizing the respective performance manifold; and one or more portions of the respective performance manifold is/are identified based on the features determined by the linking, the portion(s) having a volume and a shape that collectively denote an expected performance of the respective model for the input. The expected performance of the prediction models for the input is compared. Based on the comparison, one or more of the models is/are suggested.

Abstract: Techniques for quantifying accuracy of a prediction model that has been trained on a data set parameterized by multiple features are provided. The model performs in accordance with a theoretical performance manifold over an intractable input space in connection with the features. A determination is made as to which of the features are strongly correlated with performance of the model. Based on the features determined to be strongly correlated with performance of the model, parameterized sub-models are created such that, in aggregate, they approximate the intractable input space. Prototype exemplars are generated for each of the created sub-models, with the prototype exemplars for each created sub-model being objects to which the model can be applied to result in a match with the respective sub-model. The accuracy of the model is quantified using the generated prototype exemplars. A recommendation engine is provided for when there are particular areas of interest.

Abstract: A system for simplified generation of systems for analysis of satellite images to geolocate one or more objects of interest. A plurality of training images labeled for a study object or objects with irrelevant features loaded into a preexisting feature identification subsystem causes automated generation of models for the study object. This model is used to parameterize pre-engineered machine learning elements that are running a preprogrammed machine learning protocol. Training images with the study are used to train object recognition filters. This filter is used to identify the study object in unanalyzed images. The system reports results in a requestor's preferred format.

Abstract: A system for automated geospatial image analysis comprising a deep learning model that receives orthorectified geospatial images, pre-labeled to demarcate objects of interest. The module presents marked geospatial images and a second set of unmarked, optimized, training geospatial images to a convolutional neural network. This process may be repeated so that an image analysis software module can detect multiple object types or categories. The image analysis software module receives orthorectified geospatial images from one or more geospatial image caches. Using a multi-scale sliding window submodule, image analysis software scans geospatial images, detects objects present and geospatially locates them.

Abstract: A system and a method generate a recommendation on a mobile device. The system and the method may use a time, a location, a venue and/or an event to generate the recommendation. Further, the system and the method may use an event database to determine current interests of the user. Still further, the system and the method for generating a recommendation on a mobile device may use a transactional history of the user and/or behavior of other users to generate the recommendation. The system and the method may recommend, for example, digital media, news and event information, editorial content and/or physical or digital merchandise. As a result, the system and the method may generate a recommendation that corresponds to the current interests of the user.

Abstract: GABAA receptor mediated hypersomnia can be treated by administering a GABAA receptor antagonist (e.g., flumazenil; clarithromycin; picrotoxin; bicuculline; cicutoxin; and oenanthotoxin). In some embodiments, the GABAA receptor antagonist is flumazenil or clarithromycin. The GABAA receptor mediated hypersomnia includes shift work sleep disorder, obstructive sleep apnea/hypopnea syndrome, narcolepsy, excessive sleepiness, hypersomnia (e.g., idiopathic hypersomnia; recurrent hypersomnia; endozepine related recurrent stupor; and amphetamine resistant hypersomnia), and excessive sleepiness associated with shift work sleep disorder, obstructive sleep apnea/hypopnea syndrome, and hypersomnia (e.g., idiopathic hypersomnia; recurrent hypersomnia; endozepine related recurrent stupor; and amphetamine resistant hypersomnia.

Abstract: A system for broad area geospatial object recognition, identification, classification, location and quantification, comprising an image manipulation module to create synthetically-generated images to imitate and augment an existing quantity of orthorectified geospatial images; together with a deep learning module and a convolutional neural network serving as an image analysis module, to analyze a large corpus of orthorectified geospatial images, identify and demarcate a searched object of interest from within the corpus, locate and quantify the identified or classified objects from the corpus of geospatial imagery available to the system. The system reports results in a requestor's preferred format.

Abstract: A system for automated geospatial image analysis comprising a deep learning model that receives orthorectified geospatial images, pre-labeled to demarcate objects of interest. The module presents marked geospatial images and a second set of unmarked, optimized, training geospatial images to a convolutional neural network. This process may be repeated so that an image analysis software module can detect multiple object types or categories. The image analysis software module receives orthorectified geospatial images from one or more geospatial image caches. Using a multi-scale sliding window submodule, image analysis software scans geospatial images, detects objects present and geospatially locates them.

Abstract: A system for simplified generation of systems for analysis of satellite images to geolocate one or more objects of interest. A plurality of training images labeled for a study object or objects with irrelevant features loaded into a preexisting feature identification subsystem causes automated generation of models for the study object. This model is used to parameterize pre-engineered machine learning elements that are running a preprogrammed machine learning protocol. Training images with the study are used to train object recognition filters. This filter is used to identify the study object in unanalyzed images. The system reports results in a requestor's preferred format.

Abstract: A system for broad area geospatial object recognition, identification, classification, location and quantification, comprising an image manipulation module to create synthetically-generated images to imitate and augment an existing quantity of orthorectified geospatial images; together with a deep learning module and a convolutional neural network serving as an image analysis module, to analyze a large corpus of orthorectified geospatial images, identify and demarcate a searched object of interest from within the corpus, locate and quantify the identified or classified objects from the corpus of geospatial imagery available to the system. The system reports results in a requestor's preferred format.

Abstract: A system for automated geospatial image analysis comprising a deep learning model that receives orthorectified geospatial images, pre-labeled to demarcate objects of interest. The module presents marked geospatial images and a second set of unmarked, optimized, training geospatial images to a convolutional neural network. This process may be repeated so that an image analysis software module can detect multiple object types or categories. The image analysis software module receives orthorectified geospatial images from one or more geospatial image caches. Using a multi-scale sliding window submodule, image analysis software scans geospatial images, detects objects present and geospatially locates them.

Abstract: GABAA receptor mediated hypersomnia can be treated by administering a GABAA receptor antagonist (e.g., flumazenil; clarithromycin; picrotoxin; bicuculline; cicutoxin; and oenanthotoxin). In some embodiments, the GABAA receptor antagonist is flumazenil or clarithromycin. The GABAA receptor mediated hypersomnia includes shift work sleep disorder, obstructive sleep apnea/hypopnea syndrome, narcolepsy, excessive sleepiness, hypersomnia (e.g., idiopathic hypersomnia; recurrent hypersomnia; endozepine related recurrent stupor; and amphetamine resistant hypersomnia), and excessive sleepiness associated with shift work sleep disorder, obstructive sleep apnea/hypopnea syndrome, and hypersomnia (e.g., idiopathic hypersomnia; recurrent hypersomnia; endozepine related recurrent stupor; and amphetamine resistant hypersomnia.

Abstract: A system for simplified generation of systems for analysis of satellite images to geolocate one or more objects of interest. A plurality of training images labeled for a study object or objects with irrelevant features loaded into a preexisting feature identification subsystem causes automated generation of models for the study object. This model is used to parameterize pre-engineered machine learning elements that are running a preprogrammed machine learning protocol. Training images with the study are used to train object recognition filters. This filter is used to identify the study object in unanalyzed images. The system reports results in a requestor's preferred format.

Abstract: Prioritizing a customer service agent's responses to customer messages. In one form, an expected response time target is determined based on a time interval between sending an agent response and receiving a customer response from a particular customer. In other forms, other objective factors, such as message intervals, customer properties, and message properties, are used to determine the expected response time target. In yet other forms, a customer conversation can be automatically closed if the customer does not respond within a predetermined maximum time interval.

Abstract: A fan system of a turbine includes a fan mid shaft made of a coated steel material configured to extend along a center axis of a turbine. The fan mid shaft having an inner diameter surface. The fan system includes a dry film lubricant that is configured to be applied to at least a portion of the inner diameter surface of the fan mid shaft.

Abstract: A system for automated geospatial image analysis comprising a deep learning model that receives orthorectified geospatial images, pre-labeled to demarcate objects of interest. The module presents marked geospatial images and a second set of unmarked, optimized, training geospatial images to a convolutional neural network. This process may be repeated so that an image analysis software module can detect multiple object types or categories. The image analysis software module receives orthorectified geospatial images from one or more geospatial image caches. Using a multi-scale sliding window submodule, image analysis software scans geospatial images, detects objects present and geospatially locates them.