Abstract: A data source is monitored. During the monitoring, an arrival at the data source of each of one or more sets of one or more features is detected. In response to detecting the arrival at the data source of at least a first set of one or more features of the one or more sets of one or more features, data is extracted from the first set of one or more features, data for at least a second set of one or more features of the one or more sets of one or more features is estimated, wherein the second set of one or more features has not yet arrived at the data source, and, based on the extracted data and the estimated data, a data quality metric is predicted.

Abstract: A satellite is disclosed, including a body and a communication device attached to the body. The body has an additively manufactured external wall structure at least partially forming an enclosed compartment, and the communication device is configured to receive and transmit data while in space.

Abstract: Systems and methods are described that enable an incoming communication requesting a real-time (e.g., voice, voice-video, etc.) communication and selectively allowing the called communication device to auto-answer the communication. The selective answering may be rule and/or attribute based and depend, entirely or in part, on presence data of a user associated with the called communication device. Auto-answering may be further configured to auto-answer all or less than all of the communication media types (e.g., only auto-answer an audio-video call with audio). Additionally, or alternatively, rules may be combined, overridden, conditionally implemented, or otherwise combined or structured relative to other rules for auto-answering an incoming communication.

Abstract: Collaboration methods and systems are provided. An illustrative collaboration method includes receiving an input indicating a desire to share image content among participants of a collaborative communication session; identifying a first portion of the image content that will have blurring applied thereto when shared among the participants of the collaborative communication session; identifying a second portion of the image content that will not have blurring applied thereto when shared among the participants of the collaborative communication session; and sharing the image content with the participants of the collaborative communication session such that the first portion of the image content is blurred and the second portion of the image content is unblurred.

Abstract: A satellite is disclosed, including a body and a communication device attached to the body. The body has an additively manufactured external wall structure at least partially forming an enclosed compartment, and the communication device is configured to receive and transmit data while in space.

Abstract: In embodiments of the present invention, features of an improved user authentication system features include receiving, by a processor of a computer system receiving a request for authorizing a first user, transmitting a prompt to a second user, receiving a first code from the second user, and transmitting the first code to a network location, and enabling access for the second user to the network location. Methods and systems include transmitting the first code to a network location accessible by authorized users.

Abstract: Aspects of the present disclosure are directed to apparatuses and methods for monitoring vital signs from a human being. Various such aspects involve an apparatus or method involving the monitoring of vital signs in a manner that facilitates enhanced characterization of physiological conditions. In many embodiments, two or more such vital signs are monitored. A signal acquisition, digitization, and computing module removing noise, extracts information useful for diagnosing a health or fitness characteristic of the human being, and/or compresses information to reduce data volume. A wireless communications circuit transmits the vital signs to a receiver.

Abstract: Systems and methods are described that enable an incoming communication requesting a real-time (e.g., voice, voice-video, etc.) communication and selectively allowing the called communication device to auto-answer the communication. The selective answering may be rule and/or attribute based and depend, entirely or in part, on presence data of a user associated with the called communication device. Auto-answering may be further configured to auto-answer all or less than all of the communication media types (e.g., only auto-answer an audio-video call with audio). Additionally, or alternatively, rules may be combined, overridden, conditionally implemented, or otherwise combined or structured relative to other rules for auto-answering an incoming communication.

Abstract: Techniques for providing high-performance buffer caches for transactional input/output (I/O) systems are disclosed. The techniques include obtaining a first logical creation time of a resource to be acquired by the first transaction during a pre-commit phase of a first transaction with an I/O system. When the first logical creation time exceeds a latest logical creation time from a set of resources previously acquired by the first transaction, the first logical creation time of the resource is compared with an earliest logical termination time from the set of resources. When the first logical creation time of the resource exceeds the earliest logical termination time from the set of resources, a conflict between the resource and the set of resources is detected, and a restart of the first transaction is triggered.

Abstract: Techniques for providing high-performance buffer caches for transactional input/output (I/O) systems are disclosed. The techniques include obtaining a first logical creation time of a resource to be acquired by the first transaction during a pre-commit phase of a first transaction with an I/O system. When the first logical creation time exceeds a latest logical creation time from a set of resources previously acquired by the first transaction, the first logical creation time of the resource is compared with an earliest logical termination time from the set of resources. When the first logical creation time of the resource exceeds the earliest logical termination time from the set of resources, a conflict between the resource and the set of resources is detected, and a restart of the first transaction is triggered.

Abstract: A system estimates quality of a digital image by accessing a corpus of digital images of one or more subjects, such as a facet of a property. The system will receive, for at least a subset of the corpus, an indicator that one or more patches of each image in the subset is out of focus. The system will train a classifier by obtaining a feature representation of each pixel in each image, along with a focus value that represents an extent to which each pixel in the image is in focus or out of focus. The system will use the classifier to analyze pixels of a new digital image and assess whether each analyzed pixel in the new digital image is in focus or out of focus. The system may use the image to assess whether an incident occurred, such as storm-related damage to the property.

Abstract: Techniques for providing high-performance buffer caches for transactional input/output (I/O) systems are disclosed. The techniques include obtaining a first logical creation time of a resource to be acquired by the first transaction during a pre-commit phase of a first transaction with an I/O system. When the first logical creation time exceeds a latest logical creation time from a set of resources previously acquired by the first transaction, the first logical creation time of the resource is compared with an earliest logical termination time from the set of resources. When the first logical creation time of the resource exceeds the earliest logical termination time from the set of resources, a conflict between the resource and the set of resources is detected, and a restart of the first transaction is triggered.

Abstract: Techniques for providing high-performance buffer caches for transactional input/output (I/O) systems are disclosed. The techniques include obtaining a first logical creation time of a resource to be acquired by the first transaction during a pre-commit phase of a first transaction with an I/O system. When the first logical creation time exceeds a latest logical creation time from a set of resources previously acquired by the first transaction, the first logical creation time of the resource is compared with an earliest logical termination time from the set of resources. When the first logical creation time of the resource exceeds the earliest logical termination time from the set of resources, a conflict between the resource and the set of resources is detected, and a restart of the first transaction is triggered.

Abstract: Techniques for providing high-performance buffer caches for transactional input/output (I/O) systems are disclosed. The techniques include obtaining a first logical creation time of a resource to be acquired by the first transaction during a pre-commit phase of a first transaction with an I/O system. When the first logical creation time exceeds a latest logical creation time from a set of resources previously acquired by the first transaction, the first logical creation time of the resource is compared with an earliest logical termination time from the set of resources. When the first logical creation time of the resource exceeds the earliest logical termination time from the set of resources, a conflict between the resource and the set of resources is detected, and a restart of the first transaction is triggered.

Abstract: A system estimates quality of a digital image by accessing a corpus of digital images of one or more subjects, such as a facet of a property. The system will receive, for at least a subset of the corpus, an indicator that one or more patches of each image in the subset is out of focus. The system will train a classifier by obtaining a feature representation of each pixel in each image, along with a focus value that represents an extent to which each pixel in the image is in focus or out of focus. The system will use the classifier to analyze pixels of a new digital image and assess whether each analyzed pixel in the new digital image is in focus or out of focus. The system may use the image to assess whether an incident occurred, such as storm-related damage to the property.

Abstract: A system estimates quality of a digital image by accessing a corpus of digital images of one or more subjects, such as a facet of a property. The system will receive, for at least a subset of the corpus, an indicator that one or more patches of each image in the subset is out of focus. The system will train a classifier by obtaining a feature representation of each pixel in each image, along with a focus value that represents an extent to which each pixel in the image is in focus or out of focus. The system will use the classifier to analyze pixels of a new digital image and assess whether each analyzed pixel in the new digital image is in focus or out of focus. The system may use the image to assess whether an incident occurred, such as storm-related damage to the property.

Abstract: A system estimates quality of a digital image by accessing a corpus of digital images of one or more subjects, such as a facet of a property. The system will receive, for at least a subset of the corpus, an indicator that one or more patches of each image in the subset is out of focus. The system will train a classifier by obtaining a feature representation of each pixel in each image, along with a focus value that represents an extent to which each pixel in the image is in focus or out of focus. The system will use the classifier to analyze pixels of a new digital image and assess whether each analyzed pixel in the new digital image is in focus or out of focus. The system may use the image to assess whether an incident occurred, such as storm-related damage to the property.

Abstract: Embodiments of a computer-implemented method for training a convolutional neural network (CNN) that is pre-trained using a set of color images are disclosed. The method comprises receiving a training dataset including multiple multidimensional images, each multidimensional image including a color image and a depth image; performing a fine-tuning of the pre-trained CNN using the depth image for each of the plurality of multidimensional images; obtaining a depth CNN based on the pre-trained CNN, wherein the depth CNN is associated with a first set of parameters; replicating the depth CNN to obtain a duplicate depth CNN being initialized with the first set of parameters; and obtaining a depth-enhanced color CNN based on the duplicate depth CNN being fine-tuned using the color image for each of the plurality of multidimensional images, wherein the depth-enhanced color CNN is associated with a second set of parameters.

Abstract: Embodiments of a computer-implemented method for training a convolutional neural network (CNN) that is pre-trained using a set of color images are disclosed. The method comprises receiving a training dataset including multiple multidimensional images, each multidimensional image including a color image and a depth image; performing a fine-tuning of the pre-trained CNN using the depth image for each of the plurality of multidimensional images; obtaining a depth CNN based on the pre-trained CNN, wherein the depth CNN is associated with a first set of parameters; replicating the depth CNN to obtain a duplicate depth CNN being initialized with the first set of parameters; and obtaining a depth-enhanced color CNN based on the duplicate depth CNN being fine-tuned using the color image for each of the plurality of multidimensional images, wherein the depth-enhanced color CNN is associated with a second set of parameters.

Abstract: Embodiments of the invention are related to systems and methods for setting parameters of implantable medical devices, amongst other things. In an embodiment, the invention includes a method for programming an implantable medical device including sensing concentrations of a predictive marker such as ET-1 in a patient, selecting programming parameter values based on the sensed concentrations of the predictive marker, and implementing the selected programming parameter values. In an embodiment the invention includes a method for detecting arrhythmia in a patient including sensing concentrations of the predictive marker in a patient, selecting a level of stringency to be used in an arrhythmia detection module based on the sensed concentrations of the predictive marker, sensing electrical signals in the patient, and evaluating the sensed electrical signals for indicia of an arrhythmia using the arrhythmia detection module. Other embodiments are also included herein.