Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include monitoring network actions between resources within a network and extracting encryption data from said network actions. The operations may include detecting connection security data from said encryption data and obtaining a resource health report for a resource in said network. The operations may include merging connection security data with said resource health report and generating a security compliance report.

Abstract: A method for predicting petrophysical properties of a three-dimensional (3D) volume includes receiving input data related to the 3D volume. The method includes determining a clustering scheme for the input data based on the input data, clustering the input data based on the clustering scheme to generate a plurality of clusters, and associating the plurality of clusters with a plurality of CRTs based on the input data. The method also includes generating predicted training sets for the petrophysical properties based on the clustering of the input data, the plurality of CRTs, or a combination thereof, selecting a representative predicted training set from the predicted training sets based on the input data, generating a model based on the representative predicted training set, and predicting the petrophysical properties of the 3D volume based on the model.

Abstract: A method for autonomously simulating infill drilling of one or more wells includes calculating a plurality of connected volumes in a reservoir model. The method also includes determining that a total hydrocarbon production of one or more existing wells inside the reservoir model has decreased below a predetermined hydrocarbon production threshold. The method also includes determining that one or more drilling rigs have a capacity to support drilling a first new well in response to determining that the total hydrocarbon production has decreased below the predetermined hydrocarbon production threshold. The first new well is a production well. The method also includes determining an opportunity index in response to determining that one or more drilling rigs have the capacity. The method also includes identifying a target in the opportunity index. The method also includes placing the first new well in the reservoir model in response to identifying the target.

Abstract: A method for tracking and mitigating greenhouse gases (GHG) in climate science and/or Earth systems modelling includes training a system to produce a trained system. The system is trained to track GHG emissions and/or flux. The method also includes receiving input data related to a situation at a site. The method also includes predicting one or more outputs using the trained system. The one or more outputs are predicted based upon the input data. The method also includes comparing decarbonization strategies based upon the one or more outputs. The method also includes recommending one of the decarbonization strategies to reduce the GHG emissions and/or flux in the situation at the site based upon the comparison.

Abstract: Workflow optimization and re-distribution involves a target task set that is determined from a plurality of tasks in a workflow and based on a data flow of the workflow. The target task set is re-distributed to obtain at least one re-distributed task set. Each re-distributed task set indicates a respective data path different from a data path of the target task set and has a same function as the target task set. A simulated data flow for the at least one re-distributed task set is obtained by simulating data flowing in at least one data path indicated by the at least one re-distributed task set. An optimized task set for the target task set is determined based on the simulated data flow for the at least one re-distributed task set.

Abstract: A resource deployment health report graph that defines a first plurality of resource dependencies set as a needed resource dependency type and a second plurality of resource dependencies set as an optional resource dependency type is generated prior to resources being connected in a container-based environment. An analysis of the resource deployment health report graph is performed to determine a status of each of the first plurality of resource dependencies and each of the second plurality of resource dependencies. It is determined whether each of the first plurality of resource dependencies and the second plurality of resource dependencies is marked ready in the resource deployment health report graph based on the analysis. In response to determining that each of the first plurality of resource dependencies and the second plurality of resource dependencies is marked ready, it is determined that an actual deployment is successfully implemented in the container-based environment.

Abstract: Managing reconciliation of custom resources by operators is provided. An operator is run to perform a reconciliation process to reconcile a current state of a custom resource with a desired state for the custom resource in response to one or more changes being detected in at least one of the custom resource and a set of objects corresponding to the custom resource. A new reconcile result is received from the operator after performing the reconciliation process. It is determined whether the new reconcile result is success. In response to determining that the new reconcile result is success, a snapshot of the custom resource along with the set of objects corresponding to the custom resource is captured. The reconciliation process of the operator is suspended until one or more other changes are detected in at least one of the custom resource and the set of objects corresponding to the custom resource.

Abstract: Mechanisms are provided, in a data processing system specifically configured to implement a computer container management platform in which Operators and Operator Controllers are used to manage at least one custom resource associated with a containerized application, to receive an Operator Deployment comprising an Operator Container having an Operator with a plurality of Operator Controllers. A process control manager (PCM) process configures each Operator Controller to execute as a separate process from each of the other Operator Controllers of the Operator Container. The Operator of the Operator Container is run at least by executing the Operator Controllers of the Operator in separate Operator runtimes based on the configuring of the Operator Controllers.

Abstract: A method includes receiving data representing reservoir properties for a subsurface volume, conducting an uncertainty analysis by simulating different model realizations representing the subsurface volume, identifying a first hot spot of the subsurface volume based on the uncertainty analysis, the first hot spot representing an area having a high predicted performance, relative to other areas of the subsurface volume, based on the simulating of the different model realizations representing the subsurface volume, identifying a second hot spot of the subsurface volume using a machine learning model that is trained to predict well performance based on the one or more reservoir properties, evaluating the first and second hot spots for well placement based on the predicted well performance at the first and second hot spots, respectively, and selecting at least one of the first hot spot or the second hot spot for well construction.

Abstract: A method includes training a proxy machine learning model to predict an output of a simulation of a physics-based model of a subsurface volume, based on simulation results generated based on the physics-based model and historical data, applying a respective set of uncertainty parameters to the trained proxy machine learning model to generate a solution, returning the generated solution as a solution responsive to determining that a difference between the generated solution and the historical data is less than an error tolerance, and visualizing one or more properties of a subsurface volume using the trained proxy model.

Abstract: A magnetic resonance imaging method includes: obtaining three-dimensional under-sampling data of a target object based on a first three-dimensional magnetic resonance imaging sequence; obtaining a three-dimensional point spread function based on the three-dimensional under-sampling data or a two-dimensional mapping data of the target object; obtaining a sensitivity map of the target object based on the data collected by three-dimensional low-resolution complete sampling; performing imaging reconstruction to the three-dimensional under-sampling data based on the three-dimensional point spread function and the sensitivity map to obtain a reconstructed magnetic resonance image. The first three-dimensional magnetic resonance imaging sequence has a first sinusoidal gradient field on a phase direction and a second sinusoidal gradient field on a layer selection direction. 0-order moments of the first and the second three-dimensional magnetic resonance imaging sequences are 0.

Abstract: Workflow optimization and re-distribution involves a target task set that is determined from a plurality of tasks in a workflow and based on a data flow of the workflow. The target task set is re-distributed to obtain at least one re-distributed task set. Each re-distributed task set indicates a respective data path different from a data path of the target task set and has a same function as the target task set. A simulated data flow for the at least one re-distributed task set is obtained by simulating data flowing in at least one data path indicated by the at least one re-distributed task set. An optimized task set for the target task set is determined based on the simulated data flow for the at least one re-distributed task set.

Abstract: A coreflood experiment may be modeled by generating a three dimensional computer simulation model of a core plug and modeling within the three dimensional computer simulation model one or both of a fluid introduction element or a fluid extraction element of a core holder used in the coreflood experiment. Once generated, the model may be loaded and used when running a simulation to model a heterogeneous distribution of fluid flow proximate one or more faces of the core plug.

Abstract: A flexible radiofrequency receiving coil array. The flexible radiofrequency receiving coil array is provided on a flexible panel and comprises several rows of coil units. Adjacent two rows of coil units in the several rows of coil units are alternately arranged. Preamplifiers are provided in the coil units. In the flexible radiofrequency receiving coil array, two preamplifiers in adjacent two coil units are provided on a same preamplifier mounting plate on the flexible panel, where multiple preamplifier mounting plates are provided on the flexible panel, and the preamplifier mounting plates of different columns and rows are linearly arranged. The flexible radiofrequency receiving coil array effectively reduces the distribution density of the preamplifiers, ensures the flexibility and maximum degree of distension of the coil array, and improves the fit of the coil array to the human body, thus increasing image signal-to-noise ration and image quality.

Abstract: A flexible radiofrequency receiving coil array. The flexible radiofrequency receiving coil array is provided on a flexible panel and comprises several rows of coil units. Adjacent two rows of coil units in the several rows of coil units are alternately arranged. Preamplifiers are provided in the coil units. In the flexible radiofrequency receiving coil array, two preamplifiers in adjacent two coil units are provided on a same preamplifier mounting plate on the flexible panel, where multiple preamplifier mounting plates are provided on the flexible panel, and the preamplifier mounting plates of different columns and rows are linearly arranged. The flexible radiofrequency receiving coil array effectively reduces the distribution density of the preamplifiers, ensures the flexibility and maximum degree of distension of the coil array, and improves the fit of the coil array to the human body, thus increasing image signal-to-noise ration and image quality.

Abstract: An access point (AP) is configured to transmit packets to a client device over a communication channel. The AP determines a motion indictor indicative of motion of the client device based on a sequence of channel state information measurements, and measures a signal-to-noise ratio (SNR). The AP selects a transmission parameter among candidate transmission parameters using a learning-based algorithm based on observation parameters including the motion indicator, the SNR, and a device identifier for the client device. The AP employs the transmission parameter to transmit packets to the client device, and measures a transmission performance associated with the transmission parameter based on the transmitted packets. The AP updates the learning-based algorithm based on the observation parameters and the transmission performance for a next pass through the selecting, the employing, and the measuring.

Abstract: A magnetic resonance imaging method includes: obtaining three-dimensional under-sampling data of a target object based on a first three-dimensional magnetic resonance imaging sequence; obtaining a three-dimensional point spread function based on the three-dimensional under-sampling data or a two-dimensional mapping data of the target object; obtaining a sensitivity map of the target object based on the data collected by three-dimensional low-resolution complete sampling; performing imaging reconstruction to the three-dimensional under-sampling data based on the three-dimensional point spread function and the sensitivity map to obtain a reconstructed magnetic resonance image. The first three-dimensional magnetic resonance imaging sequence has a first sinusoidal gradient field on a phase direction and a second sinusoidal gradient field on a layer selection direction. 0-order moments of the first and the second three-dimensional magnetic resonance imaging sequences are 0.

Abstract: Embodiments of the invention provide a method, system and computer program product for personalized key object detection in a live video stream. The method includes streaming a live video stream in a window of a computing device and during the streaming, collecting biophysical data of an end user viewing the playing back and responding to ones of the collected biophysical data that indicate a positive reaction by associating a contemporaneously displayed frame of the live video stream with the positive reaction. Thereafter, each corresponding frame associated with positive feedback can be processed by identifying key words presented in text of the feedback to the corresponding frame, matching the identified key words to a tag of an object visually presented in the corresponding frame, and storing a reference to the object in connection with the end user as an object of interest for which targeted marketing may be presented.

Abstract: Embodiments of the invention provide a method, system and computer program product for personalized key object detection in a live video stream. The method includes streaming a live video stream in a window of a computing device and during the streaming, collecting biophysical data of an end user viewing the playing back and responding to ones of the collected biophysical data that indicate a positive reaction by associating a contemporaneously displayed frame of the live video stream with the positive reaction. Thereafter, each corresponding frame associated with positive feedback can be processed by identifying key words presented in text of the feedback to the corresponding frame, matching the identified key words to a tag of an object visually presented in the corresponding frame, and storing a reference to the object in connection with the end user as an object of interest for which targeted marketing may be presented.

Abstract: An access point (AP) is configured to transmit packets to a client device over a communication channel. The AP determines a motion indictor indicative of motion of the client device based on a sequence of channel state information measurements, and measures a signal-to-noise ratio (SNR). The AP selects a transmission parameter among candidate transmission parameters using a learning-based algorithm based on observation parameters including the motion indicator, the SNR, and a device identifier for the client device. The AP employs the transmission parameter to transmit packets to the client device, and measures a transmission performance associated with the transmission parameter based on the transmitted packets. The AP updates the learning-based algorithm based on the observation parameters and the transmission performance for a next pass through the selecting, the employing, and the measuring.