Abstract: Embodiments generate digital plans for agricultural fields. In an embodiment, a model receives digital inputs including stress risk data, product maturity data, field location data, planting date data, and/or harvest date data. The model mathematically correlates sets of digital inputs with threshold data associated with the stress risk data. The model is used to generate stress risk prediction data for a set of product maturity and field location combinations. In a digital plan, product maturity data or planting date data or harvest date data or field location data can be adjusted based on the stress risk prediction data. A digital plan can be transmitted to a field manager computing device. An agricultural apparatus can be moved in response to a digital plan.

Abstract: Techniques are provided for receiving a first set of historical agricultural data and a second set of historical agricultural data; generating a plurality of projected target yield ranges using the first set and the second set of historical agricultural data by generating a historic yield distribution; generating one or more yield ranking scores for one or more fields of a grower using the first set of historical agricultural data, and assigning a projected target yield range of the plurality of projected target yield ranges to each of the one or more fields based on the one or more yield ranking scores to generate assigned projected target yield ranges; receiving a third set of historical agricultural data comprising seed optimization data, and generating a recommended change in seed population or a recommended change in seed density; causing displaying the yield improvement recommendation for each of the one or more fields.

Abstract: The present invention provides a Gabor cube feature selection-based classification method for hyperspectral remote sensing images, comprising the following steps: generating three-dimensional Gabor filters according to set frequency and direction parameter values; convoluting hyperspectral remote sensing images with the three-dimensional Gabor filters to obtain three-dimensional Gabor features; selecting three-dimensional Gabor features, classification contribution degrees to various classes of which meet preset requirements, from the three-dimensional Gabor features; and classifying the hyperspectral remote sensing images by a multi-task joint sparse representation-based classification means by using the selected three-dimensional Gabor features. The present invention is based on the three-dimensional Gabor features, and the used three-dimensional Gabor features contain rich local change information of a signal and are competent in feature characterizing.

Abstract: The present disclosure provides an improved approach to implement a management infrastructure for computing environments. The user interfaces for local management nodes are cached at a central management node. The cached copies of the local node UIs can then be executed as if the user was actually operating from the local node.

Abstract: Embodiments generate digital plans for agricultural fields. In an embodiment, a model receives digital inputs including stress risk data, product maturity data, field location data, planting date data, and/or harvest date data. The model mathematically correlates sets of digital inputs with threshold data associated with the stress risk data. The model is used to generate stress risk prediction data for a set of product maturity and field location combinations. In a digital plan, product maturity data or planting date data or harvest date data or field location data can be adjusted based on the stress risk prediction data. A digital plan can be transmitted to a field manager computing device. An agricultural apparatus can be moved in response to a digital plan.

Abstract: Techniques are provided for receiving a first set of historical agricultural data and a second set of historical agricultural data; generating a plurality of projected target yield ranges using the first set and the second set of historical agricultural data by generating a historic yield distribution; generating one or more yield ranking scores for one or more fields of a grower using the first set of historical agricultural data, and assigning a projected target yield range of the plurality of projected target yield ranges to each of the one or more fields based on the one or more yield ranking scores to generate assigned projected target yield ranges; receiving a third set of historical agricultural data comprising seed optimization data, and generating a recommended change in seed population or a recommended change in seed density; causing displaying the yield improvement recommendation for each of the one or more fields.

Abstract: The present disclosure provides an improved approach to implement a management infrastructure for computing environments. The user interfaces for local management nodes are cached at a central management node. The cached copies of the local node UIs can then be executed as if the user was actually operating from the local node.

Abstract: Techniques are provided for automatically assigning hybrid products or seed products to agricultural fields with optimal yield performance.

Abstract: Techniques are provided for receiving a first set of historical agricultural data for one or more fields of a grower and a second set of historical agricultural data comprising a dataset of hybrid seed properties; cross-referencing the first set and the second set of historical agricultural data to generate a yield range improvement recommendation for each of the one or more fields, wherein the yield improvement recommendation comprises a recommended change in seed population or a recommended change in seed density; generating predictive yield data for the one or more fields by applying the yield improvement recommendation to the first set of historical agricultural data; generating comparison yield data using the grower yield data and the predictive yield data for the one or more fields; and causing displaying the comparison yield data for the grower.

Abstract: A node at a server side of a client-server system receives a request corresponding to a user account maintained in the server side. If login credentials in the request are valid, the node generates a session and a set of values including session metadata, a timeframe, and a signature associated with the session, wherein the signature is generated from the session metadata, the timeframe, and a salt that is shared among nodes at the server side. The session and the set of values are sent to a client from which the request originated. An additional node at the server side receives a request to access the session and obtains values from a value included in the request corresponding to the signature associated with the session using the salt. Session access is granted or denied based at least in part on whether the obtained values match the session metadata and timeframe.

Abstract: A method for database management is disclosed. The method may include receiving a plurality of crime reports. Field data and/or narrative field data may be extracted from the plurality of crime reports. Further, a plurality of tokens may be generated from the narrative field data. The plurality of tokens may be sent to a neural network. In response, crime prediction data may be received from the neural network. Based on the crime prediction data and field data, related crimes may be determined. The related crimes may be plotted to map. Further, a visual display of the map may be generated. The visual display may be sent to a user portal and the user portal may then display the visual display as a graphical user interface.

Abstract: Techniques are provided for generating a set of target hybrid seeds with optimal yield and risk performance, including a server receiving a candidate set of hybrid seeds along with probability of successful yield values, associated historical agricultural data and property information, and selecting a subset of the hybrid seeds that have probability of success values greater than a filtering threshold. The server generates representative yield values for hybrid seeds based on the historical agricultural data and risk values for each hybrid seed. The server generates a dataset of target hybrid seeds for planting based on the risk values, the yield values, and the properties for the target fields. The dataset of target hybrid seeds includes target hybrid seeds that meet a specific threshold for a range of risk values. The server causes display of the dataset of target hybrid seeds including yield values and risk values for the target fields.

Abstract: Techniques are provided for generating target success group of hybrid seeds for target fields include a server receiving agricultural data records that represent crop seed data describing seed and yield properties of hybrid seeds and first field geo-location data for agricultural fields where the hybrid seeds were planted. The server receives second geo-locations data for target fields where hybrid seeds are to be planted. The server generates a dataset of hybrid seed properties that include yield values and environmental classifications for hybrid seeds and then a dataset of success probability scores that describe the probability of a successful yield on the target fields based on the dataset of hybrid seed properties and the second geo-location data. The server generates target success yield group of hybrid seeds and probability of success values based on success probability scores and a yield threshold. The server causes display of the target success yield group.

Abstract: The present invention provides a Gabor cube feature selection-based classification method for hyperspectral remote sensing images, comprising the following steps: generating three-dimensional Gabor filters according to set frequency and direction parameter values; convoluting hyperspectral remote sensing images with the three-dimensional Gabor filters to obtain three-dimensional Gabor features; selecting three-dimensional Gabor features, classification contribution degrees to various classes of which meet preset requirements, from the three-dimensional Gabor features; and classifying the hyperspectral remote sensing images by a multi-task joint sparse representation-based classification means by using the selected three-dimensional Gabor features. The present invention is based on the three-dimensional Gabor features, and the used three-dimensional Gabor features contain rich local change information of a signal and are competent in feature characterizing.

Abstract: In one embodiment, a computing device receives user input from a client device. The user input corresponds to a request for a task to be performed by each entity of a set of entities from a virtualization environment. The request for the task is sent to the set of entities. The computing device receives feedback from each entity of the set of entities. The feedback corresponds to the progress of each entity's individual task for the request. The computing device aggregates the feedback from the set of entities into a single parent task, and sends only the reference to the parent task to the client device for display.

Abstract: A system and method of designing a transmit beam pattern for Waveform Diversity is provided. The method can include minimizing a difference between the transmit beampattern and a desired beampattern under an elemental constraint, and minimizing the cross-correlations between the plurality of probing signals at the one or more target locations. Desirable features of a probing signal can be achieved by designing a covariance matrix of the probing signal. The method also can include minimizing the peak sidelobe level while pointing an energy beam in a prescribed direction under an elemental power constraint.