Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: A method for remediating developmentally delayed plants within a field of crops using at least one work vehicle during a field operation. The method comprises identifying delayed plants within the field with a sensor on the work vehicle and generating, with a processor, location data associated with the location of the delayed plant with the field. Upon arriving at the location of the delayed plant with the work vehicle, the delayed plant is remediated.

Abstract: A computer-implemented method of controlling a mobile agricultural machine includes obtaining prior field data representing a position of plants in a field, obtaining in situ plant detection data from operation of the mobile agricultural machine in the field, determining a position error in the prior field data based on the in situ plant detection data, and generating a control signal that controls the mobile agricultural machine based on the determined position error.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: Improved systems are provided for implementing low-cost, low-power, highly compatible bidirectional video and user interface links. These systems permit a remote terminal to present a video user interface (e.g., a touchscreen interface) and to receive an HD video stream for a base system that is in communication with the terminal via Internet Protocol or some other low-cost, reliable long-distance communication means. To reduce complexity, bandwidth requirements, and power, transmission of HD video from the terminal to the base can be accomplished using a system-on-chip that performs video compression, which may be essentially lossless, and that transmits the compressed stream over a network interface. The transmission of video from the base to the terminal can be accomplished in a lossy and/or lower-resolution manner via a USB-over-network channel. This channel can then be instantiated at the base unit as a video-over-USB device, improving compatibility and reducing configuration requirements at the base.

Abstract: Network systems, classification methods, and related apparatuses for security analyses of electronic messages are disclosed. An apparatus includes an input terminal to receive message data corresponding to an electronic message to be delivered to a destination device and processing circuitry. The processing circuitry is configured to, if the electronic message includes an attached file, disassemble the attached file to obtain assembly code from the attached file. The processing circuitry is also configured to translate the assembly code to generate function labels corresponding to functions the assembly code is configured to instruct the destination device to perform. The processing circuitry is further configured to classify the electronic message as anomalous responsive to one or more of the generated function labels being identified as suspicious.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: An adjustable power and data rail for static height and vertically adjustable desks. The adjustable power and data rail fits between the static height and vertically adjustable desks and expands as needed either horizontally or vertically to match the installation configuration with paired multiple desks. The power and data rail provides connectivity for each of the static height or vertically adjustable desks to data and power connectors.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: A priori georeferenced vegetative index data is obtained for a worksite, along with field data that is collected by a sensor on a work machine that is performing an operation at the worksite. A predictive model is generated, while the machine is performing the operation, based on the georeferenced vegetative index data and the field data. A model quality metric is generated for the predictive model and is used to determine whether the predictive model is a qualified predicative model. If so, a control system controls a subsystem of the work machine, using the qualified predictive model, and a position of the work machine, to perform the operation.

Abstract: A priori geo-referenced data is obtained for a worksite, along with field data that is collected by a sensor on a work machine that is performing an operation at the worksite. A predictive model is generated, while the machine is performing the operation, based on the geo-referenced data and the field data. A model quality metric is generated for the predictive model and is used to determine whether the predictive model is a qualified predicative model. If so, a control system controls a subsystem of the work machine, using the qualified predictive model, and a position of the work machine, to perform the operation.

Abstract: Network security and related apparatuses, methods, and security systems are disclosed. An apparatus includes a variational autoencoder trained to reconstruct a benign packet flow representation of a benign packet flow corresponding to a benign stream of packets. The processing circuitry is configured to apply a packet flow representation of a packet flow corresponding to a received stream of packets to the variational autoencoder to generate a reconstructed packet flow representation. The packet flow representation includes one or more of a determined transfer entropy corresponding to the received stream of packets, flow derived metadata, or a Granger causality of the packet flow. The processing circuitry is also configured to determine a reconstruction loss of the reconstructed packet flow representation and determine whether the received stream of packets is anomalous responsive to the determined reconstruction loss.

Abstract: A field planting system for planting seeds of at least two plant genotypes in a field includes a multi-variety planter operable to plant the seeds of the at least two plant genotypes in the field. The field planting system also includes a controller in operable communication with the multi-variety planter. The controller is configured to receive georeferenced field information for the field and plant information for the at least two plant genotypes, and generate a planting map for the field based on the georeferenced field information and the plant information, the planting map including a planting pattern for interplanting the seeds of the at least two plant genotypes. The controller is further configured to monitor a location of the multi-variety planter in the field, and control the multi-variety planter to plant the seeds of the at least two plant genotypes in the field according to the planting map.

Abstract: A seeding machine moves over the ground and includes a frame, at least one hopper containing seeds to be planted and planting row units connected to the frame. Each of the row units includes a seed metering device that separates and guides individual seeds into a planting position, and a shaft that reciprocates with respect to the frame through a stroke path. The stroke path includes extension towards the ground to a lowered position and retraction away from the ground to a raised position. The shaft engages one of the seeds from the planting position while the shaft is near the raised position. The shaft moves the one of the seeds downward while the shaft extends toward the ground to create an opening in the ground by pressing the one of the seeds into ground while the shaft is near the lowered position.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.