Abstract: One of the purposes of the present disclosure is to provide a plant management device and the like which are capable of supporting plant inspection work. A plant management device according to an embodiment of the present disclosure is provided with: a display control unit that displays a plant model on a display device, the plant model being an image of a facility included in a plant; and a reception unit that receives an operation by a user on the plant model displayed by the display device. The display control unit displays, on the display device being operated by the user, information corresponding to a role of the user and the operation of the user.

Abstract: An assistance method comprising steps of: acquiring information related to a process or a reduced system when the process to be performed in a plant is performed in the reduced system with a smaller scale than the plant; and generating at least a part of a model for predicting a process to be performed in the plant, or an intermediate system with a scale between the plant and the reduced system, based on a relationship between systems when the process is performed in a plurality of systems of different scales, from the information.

Abstract: A method and apparatus for monitoring a machine with at least one rotating component. In the method, accelerometer data collected for the machine is received by a data processing apparatus. An ellipse descriptive of movement of the machine in time domain and/or frequency domain is determined based on the accelerometer data. At least one ellipse parameter defining the ellipse is then used in monitoring the machine.

Abstract: This application relates to the field of robot control, and provides a motion state control method and apparatus, a device, and a readable storage medium. The method includes the following steps: Step 301: Acquire basic data and motion state data, the basic data being used for representing a structural feature of a wheeled robot, and the motion state data being used for representing a motion feature of the wheeled robot. Step 302: Determine a state matrix of the wheeled robot based on the basic data and the motion state data, the state matrix being related to an interference parameter of the wheeled robot, the interference parameter corresponding to a balance error of the wheeled robot. Step 303: Determine, based on the state matrix, a torque for controlling the wheeled robot. Step 304: Control, by using the torque, the wheeled robot to be in a standstill state.

Abstract: A system and method for operation of an autonomous vehicle (AV) yard truck is provided. A processor facilitates autonomous movement of the AV yard truck, and connection to and disconnection from trailers. A plurality of sensors are interconnected with the processor that sense terrain/objects and assist in automatically connecting/disconnecting trailers. A server, interconnected, wirelessly with the processor, that tracks movement of the truck around and determines locations for trailer connection and disconnection. A door station unlatches/opens rear doors of the trailer when adjacent thereto, securing them in an opened position via clamps, etc. The system computes a height of the trailer, and/or if landing gear of the trailer is on the ground and interoperates with the fifth wheel to change height, and whether docking is safe, allowing a user to take manual control, and optimum charge time(s). Reversing sensors/safety, automated chocking, and intermodal container organization are also provided.

Abstract: According to an implementation, a circuit includes a trio of first switches, a pair of second switches, a pair of inductors including a primary inductor and a secondary inductor, and a first capacitor, where: the circuit is configured to regulate a load. According to an implementation, a circuit includes a voltage balancer and two or more stages. Each stage of the two or more stages includes: a two-phase isolated voltage regulator (IVR) including at least a pair of inversely coupled dual inductors and a differential voltage input, and a respective Zener diode and capacitor combination coupled to the voltage balancer and the first two-phase IVR. In certain aspects, the two or more stages are coupled in series.

Abstract: Apparatus and methods for bandgap reference generators are disclosed. In certain embodiments, a bandgap reference generator includes a low voltage bandgap reference circuit that generates a first bandgap reference voltage, a high voltage bandgap reference circuit that generates a second bandgap reference voltage, a bandgap selector circuit that outputs the first bandgap reference voltage or the second bandgap reference voltage as a selected bandgap reference voltage based on a voltage level of the power supply voltage, and a bandgap translator circuit that generates an output bandgap reference voltage based on the selected bandgap reference voltage.

Abstract: Track plans to improve clock skew arc disclosed. In one aspect, a node array includes a plurality of nodes with clock distribution circuitry configured to distribute a clock signal to each of the nodes. The clock signal propagates in at least a first direction between adjacent nodes. The node (202) further includes a track plan comprising a plurality of wires to carry communication signals propagating between adjacent nodes. The plurality of wires include a first wire (404) configured to carry a first communication signal in a direction opposite to the first direction and a second wire (402) configured to carry a second communication signal in the first direction, where the first wire has a width that is greater than a width of the second wire.

Abstract: A computing system includes a first computing platform and a virtual exchange computing platform, where the first computing platform provides an application and a first electronic value token and the virtual exchange computing platform is communicatively coupled to the first computing platform. The virtual exchange computing platform receives the information corresponding to the first electronic value token and calculates, via API functions linking to banking as a service (BaaS) functionality processed by a valuation computing platform, a valuation of the first electronic value token. The virtual exchange computing platform causes presentation, via a network and on a first user device, a user interface screen presenting a visualization of a value of the electronic value token and comprising an input and triggers, based on a received trade input from the user interface, a virtual exchange of value involving the first electronic value token.

Abstract: In the information processing device, the control unit receives an input of information including the remaining price of the first vehicle in use by the user, the remaining bond of the first vehicle, the monthly insurance premium of the first vehicle, the delivery date of the second vehicle that the user desires to transfer, and the vehicle type of the third vehicle that can be used in the cancellation fee free plan, and calculates the payment amount in a case where it is assumed that the third vehicle is used until the delivery date of the second vehicle. The control unit outputs information including the calculated payment amount.

Abstract: Automatic generation of optimized aggregation metrics for usage-based insurance (UBI) includes performing a high-dimensional Bayesian optimization on a data archive, the data archive including a plurality of signals from vehicles and corresponding UBI effects, wherein the high-dimensional Bayesian optimization includes performing testing on weighted groups of the plurality of signals using one or more aggregation functions; and transmitting the one or more aggregation functions to a vehicle to cause the vehicle to provide aggregated signals for input to a UBI model to predict a UBI rate for the vehicle.

Abstract: Maintenance method and maintenance system for smart gas pipeline network are provided. The method includes: determining a preset frequency; controlling the gas metering device in the target region to obtain gas statistical data at the preset frequency; obtaining historical gas consumption data in the target region; determining target demand information of the target region at a future time point; predicting a target difference amplitude of a gas supply and demand difference at the future time point in the target region; for the target region where the target difference amplitude meets a first preset condition, determining a reason for supply and demand difference through a reason model; determining a gas supply adjustment parameter; generating a gas supply adjustment instruction, and sending the gas supply adjustment instruction to a terminal device and the gas metering device to instruct an instruction execution object to perform an adjustment on gas supply.

Abstract: Disclosed are methods, systems, and non-transitory computer readable memory for processing, analyzing, and visualizing complex digital object sets using large language models. For instance, a method may include receiving a set of digital objects; indexing the received set of digital objects to generate indexed data; generating a timeline prompt based on the indexed data; processing the timeline prompt to generate a timeline response; and outputting the timeline response as an interactive timeline of based on the set of digital objects.

Abstract: Input/output filter units for use in a graphics processing unit include a first buffer configured to store data received from, and output to, a first component of the graphics processing unit; a second buffer configured to store data received from, and output to, a second component of the graphics processing unit; a weight buffer configured to store filter weights; a filter bank configurable to perform a plurality of types of filtering on a set of input data, the plurality of types of filtering comprising texture filtering types and pixel filtering types; and control logic configured to cause the filter bank to: (i) perform one of the plurality of types of filtering on a set of data stored in one of the first and second buffers using a set of weights stored, and (ii) store the results of the filtering in one of the first and second buffers.

Abstract: Certain aspects of the present disclosure provide techniques and apparatus for efficient scaling of inputs to be processed by a machine learning model. An example method generally includes receiving, by a machine learning model, an input having a starting size in a plurality of dimensions. The method further includes scaling, by the machine learning model, the input in one or more dimensions of the plurality of dimensions to generate a scaled input, wherein the input is scaled in each respective dimension of the one or more dimensions based on a respective stride length determined based on a starting size in the respective dimension and a target size in the respective dimension, and the respective stride length associated with at least one dimension in the one or more dimensions comprises a non-integer value. The method further includes generating, by the machine learning model, an inference based on the scaled input.

Abstract: A data processing apparatus according to an embodiment includes processing circuitry. The processing circuitry is configured to output first complementary data by inputting, to a first neural network, first partial sampling data resulting from performing a partial sampling process; to obtain first corrected data, by performing a process to improve a consistency degree between the first complementary data and the first partial sampling data; to generate second partial sampling data, on the basis of the first corrected data and the first partial sampling data; and to output second complementary data, by inputting the second partial sampling data to a second neural network.

Abstract: Disclosed are systems, apparatuses, processes, and computer-readable media to capture images with subjects at different depths of fields. A method of processing image data includes obtaining a first image captured using an image sensor, the first image being associated with a first exposure: obtaining a second image captured using the image sensor, the second image being associated with a second exposure that is longer than the first exposure: modifying a first region of the first image based on a first transformation and a second region of the first image based on a second transformation to generate a modified first image; and generating a combined image at least in part by combining the modified first image and the second image.

Abstract: A method for attacking a neural network that includes receiving an input data that includes an image and ground truth label, adding a pre-determined amount of noise to the image, denoising the noisy image utilizing a diffusion model that includes a deep equilibrium root solver, determining a first gradient of the denoised image with respect to the input data including at least the image, wherein the first gradient is associated with the diffusion model, utilizing the denoised image at downstream model, outputting a predicated label associated with the denoised image, determining a loss utilizing with the predicted label and the ground truth label, determining a second gradient associated with the downstream model utilizing at least the loss, and outputting an aggregate gradient that represents an error of the neural network output utilizing the predicted label, wherein the aggregate gradient is calculated utilizing the first gradient and the second gradient.

Abstract: A target element generation method and apparatus, an electronic device, and a storage medium are provided. The method includes: displaying an editing page on which a stylized image is displayed, where the stylized image is an image generated by performing target style conversion on an initial image; and displaying, in a target region of the stylized image, a target element corresponding to a processing operation for the target region in response to the processing operation for the target region, where the target element is an element generated by re-drawing the target region based on an initial element corresponding to the processing operation.

Abstract: Examples disclosed herein may involve a computing system that is operable to (i) receive image data captured from one or more devices, (ii) based on the image data, generate at least two batches of data corresponding to an area of a global map, wherein each batch of data comprises (a) a respective group of images from the received image data, and (b) one or more common images comprising one or more common visual features, (iii) generate a respective reconstruction of the area of the global map for each of the at least two batches of data, and (iv) fuse the respective reconstructions of the area of the global map using the one or more common visual features from the one or more common images.