Abstract: Methods, devices and systems are provided for performing for multi-user (MU) transmission. A wireless transmit/receive unit (WTRU) may be configured to receive a frame, decode the received frame and determine whether the received frame is a null data packet (NDP) multi-user (MU) media access control (MAC) physical layer convergence protocol (PLCP) protocol data unit (PPDU) (NDP MU MAC PPDU) based on meeting an NDP condition. The NDP MU MAC PPDU may correspond to an MU transmission and may include a PLCP header which includes an NDP signal (SIG) field having MU control information. Based on the received frame meeting the NDP condition, the WTRU may be further configured to process the NDP SIG field, generate a response based on the NDP SIG field and the MU control information, and transmit the response.

Abstract: A computing device for predicting an expected loss for a set of claim transactions is provided. The computing device predicts, at a first machine learning model, a claim frequency of the set of claim transactions over a given time period and trained using historical frequency data and based on a segment type defining a type of claim, each type of segment having peril types. The computing device also predicts, at a second machine learning model, claim severity of the set of claim transactions during the given time period, the second machine learning model trained using historical severity data and based on the segment type and the corresponding peril types. The computing device then determines the expected loss for the set of claim transactions over the given time period by applying a product of prediction of the first machine learning model and the second machine learning model.

Abstract: This disclosure teaches a system and method for monitoring an extracorporeal blood circuit of a patient and identifying a needle dislodgement. The method includes identifying a potential needle dislodgement event based on changes in pressure of the extracorporeal blood circuit, searching for a heart rate of a patient by analyzing an optical backscatter signal from an optical sensor attached to the extracorporeal blood circuit or by analyzing a pressure signal representative of the pressure in the extracorporeal blood circuit, and verifying the potential needle dislodgement event is a needle dislodgement based on the absence of the heart rate.

Abstract: A method for estimating the strength of a laser welded blank including a first blank and a second blank joined together by a weld seam. The method may include forming a plurality of indentations in the first blank, the second blank, and the weld seam to determine an average value of a micro-hardness (Vickers); determining a scale-up ratio K; multiplying the scale-up ratio K by the average values of the micro-hardness of each of the first blank, the second blank, and the weld seam to obtain a scaled-up average value of the microhardness of each of the first blank, the second blank, and the weld seam; running a finite elemental analysis (FEA) simulation using the scaled-up average values of the microhardness; and based on the results of the simulation, determining whether the strength of the laser welded blank is sufficient to withstand being subjected to a forming process.

Abstract: Multiple channels are aggregated. In an example embodiment, first data is transmitted on a first channel to a wireless device, and second data is simultaneously transmitted on a second channel to the wireless device. The first data and the second data are transmitted in a coordinated manner by aggregating the first channel and the second channel. Various example channel characteristics and combinations thereof are described. Different data allocation options for aggregated channels are described. Other alternative implementations are also presented herein.

Abstract: A computer-implemented method of reducing noise in magnetic resonance (MR) images is provided. The method includes executing a neural network model of analyzing MR images, wherein the neural network model is trained with a pair of pristine images and corrupted images. The pristine images are the corrupted images with noise reduced, and target output images of the neural network model are the pristine images. The method also includes receiving first MR signals and second MR signals, reconstructing first and second MR images based on the first MR signals and the second MR signals, and analyzing the first MR image and the second MR image using the neural network model. The method further includes deriving a denoised MR image based on the analysis, wherein the denoised MR image is a combined image based on the first MR image and the second MR image and outputting the denoised MR image.

Abstract: Robotic systems and associated methods are described herein. The robotic system may collect measurements from various sensors corresponding to motion of the robotic system, the surrounding environment of the robotic system, or both. The robotic system may generate measurement data based on the collected measurements. Measurements from a particular sensor may be processed in conjunction with different sensors of the robotic system, which may facilitate more accurate or more useful measurement data. The systems and methods of the present disclosure enable the detection, labeling, and locating of features in real time or near real time using the robotic system with little or no reliance on human interaction to detect and map the features. The disclosure provides enhanced accuracy and efficiency as it enhances the functionality and reduces the reliance on human detection of features.

Abstract: A classification model is generated based on historical exercise information. User exercise information is classified into an exercise category using the classification model. Recommendations based on the exercise category is identified. A customized exercise recommendation is determined from the identified recommendations based on a comparison of the user exercise information and expected progress data. This customized recommendation is provided to a user device for consumption.

Abstract: Robotic systems and associated methods are described herein. The robotic system may collect measurements from various sensors corresponding to motion of the robotic system, the surrounding environment of the robotic system, or both. The robotic system may generate measurement data based on the collected measurements. Measurements from a particular sensor may be processed in conjunction with different sensors of the robotic system, which may facilitate more accurate or more useful measurement data. The systems and methods of the present disclosure enable the detection, labeling, and locating of features in real time or near real time using the robotic system with little or no reliance on human interaction to detect and map the features. The disclosure provides enhanced accuracy and efficiency as it enhances the functionality and reduces the reliance on human detection of features.

Abstract: A game controller for a mobile device that includes a first handle, a first bumper, and a first switch. The first handle is configured to contact and support a mobile device. The first bumper is coupled to the first handle. The first bumper is configured to accept touch inputs. The first bumper includes a pivot rod at a first end of the first bumper that is configured to engage a track slot of the first handle. The pivot rod is configured to rotate within the track slot and to translate within the track slot. The first bumper further includes a plunger at a first-span distance from the pivot rod. The first switch is within the first handle and is configured to be activated by touch inputs to the first bumper. The plunger of the first bumper is configured to contact and impart a force to the first switch.

Abstract: Robotic systems and associated methods are described herein. The robotic system may collect measurements from various sensors corresponding to motion of the robotic system, the surrounding environment of the robotic system, or both. The robotic system may generate measurement data based on the collected measurements. Measurements from a particular sensor may be processed in conjunction with different sensors of the robotic system, which may facilitate more accurate or more useful measurement data. The systems and methods of the present disclosure enable the detection, labeling, and locating of features in real time or near real time using the robotic system with little or no reliance on human interaction to detect and map the features. The disclosure provides enhanced accuracy and efficiency as it enhances the functionality and reduces the reliance on human detection of features.

Abstract: A method and system for locating a branch conduit opening into a main pipe following lining the main pipe with a liner includes moving a robot down the lined main pipe and scanning the liner using an infrared scanner mounted on the robot. A temperature drop outside the liner as compared to the adjacent surfaces to acquire infrared data is sensed with an infrared scanner. The infrared data is compared with other location data regarding the branch conduit opening and a branch conduit opening location outside of the liner is determined based on the infrared data and the other data. In another aspect, the infrared scanner is tuned to more particularly sense temperatures associated with the presence of a branch conduit opening.

Abstract: Robotic systems and associated methods are described herein. The robotic system may collect measurements from various sensors corresponding to motion of the robotic system, the surrounding environment of the robotic system, or both. The robotic system may generate measurement data based on the collected measurements. Measurements from a particular sensor may be processed in conjunction with different sensors of the robotic system, which may facilitate more accurate or more useful measurement data. The systems and methods of the present disclosure enable the detection, labeling, and locating of features in real time or near real time using the robotic system with little or no reliance on human interaction to detect and map the features. The disclosure provides enhanced accuracy and efficiency as it enhances the functionality and reduces the reliance on human detection of features.

Abstract: A method and system for reestablishing fluid communication between a main pipe and a branch conduit includes moving a robot down the lined main pipe. Visual images of the liner in the main pipe are transmitted from a camera associated with the robot to a monitor outside of the main pipe for viewing by a human operator. An interior view of the lined main pipe from the transmitted visual images is displayed on the monitor. An image representing the location of the branch conduit opening is superimposed on the monitor so that the image appears on the monitor to be located on the liner as shown in the interior view.

Abstract: A method and system for using a remote cutter to make cuts, for example in a pipe liner. An automated cutting path is computed for a cutting tool as a function of shape and position data relating to an opening of the branch conduit into the main pipe. The cutting tool is moved along the computed cutting path to cut the liner for reestablishing fluid communication between a branch conduit extending from a host pipe and the lined main pipe.

Abstract: Robotic systems and associated methods are described herein. The robotic system may collect measurements from various sensors corresponding to motion of the robotic system, the surrounding environment of the robotic system, or both. The robotic system may generate measurement data based on the collected measurements. Measurements from a particular sensor may be processed in conjunction with different sensors of the robotic system, which may facilitate more accurate or more useful measurement data. The systems and methods of the present disclosure enable the detection, labeling, and locating of features in real time or near real time using the robotic system with little or no reliance on human interaction to detect and map the features. The disclosure provides enhanced accuracy and efficiency as it enhances the functionality and reduces the reliance on human detection of features.

Abstract: Robotic systems and associated methods are described herein. The robotic system may collect measurements from various sensors corresponding to motion of the robotic system, the surrounding environment of the robotic system, or both. The robotic system may generate measurement data based on the collected measurements. Measurements from a particular sensor may be processed in conjunction with different sensors of the robotic system, which may facilitate more accurate or more useful measurement data. The systems and methods of the present disclosure enable the detection, labeling, and locating of features in real time or near real time using the robotic system with little or no reliance on human interaction to detect and map the features. The disclosure provides enhanced accuracy and efficiency as it enhances the functionality and reduces the reliance on human detection of features.

Abstract: An image may be received from a sensor associated with a capture area. Background elements associated with the capture area may be removed and a cleaned image generated. Objects may then be detected in this cleaned image. A spatial partition model may be generated to understand z-index and partially obscured areas while preserving relative object sizes. This model may be used to determine and remove foreground elements that may obstruct objects of interest. Object detection may be performed again on the further cleaned image. Detected objects may be filtered based on predefined criteria for different object classes.

Abstract: Methods, devices, or systems that may allow for remote monitoring of a capture area or the automatic inspection of a capture area, such as an adhesive board, among other things. In one aspect, the disclosed subject matter includes receiving an image of a capture area, generating current detection boxes associated with objects (e.g., pests) by performing object detection on the image, determining output boxes by comparing the current detection boxes with historical detection boxes, generating the output boxes, and transmitting an object count based on the output boxes.

Abstract: An adaptive object recognition system utilizes relevance-based weighting and scoring that may assist with accuracy and stability. The system receives multiple recognition results for objects across video frames. Weights are assigned to results based on their stability over frames and the relevance scoring of neighboring areas. This allows more confidence to be placed in consistent detections and clearer image regions. The system decouples high and low accuracy areas to apply appropriate thresholding. Temporal analysis is used to favor frequently detected objects. Weighted results are combined to generate final recognitions that are more robust to non-uniform image quality and noise.