Abstract: Methods, apparatus and systems for wireless sensing are described. In one example, a described system in a wireless data communication network comprises: a transmitter configured to transmit a time series of at least one wireless sounding signal (WSS) based on a standard wireless network protocol associated with the wireless data communication network, and a receiver. The wireless data communication network comprises a physical (PHY) layer, a medium access control (MAC) layer, and at least one higher layer. The receiver is configured to: receive the time series of at least one WSS (TSWSS) based on the standard wireless network protocol through a wireless channel of a venue, and perform a plurality of wireless sensing measurements based on the received TSWSS to obtain sensing measurement results based on the standard wireless network protocol.

Abstract: A vehicle seat including: a seat back that is tiltable forward around a reclining rod; a support rod that extends along the seat width direction and is supported at a support member that is attached to a vehicle body floor part; and a coupling mechanism that couples the support rod with the reclining rod, the coupling mechanism is configured to attain: a first coupling state that is a coupling state when the seat back is at a position supporting the back area of the seated vehicle occupant, and a second coupling state that is a coupling state when the seat back is tilted forward and a rear face of the seat back is made horizontal, a distance from the support rod to the reclining rod in a seat side view is longer in the second coupling state than in the first coupling state.

Abstract: Methods, apparatus and systems for wireless sensing are described. In one example, a described system in a wireless data communication network comprises: a transmitter configured to transmit a time series of at least one wireless sounding signal (WSS) based on a standard wireless network protocol associated with the wireless data communication network, and a receiver. The wireless data communication network comprises a physical (PHY) layer, a medium access control (MAC) layer, and at least one higher layer. The receiver is configured to: receive the time series of at least one WSS (TSWSS) based on the standard wireless network protocol through a wireless channel of a venue, and perform a plurality of wireless sensing measurements based on the received TSWSS to obtain sensing measurement results based on the standard wireless network protocol.

Abstract: Methods, apparatus and systems for wireless sensing are described. In one example, a described system in a wireless data communication network comprises: a transmitter configured to transmit a time series of at least one wireless sounding signal (WSS) based on a standard wireless network protocol associated with the wireless data communication network, and a receiver. The wireless data communication network comprises a physical (PHY) layer, a medium access control (MAC) layer, and at least one higher layer. The receiver is configured to: receive the time series of at least one WSS (TSWSS) based on the standard wireless network protocol through a wireless channel of a venue, and perform a plurality of wireless sensing measurements based on the received TSWSS to obtain sensing measurement results based on the standard wireless network protocol.

Abstract: Disclosed herein are image-based object recognition method and system by and in which a learning server performs image-based object recognition based on the learning of environment variable data. The image-based object recognition method includes: receiving an image acquired through at least one camera, and segmenting the image on a per-frame basis; primarily learning labeling results for one or more objects in the image segmented on a per-frame basis; performing primary reasoning by performing object detection in the image through a model obtained as a result of the primary learning; performing data labeling based on the results of the primary reasoning, and performing secondary learning with weights allocated to respective boxes obtained by the primary reasoning and estimated as object regions; and finally detecting one or more objects in the image through a model generated as a result of the secondary learning.

Abstract: The present disclosure is directed to systems and methods for performing reading comprehension with machine learning. More specifically, the present disclosure is directed to a Neural Symbolic Reader (example implementations of which may be referred to as NeRd), which includes a reader to encode the passage and question, and a programmer to generate a program for multi-step reasoning. By using operators like span selection, the program can be executed over a natural language text passage to generate an answer to a natural language text question. NeRd is domain-agnostic such that the same neural architecture works for different domains. Further, NeRd is compositional such that complex programs can be generated by compositionally applying the symbolic operators.

Abstract: A polishing system includes a pressure system, a substrate carrier including a membrane, a first sensor, and a control system. A first compartment of the membrane is fluidly coupled to the pressure system. The first sensor is configured to monitor the pressure system and produce a first output based on conditions detected in the pressure system. The control system coupled to the first sensor and configured to process the first output to produce a first processed output, and the control system configured to compare the first processed output to a threshold to detect a presence of a fluid in the pressure system.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing neural architecture search for machine learning models. In one aspect, a method comprises receiving training data for a machine learning, generating a plurality of candidate neural networks for performing the machine learning task, wherein each candidate neural network comprises a plurality of instances of a layer block composed of a plurality of layers, for each candidate neural network, selecting a respective type for each of the plurality of layers from a set of layer types that comprises, training the candidate neural network and evaluating performance scores for the trained candidate neural networks as applied to the machine learning task, and determining a final neural network for performing the machine learning task based at least on the performance scores for the candidate neural networks.

Abstract: A wrist-worn electronic device comprises a lower housing, an upper housing, a plurality of bezel connectors, a first global navigation satellite system (GNSS) antenna, a second GNSS antenna, and a communication antenna. The lower housing includes a side wall. The upper housing includes a bezel. The bezel connectors each provide an electrical connection to the bezel. The first GNSS antenna is configured to receive a first GNSS wireless signal. The second GNSS antenna is configured to receive a second GNSS wireless signal. The communication antenna is configured to transmit and receive a communication wireless signal. Each antenna is formed from a portion of the circumference of the bezel, a portion of the circumference of the side wall, and two of the bezel connectors.

Abstract: A computer-implemented method according to one embodiment includes performing object detection on a frame to identify a set of objects within the frame, and determining a location of each object of the set of objects within the frame. The method further includes constructing a code tree structure for the frame. The code tree structure defines the determined locations. A rule defining modifications to make to at least some of the objects is received and the code tree structure is crawled. The rule is applied to the objects during the crawling. The method further includes layering the modifications defined in the rule on the set of objects within the frame. A computer program product according to another embodiment includes a computer readable storage medium having program instructions embodied therewith. The program instructions are readable and/or executable by a computer to cause the computer to perform the foregoing method.

Abstract: A system and method for optimizing industrial assembly process in an industrial environment is disclosed. A system operates on artificial intelligence (AI) based conversational/GUI platform, where it receives user commands related to industrial assembly process improvement queries. By analyzing received user commands, system identifies type of industrial assembly process mentioned by extracting relevant keywords or other attributes. Using trained AI-based classification table, system determines performance attributes associated with identified type of process. The system leverages various sources such as domain knowledge, organization-specific knowledge bases, data from tools/internet-based services, and statistical measurements from industrial environment.

Abstract: The disclosed embodiments include computerized methods, systems, and devices, including computer programs encoded on a computer storage medium, for generating terms of a search query based on a user's spoken utterances, identifying multiple cross-platform messages based on the generated terms, and to generating, via a presentation device, a single interface that enables the user to interact with identified messages. Based on a spoken utterance, the disclosed embodiments may determine user-specified search terms and/or criteria, and based on the user-specified search terms and/or criteria, may obtain cross-platform message data that corresponds to the search query. The communications device may generate one or more interface elements that describe corresponding ones of the cross-platform messages, which may be presented within a unified graphical user interface or voice-user interface by a communications device.

Abstract: Several heart wall remodeling devices and methods are disclosed. One heart wall remodeling device includes a trimming tool for trimming a line within a patient. The trimming tool includes an actuator for manipulation by a user, a moveable inner shaft coupled to the actuator, and an outer sleeve coupled to the inner shaft. The outer shaft includes a backstop disposed along an inner wall of the outer sleeve and a channel disposed between a first end and a second end of the outer sleeve. The inner shaft includes an inner shaft, a compressible member, and a cutter.

Abstract: A system and method for learning human activities from video demonstrations using video augmentation is disclosed. The method includes receiving original videos from one or more data sources. The method includes processing the received original videos using one or more video augmentation techniques to generate a set of augmented videos. Further, the method includes generating a set of training videos by combining the received original videos with the generated set of augmented videos. Also, the method includes generating a deep learning model for the received original videos based on the generated set of training videos. Further, the method includes learning the one or more human activities performed in the received original videos by deploying the generated deep learning model. The method includes outputting the learnt one or more human activities performed in the original videos.

Abstract: Methods, apparatus and systems for wireless motion monitoring to ensure security are described. In one example, a described system comprises: a transmitter configured for transmitting a first wireless signal through a wireless multipath channel of a venue; a receiver configured for receiving a second wireless signal through the wireless multipath channel; and a processor. The second wireless signal differs from the first wireless signal due to the wireless multipath channel and a motion of an object in the venue. The processor is configured for: obtaining a time series of channel information (TSCI) of the wireless multipath channel based on the second wireless signal; computing a spatial-temporal information (STI) based on the TSCI; monitoring the motion of the object based on the TSCI and the STI; performing a task based on the monitoring; and generating a response based on the task.

Abstract: Methods and systems for implementing traffic mirroring for network telemetry are disclosed. An embodiment of a method for implementing traffic mirroring for network telemetry involves identifying network traffic at a network appliance that is to be subjected to traffic mirroring for network telemetry, and selecting from available options of transmitting enhanced mirrored network traffic from the network appliance to a collector, wherein the enhanced mirrored network traffic is generated at the network appliance by at least one of compressing and encrypting the network traffic, and transmitting mirrored network traffic from the network appliance to the collector without compressing or encrypting the network traffic.

Abstract: A rub rail coupled to a side rail including a first top notch and a first bottom notch, the rub rail including: a top chamfer; a top horizontal face diagonally connected to the top chamfer; a second top notch extending out of the top horizontal face; a side vertical face diagonally connected to the top chamfer; a bottom chamfer; a bottom horizontal face diagonally connected to the bottom chamfer; a second bottom notch extending out of the bottom horizontal face; wherein the second top notch couples to the first top notch, and wherein the second bottom notch couples to the first bottom notch.

Abstract: A system for predicting and summarizing medical events from electronic health records includes a computer memory storing aggregated electronic health records from a multitude of patients of diverse age, health conditions, and demographics including medications, laboratory values, diagnoses, vital signs, and medical notes. The aggregated electronic health records are converted into a single standardized data structure format and ordered arrangement per patient, e.g., into a chronological order. A computer (or computer system) executes one or more deep learning models trained on the aggregated health records to predict one or more future clinical events and summarize pertinent past medical events related to the predicted events on an input electronic health record of a patient having the standardized data structure format and ordered into a chronological order.

Abstract: Provided herein are devices, systems, and methods for a three-dimensional registering, tracking, and/or guiding an object of interest, such a body part, a surgical tool, or an implant, during a surgical procedure. Such devices, systems, and methods may offer minimally invasive, high precision registering, tracking, and/or guiding of the object of interest using a patterned light beam and data processing using artificial intelligence. The methods, devices, and systems disclosed herein may be compatible with a simple marker or markers placed by a minimally invasive method on the object of interest.

Abstract: The present disclosure is directed to an automated neural architecture search approach for designing new neural network architectures such as, for example, resource-constrained mobile CNN models. In particular, the present disclosure provides systems and methods to perform neural architecture search using a novel factorized hierarchical search space that permits layer diversity throughout the network, thereby striking the right balance between flexibility and search space size. The resulting neural architectures are able to be run relatively faster and using relatively fewer computing resources (e.g., less processing power, less memory usage, less power consumption, etc.), all while remaining competitive with or even exceeding the performance (e.g., accuracy) of current state-of-the-art mobile-optimized models.