Abstract: Sensors and methods for determining the state of charge of a battery are described. The state of charge is determined in some instances by applying a current perturbation having a frequency to the battery terminals, monitoring the response signal, and determining the phase of the response signal. The phase may be correlated to the state of charge of the battery, so that once the phase is determined, a determination of the state of charge of the battery may be made. In some situations, the state of charge may be used to determine the operating condition of a load connected to the battery. In some embodiments, the state of charge may be used to determine whether the battery is defective.

Abstract: Provided is an image and segmentation label generative model for tree-structured data and application. The model includes a simulation model for tree-structured image designed based on a small amount of expert knowledge and a generative network model based on morphological loss function. The present application can generate a simulated tree-structured image with labels that have a style highly similar to that of the real target image. This technology can generate image and segmentation labels for tree target in various medical images, such as brain neurons, retinal vessels, and trachea in the lungs, and the data quality can reach the level of manually annotated data. The model according to the present disclosure is the first model with the ability to automatically generate segmentation level data, and has the advantages of simple and flexible model configuration, high-quality generated data, and a wide range of applications.

Abstract: A method comprises identifying a candidate entity for matching with one or more target entities from a plurality of target entities, and for one or more of the target entities: determining a target suitability measure indicative of a suitability of the target entity to the candidate entity based on desired target entity attributes of the candidate entity and corresponding one or more target entity attributes associated with the target entity; determining a candidate suitability measure indicative of a suitability of the candidate entity to the target entity based on one or more desired candidate entity attributes of the target entity and corresponding one or more candidate entity attributes associated with the candidate entity; determining a matching score for the candidate entity and target entity pair as a first function of the target suitability measure and the candidate suitability measure; and. determining suggested target entities for matching with the candidate entity.

Abstract: Techniques for providing positioning information to a mobile device are discussed. An example apparatus for determining a location of a mobile device includes at least one server comprising a data structure containing precise positioning subscription options associated with the mobile device, a plurality of client internet of things devices configured to communicate with the at least one server, such that at least one of the plurality of client internet of things devices is a serving internet of things device configured to provide precise positioning information to the mobile device, and such that the serving internet of things device is selected from the plurality of client internet of things devices based on the precise positioning subscription options.

Abstract: The present invention is directed to a removable sample holder for analytical instruments or apparatuses that utilizes a prism. For example, sample devices of the invention can be used in a surface plasmon resonance (SPR) spectroscopy, a plasmon-waveguided resonance (PWR) spectroscopic device, as well as other spectroscopy devices known to one skilled in the art that uses a prism. The present invention is also directed to methods for using the same. The sample holder device (10) includes a sample injection port (100), a prism retainer (200) and a sample compartment base (300). Unlike conventional SPR and PWR instruments that have a built-in sample chamber, the sample holder device (10) of the present invention provides a separate sample chamber that can be readily removed and replaced. Furthermore, by allowing ready replacement of the prism the sample holder device (10) of the invention allows user to fabricate custom sensor chips.

Abstract: A method for training a model comprises obtaining a set of labeled training samples each associated with a given label. For each labeled training sample, the method includes generating a pseudo label and estimating a weight of the labeled training sample indicative of an accuracy of the given label. The method also includes determining whether the weight of the labeled training sample satisfies a weight threshold. When the weight of the labeled training sample satisfies the weight threshold, the method includes adding the labeled training sample to a set of cleanly labeled training samples. Otherwise, the method includes adding the labeled training sample to a set of mislabeled training samples. The method includes training the model with the set of cleanly labeled training samples using corresponding given labels and the set of mislabeled training samples using corresponding pseudo labels.

Abstract: An Real-Time Kinematic (RTK) and/or Differential GNSS (DGNSS) system is disclosed in which correction data from a plurality of reference stations is provided to the mobile device. A selection of reference stations (from which correction data is provided to the mobile device) can be made based on factors such as the approximate location of the mobile device, geometry of the reference stations, and/or other factors. The mobile device can combine the correction data from the plurality of reference stations in different ways to determine an accurate position fix for the mobile device, without interpolating correction data from the plurality of reference stations.

Abstract: A computer-implemented method for determining entity characteristics. The method comprising: determining a numerical representation of each of a plurality of second entities, each numerical representation comprising a multi-dimensional vector characteristic of the respective second entity, wherein each second entity is associated with one or more first entities; reducing the dimensionality of the numerical representations to produce a plurality of reduced dimensionality numerical representations; and determining a specialisation of each of the plurality of first entities based on the respective reduced dimensionality numerical representations.

Abstract: Techniques for implementing a mixed signal feedback design for verification that reduce production and verification time by enabling piecemeal verification of components of a circuit design selectively, accurately, and exhaustively before a final, overall circuit design is completed are disclosed. Circuit nodes in an emulation model are selected and mixed signal feedback is provided to the nodes in response to signals detected at the nodes such that behavior of unavailable or unverified components to be located at the nodes can be simulated. Mixed signal feedback can be provided to the node to enable verification of the emulation model without having to wait for the unverified or unavailable components to be provided or verified. A request for manufacture may be generated including aspects of the emulation model to enable verification of a fabricated circuit in a similar or identical manner to those used to verify the emulation model.

Abstract: A combination micro/macro-fluidic analysis system with one or more of a droplet transition unit, a droplet cleaving unit, a droplet synchronization, and a merging unit to enable highly efficient complex droplet microfluidic assays.

Abstract: The present disclosure provides a display device, including: a backlight module; side frames on different sides of the display module; a first supporting part is provided on at least one side frame, and extends toward a middle part of the backlight module; a panel assembly on a light-emitting side of the backlight module and including a first display panel, a second display panel and a connection layer between the first display panel and the second display panel, where the first display panel, the second display panel and the connection layer define an accommodation space, the first supporting part extends into the accommodation space, the first display panel is on a side of the first supporting part away from the backlight module, and the second display panel is supported by the backlight module; the first display panel and the side frame overlap in a thickness direction of the display device.

Abstract: Constructing a feature segment-based ensemble can include generating a data structure for each element of an initial set of training data. Multiple strongly correlated features of the elements can be identified as well as weakly correlated features. For each strongly correlated feature, a feature segmentation training set can be generated, each training set's elements each containing one of the strongly correlated features and excluding other strongly correlated features. One or more machine learning algorithms can be selected from a software library. The one or more machine learning algorithms can be applied to the feature segmentation training sets to train multiple machine learning models. Each machine learning model that improves the predictive accuracy of the feature segment-based ensemble can be integrated in the feature segment-based ensemble.

Abstract: Determining a class-specific predictor indicator importance can include generating, using machine learning, a prediction model having a tree structure including nodes, class label subgroups, and class-specific predictor indicators. A class-specific predictor indicator importance can be generated for a selected class-specific predictor indicator by merging a term predictor indicator frequency and a purity predictor indicator frequency at each instance of the selected class-specific predictor indicator within one or more nodes of the tree structure. A representation of the tree structure displayed in a graphical user interface can depict each path between a root node of the tree structure and a leaf node mapped to the selected class label subgroup having a node containing an instance of the selected class-specific predictor indicator in a manner that contrasts with other paths between the root node and other leaf nodes of the tree structure.

Abstract: Trajectory value learning for autonomous systems includes generating an environment image from sensor input and processing the environment image through an image neural network to obtain a feature map. Trajectory value learning further includes sampling possible trajectories to obtain a candidate trajectory for an autonomous system, extracting, from the feature map, feature vectors corresponding to the candidate trajectory, combining the feature vectors into the input vector, and processing, by a score neural network model, the input vector to obtain a projected score for the candidate trajectory. Trajectory value learning further includes selecting, from the candidate trajectories, the candidate trajectory as a selected trajectory based on the projected score, and implementing the selected trajectory.

Abstract: A method for rehearsal-free continual learning includes obtaining a set of training samples where training sample in the set of training samples is associated with a respective task of a plurality of different tasks. The method includes obtaining a task-invariant prompt representative of learned knowledge common to each respective task of the plurality of different tasks. The method includes, for each respective task of the plurality of different tasks, obtaining a respective task-specific prompt representative of learned knowledge specific to the respective task. The method includes, during each of one or more training iterations, for each respective training sample in the set of training samples, selecting the respective task-specific prompt representative of the respective task of the respective training sample and training a model using the task-invariant prompt and the selected respective task-specific prompt.

Abstract: A method including: providing a design data of an integrated circuit (IC), the design data comprising a first cell; identifying a first conductive line in the first cell as a critical internal net of the first cell, wherein the first conductive line is electrically connected between an input terminal of the first cell and an output terminal of the first cell; providing a library of the first cell, wherein the library includes a table of timing or power parameters of the first cell based on a multidimensional input set associated with the critical internal net; updating the design data by determining a timing or power value of the first cell based on the table; performing a timing analysis on the updated design data; and forming a photomask based on the updated design data.

Abstract: Systems and methods for performing semantic segmentation of three-dimensional data are provided. In one example embodiment, a computing system can be configured to obtain sensor data including three-dimensional data associated with an environment. The three-dimensional data can include a plurality of points and can be associated with one or more times. The computing system can be configured to determine data indicative of a two-dimensional voxel representation associated with the environment based at least in part on the three-dimensional data. The computing system can be configured to determine a classification for each point of the plurality of points within the three-dimensional data based at least in part on the two-dimensional voxel representation associated with the environment and a machine-learned semantic segmentation model. The computing system can be configured to initiate one or more actions based at least in part on the per-point classifications.

Abstract: The purpose of the present invention is to provide an emitter capable of easily and highly efficiently emitting electrons, an electron gun using same, and an electronic device. This emitter is provided with a cathode holder, and an acicular substance secured to the cathode holder. An end, to which the acicular substance is secured, of the cathode holder is bent at ? (?(°) satisfies 5<??70) that is an angle formed with respect to a cathode axis being the longitudinal direction of the cathode holder, the acicular substance is a single crystal nanowire or nanotube, and a relation L/T between the thickness T (?m) of the end of the cathode holder and a length L (?m) by which the acicular substance protrudes from the end satisfies 0.3?L/T?2.5.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to self-checkout verification at a retail facility. In some embodiments, there is provided a system for self-checkout verification at a retail facility including a first optical imaging unit; and a control circuit. The control circuit configured to: receive purchase receipt data; receive one or more images of the items in the container; and execute a machine learning model trained to: perform item detection, item classification, and item verification of each item shown in the one or more images; and output electronic data corresponding to an electronic receipt of the items in the container. The control circuit may automatically detect each unpaid item in the container based on a comparison of the purchase receipt data with the electronic data; and provide an alert signal in response to automatically detecting an unpaid item.

Abstract: A method, system, and computer for balance weighted voting. The method may comprise receiving, by a network interface, a scoring request. The method may further comprise, by a processing unit in response to the scoring request, generating a plurality of scores using a plurality of models. normalizing the plurality of scores, calculating an evaluation-based weighting factor from a first subset of the normalized scores, calculating a prediction-based based weighting factor from a second subset of the normalized scores, and calculating a balanced weighting predictor from the evaluation-based weighting factor and the prediction-based weighting factor. The method may further comprise returning, by the network interface, the balanced weighting predictor as an ensemble score for the scoring request.