Abstract: Techniques regarding one or more automated machine learning processes that analyze time series data are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a time series analysis component that selects a machine learning pipeline for meta transfer learning on time series data by sequentially allocating subsets of training data from the time series data amongst a plurality of machine learning pipeline candidates.

Abstract: In general, techniques are described by which provide confirmed automated access to portions of vehicles. A control system comprising a processor, and a memory may be configured to perform the techniques. The memory may store instructions that, when executed, cause the processor to determine that the authorized operator of the vehicle is intending to access a portion of the vehicle, and output, responsive to determination, a confirmation request to the authorized operator. The confirmation request may request confirmation that the authorized operator is intending to access the portion of the vehicle. The memory may also store instructions that, when executed, cause the processor to receive, from the authorized operator, a confirmation response indicating whether the authorized operator is intending to access at least the portion of the vehicle, and automatically open, based on the confirmation response, at least the portion of the vehicle.

Abstract: A polishing head assembly for polishing of semiconductor wafers includes a polishing head and a cap. The polishing head has a top portion and a recess along a bottom portion. The recess has a recessed surface. Holes extend from the top portion through the recessed surface. The cap is positioned within the recess and the cap has an annular wall and a floor extending across the annular wall. The annular wall has apertures corresponding to the holes. The floor is spaced from the recessed surface to form a chamber therebetween. The polishing head assembly also includes a band that circumscribes a portion of the annular wall. The holes and the corresponding apertures receive fasteners to removably secure the annular wall to the recessed surface.

Abstract: An insert comprising: (a) a cover layer; (b) a spacer layer located below the cover layer; (c) a connection material that is adapted to extend between and connect the cover layer to a trim layer so that the insert is fixed to the trim layer.

Abstract: Transgenic mammals that express bovine-based immunoglobulins are described herein, including transgenic rodents that express bovine-based immunoglobulins for the development of bovine therapeutic antibodies.

Abstract: Methods and systems for generating an environment include training transformer models from tabular data and relationship information about the training data. A directed acyclic graph is generated, that includes the transformer models as nodes. The directed acyclic graph is traversed to identify a subset of transformers that are combined in order. An environment is generated using the subset of transformers.

Abstract: In a method for ranking machine learning (ML) pipelines for a dataset, a processor receives first performance curves predicted by a meta learner model for a plurality of ML pipelines. A processor allocates a first subset of data points from the dataset to each of the plurality of ML pipelines. A processor receives first performance scores for each of the ML pipelines for the first subset of data points. A processor updates the meta learner model using the first performance scores. A processor receives second performance curves from the meta learner model updated with the first performance scores. A processor ranks the plurality of ML pipelines based on the second performance curves.

Abstract: To automate time series forecasting machine learning pipeline generation, a data allocation size of time series data may be determined based on one or more characteristics of a time series data set. The time series data may be allocated for use by candidate machine learning pipelines based on the data allocation size. Features for the time series data may be determined and cached by the candidate machine learning pipelines. Predictions of each of the candidate machine learning pipelines using at least the one or more features may be evaluated. A ranked list of machine learning pipelines may be automatically generated from the candidate machine learning pipelines for time series forecasting based upon evaluating predictions of each of the one or more candidate machine learning pipelines.

Abstract: A stationary blade for the blade set suitable for use with a hair cutting appliance that includes of wall segments fixedly interconnected forming a segmented stack, wherein an intermediate wall segment is disposed between a first wall segment and a second wall segment jointly forming, at an end of the segmented stack at least one toothed leading edge comprising a plurality of mutually spaced apart projections defining a plurality of teeth and respective tooth spaces, wherein the intermediate wall segment comprises a cutout and wherein the cutout in the intermediate wall segment, the first wall segment and the second wall segment define therebetween a guide slot for a movable blade.

Abstract: Method of producing an activated clostridial neurotoxin. Composition comprising an activated clostridial neurotoxin. Method of treatment using a composition comprising an activated clostridial neurotoxin.

Abstract: A system and method for discreet routing of a vehicle are described. The system and method provide a way of getting a subject vehicle from Point A to Point B while minimizing the visibility of the subject vehicle by one or more observers. In one embodiment, the method includes (1) determining a location of one or more observers within a target area and (2) applying elevation data to a plurality of grid squares within the target area. Based on the elevation data, a field-of-view (FOV) for each of the one or more observers is determined. The FOV includes one or more of the plurality of grid squares that are visible from the location of the observer. The method includes determining a route from an initial location to a destination location within the target area that minimizes an amount of the route within the FOV of the one or more observers.

Abstract: A gas turbine engine includes: a compressor section including a compressor mean radius; a combustor section fluidly coupled downstream of the compressor section and include a combustor mean radius; and a turbine section fluidly coupled downstream of the combustor section and a turbine mid-span radius. The combustor mean radius is greater than each of the compressor mean radius and the turbine mid-span radius.

Abstract: A gas turbine engine includes: a compressor section including a compressor mean radius; a combustor section fluidly coupled downstream of the compressor section and include a combustor mean radius; and a turbine section fluidly coupled downstream of the combustor section and a turbine mid-span radius. The combustor mean radius is greater than each of the compressor mean radius and the turbine mid-span radius.

Abstract: To rank time series forecasting in machine learning pipelines, time series data may be incrementally allocated from a time series data set for testing by candidate machine learning pipelines based on seasonality or a degree of temporal dependence of the time series data. Intermediate evaluation scores may be provided by each of the candidate machine learning pipelines following each time series data allocation. One or more machine learning pipelines may be automatically selected from a ranked list of the one or more candidate machine learning pipelines based on a projected learning curve generated from the intermediate evaluation scores.

Abstract: Systems for implanting semiconductor structures with ions are disclosed. The semiconductor structure is positioned on a heatsink and ions are implanted through a front surface of the semiconductor structure to form a damage region in the semiconductor structure. A parameter related to the coefficient of friction of the heatsink is measured. The parameter is compared to a baseline range.

Abstract: An automated analytic tool (AAT) apparatus analyzes a machine learning system (MLS). The tool comprises a processor configured to receive experiment parameters associated with an experiment performed on the MLS, and captures information from a plurality of stages of the experiment. The information comprises information regarding MLS results and choices made during the experiment. The tool automatically revise the captured information into revised information utilizing a knowledge base comprising information from prior experiments. The tool then presents the revised information to a user.

Abstract: Techniques regarding one or more automated machine learning processes that analyze time series data are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a time series analysis component that selects a machine learning pipeline for meta transfer learning on time series data by sequentially allocating subsets of training data from the time series data amongst a plurality of machine learning pipeline candidates.

Abstract: An embodiment of the invention may include a method, computer program product, and system for creating a data analysis tool. The method may include a computing device that generates an AI pipeline based on an input dataset, wherein the AI pipeline is generated using an Automated Machine Learning program. The method may include converting the AI pipeline to a non-native format of the Automated Machine Learning program. This may enable the AI pipeline to be used outside of the Automated Machine Learning program, thereby increasing the usefulness of the created program by not tying it to the Automated Machine Learning program. Additionally, this may increase the efficiency of running the AI pipeline by eliminating unnecessary computations performed by the Automated Machine Learning program.

Abstract: Various implementations include approaches for controlling a wearable audio device. In some cases, a method includes: detecting an initiation trigger for initiating a spatialized augmented reality (AR) menu mode; providing at least two distinct audio choices corresponding with spatially delineated zones in a menu defined relative to a physical position of the wearable audio device, in response to the initiation trigger, wherein each audio choice is associated with a selection from the menu; receiving a selection command indicating selection of one of the audio choices, wherein the selection command comprises a gesture detected by a gesture detection system at the wearable audio device; and in response to receiving the selection command: a) initiating playback of audio content associated with the selected audio choice, b) adjusting a setting at the wearable audio device, c) entering an additional menu related to the selection command, or d) exiting the menu.

Abstract: An insert comprising: (a) a cover layer; (b) a spacer layer located below the cover layer; (c) a connection material that is adapted to extend between and connect the cover layer to a trim layer so that the insert is fixed to the trim layer.