Abstract: A solar system comprises at least one solar panel with a plurality of solar cells. The solar panels include first and second split-circuits to extract electrical energy from the solar panel. The first split-circuit includes solar panel wires that electrically connect, in series, the solar cells of the first split-circuit to extract electrical energy from the solar panel. Similarly, the second split-circuit includes solar panel wires that electrically connect, in series, the solar cells of the second split-circuit to extract electrical energy from the solar panel. The first and second split-circuits are configured to generate a voltage not to exceed a voltage specification, such as a voltage specification of 35 volts.

Abstract: A drilling data analytics engine disclosed herein automatically corrects drilling data with predictive modeling. A drilling data quality analyzer segregates drilling data into good drilling data and bad drilling data that has missing, incomplete, or incorrect entries. For each bad data entry in the bad drilling data, the drilling data analytics engine preprocess drilling data attribute values for the corresponding task not including the drilling data attribute value for the bad data entry and inputs the preprocessed drilling data attribute values into a trained predictive model. The trained predictive model is trained on good drilling data to estimate values for the drilling attribute corresponding to the bad data entry.

Abstract: A drilling data correction system corrects drilling data entries in high-importance drilling data segments using machine learning and rules-based drilling models. A data importance analyzer identifies high-importance data segments in incoming drilling data. The drilling data correction system inputs features of drilling data into machine learning drilling models and rules-based drilling models trained to predict the high-importance data segments. Predictions from the machine learning drilling models and rules-based drilling models are presented to a user based on drilling data prediction criteria. The machine learning drilling data predictions are used to automatically correct the high-importance data segments, or the user chooses between machine learning drilling data predictions and rules-based drilling data predictions to correct the high-importance drilling data segment.

Abstract: A method implemented by a computing system comprises receiving, by the computing system and from a user device, a subject profile information that specifies a plurality of body measurements associated with one or more images of a subject that are captured by the user device. The computing device receives a selection of a garment, where the garment is associated with a category, a brand, a style, and a plurality of sizes. A sizing recommendation engine of the computing system determines, based on the plurality of body measurements, a particular size of the garment that is associated with the subject profile information. The computing system communicates the particular size to the user device.

Abstract: A method, system, apparatus, and/or device for sensing an input in an augmented reality construct. The method, system, apparatus, and/or device may include a mixed-reality device, comprises memory and one or more processors communicatively coupled to a sensor, a touch device, and a display device that is at least partially transparent and configured to display a virtual object. The store instructions executable by the one or more processors to generate virtual object data for displaying a virtual object by the display device; output the virtual object data to the display device; receive, from the sensor, interaction data corresponding to a free-space interaction by a hand of a user with the virtual object; generate touch input data based on the interaction data; and output the touch input data to the touch device.

Abstract: The subject matter described herein provides systems and techniques to counter a high write amplification in physical memory, to ensure the longevity of the physical memory, and to ensure that the physical memory wears in a more uniform manner. In this regard, aspects of this disclosure include the design of a Flash Translation Layer (FTL), which may manage logical to physical mapping of data within the physical memory. In particular, the FTL may be designed with a mapping algorithm, which uses reinforcement learning (RL) to optimize data mapping within the physical memory. The RL technique may use a Bellman equation with q-learning that may rely on a table being updated with entries that take into account at least one of a state, an action, a reward, or a policy. The RL technique may also make use a deep neural network to predict particular values of the table.

Abstract: A system is described for determining a likelihood of a type of fluid in a subterranean reservoir. The system may include a processor and a non-transitory computer-readable medium that includes instructions executable by the processor to cause the processor to perform various operations. The processor may receive pre-stack seismic data having seismically-acquired data elements for geometric locations in a subterranean reservoir. The processor may determine, using the pre-stack seismic data, input features for each geometric location and may execute a trained model on the input features for determining a likelihood of a type of fluid in the subterranean reservoir and for determining a list of features affecting the likelihood. The processor may subsequently output the likelihood and the list of features.

Abstract: A method of rendering a service graph responsive to a query comprises generating a plurality of frontend traces and a plurality of backend traces associated with an application or website. The method also comprises determining connection information between one or more frontend traces of the plurality of frontend traces and corresponding backend traces of the plurality of backend traces. Further, the method comprises consolidating the one or more frontend traces with the corresponding backend traces to form one or more end-to-end traces using the connection information. Responsive to the query, the method comprises retrieving a set of exemplary end-to-end traces from the one or more end-to-end traces and rendering a service graph in accordance with constraints applied in the query using the set of exemplary end-to-end traces and the connection information.

Abstract: An on chip leakage-current detection device including a first inverter where the magnitude of delay of the output signal of the first inverter is determined by a leakage current of a target device. The leakage-current detection device further includes: a capacitor that is charged by the output signal of the first inverter; a second inverter coupled to capacitor that switches states when the capacitor is charged to a switching level; an odd number of additional inverters coupled in a sequence with a second-inverter output. The output of the leakage-current detection device has a frequency proportional to the leakage of the target device.

Abstract: Computing machine(s) access an input image of footwear, the input image comprising a pixel or voxel based image. The computing machine(s) generate, based on the input image and using machine learning engines, a 3D (three-dimensional) CAD (computer-aided design) digital asset comprising a NURBS (non-uniform rational basis spline) model of the footwear. Generating the 3D CAD digital asset comprises: identifying, using a trained classification engine, a visual component of the footwear and iteratively fitting, for the visual component of the footwear, a spline using a trained reinforcement learning engine until the spline is within a predefined average distance from the visual component. The 3D CAD digital asset comprises the spline. The machine learning engines comprise the trained classification engine and the trained reinforcement learning engine. The computing machine(s) provide an output representing the 3D CAD digital asset.

Abstract: Some implementations are directed to adapting a client application on a feature phone based on experiment parameters. Some of those implementations are directed to adapting an assistant client application, where the assistant client application interacts with remote assistant component(s) to provide automated assistant functionalities via the assistant client application of the feature phone. Some implementations are additionally or alternatively directed to determining whether an invocation, of an assistant client application on a feature phone, is a request for transcription of voice data received in conjunction with the invocation, or is instead a request for an assistant response that is responsive to the transcription of the voice data (e.g., includes assistant content that is based on and in addition to the transcription, and that optionally lacks the transcription itself).

Abstract: The present disclosure generally relates to performance recreation, and in particular, the recreation of observed human performance using reinforcement learning. In this regard, a first object is identified from a plurality of objects. The manipulation of the first object is tracked from a first position to a second position. A characterization of the manipulation is generated. A policy that controls a mechanical gripper to recreate the manipulation is generated based on an iteratively increasing cumulative award. The mechanical gripper iteratively recreates the manipulation to increase a cumulative award with each recreation.

Abstract: Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. COVID-19 is affecting the whole world and it's not only taking lives but also heavily penalizing the economy. This new invention ‘Novel Pens/Pencils Sanitizing Machine’ helps in reducing the risks of getting COVID-19 and other common infectious diseases like Flu, common cold etc. through the use of common pens and pencils. Many facilities front desk like schools, doctor's offices, Hospitals, private offices share the same pens or pencils with others or sanitizes the pens or pencils manually which is a time taking and tedious job. This machine sanitizes bunch of pens and pencils in one go in an automated way.

Abstract: A method, system, apparatus, and/or device for sensing an input in an augmented reality construct. The method, system, apparatus, and/or device may include a mixed-reality device, comprises memory and one or more processors communicatively coupled to a sensor, a touch device, and a display device that is at least partially transparent and configured to display a virtual object. The store instructions executable by the one or more processors to generate virtual object data for displaying a virtual object by the display device; output the virtual object data to the display device; receive, from the sensor, interaction data corresponding to a free-space interaction by a hand of a user with the virtual object; generate touch input data based on the interaction data; and output the touch input data to the touch device.

Abstract: A free space input standard is instantiated on a processor. Free space input is sensed and communicated to the processor. If the free space input satisfies the free space input standard, a touch screen input response is invoked in an operating system. The free space input may be sensed using continuous implicit, discrete implicit, active explicit, or passive explicit approaches. The touch screen input response may be invoked through communicating virtual touch screen input, a virtual input event, or a virtual command to or within the operating system. In this manner free space gestures may control existing touch screen interfaces and devices, without modifying those interfaces and devices directly to accept free space gestures.

Abstract: Embodiments detect and predict data disparity issues in data warehouses. Embodiments derive meaningful insights about the events occurred prior to the data disparity and correlate the events to understand the root cause of the data disparity (or the root cause of an alert generated as a result of detecting the data disparity). Embodiments either take or recommend actionable measures to prevent further occurrences of the event identified as the root cause. According to various embodiments, when the monitored data is transaction data (e.g. transaction volume, transaction amount, transaction processing speed, etc.), internal events (e.g. data job failures, job delays, job server maintenances) or external events (e.g. seasonal holiday events, natural calamities) may cause a dip or spike in the transaction data resulting in a data quality anomaly (i.e. a data disparity).

Abstract: The invention relates to a center break switch having a contact system for electrical current conduction and bus transfer switching. The contact system includes two moving contacts. One of the two moving contacts includes a finger contact and the other moving contact includes a first contact. Each moving contact includes a contact for bus transfer switching, wherein one of the two contacts includes a spherical contacting element, and the other contact includes a rectangular contacting element. The spherical contacting element and the rectangular contacting element engage during switching for the bus transfer, and stay in contact when the finger contact is engaged with the first contact for electrical current conduction.

Abstract: Some implementations are directed to adapting a client application on a feature phone based on experiment parameters. Some of those implementations are directed to adapting an assistant client application, where the assistant client application interacts with remote assistant component(s) to provide automated assistant functionalities via the assistant client application of the feature phone. Some implementations are additionally or alternatively directed to determining whether an invocation, of an assistant client application on a feature phone, is a request for transcription of voice data received in conjunction with the invocation, or is instead a request for an assistant response that is responsive to the transcription of the voice data (e.g., includes assistant content that is based on and in addition to the transcription, and that optionally lacks the transcription itself).

Abstract: A method, system, apparatus, and/or device for sensing an input in an augmented reality construct. The method, system, apparatus, and/or device may include a mixed-reality device, comprises memory and one or more processors communicatively coupled to a sensor, a touch device, and a display device that is at least partially transparent and configured to display a virtual object. The store instructions executable by the one or more processors to generate virtual object data for displaying a virtual object by the display device; output the virtual object data to the display device; receive, from the sensor, interaction data corresponding to a free-space interaction by a hand of a user with the virtual object; generate touch input data based on the interaction data; and output the touch input data to the touch device.