Abstract: Techniques are described herein for translating source code in one programming language to source code in another programming language using machine learning. A method includes: receiving first source code in a first higher-level programming language; processing the first source code, or an intermediate representation thereof, using a sequence-to-sequence neural network model to generate a sequence of outputs, each including a probability distribution; generating second source code in a second higher-level programming language by, for each output in the sequence of outputs: determining a highest probability in the probability distribution associated with the output; in response to the highest probability exceeding a first threshold, generating a predicted portion of the second source code based on a token that corresponds to the highest probability; and in response to the highest probability not exceeding the first threshold, generating a placeholder; and outputting the second source code.

Abstract: Embodiments herein disclose a method and electronic device for predicting multi-modal drawings. The method includes: receiving, by the electronic device, at least one of a text input and strokes of a drawing and determining, by the electronic device, features associated with the text input and features associated with the strokes of the drawing. The method includes classifying, by the electronic device, the features associated with the text input and the features associated with the strokes of the drawing into one of a dominant feature and a non-dominant feature and performing, by the electronic device, early concatenation or late concatenation of the features based on the classification; classifying, by the electronic device, the strokes of the drawing based on the concatenation into a category using a deep neural network (DNN) model; and predicting, by the electronic device, primary drawings corresponding to the category.

Abstract: According to an aspect, a method includes receiving, over a network, a conversation view request to retrieve messages from a conversation graph stored on a messaging platform from a first user account, generating a ranked list of messages for at least a portion of the messages from the conversation graph, identifying, from the ranked list of messages, a message authored by a second user account having an indirect relationship to the first user account in an engagement graph, selecting a social context object for the message based on a type of the indirect relationship, and transmitting, over the network, information to display the message and the social context object, the social context object providing information about the type of the indirect relationship.

Abstract: This disclosure relates to the use of “pseudo-images” to perform image recognition, e.g., to perform facial image recognition. In an embodiment, the pseudo-image is obtained by starting with a real world image and, after optional preprocessing, subjecting the image to a non-linear transformation that converts the image into a pseudo-image. While real world objects (or, more generally, real world patterns) may be perceivable in the starting image, they cannot be perceived in the pseudo-image. Image recognition takes place by comparing the pseudo-image with a library of known pseudo-images, i.e., image recognition takes place in pseudo-image space without a return to real world space. In this way, robust image recognition is achieved even for imperfect real world images, such as, real world images that have been degraded by noise, poor illumination, uneven lighting, and/or occlusion, e.g., the presence of glasses, scarves, or the like in the case of facial images.

Abstract: Coarse resolution satellite data has limited information content of land captured in the images and small area field boundary detection is technically challenging. Embodiments of the present disclosure provide a method and system for detection of field boundaries using coarse resolution satellite data and GIS. Multi-layer crop segmentation approach is used over RoI, wherein agricultural land related segments are derived from a soil layer, a temporal stack for a current season and a temporal change layer from the coarse resolution satellite data of the RoI. Segmentation based on different aspects captures various details at each segmentation layer. The segments are then combined, which aggregates all information related to the land to accurately detect the field boundaries in the RoI. The field boundaries are further refined using GIS topology operations. Baseline cadastral maps are updated using information from maps generated using refined field boundaries identified in real time for each season.

Abstract: Among other things, equipment is located at an intersection of a transportation network. The equipment includes an input to receive data from a sensor oriented to monitor ground transportation entities at or near the intersection. A wireless communication device sends to a device of one of the ground transportation entities, a warning about a dangerous situation at or near the intersection, there is a processor and a storage for instructions executable by the processor to perform actions including the following. A machine learning model is stored that can predict behavior of ground transportation entities at or near the intersection at a current time. The machine learning model is based on training data about previous motion and related behavior of ground transportation entities at or near the intersection.

Abstract: A circuit interrupter includes separable contacts; an operating mechanism; an electronic trip unit; and a current sensor assembly including: a harvester circuit having a primary conductor through which input current passes, a secondary winding and a harvester core structured to saturate at a first input current level, a Rogowski coil structured to measure voltage at an output of the Rogowski coil, the measured voltage indicative of output current of the Rogowski coil, where linearity of the output of Rogowski coil deviates more than a deviation tolerance based at least in part on saturation of the harvester core at the first input current level, and a compensation coil arranged at 180 degree opposite to the secondary winding of the harvester core, the compensation coil structured to delay saturation of the harvester core until the input current reaches a second input current level higher than the first input current level.

Abstract: A method for monitoring air quality is described. The method includes measuring environmental components at multiple locations using multiple mobile sensor platforms to provide sensor data. The environmental components include particulate matter having a size range and ambient gases. The sensor data includes particulate matter data having the size range and ambient gas data captured at the plurality of locations. The method also includes determining a signature based on the particulate matter data including the size range, and at least one additional factor. The at least one additional factor includes the ambient gas data. The method also includes identifying a source based on the signature.

Abstract: Techniques are disclosed for processing data packets and implementing policies in a software defined network (SDN) of a virtual computing environment. At least one SDN appliance is configured to disaggregate enforcement of policies of the SDN from hosts of the virtual computing environment. The servers are communicatively coupled to network interfaces of the SDN appliance. The servers host a plurality of virtual machines The SDN appliance comprises a plurality of smart network interface cards (sNICs) configured to implement functionality of the SDN appliance.

Abstract: Non-relational database operations are invoked to provide results consistent with commands specified in a relational query language. A request to access data in a non-relational database is received that includes one or more commands specified in a query language for accessing data according to a relational data scheme. The request may be evaluated to determine one or more Application Programming Interfaces (APIs) to invoke operations at the non-relational database that provide a result consistent with the commands specified in the query language. The determined APIs are executed and a result returned for the request based on the execution of the APIs.

Abstract: In one embodiment, a system for managing a virtualization environment comprises a plurality of host machines, one or more virtual disks comprising a plurality of storage devices, a virtualized file server (VFS) comprising a plurality of file server virtual machines (FSVMs), wherein each of the FSVMs is running on one of the host machines and conducts I/O transactions with the one or more virtual disks, and a virtualized file server self-healing system configured to identify one or more corrupt units of stored data at one or more levels of a storage hierarchy associated with the storage devices, wherein the levels comprise one or more of file level, filesystem level, and storage level, and when data corruption is detected, cause each FSVM on which at least a portion of the unit of stored data is located to recover the unit of stored data.

Abstract: The present technology can move operating system folders into a sync folder of a cross platform content management system, and redirect the operating system to look for the OS folders in the sync folder. The present technology also provides an invariant checker to make sure that another application has not moved the OS folders after they have been placed in the sync folder, and provides solutions when the OS folders are moved out of the sync folder of the content management system. Additionally, when OS folders for multiple client devices are in the sync folder on the content management system, the present technology can provide a mechanism to make the content items in an OS folder on a first client device also sync into an OS folder on second client device.

Abstract: Techniques including receiving a first set of values for processing by a machine learning (ML) network, storing a first portion of the first set of values in an on-chip memory, processing the first portion of the first set of values in a first layer of the ML network to generate a second portion of a second set of values, overwriting the stored first portion with the generated second portion, processing the second portion in a second layer of the ML network to generate a third portion of a third set of values, storing the third portion, repeating the steps of storing the first portion, processing the first portion, overwriting the stored first portion, processing the second portion, and storing the third portion for a fourth portion of the first set of values until all portions of the first set of values are processed to generate the third set of values.

Abstract: Among other things, equipment is located at an intersection of a transportation network. The equipment includes an input to receive data from a sensor oriented to monitor ground transportation entities at or near the intersection. A wireless communication device sends to a device of one of the ground transportation entities, a warning about a dangerous situation at or near the intersection, there is a processor and a storage for instructions executable by the processor to perform actions including the following. A machine learning model is stored that can predict behavior of ground transportation entities at or near the intersection at a current time. The machine learning model is based on training data about previous motion and related behavior of ground transportation entities at or near the intersection.

Abstract: A plurality of first entities have been previously associated with a predefined activity. By performing a clustering algorithm on the first entities, a subset of the first entities is identified that have met a predefined criterion. Via a Natural Language Processing (NLP) technique, a multi-dimensional matrix is generated. The matrix has a plurality of vectors associated with attributes of the subset of the first entities. A neural network model is trained with the multi-dimensional matrix. A plurality of second entities are on a list that contains entities that have been flagged for engaging in, or having engaged, the predefined activity. Based on the trained neural network model, a prediction is made whether scanning the second entities against a plurality of third entities for matches will cause a number of alerts having a predefined characteristic to exceed a predefined threshold. The alerts correspond to matches that needs further investigation.

Abstract: Techniques are provided for utilizing Wi-Fi positioning based contact tracing. An example method for reporting signal measurements to a contact tracing network includes activating a contact tracing application on a user equipment based on a proximity to the contact tracing network, receiving one or more measurement signals from a station in the contact tracing network, and reporting a signal measurement and station identification to a network entity.

Abstract: An apparatus including a circuit structure including a device stratum including a plurality of devices including a first side and an opposite second side; and a metal interconnect coupled to at least one of the plurality of devices from the second side of the device stratum. A method including forming a transistor device including a channel between a source region and a drain region and a gate electrode on the channel defining a first side of the device; and forming an interconnect to one of the source region and the drain region from a second side of the device.

Abstract: Disclosed are systems and techniques for performing mapping using radio frequency (RF) sensing. For instance, a server can obtain a first set of RF sensing data and orientation data corresponding to a first wireless device from a plurality of wireless devices. The first set of RF sensing data can be associated with at least one received waveform that is a reflection of a transmitted waveform from a first reflector. Based on the first set of RF sensing data, orientation data, and location data corresponding to the first wireless device, an indoor map can be generated that includes a reference to the reflector.

Abstract: Stacked transistor structures having a conductive interconnect between source/drain regions of upper and lower transistors. In some embodiments, the interconnect is provided, at least in part, by highly doped epitaxial material deposited in the upper transistor's source/drain region. In such cases, the epitaxial material seeds off of an exposed portion of semiconductor material of or adjacent to the upper transistor's channel region and extends downward into a recess that exposes the lower transistor's source/drain contact structure. The epitaxial source/drain material directly contacts the lower transistor's source/drain contact structure, to provide the interconnect. In other embodiments, the epitaxial material still seeds off the exposed semiconductor material of or proximate to the channel region and extends downward into the recess, but need not contact the lower contact structure.

Abstract: In implementations of systems for generating images for virtual try-on and pose transfer, a computing device implements a generator system to receive input data describing a first digital image that depicts a person in a pose and a second digital image that depicts a garment. Candidate appearance flow maps are computed that warp the garment based on the pose at different pixel-block sizes using a first machine learning model. The generator system generates a warped garment image by combining the candidate appearance flow maps as an aggregate per-pixel displacement map using a convolutional gated recurrent network. A conditional segment mask is predicted that segments portions of a geometry of the person using a second machine learning model. The generator system outputs a digital image that depicts the person in the pose wearing the garment based on the warped garment image and the conditional segmentation mask using a third machine learning model.