Abstract: Devices, systems, and methods are provided for smart shopping based on recognition of objects presented in video. A method may include identifying, by a first device, using a machine learning model using a computer vision technique, objects represented in video content; determining that an object of the objects is available for purchase using an online retail system; causing concurrent presentation of the video content and a first indication that the object is available for purchase using the online retail system; receiving, from a second device, a second indication of a user selection of the first indication, wherein the user selection is indicative of a request to present additional information associated with the object; generating, based on the request, presentation data including the additional information and an option to purchase the object using the online retail system; and causing, based on the request, presentation of the presentation data.

Abstract: A system and a method provide an Artificial Intelligence (AI) companion for each Function Block in a Programmable Logic Controller (PLC) program to integrate AI in automation systems. Multiple function blocks and system function blocks are grouped into a logic group. A control problem is broken down from a top level into logical partitions as several functions that are programmed as Function Blocks in a PLC program. Each Function Block and the entire PLC program are integrated with an associated AI Companion. A runtime system for the AI Companion provides new runtime capabilities. An approach to implementing the AT Companions is provided. A method of controlling an automation process is also provided.

Abstract: Techniques for performing a machine learning model based spatial-temporal adaptive shift for end-to-end text-video retrieval are described.

Abstract: Methods, systems, and devices for managing regions of a memory system are described. A memory system may include a non-volatile memory device and may receive a host performance booster (HPB) command (e.g., a read command) associated with one or more regions of the non-volatile memory device. The memory system may determine whether the region(s) associated with the HPB command are active. In instances where one or more of the associated regions are inactive, the memory system may activate the region(s) and deactivate one or more other regions based on a recency parameter (e.g., a timing parameter). The memory system may process the received HPB command based on the associated region(s) being active.

Abstract: Methods, systems, and devices for read operations for active regions of a memory device are described. A memory system that includes a non-volatile memory device may receive a command to enter a first power mode. Before entering the first power mode, the memory system may store an indication of the active regions of the non-volatile memory device that are active for use as part of a host performance booster (HPB) mode. The memory device may receive an HPB command while in the first power mode, and may subsequently enter (e.g., re-enter) the second power mode. In some examples, the HPB command may be processed based on its physical address being included in one of the active regions of the non-volatile memory device.

Abstract: A system for processing data in an industrial environment includes a sensor that communicates sensor data acquired from a factory floor as a multicast data stream where each frame is tagged with a sequence identifier indicative of a position of that frame in the data stream. A network switch distributes the data stream to a group of multicast endpoints. The system includes a controller with a plurality of modularly connected processing units. Each processing unit is further connected to the network switch and configured as a respective endpoint of the group of multicast endpoints. Each processing unit selectively processes frames of the data stream in dependence of the sequence identifier of individual frames by executing a data processing module, to produce an output result associated with each processed frame. The controller assembles the output result and the sequence identifier of each processed frame from the plurality of processing units.

Abstract: A system and method are disclosed for production process monitoring using graph learning. A production ontology is generated based on data received from an engineering design process, the ontology including selection of production machines, definition of a product, and workflow design. A production graph is instantiated based on the production ontology. Production process data is read from control systems of the production environment and the production graph is populated with the production process data to generate a time series of production graphs. Prediction information is received from historical production graphs of related production processes. Offline runtime analytics are performed on the production graph to yield analytics results including a plurality of predictors. The predictors include knowledge from the received prediction information leveraged with a weight sharing initialization.

Abstract: A real-time computer system for automated acoustic anomaly detection in a programmable logic controller (PLC) is disclosed, the computer system being deployed onto a backplane of the PLC. The computer system includes at least one processor with a real-time operating system and a memory having algorithmic modules stored thereon executable by the processor. The modules include a digital signal processing module configured to apply a windowing function to the sound signal data captured by a sensor, the sound signal data representative of sound emitted by an energized work product under quality inspection. The modules further include a feature extraction component configured to extract acoustic features from each sound window, and an anomaly detector module configured to operate a machine learning-based model to execute acoustic anomaly detection according to results of a classification operation on the acoustic features.

Abstract: The embodiments of the present disclosure provide an image display method and apparatus, an electronic device, a readable storage medium, and a chip, and the image display method includes: acquiring panorama information; determining position information of a display screen in the panorama information; determining a screen contour region of the display screen according to the position information, and determining an occlusion region that does not belong to the display screen in the screen contour region; determining a display region according to the occlusion region; and displaying preset image information in the display region.

Abstract: Methods, systems, and devices for read operations for active regions of a memory device are described. A memory system that includes a non-volatile memory device may receive a command to enter a first power mode. Before entering the first power mode, the memory system may store an indication of the active regions of the non-volatile memory device that are active for use as part of a host performance booster (HPB) mode. The memory device may receive an HPB command while in the first power mode, and may subsequently enter (e.g., re-enter) the second power mode. In some examples, the HPB command may be processed based on its physical address being included in one of the active regions of the non-volatile memory device.

Abstract: A system and method for promoting candidate plans for upgrade in vendor provided devices or services. A context engine generates an automation context term for a target application using inference algorithms based on a retrieved ontology of the industrial automation system. A mapping engine queries a digital catalog for candidate upgrade devices or services related to the context term and maps key performance indicators related to the context term for each candidate device or service. A cost-performance engine estimates performance improvement for each of the candidate upgrade devices or services using algorithms that generate one or more simulation models for calculating the performance improvements. A ranked list of candidate plans for upgrade of devices or services is delivered with cost and performance information to one or more graphical user interfaces in the automation system for display to a one or more users.

Abstract: Disclosed are a high-power repeat-frequency solid-state switch controlled by a combination of an optical amplification and an electrical amplification, and a method.

Abstract: Disclosed are a high-power repeat-frequency solid-state switch controlled by a combination of an optical amplification and an electrical amplification, and a method.

Abstract: Heat-and-cold recovery system based on liquid cooling data center (energy storage power station) includes high-temperature heat pump, pressure-less heat-storage tank, pressurized heat-storage tank, absorption-type water chiller group, compression-type water chiller group, water cold-storage tank, and PCM cold-storage tank.

Abstract: Methods, systems, and devices for techniques for efficiently handling misaligned sequential reads are described. A memory system may include a memory device that includes multiple memory dies. The memory system may receive a first read command and a second read command from a host system. The first read command may be associated with a first set of physical addresses and the second read command may be associated with a second set of physical addresses. The memory system may determine, based on the first set of physical addresses and the second set of physical addresses, that the first read command and the second read command are for a same memory die of the multiple memory dies. The memory system may then transmit to the memory die a read request that indicates the first set of physical addresses and the second set of physical addresses.

Abstract: HMI screens are typically manually engineered or arranged. For example, HMI screens can include various elements, and an engineer often arranges the HMI elements on a given HMI screen, for instance one by one, until the final design of the HMI screen is complete. It is recognized herein that existing approaches to designing and arranging HMI screens lack efficiency, and can be tedious and redundant. Method, systems, and apparatuses described herein can automatically arrange elements of human-machine interface (HMI) screens. In an example aspect, a computing system includes a deep learning model, for instance an autoencoder or a generative adversarial network (GAN), configured to learn and design HMI screen arrangements.

Abstract: Described embodiments provide a technique for commissioning an AI-based inspection system. In particular, the described embodiments provide a tool for field engineers to perform tasks including data collection, and training, testing and deployment of an AI algorithm, onsite, with instant feedback. The described tasks are carried out in the same physical environment to arrive at the same sensor setting that is then used by the field device on which the AI algorithm is deployed. Deployment cycle is significantly reduced. The technique leverages the recognition that inspection tasks in industrial settings are repetitive in nature and are carried out in a controlled environment, whereby the AI algorithm need not be generalized beyond the specific use case.

Abstract: A system and method for constructing a reconfigurable runtime system used in an automation system using reusable runtime functions (RRFs) is disclosed. A specialization module executes a specialization operation to configure or customize at least one RRF to satisfy functional requirements of the automation system. A stitching module executes a stitching operation that connects output of at least one RRF to input of one or more other RRFs. A stacking module executes a stacking operation that stacks RRFs as layers to create new abstractions, functionality and services. The specialization operation, the stitching operation, and the stacking operation are performed according to a runtime specification language.