Abstract: Systems, computer program products, and methods are described herein for analyzing system health of individual electronic components using component relational graphs. The method includes receiving a process request. The process request is a request to execute a process. The method also includes determining one or more components of the system used during the process. The method further includes generating a component knowledge graph for the process. The component knowledge graph includes one or more nodes corresponding to each of one or more components used during the process. The method still further includes determining a component health rating for each of the one or more components used in the process.

Abstract: Systems, computer program products, and methods are described herein for analyzing system health of individual electronic components using image mapping. The method includes receiving a component health image for a component based on an execution of a process. The method also includes comparing the component health image based on the execution of the process to previous component health image(s) for the component based on one or more previous executions of the process The method further includes determining a component health image similarity score based on the comparison of the component health image to the one or more previous component health images for the component. The method still further includes determining a component health action based on the component health image similarity score. The component health action includes causing a transmission of an alert in an instance in which the component health image similarity score is outside of a threshold range.

Abstract: Embodiments of the present invention provide a system for analyzing operational parameters of electronic and software components associated with entity applications to detect anomalies. The system is configured for extracting one or more historical images associated with resiliency status of electronic and software components associated with an entity application, analyzing the one or more historical images to generate a pixel wise average of the one or more historical images, generating similarity scores between the one or more historical images, determining a distribution of the similarity scores, receiving a real-time image associated with a current resiliency status of the electronic and software components associated with the entity application, generating a real-time image similarity score for the real-time image, and comparing the real-time image similarity score with the distribution to detect presence of an anomaly.

Abstract: Systems, computer program products, and methods are described herein for performance monitoring using aggregated telemetry. The present disclosure is configured to receive, from the first performance monitoring engine, a first metadata associated with the first resiliency status; receive, from the second performance monitoring engine, a second metadata associated with the second resiliency status; determine, using a machine learning (ML) subsystem, an overall resiliency status of the device based on at least the first metadata, the second metadata, the first resiliency status, and the second resiliency status; determine one or more actions to be executed on the device, wherein the one or more actions are associated with the overall resiliency status; generate a notification indicating the overall resiliency status of the device and the one or more actions associated with the overall resiliency status; and transmit control signals configured to cause a user input device to display the notification.

Abstract: Systems, computer program products, and methods are described herein for real-time overload detection using image processing analysis. The present disclosure is configured to receive a first set of images associated with a device, wherein the one or more images are associated with a resiliency status of the device; deploy, using a machine learning (ML) subsystem, a trained ML model on the first set of images of the device; determine, using the trained ML model, a change in the resiliency status of the device based on the first set of images; and generate a notification indicating the change in the resiliency status of the device; and transmit control signals configured to cause a first user input device to display the notification.

Abstract: A bassinet includes a base, a column assembly rotatably connected to the base at a first end of the column assembly, an arm rotatably connected to a second end of the column assembly, a tub frame pivotably connected to the arm, an infant tub retained within the tub frame, the infant tub including a front wall, a back wall, and two side walls and having areas of reduced height along the front wall and at least one of the side walls to provide enhanced access to the infant located within the infant tub, and an insert configured to reversibly fit within an interior of the infant tub.

Abstract: A method and reconfigurable computer architecture protect binary opcode, or other data and instructions by providing an encryption capability integrated into an instruction issue unit of a protected processor. Opcodes are encrypted at their source, and encrypted opcodes are then delivered to the CPU and decrypted “inside” the CPU. Access into the CPU is prevented. Each form of code or data selected for protection is protected from unauthorized viewing or access. Commonly, the binary executable, or object, code is selected for protection. However, protected information could also include source code or data sets or both. Encrypting opcodes will result in making unique opcodes for each processor. Encryption keys and hidden opcode algorithms provide further security.

Abstract: In an oxidation process in a shell and tube reactor (10), an improvement is disposing a short bed of packing material (30) about the tube (50) inlets. The short bed operates to direct contaminants derived from heat exchange media away from the headspace (20) and thus prevents formation of combustible gas mixtures.