Abstract: Embodiments herein describe using a reference laser locked to an atomic reference to adjust the wavelength of a seed laser. A frequency adjuster (e.g., a frequency doubler) can adjust the seed laser to a different wavelength/frequency for a particular application. A controller can adjust the wavelength of the seed laser by comparing the reference laser to the adjusted seed laser generated by the frequency adjuster.

Abstract: A system for identifying recurring alarms includes a non-transitory computer readable medium configured to store instructions; and a processor. The processor is configured to execute the instructions for correlating an alarm log with a rule, the alarm log includes information related to a plurality of faults. The processor is configured to execute the instructions for determining whether any of the plurality of faults satisfy criteria of the rule; and identifying an earliest fault of the plurality of faults that satisfies all of the criteria of the rule in response to a determination that at least one fault of the plurality of faults satisfies all of the criteria of the rule. The processor is configured to execute the instructions for comparing the earliest fault with an incident log; and generating an incident in response to a determination that the earliest fault does not match any open entry in the incident log.

Abstract: A critical path based proactive optimization that includes collecting data on the tasks of contextual situation for performing a process and training a twin computing simulation model using the collected data for each task in the process. A contextual situation simulation is run using the simulation models for each task in the process to determine a critical path that causes delay in the process. An optimized task is determined from the tasks of the contextual situation using machine learning employing the collected data, wherein the optimized task mitigates delay in the process from the critical path.

Abstract: Selective training of neural networks using motion estimation, including: selecting, from a plurality of pixels in video data from a vehicle, based on motion relative to the vehicle, one or more pixels; and training a neural network based on the video data by zeroing out an error function applied to the selected one or more pixels.

Abstract: Methods and techniques are described for enhancing positioning related protocols in order to indicate when one location session is different from another location session. One or more messages provided in a location session by a location server to a user equipment (UE) may include a session indication, such as a session identifier (ID), where a different session ID is provided for each location session. The session indication may be a new session indicator provided in an initial message in a location session or an end session indicator provided in a final message in a location session. An extra message may be sent by the location server indicating that the location session has ended. A correlation ID provided by a network entity to the location server may be included in messages as the session indication, e.g., where a different correlation ID is provided for each location session.

Abstract: A system for identifying correlated alarms includes a non-transitory computer readable medium configured to store instructions thereon; and a processor connected to the non-transitory computer readable medium. The processor is configured to execute the instructions for identifying a parent alarm from an alarm log based a plurality of rules, wherein the alarm log comprises a plurality of alarm, and the plurality of alarms contains the identified parent alarm. The processor is configured to execute the instructions for determining whether the plurality of alarms includes a child alarm associated with the identified parent alarm based on the plurality of rules. The processor is configured to execute the instructions for generating an incident in response to a determination that the plurality of alarms includes the child alarm, wherein the incident includes instructions for resolving the parent alarm.

Abstract: A computing device determines similarity between a chat conversation and one or more other chat conversations in public chat channels within computer messaging software and automatically presents the similar public chat channels to a user. A computing device accesses a real-time chat conversation, the chat conversation taking place between a plurality of participants. The computing device analyzes the real-time chat conversation to generate a word density function model modeling at least a part of the real-time chat conversation. The computing device accesses one or more persistent conversations held in a plurality of public chat channels. The computing device determines one or more persistent conversations held in similar public chat channels based upon the generated word density function model. The computing device presents the determined one or more persistent similar public chat channels to a user.

Abstract: A vehicle power module assembly including first and second power modules is provided. The first power module may include a first lock feature extending from a lower portion of a first minor side at a first central axis. The second power module may include a second lock feature at an upper portion of a second minor side at a second central axis. The lock features may be sized for interlock with one another to secure the power modules to one another. The first lock feature may be a loop element defining a through-hole and the second lock feature may be a wedge. The through-hole may be sized for the wedge to extend therein and to interlock the first power module and the second power module to one another. The first lock feature may be a flexible hook element and the second lock feature may be a slot.

Abstract: The present invention discloses a process for extracting biomolecules from biomass using an extraction apparatus. Further, the present invention provides an ultrasonic process that extracts lutein pigments from marigolds using an extraction apparatus that requires at least two repeating units of reactor setup. Here the present invention shows an extraction efficiency in the range of 95-100% and purity of biomolecules with a range of 90-95% under mild reaction conditions.

Abstract: A method of wireless communication performed by a first transmission device incudes receiving a first set of observations from a first receiving device based on transmissions from the first transmission device to the first receiving device at a previous time slot of a fixed contention-based spectrum sharing system. The first transmission device shares a spectrum with a second transmission device. The method also includes measuring an energy level from an ongoing data transmission of the second transmission device at a current time slot. The method further includes generating, at an artificial neural network of the first transmission device, at least one of a transmission determination, a set of transmission parameters, or a combination thereof, based on a second set of observations, the energy level, and a counter.

Abstract: Provided are techniques for digital twin functional and non-functional simulation testing. An indication is received that digital twin functional and non-functional simulation testing is to start for an application being developed, where a first portion of code for the application has been developed and a second portion of the code for the application has not been developed. Application data and an application landscape are retrieved. The digital twin functional and non-functional simulation testing is performed to identify which functional and non-functional requirements are not being met by the first portion of the code. For the functional and non-functional requirements that are not being met, suggestions are provided for at least one of the first portion and the second portion to meet one or more of the functional and non-functional requirements. One or more of the suggestions are implemented.

Abstract: Embodiments detect duplicate invoices, each invoice including a plurality of fields. Embodiments generate synthetic training data using a plurality of training invoices and generating one or more modified fields for each of the plurality of training invoices. Embodiments train a machine learning model using the synthetic training data and generate a plurality of candidate invoice pairs. Embodiments input the plurality of candidate invoice pairs to the trained machine learning model and generate, by the trained machine learning model, a prediction of whether each of the candidate invoices pairs is a duplicate invoice pair.

Abstract: A computer implemented method manages nonintelligent items. A computer system identifies a workflow to be performed. The computer system identifies a group of the nonintelligent items involved in actions for the workflow. The computer system attaches a set of computing devices to the group of the nonintelligent items to convert the group of the nonintelligent items into a group of converted nonintelligent items. The computer system performs the actions in the workflow using the group of converted nonintelligent items.

Abstract: A system and method for managing network traffic in a distributed environment. the system including: a plurality of logic modules configured to determine policy data related to bandwidth management and at least one split criteria for a basis for shaping network traffic; a control processor associated with each one of the plurality of logic modules, each control processor configured to determine data associated with each of a plurality of traffic flows at the associated logic module and to coordinate traffic actions over the plurality of logic modules; a packet processor associated with each control processor and configured to determine a traffic action based on each traffic flow and received policy data; and at least two shaper objects configured to receive a split of the traffic flows and enforce the determined traffic action on their respective traffic flow.

Abstract: A method of wireless communication performed by a first transmission device includes determining a set of spectrum sharing parameters based on sensing performed during a sensing period of a current time slot in a fixed contention based spectrum sharing system. The first transmission device shares a spectrum with a second transmission device. The method also includes determining, at a first artificial neural network of the first transmission device, a transmission device action, and/or a transmission parameter in response to receiving the set of spectrum sharing parameters. The method further includes transmitting, from the first transmission device, to a first receiving device during a data transmission phase of the current time slot based on the transmission device action and/or the transmission parameter.

Abstract: A product management computer system that can include one or more processors, and a computer-readable medium comprising instructions stored therein, which when executed by the processors, can cause the processors to: receive data representing a target product of interest to a user of the system, wherein the target product is described by a plurality of variable-value attributes associated; process the received data through a machine-learning-produced algorithm and generating data representing a first set of substitute product candidates for the target product and wherein each substitute product candidate has a corresponding match-score that represents a degree of determined similarity between that substitute product candidate and the target product; transform the generated data that represents the first set of substitute product candidates into data representing a refined set of substitute product candidates by processing the generated data utilizing a constraint-based algorithm; and output data representing

Abstract: A computer implemented method for identifying substitute products for a target product via a distributor's product management computer system, the method includes: receiving, at a distributor's product management computer system, data representing a target product of interest to a user of the system, wherein the target product is described by a plurality of variable-value attributes associated therewith; processing the received data through a machine-learning-produced algorithm and thereby generating data representing a first set of substitute product candidates for the target product and wherein each substitute product candidate has a corresponding match-score that represents a degree of determined similarity between that substitute product candidate and the target product; transforming the generated data that represents the first set of substitute product candidates into data representing a refined set of substitute product candidates by processing the generated data utilizing a constraint-based algorithm;

Abstract: A computer-implemented method, system and computer program product for efficient resource utilization. A workflow of manufacturing a product using various machines at each plant of an organization is created, where the workflow illustrates which machines are utilized to produce the product using one or more raw materials. A production rate for the product at each plant manufacturing the product is predicted based on the workflow. An amount of a raw material required by a first plant to produce the product is determined based on the predicted production rate for the product at the first plant. An amount of the raw material is then routed to the first plant from one or more other plants based on minimizing the system inventory carrying cost and minimizing the system transportation cost if the first plant needs an additional amount of the raw material to realize the predicted production rate for the product.

Abstract: A product management computer system that can include one or more processors, and a computer-readable medium comprising instructions stored therein, which when executed by the processors, can cause the processors to: receive data representing a target product of interest to a user of the system, wherein the target product is described by a plurality of variable-value attributes associated; process the received data through a machine-learning-produced algorithm and generating data representing a first set of substitute product candidates for the target product and wherein each substitute product candidate has a corresponding match-score that represents a degree of determined similarity between that substitute product candidate and the target product; transform the generated data that represents the first set of substitute product candidates into data representing a refined set of substitute product candidates by processing the generated data utilizing a constraint-based algorithm; and output data representing

Abstract: A computer method for identifying product in a distributor's inventory system that fulfills a product request made via a natural language query. the natural language query is received as a product request including multiple words in sequential order. The words are vectorized into word-vectors that are concatenated and used to generate a query embedding. The query embedding is processed utilizing a trained product category classifier that predicts which product category the requested product belongs. Forward and backward sequence vectors are generated from the sequentially ordered words of the query that are concatenated and processed using a trained model specific to the predicted product category. The sequence vectors represent positional relationships between the words of the natural language query. Thereafter, the system identifies product attribute(s) embodied in the natural language query that each correspond to a predetermined key-characteristic of the category.