Abstract: The present invention provides a method (300) for operating a video laryngoscope, enhancing usability during endotracheal intubation procedures. The method involves controlling a display unit attached to a laryngoscope handle to present real-time visual data captured by a camera housing located at the distal end of the handle. The display unit automatically adjusts the orientation of the displayed visual data based on the angle of the display unit relative to the handle, ensuring proper alignment during the procedure. The method (300) includes capturing and storing visual data in an integrated memory module, providing clinicians with the ability to review, manage, and capture data through a user-friendly interface. Additionally, the video laryngoscope (100) enables secure connection to external devices for data transfer using password-protected encryption to safeguard patient information.

Abstract: The present invention provides a video laryngoscope (100) to perform the intubation process. The video laryngoscope (100) includes a handle (10), a blade (20), a display unit (30), and an attachment assembly (25). The handle (10) includes a camera housing (16) with an image sensor (161) and a light source (162) arranged therein. The image sensor (161) is attached to the handle (10) through a camera channel (15) to visualise the path of the endotracheal tube. The camera housing (16) has a deflector (18) to avoid the blurry and distorted visuals generated due to the scattering of the light from the light source (162). The blade (20) is arranged on the handle (10) to cover the handle (10) and the camera channel (15). Further, the display unit (30) is provided for better visibility of the display screen (34) to visualise the path of the endotracheal tube.

Abstract: The present invention provides a video laryngoscope (100) to perform the intubation process. The video laryngoscope (100) includes a handle (10), a blade (20), a display unit (30), and an attachment assembly (25). The handle (10) includes a camera housing (16) with an image sensor (161) and a light source (162) arranged therein. The image sensor (161) is attached to the handle (10) through a camera channel (15) to visualise the path of the endotracheal tube. The camera housing (16) has a deflector (18) to avoid the blurry and distorted visuals generated due to the scattering of the light from the light source (162). The blade (20) is arranged on the handle (10) to cover the handle (10) and the camera channel (15). Further, the display unit (30) is provided for better visibility of the display screen (34) to visualise the path of the endotracheal tube.

Abstract: The present invention provides a video laryngoscope (100) to perform the intubation process. The video laryngoscope (100) includes a handle (10), a blade (20), a display unit (30), and an attachment assembly (25). The handle (10) includes a camera housing (16) with an image sensor (161) and a light source (162) arranged therein. The image sensor (161) is attached to the handle (10) through a camera channel (15) to visualise the path of the endotracheal tube. The camera housing (16) has a deflector (18) to avoid the blurry and distorted visuals generated due to the scattering of the light from the light source (162). The blade (20) is arranged on the handle (10) to cover the handle (10) and the camera channel (15). Further, the display unit (30) is provided for better visibility of the display screen (34) to visualise the path of the endotracheal tube.

Abstract: The present invention provides a video laryngoscope (100) to perform the intubation process. The video laryngoscope (100) includes a handle (10), a blade (20), a display unit (30), and an attachment assembly (25). The handle (10) includes a camera housing (16) with an image sensor (161) and a light source (162) arranged therein. The image sensor (161) is attached to the handle (10) through a camera channel (15) to visualise the path of the endotracheal tube. The camera housing (16) has a deflector (18) to avoid the blurry and distorted visuals generated due to the scattering of the light from the light source (162). The blade (20) is arranged on 10 the handle (10) to cover the handle (10) and the camera channel (15). Further, the display unit (30) is provided for better visibility of the display screen (34) to visualise the path of the endotracheal tube.

Abstract: A text reconstruction system for reconstructing a primary text data is provided. A voice input signal of a user is converted into an input text data by a speech recognition module. A text classifier module generates one or more tokens and adds the tokens into a word bag corresponding to the user. A text identifier module generates a text corpus based on the input text data. A user profile builder module creates a user profile based on the word bag, the input text data, and the text corpus. A decision module determines, based on the word bag, whether the primary data is to be reconstructed and reconstructs the primary text data to generate a personalized text data based on the user profile.

Abstract: The present invention relates to a process according to Scheme 1 for the preparation of microbiocidal 5-trifluoromethyl-1,2,4-oxadiazole derivatives of formula (I) suitable for use, e.g., as active ingredients, which have microbiocidal activity, in particular, fungicidal activity.

Abstract: Techniques are disclosed for hyper-segmented personalization using machine learning-based models in an information processing system. For example, a method obtains one or more product experience recommendation data sets respectively from one or more product entities, and one or more purchase experience recommendation data sets respectively from one or more commerce entities. The method applies a federated ensemble-based machine learning algorithm to at least one of the one or more purchase experience recommendation data sets and at least one of the one or more product experience recommendation data sets to generate a personalized model, and causes adaptation of a purchasing interface of at least one of the one or more commerce entities with respect to a given user based on the personalized model.

Abstract: Methods, apparatus, and processor-readable storage media for automatically prioritizing supply chain-related demand using artificial intelligence techniques are provided herein.

Abstract: Requests to create entries in a hardware nexthop table can be delayed so that table entry creation rate can be dampened to reduce the occurrence of table overflow under certain transient conditions. When table utilization exceeds a threshold, received creation requests can be buffered instead of being processed right away. When table utilization falls below the threshold, received creation requests can be processed immediately without being buffered. Buffered creation requests can be periodically drained.

Abstract: In one implementation, a system for generating composites performance is disclosed. The system may access designated-value account information associated with designated-value accounts, each with a respective rate of return. The system parses the designated-value account information into sets of strategy-based designated-value accounts. The system may concurrently parse with a first processor, a first set of strategy-based designated-value accounts and with a second processor, a second set of strategy-based designated-value accounts by applying logical rulesets to determine membership eligibility in the sets of strategy-based designated-value accounts. The system may generate composites performance by applying statistical analysis to the sets of strategy-based designated-value accounts based on the respective rate of return of each included designated-value account. The system may output the composites performance to indicate performance of the sets of strategy-based designated-value accounts.

Abstract: In one aspect, an example methodology implementing the disclosed techniques includes, by a product subscription service, receiving information regarding a hardware asset being returned at an end of a subscription and predicting, using a first machine learning (ML) model, whether the hardware asset has reached EOL. The method also includes, responsive to predicting that the hardware asset has reached EOL, creating, by the product subscription service, a work order to dispatch an eco-partner. The method may further include, by the product subscription service, responsive to predicting that the hardware asset has not reached EOL, predicting, using a second ML model, one or more new subscription orders matching the hardware asset and recommending the one or more matching new subscription orders as possible fits for the hardware asset.

Abstract: A system is provided for automatically generating electronic artifacts using extended functionality. In particular, the system may use a template-based process to automatically generate artifacts based on a defined set of parameters and/or variables. The system may further use one or more plugins which may provide extended functionality with respect to the artifact generation process. Accordingly, the artifact generation process may include initializing a parameter list based on application parameters and/or plugin parameters, processing the parameters, generating variables based on the parameters, and replacing variables in scheme template files with appropriate values (e.g., user supplied or plugin generated values) to output an artifact file to a predetermined location. In this way, the system provides a robust and efficient way to automatically generate artifacts.

Abstract: Techniques are disclosed for a multi-layer micro model analytics framework for analyzing or otherwise processing data. For example, a method comprises building two or more micro models respectively for two or more stages of a given process, wherein each micro model of the two or more micro models comprises a user interaction layer and a predictive learning layer that coordinate to train the micro model based on input to the user interaction layer and data accessible by the predictive learning layer for the corresponding stage of the two or more stages of the given process. The method then assembles the two or more micro models to perform analysis for the given process. In one non-limiting example, the given process is a new product introduction process and each micro model is built and trained to perform analytics for a specific lifecycle stage of the process.

Abstract: Methods, apparatus, and processor-readable storage media for temporal supply-related forecasting using artificial intelligence techniques are provided herein. An example computer-implemented method includes determining one or more forecasts pertaining to supply of at least one item by processing supply-related data using one or more artificial intelligence techniques; generating, based at least in part on the one or more forecasts, one or more temporal recommendations associated with one or more orders of at least one a portion of the at least one item; and performing one or more automated actions based at least in part on the one or more temporal recommendations.

Abstract: Techniques are disclosed for a multi-layer micro model analytics framework for analyzing or otherwise processing data. For example, a method comprises building two or more micro models respectively for two or more stages of a given process, wherein each micro model of the two or more micro models comprises a user interaction layer and a predictive learning layer that coordinate to train the micro model based on input to the user interaction layer and data accessible by the predictive learning layer for the corresponding stage of the two or more stages of the given process. The method then assembles the two or more micro models to perform analysis for the given process. In one non-limiting example, the given process is a new product introduction process and each micro model is built and trained to perform analytics for a specific lifecycle stage of the process.

Abstract: Disclosed are apparatuses, systems, and techniques that improve efficiency and quality of data streaming in time-sensitive network communications. The techniques include but are not limited to proactive replacement of packets in network communications that use forward error correction techniques. Proactive replacement of packets that have been lost or can potentially become lost reduces network latency and increases the number of timely communicated data messages.

Abstract: A system is provided for automatically generating electronic artifacts using extended functionality. In particular, the system may use a template-based process to automatically generate artifacts based on a defined set of parameters and/or variables. The system may further use one or more plugins which may provide extended functionality with respect to the artifact generation process. Accordingly, the artifact generation process may include initializing a parameter list based on application parameters and/or plugin parameters, processing the parameters, generating variables based on the parameters, and replacing variables in scheme template files with appropriate values (e.g., user supplied or plugin generated values) to output an artifact file to a predetermined location. In this way, the system provides a robust and efficient way to automatically generate artifacts.

Abstract: Techniques are disclosed for domain-driven intent-based feedback data analysis. For example, a method comprises obtaining a feedback data set, and classifying the feedback data set into at least one domain of a plurality of domains. The feedback data set is mapped to a domain data set corresponding to the at least one domain, and a root cause is computed for the feedback data set to enable one or more actions to be taken in response to the feedback data set based on the root cause. By way of further example, computing the root cause for the feedback data set may further comprise utilizing at least one computed intent attribute, at least one computed sentiment attribute, and the domain data set to compute a decision on the root cause for the feedback data set.

Abstract: A system is provided for automatically generating electronic artifacts using extended functionality. In particular, the system may use a template-based process to automatically generate artifacts based on a defined set of parameters and/or variables. The system may further use one or more plugins which may provide extended functionality with respect to the artifact generation process. Accordingly, the artifact generation process may include initializing a parameter list based on application parameters and/or plugin parameters, processing the parameters, generating variables based on the parameters, and replacing variables in scheme template files with appropriate values (e.g., user supplied or plugin generated values) to output an artifact file to a predetermined location. In this way, the system provides a robust and efficient way to automatically generate artifacts.