Abstract: A film composition including acid copolymer in a range of 1 to 10%, metallocene Linear low-density polyethylene (LLDPE) in a range of 5 to 15%, low density polyethylene (LDPE) in a range of 5 to 10%, anti-block masterbatch in the range of 0.5 to 1%, high density polyethylene (HDPE) in a range of 20 to 50%, plastomer in a range of 5 to 30% and slip additive in a range of 0.5 to 1%. Also disclosed is a film made from the film composition and to a laminate made from the film.

Abstract: A vehicle can include an assembly, a body, a first connection point, and a second connection point. The first connection point can be disposed on a surface of the body. The first connection point can receive a first element of the assembly. The first connection point can couple the first element with the body to provide structural support to at least one of the assembly or the body. The second connection point can be disposed on the surface of the body. The second connection point can be adjacent to the first connection point. The second connection point can receive a second element of the assembly that is configured to provide an electrical connection or a hydraulic connection between the body and the assembly.

Abstract: Methods, non-transitory computer readable media, apparatuses, and systems for image and depth map generation include receiving a prompt and encoding the prompt to obtain a guidance embedding. A machine learning model then generates an image and a depth map corresponding to the image based on the guidance embedding. The image and the depth map are each generated based on the guidance embedding.

Abstract: A system and associated methods provide solutions for reducing a volume of traffic through a multicast network attributed to repeated maintenance messages, which are required in order to maintain a multicast connection. The system configures provider edge devices to generate and send maintenance messages on behalf of members of a multicast group to establish and maintain the multicast connection and provides options for determining unknown locations of sources and/or subscribers, thereby reducing the overall volume of traffic transmitted over the multicast network.

Abstract: An artificial intelligence (AI)-based system for detecting malware in endpoint devices using a multi-source data fusion and method thereof are disclosed. The AI-based system collects at least one of: endpoint visibility data, publicly available information, and sandbox analysis data using the multi-source data fusion. By using the collected data, the AI-based system generates one or more numerical embeddings for at least one of: one or more files and one or more applications of each endpoint device using one or more AI models. The AI-based system is configured with the one or more AI models to generate one or more dynamic directed graphs based on the generated one or more numerical embeddings to compute a maliciousness risk score. The maliciousness risk score of at least one of the: one or more files and one or more applications is used for detecting the malware in the one or more endpoint devices.

Abstract: A data privacy system and method is disclosed. The method includes providing at least one processor, at least one memory device including computer-readable instructions, and at least one user device in communication with the at least one processor via a network connection. The at least one processor, upon execution of the computer-readable instructions, is configured to generate a predictive model during training of a machine learning program using a training data set including a personal data set of one or more users. The predictive model is configured to predict at least one predicted data privacy and/or data portability measure of at least one of the users. At least one quick response code embedded with data or a link to the data based upon the at least one predicted data privacy and/or data portability measure is generated to provide enhanced data privacy protection and data portability.

Abstract: A system and method for controlling the operating conditions of an electrolyzer unit receives input data associated with that unit from databases. The system applies a machine learning model on the input data and predicts an operating load condition of the electrolyzer unit for a first time period. The system also determines an operating temperature range for the electrolyzer unit for the first time period based on the operating load condition. The system determines the flow rate of a coolant from a cooling unit to the electrolyzer unit based on the determined operating temperature range and the predicted operating load condition. The system controls the cooling unit to modify the flow rate of the coolant to the electrolyzer unit based on the determined flow rate of the coolant to maintain the determined operating temperature range.

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: Methods and systems for object detection include generating a negative description for an input image of a road scene, based on a positive description of the input image, using a language model. A negative image is generated based on the input image and the negative description by replacing a portion of the input image that is described by the positive description with content that is described by the negative description using a generative image model. An object detection model is trained with the input image, the positive description, the negative description, and the negative image. An object is identified within a driving scene using the trained object detection model. A driving action is performed in a self-driving vehicle responsive to the identified object.

Abstract: Processes for monitoring downhole corrosion and directing operational plans using same. In some embodiments, the process can include acquiring a plurality of corrosion factors for at least one well. The process can also include acquiring a plurality of corrosion loss logs for the at least one well. The plurality of corrosion factors and the plurality of corrosion loss logs can be provided to a repository. The repository can be provided to a machine learning model to generate a corrosion prediction. At least the plurality of corrosion factors, the plurality of corrosion loss logs, and the corrosion prediction can be combined into a user dashboard. The user dashboard can be used to determine an operational plan for the at least one well. The determined operational plan for the at least one well can be carried out.

Abstract: The present disclosure relates to a composition comprising an active ingredient or drug for degenerative disorders, one or more plant-derived neuroprotective ingredients and one or more nutraceutically or pharmaceutically acceptable excipient and a method of preparing the same. The composition delivers the active ingredient or the drug to the predetermined location of the body with success.

Abstract: Systems and methods include extracting item parameters from images of items positioned at a POS system. Item parameters associated with each item when mapped into a feature vector for each item are indicative as to an identification of the item. The feature vectors are analyzed to determine whether item parameters when combined and mapped into the feature vectors match a corresponding feature vector stored in a database. The database stores different combinations of item parameters as mapped into different stored feature vectors with different stored feature vectors associated with different items thereby identifying each item based on each different combination of item parameters as mapped into each stored feature vector associated with each item. Each item positioned at the POS system is identified when the feature vectors associated with each item match a corresponding stored feature vector as stored in the database.

Abstract: Embodiments of the disclosure describe a method for transferring profile information associated with a physical subscriber identity module (pSIM) of a first electronic device to an embedded SIM (eSIM) of a second electronic device. The method includes creating an enhanced feature short message delivery point (EF-SMDP) file directory in a memory associated with the pSIM. The method includes obtaining eSIM identity (EID) and international mobile equipment identity (IMEI) associated with the eSIM by utilizing a first connection. The method includes sending a first request directly to a subscription manager data preparation (SMDP) server. The method includes obtaining an authorization from the SMDP server for the first request, the first electronic device stores the profile information in a virtual Local Profile Assistant (LPA) module. The method includes transferring the profile information from the virtual LPA module to the eSIM over the first connection.

Abstract: A gas-solid contacting system (100) with structured packing (108) is disclosed. The structured packing (108) comprises a gas header (102) with an inlet to receive a gas. A plurality of vertically aligned tubes (104) is fluidically connected to the gas header (102), wherein each vertically aligned tube (104) comprises openings (180) to distribute the gas at different heights in a radial direction. A structured packing element (106) is arranged on each vertically aligned tube (104), wherein the structured packing element (106) comprises one or more plates attached to the vertically aligned tube (104) to create a convoluted 3-dimensional flow path for smooth flow and radial distribution of a solid particulate stream.

Abstract: Methods, systems, and computer-readable media are disclosed herein combine randomization functionalities with the machine-learning prioritization of workflows for performance testing. In aspects, a primary workflow having a sequence of user interface steps is input. Testing workflows are generated that represent each variable position of unlocked steps in the sequence of the primary workflow while maintaining the sequential position of any locked steps. These testing workflows are then ingested to a machine learning model that identifies as subset of the testing workflows to prioritize over other. Specifically, testing workflows are prioritized that at least partially match sequence patterns in historical workflow data that is associated with vulnerable computer code. The subset is output and tested by testing engine to generate a report of any vulnerable computer code.

Abstract: One or more engine instances are executed on each host to form an engine cluster. A plurality of control instances are executed on a first set of hosts to form a control cluster and comprise a control instance leader and one or more control instance followers. In response to a first host indicating a failure of a neighbor host, a pair-wise focused investigation is initiated to check peer-to-peer connections between the first host and the neighbor host. In response to one or more additional hosts indicating failures of neighbor hosts while the pair-wise focused investigation is being performed, a wide investigation is performed to check connections between the control cluster and the plurality of hosts. One or more hosts are added to an eviction list and an eviction protocol is performed to evict the one or more hosts from the engine cluster using the eviction list.

Abstract: A system, e.g., a system on a chip (SoC) includes a first domain including a first processor configured to boot the system; a second domain including a processing subsystem having a second processor; and isolation circuitry between the first domain and the second domain During boot-up of the system, the first processor provides code to the second domain. When the code is executed by the second processor, it configures the processing subsystem as either a safety domain or as a general-purpose processing domain. The safety domain may an external safety domain or an internal safety domain.

Abstract: A method provides techniques for emoji management for electronic messaging. The message includes detecting, by a processor of an electronic device, selection of an emoji for sending within a message. A recipient is identified for the message. The method further includes determining one or more attributes that can be associated with the emoji, and retrieving at least one of a recipient emoji reception preference and a sender emoji transmission preference for the one or more attributes. The emoji is modified based on the one or more attributes corresponding to the at least one of the recipient emoji reception preference and the sender emoji transmission preference. The method continues with transmitting the message with the modified emoji to the recipient.

Abstract: Systems and methods include extracting item parameters from images of items positioned at a POS system. Item parameters associated with each item when mapped into a feature vector for each item are indicative as to an identification of the item. The feature vectors are analyzed to determine whether item parameters when combined and mapped into the feature vectors match a corresponding feature vector stored in a database. The database stores different combinations of item parameters as mapped into different stored feature vectors with different stored feature vectors associated with different items thereby identifying each item based on each different combination of item parameters as mapped into each stored feature vector associated with each item. Each item positioned at the POS system is identified when the feature vectors associated with each item match a corresponding stored feature vector as stored in the database.

Abstract: Presented herein are systems and methods for the employment of machine learning models for image processing. A method may include a capture of a video feed including image data of a document at a client device. The client device can provide the video feed to another computing device. The method can include, by the client device or the other computing device object recognition for recognizing a type of document and capturing an image exceeding a quality threshold of the document amongst the frames within the video feed. The method may further include the execution of other image processing operations on the image data to improve the quality of the image or features extracted therefrom. The method may further include anti-fraud detection or scoring operations to determine an amount of risk associated with the image data.