Abstract: A door system comprises a door, the door including a latch assembly configured to latch the door to a door frame to maintain the door in a closed position and to unlatch to allow the door to open to an opened position. A foot pedal is operatively connected to unlatch the latch assembly upon actuation by a user's foot. In certain embodiments, a handle can be operatively connected to unlatch the latch assembly upon actuation a user. The door system further includes the door frame and set of hinges operatively connecting the door to the door frame.

Abstract: A touchless system for an aircraft cabin is disclosed. The system includes machine-readable codes placed on passenger seats and other aircraft surfaces that may be scanned and linked to cabin control systems through an application installed on personal portable electronic devices. The system also includes a communication system linked to the personal portable electronic devices via the application and linked to the cabin control systems that facilitates the control of one or more control systems by the personal portable electronic device. One of the cabin control systems is configured as an overhead storage container configured with a gesture sensing system, allowing the storage lid to be opened through specific gestures.

Abstract: A system comprises a door including a latch assembly configured to latch the door to a doorframe in a closed position of the door. An latch actuator is operatively connected to the latch assembly to drive the latch assembly to latch and unlatch the door. A exterior touchless sensor operatively connected to the actuator to cause the actuator to unlatch the latch assembly upon receipt of touchless input from a user.

Abstract: A disinfection system is disclosed. The disinfection system includes a base, a first arm mechanically coupled to the base at a first joint, a second arm mechanically coupled to the first arm at a second joint, and an emission module mechanically coupled to the second arm at a third joint. The emission module may include a third arm that includes one or more scanners configured to emit electromagnetic energy further configured to disinfect a first surface. The emission module may also include the one or more scanners, focusing lens, a lens frame, and a rotary actuator, wherein the rotary actuator is configured to align one of the one or more scanners with the focusing lens to produce a narrow electromagnetic beam, or position the focusing lens out of alignment with the one of the one or more scanners to produce a broad electromagnetic beam.

Abstract: The present exemplary embodiment discloses a method and system for utilizing machine learning and artificial intelligence to selecting an optimal conversion driver to convert a document into a printable form. The methods include receiving at least one user print request and at least one user submitted file associated with the user request, optimizing the conversion of a file by executing, by at least one computer processor, determining that format conversion is necessary for the file, identifying least one of a plurality of file conversion drivers as optimal for converting the file, causing the optimal file conversion driver to convert the file into a printer readable format, and printing the converted file. The conversion drivers may be selected from remote or local conversion engines. The machine learning employs artificial intelligence to select the optimal conversion path by analyzing the properties of the document submitted for conversion.

Abstract: A disinfection system is disclosed. The disinfection system includes a base, a first arm mechanically coupled to the base at a first joint, a second arm mechanically coupled to the first arm at a second joint, and an emission module mechanically coupled to the second arm at a third joint. The emission module may include a third arm that includes one or more scanners configured to emit electromagnetic energy further configured to disinfect a first surface. The emission module may also include the one or more scanners, focusing lens, a lens frame, and a rotary actuator, wherein the rotary actuator is configured to align one of the one or more scanners with the focusing lens to produce a narrow electromagnetic beam, or position the focusing lens out of alignment with the one of the one or more scanners to produce a broad electromagnetic beam.

Abstract: Methods and systems herein identify and redact personally identifiable information. A PII sensitivity detection framework includes multiple layers where each layer corresponds to a computer model. The framework analyzes data stored within different data tables and predicts whether a data column includes PII. The first layer corresponds to an artificial intelligence model that analyzes each column metadata and predicts a first score indicative of a likelihood of PII. The second layer corresponds to a rule-based computer model that uses various rules to determine a second score indicative of a likelihood of PII for each column. The third layer corresponds to a column content model that analyzes content of each column using various natural language processing techniques to generate a third score indicative of a likelihood of PII. The framework masks data being presented to a user based on the scores generated via execution of one or more of the layers.

Abstract: A method for generating an agricultural cut-point for an agricultural item includes capturing an image of the agricultural item, generating a depth estimation of the agricultural item, segmenting the image of the agricultural item to generate a segmented image that identifies different segments of the agricultural item, detecting an agricultural feature of the agricultural item based on the image of the agricultural item, generating a two-dimensional cut-point based on the segmented image and the agricultural feature, and generating a three-dimensional cut-point based on the two-dimensional cut-point and the depth estimation of the agricultural item.

Abstract: One or more structural equations modeling a physical process over time may be sampled using simulated parameter values to generate input data signal values. A noise generator may be applied to the input data signal values to generate noise values. The noise values and the input data signal values may be combined to determined noisy data signal values. These noisy data signal values may in turn be used in combination with one or more states to train a prediction model.

Abstract: In a training phase, training data may be used to train a supervised machine learning prediction model and an unsupervised machine learning segmentation model. Then, in a testing phase, the supervised machine learning prediction model may be used to predict a target outcome for a test data observation. Also, the unsupervised machine learning segmentation model may be used to evaluate the novelty of the test data observation relative to the training data.

Abstract: Techniques and mechanisms described herein provide automated processes for integrating supervised and unsupervised classification results of a test data observation with training data observations in a feature space. Novelty of the test data observation relative to the feature space may be measured using one or more distance metrics. Novelty of a test data observation may be further refined by comparison to a confusion matrix segment determined based on a supervised model. Based on the novelty information, the supervised and/or unsupervised models may be updated, for instance via incremental or batch training.

Abstract: The present invention relates to methods and pharmaceutical compositions for treating heart failure in a pediatric human patient comprising administration to said patient of a therapeutically effective amount or a prophylactically effective amount of a combination of a therapeutic agent blocking the angiotensin receptor and a therapeutic agent inhibiting the NEP enzyme, in particular of a combination of sacubitril and valsartan in a pharmaceutically acceptable form and in a 1:1 molar ratio.

Abstract: Methods and systems identify and redact PII. A PII sensitivity detection framework includes multiple layers where each layer corresponds to a model. The framework analyzes data stored within different data tables and predicts whether a data column includes PII. The first layer corresponds to an AI model that analyzes each column metadata and predicts a first score indicative of a first likelihood of PII existence. The second layer corresponds to a rule-based model that uses various rules to determine a second score indicative of a second likelihood of PII existence for each column. The third layer corresponds to a column content model that analyzes content of each column using various natural language processing techniques to generate a third score indicative of a third likelihood of PII existence. The framework masks data presented to a user based on the scores generated via execution of one or more of the layers.

Abstract: One or more structural equations modeling a physical process over time may be sampled using simulated parameter values to generate input data signal values. A noise generator may be applied to the input data signal values to generate noise values. The noise values and the input data signal values may be combined to determined noisy data signal values. These noisy data signal values may in turn be used in combination with one or more states to train a prediction model.

Abstract: The present invention discloses an adsorbent composition for removing halogen-containing contaminants such as hydrogen chloride from gas streams and a process for its formation. The adsorbent composition comprises an active metal component and a carrier or binder. The active metal component is selected from the group consisting of sodium, potassium, magnesium, calcium and barium and the carrier/binder is selected from a group of clay materials like sepiolite, montmorillonite, kaolin or attapulgite.

Abstract: A video player for playing a video stream that receives a master playlist identifying at least one variant playlist identifying a video file encoded as a series of video frames that when decoded provide the video stream. The video player based upon a configuration tag in the master play list selectively determining whether the video file is to be processed in a trusted execution environment. The trusted execution environment of the video player selectively includes at least one of (i) hack one, only hack one; (ii) output and link protection; (iii) hardware root of trust; and (iv) forensic watermarking, and decrypts and/or decodes the video stream in such an environment.

Abstract: Described embodiments provide systems and methods for remapping connections to tunnels selected based on a security level of the communications. A first network device may be in communication with a second network device via a plurality of communication tunnels. The plurality of communication tunnels may include an encrypted communication tunnel and an unencrypted communication tunnel. The first network device may receive a packet, the packet including header information and a payload. The first network device may determine whether the received packet is encrypted to meet a threshold level of security. The first network device may, responsive to determining that the packet is to meet the threshold level of security, communicate an identifier of the payload and the header information to the second network device via the encrypted communication tunnel, and communicate the payload to the second network device via the unencrypted communication tunnel.

Abstract: A feature data segment may be determined by applying a feature segmentation model to a test data observation. The feature segmentation model may be pre-trained via a plurality of training data observations and may divide the plurality of training data observations into a plurality of feature data segments. A predicted target value may be determined by applying to a test data observation a prediction model pre-trained via a plurality of training data observations. One or more distance metrics representing a respective distance between the test data observation and the feature data segment along one or more dimensions may be determined. The one or more distance metrics may be represented in a user interface. An updated prediction model and an updated feature segmentation model that both incorporate the test data observation and the training data observations may be determined based on user input.

Abstract: An organic flow battery having a positive electrode electrolyte containing organic compounds with extended conjugation and/or cyclic side chains is provided. The flow battery includes a positive electrode and a positive electrode electrolyte including first solvent and a first redox couple. The positive electrode electrolyte flows over and contacting the positive electrode. The first redox couple includes a first organic compound and a reduction product of the first organic compound. The flow battery also includes a negative electrode and a negative electrode electrolyte including a second solvent and a second redox couple. The negative electrode electrolyte flows g over and contacts the positive electrode. Typically, an ion exchange membrane is interposed between the positive electrode and the negative electrode Characteristically, the first organic compound resists crossover through the ion exchange membrane.

Abstract: Sustained release pharmaceutical dosage forms include a core containing at least one swellable, water soluble, pH independent polymer and a first water insoluble, pH independent polymer, and a permeable membrane coat containing a swellable, water soluble, pH independent polymer and a second water insoluble, pH independent polymer. The sustained release pharmaceutical dosage forms are free of osmagens and/or diluents and demonstrate similar release characteristics as compared to known sustained release formulations that contain osmagens and/or diluents. Additionally, the release profile for the sustained release pharmaceutical dosage forms is resistant to dose dumping in the presence of alcohol.