Abstract: Methods and systems for dynamically updating machine learning models that provide conversational responses through the use of a configuration file that defines modifications and changes to the machine learning model are disclosed. For example, the configuration file may be used to define an expected behavior and required attributes for instituting modifications and changes (e.g., via a mutation algorithm) to the machine learning model.

Abstract: A track rail fastening system includes a direct fixation fastener assembly having a direct fixation fastener, and a laterally elongated support block. Fastener holes for receiving fastener-clamping fasteners, and fastener holes for receiving bracket-clamping fasteners, are formed in the support block. The respective sets of fastener holes are arranged in different anchor patterns. Fastener-clamping fasteners are received in one of the sets of fastener holes and claim direct fixation fastener to the support block. Bracket-clamping fasteners clamp a third-rail support bracket to the support block, and are received in one of the sets of fastener holes. The third-rail support bracket is cantilevered to the support block.

Abstract: An assembler system for manufacturing vapor-generating articles may include a rotatable assembly drum including an outer face and a flute in the outer face. The flute is structured and arranged to hold a first section and a second section of the vapor-generating article. The system also includes a first mechanism that translates the first section relative to the second section while the first section and the second section are in the flute. The system additionally includes a second mechanism that rotates the first section relative to the second section while the first section and the second section are in the flute. The translating and the rotating connect the first section to the second section to form the vapor-generating article.

Abstract: This disclosure relates generally to optimizing markdown price and, more particularly, to a method and a system for optimizing E-commerce markdown price based on contextual bandit technique. E-commerce and retail industries employ several strategies to boost business, of which markdown pricing is popular. The online markdown pricing problem is particularly challenging due to the high variability in demand. The existing state-of-art CB based techniques to optimize the markdown price, are designed to either clear off maximum inventory or as a revenue maximization problem and do not explicitly consider contextual features.

Abstract: There is a need for design and implementation of interfaces for providing user-friendly feedback while creating and updating compliant passwords. This disclosure relates to a method of creating compliant password by in-place feedback to a password composition policy (PCP). A policy-enabled-virtual keyboard (PKBD) receives input from a user and is processed based on parameters associated with the PCP to identify accessible and inaccessible keys on the PKBD with in-place feedback. The in-place feedback is provided to highlight accessible keys of the PKBD for the user, if class associated with character, or mandated number of characters by the PCP are received are covered. Alternatively, the keys of the PKBD are disabled for access to the user by validating if class associated with character received are not covered, and a deviation of the parameters. A compliant password is created based on the PCP by providing in-place feedback for a resultant validation.

Abstract: A heater system for a non-combustible aerosol-generating device includes a heater element and a fuse element. The heater element has a heating region, a first terminal and a second terminal. The fuse element is electrically connected between the first terminal and the second terminal in parallel with the heater element. The fuse element has a region configured to induce a localized hot spot to cause the fuse element to open circuit in response to power applied between the first terminal and the second terminal.

Abstract: Methods and systems are described herein for determining data quality using data reconstruction models. The system receives a dataset including entries and features and generates a machine learning model for each feature of the dataset. Each model may be trained to generate predictions for a corresponding feature based on other features of the dataset. The system may input, into each model, values of the other features to obtain prediction values for the corresponding feature. For a subset of entries for which a difference between the predicted and actual values of the corresponding feature satisfies a threshold, the system may determine relative impacts of the other features on the corresponding feature. The system may then transmit, to a user, a subset of the other features having relative impacts that meet a feature impact threshold.

Abstract: Systems and methods for generating communications based on user account activity data are described herein. For example, the system may obtain an input activity log and generate an activity log transformation. The system may input the activity log transformation into a vector encoding model to obtain a first output vector encoding. The system may input the first output vector encoding into a contrastive machine learning model to obtain a first matching vector encoding. The system may access a first plurality of vector encodings from a communication database. Based on comparing each vector encoding in the first plurality of vector encodings with the first matching vector encoding, the system may generate the matching communication.

Abstract: Optimized chimeric antigen receptors (CARs) targeting glypican-3 (GPC3) and having a 12-amino acid hinge region derived from human IgG4 are described. The optimized CARs also include a transmembrane domain from either CD8 or CD28, an intracellular co-stimulatory domain and an intracellular signaling domain. Immune cells or induced pluripotent stem cells expressing the optimized CARs can be used to treat GPC3-positive solid tumors.

Abstract: Disclosed herein is a method for training a system to segment a computerized tomography (CT) image, comprising receiving a plurality of data groups, each group comprising an image pair comprising a CT image, a magnetic resonance (MR) image and a segmentation mask for the MR image; training a first generator of a first generative adversarial network (GAN) using the image pairs, to generate a synthetic MR image from a CT image based on relationships between image features of the CT image and MR image in each image pair; and training a second generator of a second GAN to generate a synthetic mask for the synthetic MR image based on relationships between features of the synthetic MR image and segmentation mask of each data group.

Abstract: A call processing system and method for processing calls from high volume callers. A frequency of call activity is monitored for callers to determine reception of a call from a high frequency caller. When a call is received from such a caller, provided is information predicted to be requested from the caller prior to the caller being voice connected to a company representative. The retrieved information is then provided to a company representative prior to the caller being voice connected with a company representative as to expedite the call. Additionally, a customized message for the high frequency caller may be generated prior to the caller being voice connected with a company representative whereby the customized message contains information predicted to be responsive to a predicted inquiry from the determined high frequency caller to mitigate the need to connect the caller to a company representative.

Abstract: A change tracer system and method are configured to trace changes in applied computer technology in a computing system. The change tracer system comprises a harvest system receiving current change data, change storage storing the current change data and historic change data, a comparator system comparing the current change data with the historic change data and determining the change from the comparison, and an output system outputting a report indicating the change. The method implements the system.

Abstract: An embodiment of the present invention may enable editing and deployment of software by including in an application container editable source code used to produce an application, and tools to edit and build the application, such as a code editor and a build tool to convert the source code to the executable application. The container may include an executable application which may execute in the environment on which the container is saved. A server in the container may control execution of the executable application and build the executable application. A remote user computer may communicate with the code editor to edit the source code, which in its updated version may be built to produce an updated version of the executable application. The server may stop execution of the existing executable application, and start execution of the updated version of the executable application.

Abstract: Classification of images is inherently a semi-supervised classification problem. Often, the labeled pixels and the unlabeled pixels in the image may have different distribution. Hence classification accuracy of such images is affected. The present disclosure proposes an umbrella framework for semi-supervised learning that considers the domains shifts in labeled and unlabeled pixels. The method proposed a two way optimization solution using deep learning models based on spectral features, spatial features, and fused spectral-spatial features. The model is trained in such a way that it is not only trained on the correct class of pixel but also on the source category of the pixel, for example, labeled pixel or unlabeled pixel. The error in the pixel class is minimized, whereas the error in the source category is encouraged simultaneously.

Abstract: A server computer receives from a resource provider device transaction data, a first set of wireless communication signals available to the resource provider device, a second set of wireless communication signals available to the resource provider device, and a sound level detected by the resource provider device. The server computer retrieves from a user device a first set of wireless communication signals available to the user device, a second set of wireless communication signals available to the user device, and a sound level detected by the user device. The server computer computes a score based on the first sets of wireless communication signals, the second sets of wireless communication signals, and the detected sound levels. The server computer transmits to an authorization computer the transaction data and the score, thereby causing the transaction to be processed or terminated based on the transaction data and the score.

Abstract: Methods and systems are described for generating dynamic interface options using machine learning models. The dynamic interface options may be generated in real time and reflect the likely goals and/or intents of a user. The machine learning model may provide these features by interpreting multi-modal feature inputs. For example, the machine learning model may include a first machine learning model, wherein the first machine learning model comprises a convolutional neural network, and a second machine learning model, wherein the second machine learning model performs a Weight of Evidence (WOE) analysis.

Abstract: Methods and systems are described herein for processing electronic messages. A processing system may be used to facilitate the processing. The system may receive a plurality of electronic messages associated with a user and may input electronic messages into a machine learning model to obtain electronic messages that contain authorization packages for entities, wherein the machine learning model is trained to identify electronic messages that contain authorization packages. The system may determine based on the electronic messages an authorization package comprising a token identifier, and entity identification data identifying an entity. The system may determine an application programming interface for communicating with an entity device and user identification data used by the user to access the entity device. The system may then transmit a command for executing a first operation at the entity device, wherein the command includes the user identification data and the authorization package.

Abstract: A device may receive a uniform resource locator (URL) and encrypted data. The device may download a first application from an application server based on the URL. The device may download and execute the first application. The first application may receive the encrypted data.

Abstract: The aerosol-generating device includes a reservoir configured to hold an aerosol-forming substrate, an aerosol generator configured to receive the aerosol-forming substrate from the reservoir, a wick configured to transfer the aerosol-forming substrate from the reservoir to the aerosol generator, a tilt sensor configured to sense an angle of orientation value of the reservoir, and electric circuitry including at least one processor configured to determine a depletion value of the aerosol-forming substrate in the reservoir based on the angle of orientation value, while the aerosol generator is in operational use.

Abstract: A method and related system of operations include obtaining, from a client computing device, a request comprising a request header field that is populated with a first domain name and updating the request by modifying the request header field to comprise a second domain name. The method further includes sending the updated request to a server, receiving a response comprising a response header, and updating the response by modifying a response header field of the response header to indicate the first domain name as an origin domain of the response. The method further includes sending the updated response to the client computing device.