Abstract: A container system including a closeable container with at least one pouch in an interior space of the container, where the pouch includes a water-soluble film including a polyvinyl alcohol (PVOH) resin blend, and a perfume and organic solvent containing household care composition at least partially enclosed in a compartment by the water-soluble film.

Abstract: A security assessment scheduling tool uses a configuration file that is configurable via a user interface, to specify one or more elements of an application to be analyzed during the scoping process. Further, the security assessment scheduling tool may automatically schedule assessments for large numbers of applications using one or more constraining optimization techniques and/or via modeling the scheduling problem as an RCPSP problem. The security assessment scheduling tool processes the RCPSP problem for a defined period of time and then schedules remaining unscheduled applications within a specified time period thereby allowing the security assessment scheduling tool to schedule assessments of tens of thousands of applications.

Abstract: A laundry detergent composition containing an ethylene oxide-propylene oxide-ethylene oxide (EO/PO/EO) triblock copolymer and a lipase enzyme and use of an ethylene oxide-propylene oxide-ethylene oxide (EO/PO/EO) triblock copolymer and lipase enzyme in the laundry detergent composition.

Abstract: A mobile tower for transportation to and rapid deployment at remote sites where the mobile tower can be engaged with the ground, the mobile tower including an extendable and retractable tower secured to a mobile support structure including a frame having a plurality of rapidly deployable outriggers, wherein the tower includes three series of pivotally interconnected tower sections or segments, sections or segments of which engage with segments of each of the other series when the tower is assembled; the mobile tower including a plurality of guy wires secured between the extendable and retractable tower and the respective outriggers to stabilize the tower after the tower is assembled. The guy wires are preferably secured to the extendable and retractable tower at first and second connecting positions that are displaced from one another about an outer perimeter. Methods of deploying the mobile tower are also disclosed.

Abstract: Methods and switches are provided for communicating electronic messages between financial institutions. One example method includes receiving, at a first switch of a plurality of switches, an electronic message for a transaction, where the electronic message includes a unique identifier for the transaction, and identifying, by the first switch, one of the plurality of switches to process the electronic message based on the unique identifier. The method also includes, in response to the first switch being the identified one of the plurality of switches, processing, by the first switch, the electronic message and, in response to a second switch of the plurality of switches being the identified one of the plurality of switches, forwarding, by the first switch, the electronic message to the second switch for processing.

Abstract: A computer system and method are provided for training a machine learning system to perform a classification task by classifying input data into one of a plurality of classes. The system is configured to: receive per class training data from which per class representations can be derived, wherein each class is described by multiple representations; process the training data to form, for at least one class, a first proxy for a relatively global portion of an item of training data and multiple proxies for distinct relatively local portions of the item of training data, each proxy corresponding to a representation of the data belonging to that class.

Abstract: A device for categorising regions in images is disclosed. The device comprising: an input for receiving a first set of images, and defining one or more regions of for each image of the first set of images and a categorisation for the one or more regions, and a second set of images, and a categorisation for each image of the second set; and a processor configured to train a first machine learning algorithm to categorise features in images by: processing the images of the first and second set using the first algorithm to estimate feature regions in the images and a categorisation for each of the feature regions, and training the first algorithm in dependence on the categorisations received for the images of the first and second sets.

Abstract: An image processing apparatus and a method are provided. The apparatus comprises a plurality of processing modules configured to operate in series to refine a raw image captured by a camera, the modules comprising a first module and a second module, each of which independently implements a respective trained artificial intelligence model, wherein: the first module implements an image transformation operation that performs an operation from the set comprising: (i) an essentially pixel-level operation that increases sharpness of an image input to the module, (ii) an essentially pixel-level operation that decreases sharpness of an image input to the module, (iii) an essentially pixel-block-level operation on an image input to the module; and the second module as a whole implements a different operation from the said set.

Abstract: An approach is provided in which the approach generates anomaly score variables using multiple unsupervised models based on a set of data records. The approach normalizes the anomaly score variables into multiple normalized variables, and constructs at least one interaction based on a first one of the normalized variables and a second one of the normalized variables. The first normalized variable corresponds to a first one of the anomaly score variables and the second normalized variable corresponds to a second one of the anomaly score variables. The approach detects a set of anomalies based on the at least one interaction and transmits the set of anomalies to a user.

Abstract: A computer implemented method for machine learning model training. A number of processor units creates a cluster model comprising labeled samples and unlabeled samples. The number of processor units identifies cluster information for the labeled samples from the cluster model. The number of processor units adds a set of new features to a set of original features for the labeled samples using the cluster information to form an extended set of features for the labeled samples, wherein the labeled samples with the set of original features and the set of new features form a training data set for training a machine learning model.

Abstract: A method includes training a plurality of different types of machine learning models using a training dataset to produce a set of trained machine learning models and determining a lift of each trained machine learning model in the set of trained machine learning models using a validation dataset. The method also includes selecting a trained machine learning model from the set of trained machine learning models that has a highest lift of the set of trained machine learning models and predicting a likelihood that a person will perform an action by applying the selected trained machine learning model to data about the person.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for integrating one or more light switch panels into a monitoring system. The methods, systems, and apparatus include actions of determining to communicate a non-traditional file to a z-wave capable device, communicate a first data packet to the z-wave capable device, based on communicating the first data packet to the z-wave capable device, alter a schedule command class payload of a second data packet to include a first portion of the non-traditional file, alter a schedule command class payload of a third data packet to include a second portion of the non-traditional file, and alter a schedule command class payload of a fourth data packet to include a third portion of the non-traditional file, and communicate, to the z-wave capable device, the altered second data packet, the altered third data packet, and the altered fourth data packet.

Abstract: A gateway is provided for controlling transfer of electronic messages between a financial institution and a transaction processing system comprising a plurality of switches. The gateway includes communication circuitry operable to receive an electronic message issued by the financial institution and processing circuitry operable to determine whether the electronic message includes enough information for a switch of the transaction processing system to process the electronic message. In response to the electronic message including enough information, the communication circuitry is further operable to transmit the electronic message over a data communications network for storage in a message queue unit associated with the transaction processing system for subsequent processing by the switch. In response to the electronic message not including enough information, the communication circuitry is operable to return the electronic message to the financial institution.

Abstract: A cutting assembly and a cutter are provided, wherein, in an apparatus for additive manufacturing with a filament, a deposition head has a body and an applicator for fixing a run of filament to a surface at a deposition location ending at a deposition termination point. The cutter assembly has a fixation element for fixing the cutter assembly relative to the deposition head, and a cutter movable relative to the fixation element. The deposition head has a deposition termination configuration and a cutting configuration, and after fixing the run of filament, the deposition head transitions from the deposition termination configuration to the cutting configuration. The cutter cuts the filament only when the deposition head is in the cutting configuration.

Abstract: A computer-implemented method, system and computer program product for improving prediction accuracy in machine learning techniques. A teacher model is constructed, where the teacher model generates a weight for each data case. The current student model is then trained using training data and the weights generated by the teacher model. After training the current student model, the current student model generates state features, which are used by the teacher model to generate new weights. A candidate student model is then trained using training data and these new weights. A reward is generated by comparing the current student model with the candidate student model using training and testing data, which is used to update the teacher model if a stopping rule has not been satisfied. Upon a stopping rule being satisfied, the weights generated by the teacher model are deemed to be the “optimal” weights which are returned to the user.

Abstract: A device for estimating a scene illumination color for a source image is configured to: determine a set of candidate illuminants and for each of the candidate illuminants, determine a respective correction of the source image; for each of the candidate illuminants, apply the respective correction to the source image to form a corresponding set of corrected images; for each corrected image from the set of corrected images, implement a trained data-driven model to estimate a respective probability of achromaticity of the respective corrected image; and based on the estimated probabilities of achromaticity for the set of corrected images, obtain a final estimate of the scene illumination color for the source image. This approach allows for the evaluation of multiple candidate illuminates to determine an estimate of the scene illumination color.

Abstract: A computer-implemented method, system and computer program product for improving prediction accuracy in machine learning techniques. A teacher model is constructed, where the teacher model generates a weight for each data case. The current student model is then trained using training data and the weights generated by the teacher model. After training the current student model, the current student model generates state features, which are used by the teacher model to generate new weights. A candidate student model is then trained using training data and these new weights. A reward is generated by comparing the current student model with the candidate student model using training and testing data, which is used to update the teacher model if a stopping rule has not been satisfied. Upon a stopping rule being satisfied, the weights generated by the teacher model are deemed to be the “optimal” weights which are returned to the user.

Abstract: A gyroplane employing torque compensated main rotor and hybrid power train is disclosed. The invention incorporates a torque-compensated main rotor system with a common Collective pitch control, which can be driven transiently during flight to allow Vertical Take-Off, Landing and Hovering (VTOLH) flight operations. Torque compensation is via a coaxial counter-rotating (CACR) rotor system, or alternatively using a single rotor in conjunction with one or more electronically-controlled, fixed-pitch, thruster motors. The use of electric motors for lift and torque compensation facilitates electronic and potentially autonomous control of all phases of vertical flight.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for integrating one or more light switch panels into a monitoring system. The methods, systems, and apparatus include actions of determining to communicate a non-traditional file to a z-wave capable device, communicate a first data packet to the z-wave capable device, based on communicating the first data packet to the z-wave capable device, alter a schedule command class payload of a second data packet to include a first portion of the non-traditional file, alter a schedule command class payload of a third data packet to include a second portion of the non-traditional file, and alter a schedule command class payload of a fourth data packet to include a third portion of the non-traditional file, and communicate, to the z-wave capable device, the altered second data packet, the altered third data packet, and the altered fourth data packet.

Abstract: A system includes a PTO device that selectively couples to a driveline of a vehicle, a motor/generator electrically coupled to an electrical power storage system, and a shared load selectively powered by one of the driveline or the motor/generator. The PTO device further includes a coupling actuator that couples the shared load to the motor/generator at a first selected ratio in a first position, and couples the shared load to the driveline at a second selected ratio in a second position.