Abstract: Methods and server systems for computing fraud risk scores for various merchants associated with an acquirer described herein. The method performed by a server system includes accessing merchant-related transaction data including merchant-related transaction indicators associated with a merchant from a transaction database. Method includes generating a merchant-related transaction features based on the merchant-related indicators. Method includes generating via risk prediction models, for a payment transaction with the merchant, merchant health and compliance risk scores, merchant terminal risk scores, merchant chargeback risk scores, and merchant activity risk scores based on the merchant-related transaction features. Method includes facilitating transmission of a notification message to an acquirer server associated with the merchant.

Abstract: Systems and computer-implemented methods are described for modeling card inactivity. For example, hierarchical modeling may be used in which a first level classifier may be trained and validated to predict whether a card will be inactive. For cards predicted to become inactive by the first level classifier, a second level classifier may be trained and validated to predict when the card will become inactive. The first level classifier may include a binary classifier that generates two probabilities that respectively predict that the card will and will not become inactive. The second level classifier may include a multi-class classifier that generates a first probability that the card will become inactive at a first time period (such as one or more months in the future) and a second probability that the card will become inactive at a second time period. The multi-class classifier may generate other probabilities corresponding to other time periods.

Abstract: The system can include a set of joints, a controller, and a model engine; and can optionally include a support structure and an end effector. Joints can include: a motor, a transmission mechanism, an input sensor, and an output sensor. The system can enable articulation of the plurality of joints.

Abstract: A cloud platform trains a machine-learned entity matching model that generates predictions on whether a pair of electronic records refer to a same entity. In one embodiment, the entity matching model is configured as a transformer architecture. In one instance, the entity matching model is trained using a combination of a first loss and a second loss. The first loss indicates a difference between an entity matching prediction for a training instance and a respective match label for the training instance. The second loss indicates a difference between a set of named-entity recognition (NER) predictions for the training instance and the set of NER labels for the tokens of the training instance.

Abstract: A growth predictor includes a monitor, a prediction engine, and a prioritization engine. The monitor receives or generates first information of a network already identified as a candidate money laundering (ML) network by an anti-money-laundering system. The prediction engine predicts second information indicative of a growth size of the ML network at a future time based on the first information. The prediction engine executes one or more predictive models to generate the second information indicative of growth size based on the first information, which indicates one or more changes that have occurred in the candidate ML network over a past period of time. The prioritization engine determines a priority of the candidate ML network based on the second information.

Abstract: The present disclosure describes an organic-inorganic metal-halide-based semiconducting material that melts at lower temperatures compared to conventional inorganic semiconductors. The hybrid material is structurally engineered to easily access both crystalline and amorphous glassy states, with each state offering distinct physical properties.

Abstract: A hierarchical neural network for predicting out of stock products comprises an input layer that receives data from data sources that store disparate datasets having different levels of attribute detail pertaining to products for sale in stores of a retailer. A first level of neural networks processes the data from the data sources into respective learned intermediate vector representations. A second level comprises a concatenate layer that concatenates the learned intermediate vector representations from the second level into a combined vector representation. A third level comprises a feed forward network that receives the combined vector representation and outputs to the retailer an out of stock probability indicating which store and product combinations are likely to have out of stock products over a predetermined timeframe.

Abstract: A method and system for synthetic data generation are provided that receive a schema configuration file in a synthetic data set request from a client application, create a set of worker processes to generate the synthetic data set based on the schema configuration file, upload the generated synthetic data to an analytics platform, and enable the client application to utilize the generated synthetic data in prediction models for the analytics platform.

Abstract: The present disclosure describes an organic-inorganic metal-halide-based semiconducting material that melts at lower temperatures compared to conventional inorganic semiconductors. The hybrid material is structurally engineered to easily access both crystalline and amorphous glassy states, with each state offering distinct physical properties.

Abstract: Systems and computer-implemented methods are described for modeling card inactivity. For example, hierarchical modeling may be used in which a first level classifier may be trained and validated to predict whether a card will be inactive. For cards predicted to become inactive by the first level classifier, a second level classifier may be trained and validated to predict when the card will become inactive. The first level classifier may include a binary classifier that generates two probabilities that respectively predict that the card will and will not become inactive. The second level classifier may include a multi-class classifier that generates a first probability that the card will become inactive at a first time period (such as one or more months in the future) and a second probability that the card will become inactive at a second time period. The multi-class classifier may generate other probabilities corresponding to other time periods.

Abstract: A telescopic differential screw mechanism based 3-DOF Parallel Manipulator system to enable differential length and omnidirectional bending is provided. The telescopic differential screw mechanism based 3-DOF Parallel Manipulator system includes a first circular rotating plate 102, a second circular rotating plate 104, three or more telescopic screw assemblies 106A-C and three or more actuators 108A-C. Each telescopic screw assembly 106 includes a pair of master screws 110, a pair of successive screws 112 and a universal joint 116. The three or more telescopic screw assemblies 106A-C are actuated differentially using the three or more actuators 108A-C to achieve omnidirectional bending with high angular rotations in a range of 0 to 75 degree.

Abstract: A multidirectional locomotive module with omnidirectional bending that is compliant along multiple axis is provided. The locomotive module includes, (A) a first part that includes (i) one or more circular rigid components which are coupled using a two degree of freedom joint, (ii) bending actuator that actuates the two degree of freedom joint enabling bending of the multidirectional locomotive module to an angle ranging from 0 to 90 degrees about a Z-axis in a direction to achieve surface compliance with an external surface, and (B) a second part that is elongated in shape with circular cross-section along a surface length and hemispherical in shape an end portion with a surface that is formed by a power transmission sprocket chain and an arrangement of curved components enabling sideways rolling of the multidirectional locomotive module, also enabling wheeled and legged locomotion in vertical position.

Abstract: A multidirectional locomotive module with omnidirectional bending that is compliant along multiple axis is provided.

Abstract: A telescopic differential screw mechanism based 3-DOF Parallel Manipulator system to enable differential length and omnidirectional bending is provided. The telescopic differential screw mechanism based 3-DOF Parallel Manipulator system includes a first circular rotating plate 102, a second circular rotating plate 104, three or more telescopic screw assemblies 106A-C and three or more actuators 108A-C. Each telescopic screw assembly 106 includes a pair of master screws 110, a pair of successive screws 112 and a universal joint 116. The three or more telescopic screw assemblies 106A-C are actuated differentially using the three or more actuators 108A-C to achieve omnidirectional bending with high angular rotations in a range of 0 to 75 degree.