A gaming system, gaming device, and method using a deck of cards containing statistics and identifying information from real-world sports players is described. The cards in the deck may contain the player scores for a set of games or matches as well as other player-related information. The gaming system and device randomly generate a hand and randomly select one of the player's pre-determined scores for each of the cards. The user's score may be determined through a variety of methods utilizing the player scores on the cards in the user's hand. The outcome of the user's hand may be determined by matching the user's score with a pay table, or for a multi-user game, the outcome may be determined by finding the highest scorer among the participating users.

To prevent intent classifiers from potentially choosing intents that are ineligible for the current input due to policies, dynamic intent classification systems and methods are provided that dynamically control the possible set of intents using environment variables (also referred to as external variables). Associations between environment variables and ineligible intents, referred to as culling rules, are used.

A manufacturing process monitoring apparatus capable of determining a manufacturing process is anomaly, without requiring any threshold value for determining the as anomaly is provided. The manufacturing process monitoring apparatus includes a data conversion unit configured to convert process data of a manufacturing facility, a feature value analysis unit configured to analyze the converted data based on information on feature values, a data restoration unit configured to restore data for each of a plurality of categories based on the information on the feature values and information on the analyzed result, a similarity calculation unit configured to calculate a similarity for each of the plurality of categories based on the data used when being analyzed and the restored data, a category determination unit configured to determine a category of the data based on the similarity for each of the plurality of categories, a category classification unit configured to classify the category to which the process data belongs, and a process state diagnostic unit configured to diagnose a state of the manufacturing process based on a result of comparison between the determined category and the classified category.

A manufacturing process monitoring apparatus capable of determining a manufacturing process is anomaly, without requiring any threshold value for determining the as anomaly is provided. The manufacturing process monitoring apparatus includes a data conversion unit configured to convert process data of a manufacturing facility, a feature value analysis unit configured to analyze the converted data based on information on feature values, a data restoration unit configured to restore data for each of a plurality of categories based on the information on the feature values and information on the analyzed result, a similarity calculation unit configured to calculate a similarity for each of the plurality of categories based on the data used when being analyzed and the restored data, a category determination unit configured to determine a category of the data based on the similarity for each of the plurality of categories, a category classification unit configured to classify the category to which the process data belongs, and a process state diagnostic unit configured to diagnose a state of the manufacturing process based on a result of comparison between the determined category and the classified category.

Disclosed are methods, systems, and non-transitory computer-readable medium for a contextual transformation of an analytical model for an industrial internet of things (IIoT) edge node. For instance, the method may include receiving the analytical model from a cloud service; obtaining local data of the IIoT edge node; analyzing the local data to determine a situational context of the IIoT edge node; determining whether to transform the analytical model based on a fit between the analytical model and the situational context; and in response to determining to transform the analytical model, transforming the analytical model based on the situational context to derive a transformed analytical model.

A method and system for detecting anomalies in mission-critical environments using word representation learning are provided. The method includes parsing at least one received data set into a text structure; isolating a protocol language of the at least one received data set, wherein the protocol language is a standardized pattern for communication over at least one communication protocol; generating at least one document from the contents of the received at least one data set, wherein the at least one document includes at least one parsed text structure referencing a unique identifier; detecting insights in the at least one generated document, wherein insights are detected in at least one representation having at least one dimension, wherein the representation is mapped to at least one learned hyperspace; extracting rules from the detected insights; and detecting anomalies by applying the extracted rules on patterns for communication over at least one communication protocol.

A method, apparatus and product for identifying data drifts. The method comprising: obtaining a baseline dataset of instances in a feature space, each of wherein being associated with a label; determining a set of clusters in the feature space, based on the baseline dataset; determining a baseline distribution of instances over the set of clusters based on the baseline dataset; for each cluster, computing a performance metric for a predictor for the each cluster, wherein the predictor is configured to estimate an estimated label for an instance, wherein the performance metric is indicative of a successful estimation of the predictor to a portion of the baseline dataset that is comprised by the cluster; obtaining a second dataset, wherein the second dataset comprising instances in the feature space; determining a second distribution of instances over the set of clusters, wherein said determining the second distribution is based on the second dataset; and based on the second distribution and on the baseline distribution, and based on at least one performance metric of at least one the cluster of the set of clusters, identifying a data drift in the second dataset with respect to the baseline dataset.

Embodiments of the disclosure relate to systems and methods for leveraging unsupervised machine learning to produce interpretable routing rules. In various embodiments, a training dataset comprising a plurality of data records is created. The plurality of data records includes message data comprising a plurality of messages and action data comprising a plurality of actions that correspond to the plurality of messages. A first machine learning model is trained using the training dataset. The first machine learning model as trained provides cluster data that indicates, for each data record of the plurality of data records of the training dataset, membership in a cluster of a plurality of clusters. An enhanced training dataset is created that comprises the message data from the training dataset, the action data from the training dataset, and the cluster data. A set of second machine learning models is trained using the enhanced training dataset, each respective second machine learning model of the set of second machine learning models providing a decision tree of a plurality of decision trees and corresponding to a distinct cluster of the plurality of clusters. Rules can be extracted from each decision tree of the plurality of decision trees and used as a basis for creating and transmitting alerts based on incoming messages.

The present disclosure discloses display verification method and apparatus for a browser, the method includes: providing the browser with image drawing data matching with a browser request page; in which the browser locally draws a display image included in the browser request page after the image drawing data is provided to the browser; acquiring a browser drawing image corresponding to the image drawing data; and performing display verification on the browser according to the browser drawing image and a standard drawing image matching with the image drawing data.

A robot programming system according to an aspect of the present disclosure includes: a robot program storage section; a press program storage section; a template program setting section that causes the robot program storage section to store, as an initial version of a robot program, a template program that instructs a robot how to move basically; a model placing section that places three-dimensional models of a workpiece, the robot, and a press machine in a virtual space; a robot movement processing section that causes the three-dimensional model of the robot to move; a press movement processing section that causes the three-dimensional model of the press machine to move; an interference detection section that detects interference between the three-dimensional models; and a robot program modification section that modifies a robot program stored in the robot program storage section to prevent interference detected by the interference detection section.