Abstract: A computer-implemented method for controlling a production system includes mapping, by a controller, the production system as a directed acyclic graph. The production system can include multiple plants that are represented as nodes and relations between the plants represented by edges of the directed acyclic graph. The method further includes generating, by the controller, a regression model for each of the plants in the production system. The method further includes predicting, by the controller, an output of each plant based on sensor data associated from each plant. The method further includes adjusting, by the controller, one or more control variables for each plant based on a target output by using machine learning. The method further includes adjusting, by the controller, the one or more control variables for each plant to generate the target output.

Abstract: A biometric measures profiling analytics system and method are presented. The system and method include collecting biometric data associated with a consumer, and determining one or more biometric variables representing a measurable aspect of the biometric data. The system and method further include generating, based on at least one of the one or more biometric variables, at least one biometric profile variable associated with the consumer, the at least one biometric profile variable representing a degree of normality or abnormality of the collected and calibrated biometric data as compared to a biometric history of the consumer. The system and method further include generating a behavioral score for the consumer based on the collected and calibrated biometric data and with at least one biometric profile variable, the behavioral score representing a degree of risk of normality or abnormality of an event associated with the biometric data.

Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for determining latent components of a metrics time series and identifying anomalous data within the metrics time series based on one or both of spikes/dips and level changes from the latent components satisfying significance thresholds. To identify such latent components, in some cases, the disclosed systems account for a range of value types by intelligently subjecting real values to a latent-component constraint for decomposing the time series and intelligently excluding non-real values from the latent-component constraint. The disclosed systems can further identify significant anomalous data values from latent components of the metrics time series by jointly determining whether one or both of a subseries of a spike-component series and a level change from a level-component series satisfy significance thresholds.

Abstract: The invention relates to an application monitoring tool. According to an embodiment of the present invention, the application monitoring tool has an integrated event/tracing API that traces distributed and non-distributed system flows. For example, a tracing approach may be integrated with a Metrics functionality in that tracing may be throttled or turned on/off based on defined intervals, threshold breaches, and/or anomaly detection of related metrics. If an application's web service calls are beginning to take longer than “normal,” an event/tracing collection feature may be activated to trace calls to enable deeper analysis of the problem.

Abstract: A method includes obtaining measurements associated with a plurality of controlled variables (CVs) and a plurality of manipulated variables (MVs). The method also includes detecting an irregular operating condition of a CV or an MV. The method also includes analyzing case specific operating conditions based on the irregular operating condition. The method further includes removing the irregular operating condition based on analyzing the case specific operating conditions.

Abstract: Systems and methods for detection and analysis of battery condition information may be used with respect to, for example, battery powered hand hygiene product dispensers. The battery condition information may be used to identify potential low battery conditions, the type of dispenser, the type or form of product dispensed, and/or to detect occurrence of a battery replacement event in a hand hygiene product dispenser. The battery condition information may further be used to determine a number of dispenses remaining for a hand hygiene product dispenser. The battery condition information may further be used to provide battery condition information for battery operated hand hygiene product dispensers in hand hygiene compliance systems.

Abstract: Among other things, embodiments of the present disclosure relate to detecting performance degradation in database systems. For example, some embodiments of the present disclosure help to identify events associated with anomalous database system parameter states and assess the severity of such anomalous events. Other embodiments may be described and/or claimed.

Abstract: According to an exemplary embodiment, a method, system, and device for providing cumulative reporting of medical information may be provided. The method, system, and apparatus may utilize software that provides access to any of a variety of medical records and/or medical data in real time and in a manner which allows it to be interpreted and shared. The method, system, and apparatus can also allow prompt alerts based on the interpretation of data shown.

Abstract: A method for estimating a fluid flow velocity may include receiving, with a processing device, a plurality of observations corresponding to a concentration of a constituent of a flowing fluid mixture, and computing a final estimate of an average velocity of the flowing fluid mixture based at least in part on the observations, wherein the constituent is undergoing a chemical reaction and the computing implements a reactive transport model.

Abstract: A bus packet format displaying method for a logic analyzer is disclosed. The logic analyzer fetches at least one packet of a bus of an electronic device. A computer host divides a plurality of bits of a second packet section of the packet into a plurality of message partitions according to a predetermined format defined in advance. Each of the message partitions has a value. The computer host gives a message name to each of the message partitions corresponding to the values and displays the message names and the values fetched by the logic analyzer on an operating screen.

Abstract: Systems and methods for calculating radiotherapy dose distribution are provided. The systems and methods include operations for receiving data representing at least one of particle trajectories or a dose deposition pattern in a simulated delivery of a radiotherapy plan; applying a dose calculation process to the received data to generate a first radiotherapy dose distribution having a first level of detail; and processing the first radiotherapy dose distribution using a trained machine learning technique to generate a second radiotherapy dose distribution having a second level of detail that enhances the first level of detail.

Abstract: An apparatus, computer program product and method of analyzing two-dimensional data input. The system is known as Syneren Signal and Image Enhancement Technology (SIETECH). SIETECH can be implemented in software or in Field Programmable Gate Array (FPGA) hardware. Some embodiments of the present invention pertain to apparatuses, method, and a computer program that is configured to cause the central processor to pass the input data to the multi-thread processors, wherein each data point is mapped on the thread level and the local lower and upper bounds are constructed simultaneously based on order statistic window.

Abstract: The present disclosure is directed toward systems and methods for identifying contributing audience segments associated with a metric anomaly. One or more embodiments described herein identify contributing factors based on statistical analysis and machine learning. Additionally, one or more embodiments identify audience segments associated with each contributing factor. In one or more embodiments, the systems and methods provide an interactive display that enables a user to select a particular anomaly for further analysis. The interactive display also provides additional interfaces through which the user can view informational displays that illustrate the factors and segments that caused the particular anomaly and how those factors correlate with each other.

Abstract: System and techniques for autonomously adaptive performance monitoring are described herein. A device state may be measured. A measurement set may be located using the device state. A difference set between the measurement set and a current measurement group may be identified. The current measurement group may be changed into a next measurement group using the difference set. A measurement package created during at least one sample period of the next measurement group may be sent to a remote device.

Abstract: Mechanisms are provided that implement a drug-adverse event causality evaluation engine to identify human resource selections based on a readability of unstructured text within an individual case safety report (ICSR) and a confidence value of the ICSR. The drug-adverse event causality evaluation engine receives the ICSR from a cognitive system. The drug-adverse event causality evaluation engine analyzes the ICSR to determine a readability value of the ICSR. The drug-adverse event causality evaluation engine determines whether or not an assessment, by a human reviewer, of the ICSR is required based on a combination of the readability value of the ICSR and the confidence value. The drug-adverse event causality evaluation engine outputs an indication of whether human reviewer assessment is required.

Abstract: A method for controlling a wind turbine includes detecting a plurality of analytic outputs relating to power performance of the wind turbine from a plurality of different analytics. The method also includes analyzing the plurality of analytic outputs relating to power performance of the wind turbine. Further, the method includes generating at least one computer-based model of the power performance of the wind turbine using at least a portion of the analyzed plurality of analytic outputs. Moreover, the method includes training the computer-based model(s) of the power performance of the wind turbine using annotated analytic outputs relating to the power performance of the wind turbine. In addition, the method includes estimating a power magnitude of the wind turbine using the machine-learned computer-based model(s). As such, the method includes implementing a control action when the power magnitude of the wind turbine is outside of a selected range.

Abstract: Mechanisms are provided that implement a drug-adverse event causality evaluation engine to identify human resource selections based on a readability of unstructured text within an individual case safety report (ICSR) and a confidence value of the ICSR. The drug-adverse event causality evaluation engine receives the ICSR from a cognitive system. The drug-adverse event causality evaluation engine analyzes the ICSR to determine a readability value of the ICSR. The drug-adverse event causality evaluation engine determines whether or not an assessment, by a human reviewer, of the ICSR is required based on a combination of the readability value of the ICSR and the confidence value. The drug-adverse event causality evaluation engine outputs an indication of whether human reviewer assessment is required.

Abstract: A set of candidate malicious activity identification models are trained and evaluated against a production malicious activity identification model to identify a best performing model. If the best performing model is one of the candidate models, then an alert threshold is dynamically set for the best performing model, for each of a plurality of different urgency levels. A reset threshold, for each urgency level, is also dynamically set for the best performing model.

Abstract: A device operation anomaly identification and reporting system includes device that generates an operating metric data stream. A management system is coupled to the device and receives and analyzes the operating metric data stream. The management system identifies peaks present in the operating metric data stream, and determines a peak height and a peak area for each of the peaks. The management system then clusters the peaks into height clusters based on their heights, and clusters the peaks into area clusters based on their areas. The management system then defines an operating periodicity for the device based on the height clusters and area clusters, and when the management system detects an operating anomaly in the device using the operating periodicity defined for the device, it generates and transmits an operating anomaly alert that reports the operating anomaly in the device.

Abstract: Automatic classifying vehicles by vocation and benchmarking vehicle performance relative to other vehicles of the same vocation are disclosed. Vehicles having a same vocation relative to each other and independent of vehicle fleet, industry vehicle application and vehicle type are benchmarked. Historical vehicle data that includes recurring vehicle usage data is stored. Using a learned trained classifier for each vehicle of the plurality of vehicles, a predicted vocation based on vehicle usage data may be obtained. A grouping based on the predicted vocations and the historical vehicle data is made. A determination from the benchmarked vehicles having better performance characteristics than other vehicles of the same predicted vocations is made. Performance of the other vehicles relative to benchmarking vehicles is made.

Abstract: An apparatus, method, and non-transitory machine-readable medium provide for improved feature extraction and fault detection in a non-stationary process through unsupervised machine learning. The apparatus includes a memory and a processor operably connected to the memory. The processor receives training data regarding a field device in an industrial process control and automation system; extracts a meaningful feature from the training data; performs an unsupervised classification to determine a health index for the meaningful feature; identifies a faulty condition of real-time data using the health index of the meaningful feature; and performs a rectifying operation in the industrial process control and automation system for correcting the faulty condition of the field device.

Abstract: A method for projecting a particle beam onto a substrate, the method includes a step of calculating a correction of the scattering effects of the beam by means of a point spread function modelling the forward scattering effects of the particles; a step of modifying a dose profile of the beam, implementing the correction thus calculated; and a step of projecting the beam, the dose profile of which has been modified, onto the substrate, and being wherein the point spread function is, or comprises by way of expression of a linear combination, a two-dimensional double sigmoid function. A method to e-beam lithography is also provided.

Abstract: Methods and systems for assessing the probabilities of the expression of one or more traits in progeny are described.

Abstract: A method for geo-location services is described. In one embodiment, the method includes tracking incidents that occur within a predetermined geographic area in relation to a subscription service, upon receiving a request for a list of incidents in relation to the predetermined geographic area, generating a notification comprising the requested list of incidents, and sending the notification to one or more subscribers within the predetermined geographic area.

Abstract: In accordance with embodiments, there are provided mechanisms and methods for facilitating dynamic workload-aware shuffling of message types in message queues in an on-demand services environment in a multi-tenant environment according to one embodiment. In one embodiment and by way of example, a method includes monitoring, in runtime, workload patterns associated with incoming workloads, where each workload is associated with a plurality of message types and the plurality of message types are inspected and processed in a predetermined order. The method may further include collecting, in runtime, information regarding each message type based on a workload pattern of its associated workload, and dynamically shuffling the order based on the information, where shuffling includes ordering a first set of message types having one or more messages ahead of a second set of message types having fewer or no messages.

Abstract: Methods, systems, and media for detecting and transforming rotated video content items are provided.

Abstract: A computing server may use one or more recommender systems to predict phenotypes of individuals based on survey responses, other phenotypes, environmental factors, and genetic data of the individuals. The computing server may retrieve survey responses of a set of individuals regarding a set of phenotypes of the individuals. The computing server may construct a matrix that includes the values of the phenotypes. The computing server may predict an undetermined phenotype of a target individual using collaborative filtering, which provides the prediction based on other phenotypes of the target individuals and based on at least another individual's phenotypes. The computing server may also predict a target phenotype based on the phenotype of other individuals who are similar to the target individual. The computing server may determine another individual is similar to the target individual based on the length of identity-by-descent (IBD) segments between the two individuals.

Abstract: A method, system, and computer program product, include identifying a plurality of pollution process sets and determining pollution sources based on pollution start times of target pollution processes with matched features in the plurality of pollution process sets within a time window.

Abstract: A method includes determining a plurality of complexity scores. Each of the plurality of complexity scores corresponds to a particular underlying component of a plurality of underlying components of a portfolio. The complexity score of the particular underlying component is based on a complexity rating of the particular underlying component and a contribution level of the particular underlying component to the portfolio. The method also includes determining a complexity score of the portfolio based on the plurality of complexity scores of the plurality of underlying components.

Abstract: Techniques to display and analyze reliability data about a large population of objects are disclosed. In some embodiments, reliability data is arranged in an array, comprising a plurality of linear arrays each of which includes reliability data for a corresponding reporting period. The reliability data includes for each of a plurality of subpopulations a corresponding reliability metric for that subpopulation with respect to the reporting period. A statistics-based conditional formatting is applied to at least a subset of cells comprising the array. The statistics-based conditional formatting may be applied by invoking a function or other automated method to apply a first cell formatting to a first set of cells having a first degree of statistical significance relative to a reference population of cells and a second cell formatting to a second set of cells having a second degree of statistical significance relative to the reference population.

Abstract: A system and computer-implemented method for automatically recognizing a new class in a classification system. The method includes accessing components of a trained convolutional neural network (CNN) that has been trained with available classes. The components are provided in a kernel space and include at least one of a plurality of kernels and a plurality of neurons of one or more layers of the CNN. Furthermore, the components are assigned to a class in accordance with the training. The method further includes applying a covariance matrix to map the components in the kernel space to eigenspace; determining, for each of the available classes, an eigen-distance between a sample and the components mapped to eigenspace; based on the eigen-distance, determining whether the sample is an outlier that does not belong to one of the classes; and creating a new class that includes the sample if determined that the sample is an outlier.

Abstract: In some examples, time-series datasets received from a system may be temporally aligned. In some examples, one of the time-series datasets may be deduplicated. In some examples, whether an anomaly has occurred in the system may be determined based on a non-deduplicated time-series dataset of the time-series datasets.

Abstract: Methods, systems, and apparatuses, including computer programs encoded on a computer storage media, are provided for facilitating group communications. The described embodiments provide a group chat application allowing a user to send multiple types of messages, including decision messages (or interactive message), to one or more group chat recipients. The decision messages may include a question, a number of answer options, and a time limit for response. Such messages may be displayed in a group chat feed to allow group participants to submit responses by selecting or ranking the answer options. Results may be determined from the submitted responses and displayed to the sender of a decision message.

Abstract: An alarm information processing apparatus includes: an acquirer that acquires alarm information generated in a predetermined period of time and identification information; at least one processor configured to: select first alarm information together with first identification information and second alarm information together with second identification information; and analyze statistics about the first alarm information and the second alarm information; and an output configured to output the statistics about alarms analyzed by the processor in a comparable form.

Abstract: Systems and methods for applying spatial correlation in integrated circuit development involve placing devices of an integrated circuit design, and obtaining spatial correlation values. Each spatial correlation value indicates a correlation coefficient between a first device and a second device, which are instances of a same device. The correlation coefficient is based on a device separation. Spatial correlation is determined as a function of an inverse of device separation. The device separation refers to one-dimensional or two-dimensional separation. The method includes determining a parameter value for the first device based on an average value of the parameter value and on the spatial correlation as the function of the inverse of the device separation, performing analysis of the integrated circuit design using the parameter value, and providing the integrated circuit design for fabrication into an integrated circuit based on finalizing the design according to the analysis.

Abstract: Embodiments of the disclosure can relate to providing an integrated power plant advisor. In one embodiment, a method for providing an integrated power plant advisor can include receiving a signal associated with a failure of a power plant or a power plant component. The method can further include determining one or more root causes associated with the failure of the power plant or the power plant component. Based at least in part on operational data and training data from one or more power plants, a ranking of the one or more root causes associated with the failure of the power plant or the power plant component can be determined. The method can further include outputting the ranking via a client device. Based at least in part on the ranking, a repair or replacement strategy for the power plant or the power plant component can be identified.

Abstract: A computer implemented method for selecting an appropriately sized meter for use in a selected application implemented by a computer processor implementing instructions stored in a non-transient memory is described. The instructions include receiving utility meter data transmitted from a plurality of utility meters, each utility meter being installed at a unique utility monitoring location, identifying incorrectly sized utility meters based on utility meter data for particular utility meters that displays quantization effects, and selecting an appropriate meter based on the identification of the utility meters displaying quantization effects.

Abstract: A method, apparatus, and virtual computer system for testing application software. A first operating system of a first operating type is run on a first processor of a first processor type in a physical computer system. A virtual machine that emulates a second processor of a second processor type is run on the first processor. A second operating system of a second operating type is run on the virtual machine with the virtual machine running on the first processor. The first processor running the first operating system and the virtual machine running the second operating system together form the virtual computer system. A tool qualifier module performs verification of an application testing tool on the virtual machine using tool qualification data to qualify the application testing tool before the application testing tool is run using the second operating system on the virtual machine to test an application program.

Abstract: An apparatus for analyzing spectral information includes a database configured to store spectral information of a plurality of materials analyzed by the apparatus, a spectroscopic unit configured to generate spectral information of a subject by filtering an optical signal received from the subject in units of wavelengths, and a controller configured to obtain correlations between spectral information of each of candidate materials from among the plurality of materials and the spectral information of the subject, and generate result information based on the correlations.

Abstract: An asset inspection system includes a robot and a server. The robot collects inspection data corresponding to an asset. The server, includes a user interface, a processor, and a memory. The memory includes instructions that, when executed by the processor, cause the processor to receive the inspection data from the robot, display the inspection data via the user-interface, receive feedback on the inspection data via the user interface, generate a human-assisted inspection based on the received feedback, analyze the inspection data via a trained model, generate an automated inspection based on the analysis by the trained model, combine the automated inspection and the human-assisted inspection to generate an inspection report, and transmit the inspection report for review.

Abstract: A matching record set with respect to a particular data record of a stream is identified based on output values produced by a particular band of locality sensitive hash functions. Using respective matching record sets corresponding to the particular data record and one or more other bands of locality sensitive hash functions, an estimate of a count of data records of the stream which meet a particular inter-record distance criterion is obtained. A determination as to whether the particular data record is to be designated as an outlier with respect to previously-observed records of the data stream is made using the estimated count.

Abstract: A failure detection device is disclosed. The failure detection device may receive operations data related to operations of a set of parts of a machine. The failure detection device may process the operations data using a condition-based processing technique. The condition-based processing technique may be associated with mapping initial values of data elements of the operations data to binary values based on satisfaction of a first set of conditions by the initial values. The failure detection device may detect a presence of a possible issue with the operations of the set of parts based on a second set of conditions, associated with the binary values and the initial values, being satisfied during a time period. The failure detection device may perform, after detecting the presence of the possible issue, a set of actions related to addressing the possible issue.

Abstract: A method of analyzing and displaying spectral-dynamic properties of an audio signal, including measuring a level over time in multiple neighboring frequency-bands based on the audio signal; calculating spectral-dynamic characterizing values based on two or more statistics of a distribution of the measured levels within each of the frequency-bands; and displaying a graphical representation of the spectral-dynamic characterizing values as a function of frequency.

Abstract: Sample size determination techniques in sequential hypothesis testing in a digital medium environment are described. The sample size may be determined before a test to define a number of samples (e.g., user interactions with digital marketing content) that are likely to be tested as part of the sequential hypothesis testing in order to achieve a result. The sample size may also be determined in real time to define a number of samples that likely remain for testing in order to achieve a result. The sample size may be determined in a variety of ways, such as through simulation, based on a gap between conversion rates for different options being tested, and so on.

Abstract: An abnormality of a system is caused by a failure or aged deterioration is determined. A monitoring apparatus includes a model storage unit, a model generation unit, and a determination unit. The model storage unit stores a monitoring model that is a model for one point in time. The model indicates a relationship among a plurality of metrics of a system. The model generation unit generates a comparison model that is the model for a point in time at which the relationship among the plurality of metrics does not conform to the monitoring model. The determination unit determines that the relationship among metrics in the system has changed in a case where the comparison model indicates the relationship among metrics among which the monitoring model indicates the relationship, and outputs a result of the determination.

Abstract: Described is an automatic anomaly detector that receives a time-series of normal and abnormal activities that include features related to entities within a computing system. A feature coherence graph for the features is constructed, with the graph then clustered such that feature spaces of entities are expanded to include features that live within a same cluster but belong to separate entities. The feature spaces are unified by mapping representations of the features spaces into a Euclidean space of feature vectors. The feature vectors related to each feature are then aligned. Sets of clusters of related abnormal activities are then generated by regressing each feature vector over only those features that it possesses. The sets of clusters are used to detect anomalous behavior. The system then identifies a node within the computer system generating the anomalous behavior and initiates an action to minimize a threat posed by the node.

Abstract: Analyzing large datasets requires prioritization of analytical calculations to reduce analysis time and resource requirements. The prioritization process includes determining characteristics of a dataset, determining a list of analytical calculations, prioritizing the list of analytical calculations based on the dataset characteristics and characteristics of the analytical calculations, selecting the highest ranked analytical calculation, and applying the selected calculation on the dataset. The prioritization process of a new calculation based on a known set of calculations includes ranking the set of calculations based on their result scores from execution on a given dataset, comparing the new calculation to the list of known set of calculation, determining a similar calculation, and assigning the rank of the similar calculation to the new calculation.

Abstract: A computer-implemented method includes identifying one or more sensor identifiers; identifying one or more activity conclusions; and identifying one or more activity derivation rules each associated with at least one of the one or more sensor identifiers and at least one of the one or more activity conclusions. The computer-implemented method further includes determining, for each of the one or more sensor identifiers, an overall predominance value based on at least one of the one or more activity derivation rules, wherein the predominance value is an estimation of the synergic significance of each of the one or more sensor identifiers to the one or more activity derivation rules. A corresponding computer program product and computer system are also disclosed.

Abstract: The present disclosure relates to a method and system for registering multi-modality images. The method may include: acquiring a first image relating to a registration model, wherein the registration model includes a plurality of reference objects; acquiring a second image relating to the registration model; determining a set of reference points based on the plurality of reference objects; determining a set of mapping data corresponding to the set of reference points in the first image and the second image; and determining one or more registration parameters based on the set of mapping data.

Abstract: According to some embodiments, system and methods are provided, comprising receiving, at a machine health module, non-parametric data associated with operation of an installed product; generating, via the machine health module, a health status for at least one of a failure type and a remaining useful life of the installed product, based on the received non-parametric data; and generating an operating response of the installed product based on the generated health status. Numerous other aspects are provided.