Abstract: Embodiments are directed to managing data visualizations. A primary visualization that is associated with a data model may be provided such that the primary visualization may be displayed in a display panel. Insight items may be generated based on the primary visualization and the data model such that the insight items may correspond to one or more visualizations that may share one or more portions of the data model and such that the insight items may be displayed in an insight panel. In response to an insight item being selected from the insight panel, additional actions may be performed, including: generating a visualization based on the insight item that is displayed in the display panel instead of the primary visualization; and generating a scratch item that includes a thumbnail view of the primary visualization such that the thumbnail view is displayed in a scratch panel.

Abstract: A circuit module with reliable margin configuration, may include a main circuit, a first auxiliary circuit and a second auxiliary circuit. When the first auxiliary circuit is on, the second auxiliary circuit may be on or off according to whether a control signal is of a first level or a second level. When the first auxiliary circuit and the second auxiliary circuit are both on, the first auxiliary circuit and the second auxiliary circuit may jointly cause an operation parameter of the main circuit to be a first value. When the first auxiliary circuit is on and the second auxiliary circuit is off, the first auxiliary circuit may cause the operation parameter to be a second value. An operation margin of the main circuit may cover a range between the first value and the second value.

Abstract: Described techniques determine performance metric values of a performance metric characterizing a performance of a system resource of an information technology (IT) system, and determine driver metric values of a driver metric characterizing an occurrence of an event that is at least partially external to the system resource. A correlation analysis may confirm a potential correlation between the performance metric values and the driver metric values as a correlation. A graph relating the performance metric to the driver metric may be generated. A plurality of extrapolation algorithms may be trained to obtain a plurality of trained extrapolation algorithms using a first subset of data points of the graph, and the plurality of trained extrapolation algorithms may be validated using a second subset of data points of the graph. A driver metric threshold corresponding to the performance metric threshold may be determined using a validated extrapolation algorithm.

Abstract: A method comprises determining a Nuclear Magnetic Resonance (NMR) response of a subsurface formation that is based on an NMR response signal that traversed through the subsurface formation and that is result of a magnetic field being emitted into the subsurface formation; determining an Archie cementation exponent for an Archie equation based on the NMR response; and determining a property of the subsurface formation based on the Archie cementation exponent.

Abstract: A computer-implemented point-cloud data acquisitioning method for acquiring point-cloud data of the inside of a mining equipment. The method includes the step of acquiring from a sensor, a first dataset and a second dataset, wherein each dataset includes datapoints at coordinates. The method extracts features from the first and second dataset and aligns the first and second dataset using the extracted features. The first and second dataset are aligned into a point-cloud data. The geometry of the mining equipment is estimated based on the point-cloud data and the point-cloud data is used to identify a region of the estimated geometry indicating insufficient data.

Abstract: Provided is a base mutation detection method, which includes: determining an initial frequency of sequencing data of samples being a specific base at an interested locus; calculating, based on the initial frequency, an expected value of each sample being the specific base at the interested locus; updating the initial frequency of the sequencing data of the samples being the specific base at the interested locus; further calculating the expected value of each sample being the specific base at the interested locus, further updating the initial frequency of the sequencing data of the samples being the specific base at the interested locus, and repeating the foregoing iteration until the expected value of each sample being the specific base at the interested locus converges; and determining, based on each converging expected value, a base mutation type and a mutation confidence at the interested locus of each sample.

Abstract: A computer implemented method for detecting regression in a relationship between a performance indicator and AI metrics includes calculating a baseline threshold of regression degradation according to a historical correlation coefficient corresponding to a performance indicator and a set of AI metrics, calculating a current correlation coefficient according to one or more current data records, identifying a correction constant according to the current correlation coefficient and a desired correlation coefficient, generating a function to predict correction constants corresponding to performance indicator data and the set AI metrics, determining a delta correction constant for each AI metric of the set of AI metrics, applying the determined delta correction constant to the set of AI metrics, and identifying a subset of AI metric outliers according to the calculated baseline threshold and the determined delta correction constant.

Abstract: A method of generating a soft sensor for a mechanical system includes defining a training dataset of sensor values received from at least one first sensor corresponding a first physical quantity. The method further includes training a Sparse Identification of Nonlinear Dynamics (SINDy) model using the training dataset to generate a mathematical function defining a relationship between the sensor values and soft sensor values corresponding to a second physical quantity. The method further includes embedding machine readable instructions based on the mathematical function into an embedded system of the mechanical system including at least one first sensor. The machine readable instructions, when executed by the embedded system, cause the embedded system to receive sensor values corresponding to the first physical quantity and generate soft sensor values based on the sensor values and the mathematical function.

Abstract: Techniques are described that facilitate online monitoring of clinical data streams in association with detecting missing data and other suspicious data deviations. According to an embodiment, a computer implemented comprises receiving, by a system comprising a processor, a data stream from a plurality of different clinical data information systems configured to report defined clinical events within the data stream and recording arrival times of received events of the defined clinical events. The method further comprises detecting, by the system, data failure events associated with the data stream based on time differences between the arrival times for defined clinical events of the same type and estimated probabilities that the time differences are expected, wherein the detecting comprises estimating the probabilities that the time differences are expected using time-to-event models developed for each of the defined clinical events of the same type.

Abstract: A system and a method are disclosed for recommending a set of actions to be performed to improve a target performance metric of a client application. An action recommendation system receives the target performance metric from a user associated with the client application. The action recommendation system determines features of the client application describing characteristics and performance history of the client application. The features of the client application and the target performance metric is provided as input to a machine learning model that outputs sets of target features that are likely to result in improvement for the target performance metric. The action recommendation system ranks the sets of target features and selects one of the sets based on the ranking. The action recommendation system determines a set of recommended actions based on the selected set of target features and presents the set of recommended actions to the user.

Abstract: Embodiments of the present invention provide a computer system, a computer program product, and a method that comprises determining a pattern within received data based on a periodicity associated with the received data; in response to a calculated signal score associated with the determined pattern of the received data meeting or exceeding a predetermined threshold transaction amount, tracing at least one location associated with the received data; and dynamically suspending an action associated with an account that generated the received data in response to the traced location not being associated with a historical baseline of the account.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for collecting, organizing, and managing third-party content from multiple sources associated with a user account to present as synthesized tasks in a consolidated graphical user interface and minimize the distraction provided by multiple interfaces. In particular, in one or more embodiments, the disclosed systems analyze content from various web-based data sources, collect relevant content, create synthesized tasks associated with the relevant content, and present the relevant content to the user grouped into synthesized tasks in a single graphical user interface. Additionally, the disclosed systems can prioritize the generated synthesized tasks within the graphical user interface and provide productivity metrics based on the degree to which an associated user interacts with the synthesized tasks.

Abstract: Embodiments herein provide a method for generating a real-time radio coverage map in a wireless network by a network apparatus. The method includes: receiving real-time geospatial information from one or more geographical sources in the wireless network; determining handover information of at least one user equipment (UE) in the wireless network from a plurality of base stations based on the real-time geospatial information; and generating the real-time radio coverage map based on the handover information of at least one UE and the real-time geospatial information.

Abstract: A method for correcting metrology data of a patterning process. The method includes obtaining (i) metrology data of a substrate subjected to the patterning process and (ii) a quality metric (e.g., a focus index) that quantifies a quality of the metrology data of the substrate; establishing a correlation between the quality metric and the metrology data; and determining a correction to the metrology data based on the correlation between the quality metric and the metrology data.

Abstract: A predictive modeling approach to managing cellular network infrastructure is disclosed. In an embodiment, a method can include receiving raw data from a plurality of data sources populated while operating a cellular network. The method can then generate per-logical cell site data by normalizing the raw data based on a set of LCSs in the cellular network to generate per-LCS data. The method can then generate an example from the per-LCS data and generate a predicted energy consumption value for the given LCS by inputting the example into a predictive model (e.g., a decision tree-based model, such as an XGBoost model). From this output, the method can determine if the predicted energy consumption value is higher than an expected energy consumption value (e.g., a historical range of consumption). If so, the method can then label the given LCS as an outlier.

Abstract: In an aspect of the disclosure, a method, a computer-readable medium, and a BMC are provided. The BMC receives an update package containing one or more updated software components of a firmware image of the BMC to replace corresponding existing software components running on the BMC. The BMC shuts down the existing software components and executes the one or more updated software components. The BMC calculates one or more first stability factors of the one or more updated software components. The BMC compares the one or more first stability factors with one or more second stability factors of the corresponding existing software components. The BMC determines whether to keep the updated software components based on a comparison result.

Abstract: A metrology module includes an estimation model that is configured to provide an estimation of independent overlay with tool induced shift on received wafers based on only one azimuth angle spectra. The estimation model can use at least one machine learning algorithm. The estimation model can be derived by the machine learning algorithm applied to calculated training data based on a first training sample set from initial metrology measurements and an additional tool induced shift training sample.

Abstract: A grinding and polishing simulation method, a grinding and polishing simulation system and a grinding and polishing process transferring method. The grinding and polishing simulation method includes the following steps. A sensing information of a grinding and polishing apparatus when grinding or polishing a workpiece is obtained. A plurality of model parameters is identified according to the sensing information. At least one quality parameter is calculated according to a machining path, a plurality of process parameters and the plurality of model parameters.

Abstract: Methods, systems, and apparatuses, for real-time operation control, among other things. There may be adjustments to a first device in which a first network service operates. The adjustment to the device may include moving a second network service of the first device to a second device. The first network service and the second network service may be associated with virtual machines.

Abstract: Systems and methods for quantitatively measuring wheel slippage in differential drive robots are disclosed herein. According to at least one non-limiting exemplary embodiment, data from wheel encoders is compared to data from a gyroscope during execution of at least one of two tests disclosed herein to produce a quantitative value proportional to wheel slippage due to a differential drive robot rotating or turning.

Abstract: An electronic computer-implemented and interactive platform is described, which permits the offer, sale, and distribution of diamonds by sellers to purchasers and, as a result, into the overall diamond marketplace. Each diamond is scanned in order to create a three-dimensional (3D) virtual model that can include images and/or other data that digitally identifies that diamond, providing a “fingerprint” of the diamond. The purchaser may have highly confidential and proprietary information that specifies the critical details of its manufacturing process for each type of cut of polished diamond, referred to as polished diamond parameters (PDPs). A planning system is used to offload time consuming and computationally expensive planning operations from the manufacturer (or other purchaser), and does so prior to a purchase. The planning system and a matching process are used by the platform to enable the data in each PDP file to be applied to the 3D virtual model of each individual diamond.

Abstract: A computer-implemented method for analyzing data obtained for a chemical and/or biological process comprises: obtaining a result of statistical data analysis on the data obtained with respect to the chemical and/or biological process; calculating, for values of process parameters obtained at groups of time points during batch processes of the chemical and/or biological process, a ratio of a correlation value to a confidence value of the correlation value, the correlation value indicating a correlation between the values of the process parameter and at a process output value; calculating, for process parameters, an average of absolute values of the ratios calculated for the values of the process parameter obtained at different groups of time points during the batch processes; excluding the values of one of the process parameters having a smallest average; and iterating, until at least one specified condition is met.

Abstract: An evaluation device (20) evaluates the operating conditions of a briquetting machine (10). The evaluation device (20) includes an evaluation information acquisition unit (220) and an evaluation data generation unit (230). The evaluation information acquisition unit (220) acquires a plurality of pieces of evaluation information indicating the evaluation results of a plurality of briquettes manufactured under the same manufacturing conditions by the briquetting machine (10). The evaluation data generation unit (230) generates evaluation data that is data obtained by comparing a plurality of pieces of evaluation information with each other.

Abstract: There is provided a device and method of filtering outliers from physiological values. The method comprises: (a) populating a window with n physiological values taken, in sequence, from a sequence of physiological values, wherein n is a positive integer; (b) determining whether the variability in the physiological values within the window is less than a predetermined threshold; (c) responsive to the variability in the physiological values within the window being less than a predetermined threshold, determining that the window comprises no outliers, and/or responsive to the variability in the physiological values within the window not being less than a predetermined threshold, determining that the window comprises at least one outlier.

Abstract: A vibration damping control apparatus for a vehicle executes preview vibration damping control while obtaining, from preview reference data, a road surface displacement related value relating to a vertical displacement of a road surface at a predicted passage position of a wheel of the vehicle. In the preview reference data, relationships are established among the road surface displacement related value obtained when a measurement vehicle actually traveled on the road surface, position information representing the position of a wheel of the measurement vehicle when the road surface displacement related value was obtained, and speed information representing the speed of the measurement vehicle when the road surface displacement related value was obtained or representing a speed range in which the speed of the measurement vehicle is contained.

Abstract: Disclosed is a multi-dimensional analysis method for a tripping risk of a whole transmission line due to a lightning shielding failure. A quantity of thunderstorm days, a tower size, a terrain proportion, an altitude, and insulation configuration data are collected for a transmission line for which a tripping risk due to a lightning shielding failure needs to be analyzed, and a striking distance, an exposure distance, a lightning resisting level of the line after altitude factor correction, and a lightning shielding failure risk of a single-base tower are calculated in turn. Characteristics of a lightning shielding failure under different nominal heights, quantities of thunderstorm days, and terrains are studied. Representative combination conditions are selected to calculate a tripping risk of a typical tower due to the lightning shielding failure. A weight coefficient is extracted, to calculate a tripping risk of the whole line due to the lightning shielding failure.

Abstract: A dynamic dispatching method for semiconductor manufacturing system relates to a dynamic dispatching rule based on self-organization for dispatching in a semiconductor manufacturing system, including S1: setting roles and parameters of self-organization units, and defining key nodes in a production environment; S2: constructing a negotiation mechanism between the self-organization units, and designing a decision-making and dispatching subject ESOU; S3: according to a decision instruction of the ESOU, designing a LSOU allocation dispatching unit for distinguishing single-batch processing and multi-batch processing; and S4: designing a dispatching mechanism based on the self-organization units to implement dynamic semiconductor dispatching. The dynamic dispatching method includes three aspects: role definitions of self-organization units, a negotiation mechanism between the self-organization units and a decision-making method thereof.

Abstract: This document describes a multiple hypothesis-based data fusion tracker. Each hypothesis aligns to a different pseudo measurement type. The fusion tracker automatically determines, using a predefined error covariance associated with the radar, which pseudo measurement type has a greater chance of being accurate for a current situation. The fusion tracker may rely on either one of two combined radar and vision calculations, or the fusion tracker may ignore the vision-based pseudo measurements and instead, rely on radar pseudo measurements alone. By selecting between three different bounding boxes, a vision angle based box, a vision lateral position based box, or a radar only based box, the fusion tracker can balance accuracy and speed when drawing, repositioning, or resizing bounding boxes, even under congested traffic or other high volume situations.

Abstract: An image processing apparatus includes a first reception section, a second reception section, an association processing section, an object detection section, and a process execution section. The first reception section receives image information acquired by an image sensor. The second reception section receives sound information that is acquired by one or plural directional microphones and that is generated for at least a partial region in a field of the image sensor. The association processing section associates the sound information with a pixel address of the image information indicating a position in the field. The object detection section detects, from the image information, at least a part of an object that is present in the field. The process execution section executes a predetermined process on the object on the basis of a result of the association performed by the association processing section.

Abstract: The present disclosure generally relates to apparatus, software and methods for detecting anomalous elements in data. For example, the data can be any time series, such as but not limited to radio frequency data, temperature data, stock data, or production data. Each type of data may be susceptible to repeating phenomena that produce recognizable features of anomalous elements. In some embodiments, the features can be characterized as known patterns and used to train a machine learning model via supervised learning to recognize those features in a new data series.

Abstract: Different computing methods and systems to at least compose at least a portion of a story are disclosed. In one embodiment, the story can be presented by an electronic device. The device can include a sensor to sense the user, and a processor. The processor can become aware of an attribute of the user. The story can depend on the attribute. In one embodiment, the attribute can be a behavior of the user. In another embodiment, the attribute can be a location of the user, or a social network of the user. The story can include a story theme and a non-story theme. The story theme can convey a concept, and the non-story theme can include scenes, scripts and/or props. The attribute can affect the story theme, the non-story theme, or both.

Abstract: Methods, systems, and apparatus for an imaging-based MicroOrganoSphere drug assay. In one aspect, a method includes obtaining image data of a well plate comprising a plurality of MicroOrganoSpheres; in response to applying a machine learning model configured to identify instances of at least some of the plurality of MicroOrganoSpheres in the image data, obtaining (i) indications indicative of each instance of the MicroOrganoSpheres and (ii) attributes of each instance of the MicroOrganoSpheres; and normalizing, based on the indications and the attributes, a well-to-well variation in the well plate.

Abstract: A method and system for statistically tracking the dynamics of a population over an area comprising entry points and exit points such that each population member entering through one entry point either exits through one exit point or stations within the area. At each entry point, an entry counter counts the number of entering members and, at each exit point, an exit counter counts the number of exiting members. Based on the counter values, the dynamics of the population are statistically tracked in terms of evolution in time of the number of members stationing in the area. The number of stationing members is retroactively adjusted when during an observation period it is determined that the number of exiting members is higher than the number of entering members, plus the number of members which were stationing within the area at the beginning of the observation period.

Abstract: Metrology systems and processing methods for continuous lithium ion battery (LIB) anode pre-lithiation and solid metal anode protection are provided. In some embodiments, the metrology system integrates at least one complementary non-contact sensor to measure at least one of surface composition, coating thickness, and nanoscale roughness. The metrology system and processing methods can be used to address anode edge quality. The metrology system and methods can facilitate high quality and high yield closed loop anode pre-lithiation and anode protection layer deposition, alloy-type anode pre-lithiation stage control improves LIB coulombic efficiency, and anode coating with pinhole free and electrochemically active protection layers resist dendrite formation.

Abstract: According to one embodiment, a defect classification apparatus includes a processor. The processor acquires a first design image which is an image based on design data created by design software and relates to a first inspection target, and acquires a first real image which is captured by imaging the first inspection target produced based on the design data. The processor converts the first design image to a reference image represented by using a second real image captured by imaging a second inspection target without a defect. The processor calculates a reliability of the reference image. The processor detects a defect in the first inspection target by comparing the reference image and the first real image and classifies the defect, based on the reliability.

Abstract: A method for predicting a failure state of an automated analyzer for analyzing a biological sample is disclosed. The method includes obtaining a prediction algorithm for predicting a failure state of an automated analyzer. The prediction algorithm is configured to predict a failure state of the automated analyzer based on calibration data and/or quality control data generated by an automated analyzer. The method also includes obtaining calibration data and/or quality control data of the automated analyzer and processing the calibration data and/or quality control data by using the prediction algorithm to predict a failure state of the automated analyzer.

Abstract: Systems and/or techniques for facilitating online-monitoring of machine learning models are provided. In various embodiments, a system can receive monitoring settings associated with a machine learning model to be monitored. In various cases, the monitoring settings can identify a first set of data features that are generated as output by the machine learning model. In various cases, the monitoring settings can identify a second set of data features that are received as input by the machine learning model. In various aspects, the system can compute a first set of statistical metrics based on the first set of data features. In various cases, the first set of statistical metrics can characterize a performance quality of the machine learning model. In various instances, the system can compute a second set of statistical metrics based on the second set of data features.

Abstract: A system and method configured in an electrical device for providing a monitoring solution that identifies the intermittent or anomalous behavior of electronic/electric appliances when in use, comprising: receiving present real-time power features like current, voltage, power factor, power consumption of the associated device, and maintaining a history of past real-time readings of the device in its ideal working periods; forming rule-based clusters of different internal states of the device from the past history data at ideal working periods; determining which of said present readings are correlated; computing a deviation between at least some of said present and at least some of said clusters; and declaring an anomaly when said present readings deviation exceeds a predetermined threshold from all of the said clusters.

Abstract: In one example, a computing node includes a metric dependency graph knowledge base to store a data structure representing a relationship between a plurality of metrics. Further, the computing node may include a processor and a memory having a metric recommendation unit. The metric recommendation unit may determine a first metric of a monitored computing-instance while a user interacts with a GUI of a monitoring application. Further, the metric recommendation unit may retrieve the data structure corresponding to the first metric. The data structure may include the first metric and a plurality of dependent metrics associated with the first metric. Further, the metric recommendation unit may apply a machine learning model on the data structure to determine a second metric from the plurality of dependent metrics. Furthermore, the metric recommendation unit may output the second metric related to the first metric on the GUI.

Abstract: Examples of the present disclosure describe systems and methods for ontology-based graph query optimization. In an example, ontology data relating to a graph or isolated collection may be collected. The ontology data may comprise uniqueness and topology information and may be used to reformulate a query in order to yield a query that is more performant than the original query when retrieving target information from a graph. In an example, reformulating a query may comprise reordering one or more parameters of the query relating to resources, relationships, and/or properties based on uniqueness information. In another example, the query may be reformulated by modifying the resource type to which the query is anchored based on the topology information. The reformulated query may then be executed to identify target information in the isolated collection, thereby identifying the same target information as the original query, but in a manner that is more performant.

Abstract: The present invention relates to a system for measuring the water volume fraction (WVF) of a mixed fluid flow in a pipe, especially wet and dry gas hydrocarbon fluid flows, the system comprising a measuring unit for measuring the dielectric permittivity of said fluid mixture, a computing unit for calculating and storing both the WVF, based on the absolute level of the dielectric permittivity, and the statistical variation of the dielectric permittivity of said fluid mixture over a predetermined period of time. The system also including an analysis unit for detecting drift in the measured WVF by comparing and analyzing the development of the WVF versus the statistical variation of the permittivity over said time period, and based on detected drift to determine whether an apparent change in the WVF is reflected in a corresponding change in the statistical variation of the permittivity, and, based on said comparison, determining if the drift is caused by a real change in the WVF.

Abstract: The disclosure describes a method associated with a simulation model of a process module configured to execute at least one module service. The process module is interlinkable or interlinked with further process modules to carry out a technical process in a cascade of module services, and includes Providing a process logic specification of the technical process, a control logic specification of the process module, a state engine of the process module from a configuration of the at least one service, and a process connection information of the technical process; Generating at least a part of the simulation model from a combination thereof, and Linking at least a part of the generated simulation model to a module type package for the process module, or extending a module type package for the process module by at least a part of the generated simulation model.

Abstract: Methods and systems for reinforcement learning with dynamic agent grouping include gathering information at a first agent using one or more sensors. Shared information is received at the first agent from a second agent. An agent model is trained at the first agent using the gathered information and the shared information. A contribution of the shared information is weighted according to a degree of similarity between the first agent and the second agent. An action is generated using the trained agent model responsive to the gathered information.

Abstract: The present invention relates to a method and device for determining the presence or absence of a target analyte in a sample. The present invention may analyze the target analyte without false results, especially false positive results by using a fitting accuracy of a nonlinear function to a data set as a direct indicator for target analyte analysis.

Abstract: Disclosed are systems and methods for providing automated or semi-automated technical support for patients using medical devices, such as continuous glucose monitoring systems. Disclosed embodiments of automated tech support system include collection and storage of copies of streams of medical device data on multiple servers, analysis and comparison of data streams, remote tech support initiation and usage of the automated tech support system for providing improved products and services by storing and analyzing historical tech support data.

Abstract: A method provides telecom operators a single Quality of Experience (QoE) index to collectively interpret service experience and network experience by way of ensemble of expectation scores. The method includes the steps of mapping Key Performance Indicators (KPIs) of time-series data into multiple probability spaces of statistical expectation functions thereby producing time-series expectation scores; applying vector geometry to said time-series expectation scores for each of said statistical expectation functions thereby producing an N-Dimensional probability vector; normalizing correlations of said N-Dimensional probability vector across said KPIs thereby producing a normalized N-Dimensional probability vector; and generating a N-Dimensional probability distribution from the normalized N-Dimensional probability vector to produce an ensemble function. The ensemble function is then be applied to time-series data thereby producing an ensemble index, which represents the QoE (Quality of Experience).

Abstract: A measurement device has: a slider which holds a substrate and is movable parallel to the XY plane; a drive system that drives the slider; a position measurement system which emits beams from a head section to a measurement surface in which grating section are provided on the slider, which receives respective return beams of the beams from the measurement surface, and which is capable of measuring position information in at least directions of three degrees of freedom including the absolute position coordinates of the slider; a mark detection system that detects a mark on the substrate; and a controller which detects the marks on the substrate using the mark detection system while controlling the drive of the slider, and which obtains the absolute position coordinates of each mark based on the detection result of each mark and measurement information by the position measurement system at the time of detection.

Abstract: Embodiments of the present invention provide systems and methods for multidimensional parts average testing for testing devices and analyzing testing results to detect outliers according to embodiments of the present invention. The testing can include calculating multivariate (e.g., bivariate) statistics using delta measurements of like devices, a ratio of measurements, or principal component analysis that identifies eigenvectors and eigenvalues to define meta parameters, for example. Raw test result data can be converted to residual space and robust regression can be performed to prevent outlier results from influencing regression, thereby reducing overkill advantageously.

Abstract: Aspects of the subject technology relate to systems and methods for predicting dysfunctions in physical systems. A dysfunction codex can be provided that includes a plurality of dysfunction models for predicting one or more dysfunctions in a physical system based on one or more specific contexts of the physical system. The dysfunction codex can be applied by selecting a dysfunction model of the plurality of dysfunction models within the dysfunction codex to apply based on the one or more specific contexts of the physical system. Further, a dysfunction of the physical system can be predicted by applying the dysfunction model to input system data of the physical system to predict the dysfunction of the physical system.

Abstract: A method for evaluating energy consumption in an industrial plant, includes capturing sensor data from at least one level of the industrial plant, from the sensor data, digitally obtaining energy consumption curves, an energy consumption curve representing, along a certain time period, discrete values of energy consumption corresponding to time intervals ?t.