Abstract: The present disclosure relates to systems, computer programs, and methods employing oral cavity image capture for determining tooth displacement (e.g., for identifying patients with, or at risk for, periodontal disease). In certain embodiments, a medical imaging device or system (e.g., an intraoral scanner or other scanner) is employed to generate baseline and test scan images of at least one tooth, where the test scan is performed when the tooth in engaged with an opposing tooth in a chewing action, or is being pushed by an outside force, and the images are processed by a computer program to determine the amount of displacement of the tooth in at least one direction.

Abstract: Systems and processes for managing an information retrieval database are provided. In a method for modeling a data object storing table relationships for tables belonging to a computer application, a first set of table links are retrieved from the data object and an enhanced set of table links are generated by appending additional table links to the first set based on linkages within the tables and/or code extensions/add-ins. A first set of field links are generated for the data object by matching metadata of the enhanced set of table links, and an enhanced set of field links are generated by performing additions, deletions, or replacements within the first set based on characteristics of the field links in the first set and/or code extensions/add-ins. A model for the data object is generated, representing the enhanced set of table links and the enhanced set of field links, and stored in a database.

Abstract: Techniques of facilitating deep learning model rescaling by computing devices. In one example, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components can comprise: a rescaling component; and a forecasting component. The rescaling component can determine a scaling ratio that maps low mesh resolution predictive data output by a partial differential equation (PDE)-based model for a sub-domain to high-resolution observational or ground-truth data for a domain comprising the sub-domain. The forecasting component can generate high mesh resolution predictive data for the domain with a machine-learning model using input data of the PDE-based model and the scaling ratio.

Abstract: Computer systems and methods are provided for increasing a rate of simulation for quantum computing devices. A quantum computing device includes a plurality of gates, each of which is coupled to one or more modes. In the provided computer systems and methods, a device definition and state information for the quantum computing device are received. The state information includes a plurality of input patterns, each of which indicates a number of input bosons that correspond to a respective mode of the quantum computing device, and an amplitude that corresponds to each input pattern. The device definition includes a plurality of sets of gate values that indicate modification by a respective gate of an input pattern probability. A first group of input patterns is generated for a first gate. The first group of input patterns includes a subset of the plurality of input patterns that meet grouping criteria.

Abstract: Disclosed are techniques for scalar solvers in flow simulations that include simulating using a scalar lattice velocity set in a computing system, movement of scalar particles representing a scalar quantity in a volume of fluid, with the scalar particles carried by flow particles of the volume of fluid, and with the movement of the scalar particles causing collisions among the scalar particles; and evaluating, a non-equilibrium post-collide scalar distribution function of a specified order that is representative of the scalar collision.

Abstract: A system for validating a flow rate of a water injection well includes a first data source providing operating data associated with the well, a data repository, a digital model of the well, a second data source, and a processor. The processor is configured to obtain operating data, including a measured flow rate, historical data, and the digital model, determine a modelled flow rate using the digital model based on the historical injection data and the operating data, compare the measured flow rate with the modelled flow rate to determine a delta, receive a second measured flow rate from the second data source, compare the second measured flow rate to the modelled flow rate to determine a second delta, and in response to determining that the second delta does not exceed the threshold value, automatically generate a request for remediation of the first data source.

Abstract: A method for the simultaneous imaging of different physical properties of an examined medium from multi-physics datasets and for digital enhancement and restoration of multiple multidimensional digital images is described. The method introduces nonnegative joint entropy determined as a joint weighted average of the logarithm of the corresponding density of the model parameters and/or images and/or their attributes. The joint entropy measures are introduced as additional constraints, and their minimization results in enforcing of the order and consistency between the different model parameters and/or multiple images and/or their transforms. The method does not require a priori knowledge about specific physical, analytical, empirical or statistical relationships between the different model parameters and/or multiple images and their attributes, nor does the method require a priori knowledge about specific geometric or structural relationships between different model parameters, images, and/or their attributes.

Abstract: The present disclosure relates to training method and apparatus for an object recognition model. There provides a training sample optimization apparatus for a neural network model for object recognition, comprising: for each training sample in a training sample database, a fluctuation determination unit configured to determine a fluctuation of model prediction of the training sample relative to a corresponding labeled identity of the training sample in a case of training the neural network model; and an optimization unit configured to determine whether the training sample can be used for training of the neural network model in the next training epoch, based on the fluctuation of the training sample.

Abstract: A robot programming device 1 is provided with a model layout unit 112 that lays out a workpiece model of a workpiece, a robot model of a robot, and a tool model of a tool in the virtual space, a machining site designation unit 113 that designates a machining site on the workpiece model, a stereoscopic shape layout unit 115 that lays out a predetermined stereoscopic shape such that a surface of the stereoscopic shape is filled in with a predetermined operation pattern and that the operation pattern is projected to at least one surface of the workpiece model, a machining path creation unit 116 that projects the operation pattern to at least one surface of the workpiece model to create a machining path for the tool, and a change unit 117 that changes the machining path and/or an operation program on the basis of the machining site.

Abstract: An exemplary random number generation system leverages the r includes at least one solar power panel of a solar power system, at least one sensor and a random number generator. The sensor senses one or more output parameters (e.g., voltage or current) from the solar power system and provides the sensed parameter to the random number generator, which uses the sensed parameter to generate a number that is truly random (i.e., is not deterministic). As an example, the random number generator may receive multiple samples of the measured parameter and generate a random number based on a difference of the multiple samples. If desired, the random number generator may include an algorithm to remove biasing in the random number.

Abstract: A method for selection of a calibration set and a validation set based on spectral similarity and modeling. The method includes: performing NIR spectrometry on original samples to obtain a spectral matrix of the original samples; randomly selecting m samples as an independent test set; calculating spectral similarity between each of the samples in the independent test set and each of the remaining samples in the original samples respectively to obtain g samples having the highest similarity to be written into the validation set; and calculating spectral similarity between each of the samples in the validation set and each of the remaining samples in the original samples respectively to obtain n samples having the highest similarity to be written into the calibration set. Based on the validation set and the calibration set selected through the method, an obtained model can predict unknown samples more accurately.

Abstract: A computer-implemented method of automatically determining an optimized design for manufacturing a real-world object includes: defining, in memory of a computer-based processor, a finite element model representing a real-world object, the finite element comprising a plurality of elements; evaluating, with the computer-based processor, a distribution of a design variable throughout a vicinity of the finite element model, using singular value decomposition (SVD), to produce a singular value for the design variable in each respective element in the vicinity of the finite element model; defining optimization constraints for the vicinity of the finite element model based on the singular values produced from the SVD; and optimizing the finite element model with respect to the design variable by locally enforcing a geometry of the real-world object in the vicinity based on the defined optimization constraints.

Abstract: Various embodiments herein provide techniques for reducing computational complexity in multiple input multiple output (MIMO, e.g., massive MIMO (mMIMO)) communications, such as efficient decomposition of a channel covariance matrix. Embodiments enable accurate mMIMO channel estimation with relatively low computational complexity compared with prior techniques. Additionally, embodiments may provide efficient beamforming and/or spatial compression. Other embodiments may be described and claimed.

Abstract: A real-time abnormity-diagnosing and interpolation method for water regime-monitoring data relates to the technical field of monitoring water regime. This method includes the following steps: acquiring water regime-monitoring data, drawing a box plot, recognizing and diagnosing abnormal data in real time based on the box plot, performing grey correlation analysis on other variables related to a predictor variable, building a BP neural network model and making training, applying the BP neural network model to predict water regime-monitoring data in real time, and performing abnormity diagnosis and data interpolation. Adopting this method, we can effectively enhance predicting and monitoring the water regime-monitoring data in real time, and diagnose abnormal data and make interpolations in time, thereby improving the reliability of data, objectively reflecting water regime changes, and effectively guiding engineering scheduling.

Abstract: A differential information extraction unit 81 receives input of a function and a provisional solution of the function, and calculates a first-order differential and a second-order differential in the provisional solution of the input function. An end condition determination unit 82 determines whether to continue updating of a solution in the function, based on the provisional solution. A number-of-updates decision unit 83 decides a number of updates of the provisional solution, based on the provisional solution, the first-order differential, and the second-order differential. A provisional solution updating unit 84 repeatedly performs a process of updating the provisional solution as many times as the decided number of updates based on the first-order differential and the second-order differential, and outputs the updated provisional solution as an optimum solution.

Abstract: A system can obtain data that is sourced from an operator of a power grid and includes data items provided on a per-segment basis for feeders. The system can branch the data items into respective feeder groups and generate a data structure based on an adjacency map for segments of a feeder group. The system can construct a feeder load profile based for a feeder on the ordered data structure. The feeder load profile depicts a load capacity for the feeder as a function of a distance from the substation. The system can then determine, based on the feeder load profile, that an available load capacity at the interconnection point is below a threshold required to support an electric vehicle (EV) charging station and identify upgrades based on variations in the feeder load profile to support the EV charging station.

Abstract: An apparatus and method for operating a new well includes receiving a plurality of data relating to drilling operations from a plurality of wells in a region, the data including data from a plurality of sensors at each of the plurality of wells and data regarding equipment used for the drilling operations at each of the plurality of wells. A plurality of parameters is calculated based on the collected data from the plurality of wells. At least one equipment and at least one operating parameter are identified to use for drilling operation of the new well within the region based on the received data and the calculated parameters. The identified at least one equipment and at least one operating parameter are applied to use for the drilling operation of the new well.

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures using generative design processes. A method includes obtaining one or more load cases and one or more design criteria for a modeled object, the one or more design criteria comprising a build material strength model indicating strength relationships between thickness of an object feature and build angle for that object feature resulting from additive manufacturing; iteratively modifying a three dimensional shape of the modeled object in accordance with the one or more design criteria and the one or more load cases, including applying the strength relationships between the thickness of the object feature and the build angle for that object feature on a per-element basis during numerical simulation of the modeled object; and providing the three dimensional shape of the modeled object for use in manufacturing a physical structure.

Abstract: Described herein is a computer implemented method for generating webpage data. The method includes processing a set of design element objects to generate a set of element-grid records, each record corresponding to a design element and including a unique column start, a unique column end, a column start offset and a column end offset. The set of element-grid records is processed to generate a webpage grid definition that defines a grid including a plurality of columns and a plurality of rows. A first design element and a second design element have a same horizontal start position and the webpage grid definition defines: a unique column start gridline for the first design element; a unique column start gridline for the second design element; and a zero-width first column between the first and second column gridlines.

Abstract: An improved method for controlling a lifting device, which moves a load along a first movement direction and along a second movement direction within a specified working area of the lifting device from a starting point to an end point. Individual movements are planned for the first movement direction and for the second movement direction, by which the load is moved further along the movement directions and brought to a newly specified end point.

Abstract: A processing pipeline for supporting advanced analytics for network monitoring and information management as well as specific analytics for particular use cases. The processing pipeline 500 takes in system data (502) and pre-processes (504) the system data. The system data (502) may include any of the types of data described above including text log files, and categorical data from various sources. The illustrated processing pipeline 500 includes two branches; a data modeling branch (506) where a model is developed for the data and a data evaluation branch (508) where the developed model is leveraged to evaluate live data. For certain event detection use cases, the output of the data evaluation branch (508) includes a score (510) (e.g., a threat level score) and context information for evaluating the threat.

Abstract: A method for generating a robot exploration path for a robot to move along includes: establishing a point cloud scene according to single-frame point cloud data collected by the robot, the point cloud scene includes a plurality of data points; classifying and marking each of the data points, the classification mark includes a ground point and an obstacle point, and taking the data points marked as ground points as a ground point cloud; generating a confidence map according to the ground point cloud, the confidence map is configured to display a location and a confidence of each of the ground points in the ground point cloud; generating a plurality of access nodes according to the confidence map; and generating an exploration path according to the access nodes.

Abstract: Anomalies are detected in network packet header data associated with a user's smart device that is in communication with one or more external sources via an electronic network. The user's smart device has one or more device classifications. Bayesian priors are stored of network traffic obtained from crowdsourced network packet header data for a plurality of smart devices having one of the same device classifications as the user's smart device. Network traffic obtained from network packet header data for the user's smart device is captured. The network traffic for the user's smart device is compared with the Bayesian priors and any anomalies are identified. The anomalies indicate potential abnormal data communication behavior regarding the user's smart device.

Abstract: A method can include receiving a stimulated rock volume dimension for a hydraulic fracture in a reservoir where the stimulated rock volume dimension defines a stimulated rock volume region: refining a grid cell model of the reservoir based on the stimulated rock volume dimension by selecting a refinement technique from a group of refinement techniques and generating new finer grid cells in the grid cell model based on the selected refinement technique: assigning a physical property value to each of the new finer grid cells using one or more physical property values selected from a group of existing physical property values; and performing a fluid flow simulation using the grid cell model with the new finer grid cells and their assigned physical property values, and the group of existing physical property values to generate fluid flow simulation results.

Abstract: A computerized method of processing data for use in weather modeling is provided. The method includes receiving, from a first data source, by a first server, microwave link data including signal attenuation information. The method also includes pre-processing, in real time, by the first server, the microwave link data, thereby producing pre-processed microwave link data. The method also includes storing the pre-processed microwave link data in a first data store. The method also includes receiving, from the first data store, by a second server, the pre-processed microwave link data. The method also includes processing, on a scheduled routine, by the second server, the pre-processed microwave link data using a data transform, thereby producing first weather data.

Abstract: A separate relationship management interface for applications that utilize application data objects to implement various application features is used to track changes to relationships between application data objects. Requests that cause writes corresponding to relationships between application data objects and requests that cause reads of relationships between application data objects may be handled using an interface that interacts with a separate data store tracking the relationships between application data objects.

Abstract: Techniques for providing improvements in agricultural science by optimizing irrigation treatment placements for testing are provided, including analyzing a plurality of digital images of a field to determine vegetation density changes in a sector of the field. The techniques proceed by comparing a distribution of pixel characteristics in the digital images for each field sector to determine sectors in which minimal differences are present. Instructions for irrigation placements and testing may then be displayed or modified based on the results of the sector determinations.

Abstract: The present invention includes embodiments of systems and methods for facilitating users' selection of compute infrastructure options that satisfy predefined performance goals. The integrated, multi-provider cloud-based platform of the present invention employs abstraction layers for communicating with and integrating the resources of multiple back-end hardware providers, multiple software providers and multiple license servers. These abstraction layers and associated functionality free users not only from having to implement and configure provider-specific protocols, but also from having to address interdependencies among selected hardware, software and license servers on a job-level basis or at other levels of granularity.

Abstract: An online voltage control method for coordinating multi-type reactive power resources is provided. First, a linearized power flow equation of branch reactive power is established, and an online voltage control model of multi-type reactive power resources including an objective function and constraint conditions is constructed. The constraint conditions includes generator reactive power constraints, reactive power compensator constraints, transformer tap position constraints, a nodal reactive power balance constraint, and slack contained nodal voltage constraints. Then, an optimization result of voltage control is obtained by solving the model.

Abstract: An AFSM core includes a destination state-cell generating a destination state-signal, and a source state-cell generating a source state-signal and causing transition of the source state-signal in response to an acknowledgement indicating transition of the destination state-signal. The acknowledgment is communicated through a delay. A state-overlap occurs between transition of the destination state-signal and transition of the source state-signal. An output-net includes a balanced logic-tree receiving inputs, including the destination state-signal, from the core, and an additional logic-tree cascaded with the balanced logic-tree to form an unbalanced logic-tree so an input to the additional logic-tree is provided by output from the balanced logic-tree and another input receives the source state-signal. Tree propagation time occurs between receipt of a transition in the destination state-signal by the balanced logic-tree and a resulting transition of the output from the balanced logic-tree.

Abstract: Systems and methods for automatically updating patient insurance information in response to a rejection by an insurance provider are provided. An indication that a prescription submitted to an insurance provider associated with a patient for payment has been rejected by the insurance provider may be received. The indication may include a rejection message associated with the rejection of the prescription. Based on the rejection message, the systems and methods may determine whether the rejection is related to incorrect insurance information. A likelihood that the prescription will be paid for when the insurance information is corrected may be calculated. Based on the calculated likelihood, the systems and methods may determine whether to initiate a patient insurance lookup system search.

Abstract: A method includes receiving intraoral scan data of an intraoral cavity of a patient; processing the intraoral scan data to determine, for each dental condition of a plurality of dental conditions, whether the dental condition is detected for the patient and a severity of the dental condition; and presenting indications of the plurality of dental conditions together in a graphical user interface (GUI), wherein the indications show, for each dental condition of the plurality of dental conditions, whether the dental condition was detected for the patient and the severity of the dental condition.

Abstract: Embodiments disclosed herein provide methods, systems, and computer program products that utilize long-range phase information to detect subtle chromosome imbalances in genotype data. Clonal expansions result from mutation followed by selective proliferation, and the embodiments disclosed herein may be used to somatic structural variant events (SVs) predictive or diagnostic of cancer and other diseases.

Abstract: The present disclosure provides an apparent resistivity-depth section generating method for short-offset electromagnetic exploration, including: determining, in field zones divided quantitatively based on the induction number, positions of a recording point for each of observation points and frequencies or a time window thereof, and taking determined positions of the recording point as the assignment point for the observation point and the frequencies or the time window thereof, where one survey line of an axial configuration generates one apparent resistivity-depth section along the survey line; and one survey line of an equatorial configuration typically generates one apparent resistivity-depth section along the survey line, and apparent resistivity-depth sections along connecting lines from the observation points to the source which are the same as observation points in the number.

Abstract: A method and system for prediction of wave properties include collecting time-series data streams from one or more wave measurement devices and processing the data to identify data parameters to establish boundary conditions of a numerical model. The numerical model may be used to compute a predicted wave field of time-series data for a variety of wave properties at a target location.

Abstract: A computer implemented method for managing datasets for a histogram. The method uses a number of processor units to determine a first span for first bins containing first datapoints in a first dataset in the datasets. The first span is determined based a distribution of the first datapoints in the first dataset and a desired number of bins. The number of processor units adjusts a second span for second bins containing second datapoints in a second dataset in the datasets to form an adjusted span that matches the first span for the first bins. The number of processor units merges the first datapoints in the first bins having the first span with the second datapoints in the second bins having the adjusted span to form a merged dataset for the histogram.

Abstract: Systems and methods presented herein are configured to train a neural network model using a first set of photographs, wherein each photograph of the first set of photographs depicts a first set of objects and include one or more annotations relating to each object of the first set of objects; to automatically create mask images corresponding to a second set of objects depicted by a second set of photographs; to enable manual fine tuning of the mask images; to re-train the neural network model using the second set of photographs, wherein the re-training is based at least in part on the manual fine tuning of the mask images; and to identify one or more individual objects in a third set of photographs using the re-trained neural network model.

Abstract: A computer-implemented method for making executable specifications in the system development and/or the system validation of a functional system for a target device for a motor vehicle. The method includes: providing a function system including at least one model view of the one or multiple functions for controlling or regulating a target device; providing a selection interface configured for selecting and changing a system part in a provided first model view by a user; transferring and displaying the system part selected and/or changed in the first model view in another model view for the user; providing a specification-and-approval interface designed for selecting and/or checking and/or further adapting the displayed system parts or changes in the other model view and for approving the changes to the system made in the first and/or in the other model view by the user; adopting in an automated manner the approved changes.

Abstract: Disclosed in the present disclosure is a classification method based on skeleton lines for building shapes. The method includes: (1) expanding a template library of buildings by combining building shape classification in architecture and building shape features in real life on the basis of inheriting advantages of a traditional template matching method; (2) avoiding influence of small depressions and protrusions of the buildings on overall shapes by constructing a least-squares template; (3) extracting the skeleton lines of the buildings and calculating feature vectors of the buildings; and (4) calculating similarity between feature vectors of skeleton lines of the buildings and skeleton lines of templates by using cosine similarity, and selecting the template with the highest similarity as a classification result of the building shapes.

Abstract: A water supply control system is disclosed that comprises a computer-implemented control system coupled to a plurality of gates, one or more pumps, and a plurality of sensors. The computer-implemented control system is configured to receive a request to transfer excess water from a non-water supply lake to a water supply lake and determine, based at least in part on data from the plurality of sensors and geographic locations of the non-water supply lake and the water supply lake, whether transferring water as requested will cause or worsen a flood event. In response to a determination that transferring water as requested will not cause or worsen a flood event, the computer-implemented control system is further configured to issue a command to cause a gate associated with a dam at the non-water supply lake to open such that water is transferred from the non-water supply lake to the water supply lake.

Abstract: The presently disclosed systems and methods provide monitoring systems and methods for assessing risk based on individual risk control categories. In an embodiment, the risk is assessed based on data for a particular control category. A subset of the data is weighted according to a first weighting function, and a different subset of the data is weighted according to a second weighting function. The weighted data is combined to generate a control health index that may be used to assess risk.

Abstract: A computer implemented method for designing chemical reactions for catalyst construction is described. The method includes extracting historical data including historic chemical reaction data and historic catalyst construction yield data and converting the historic chemical reaction data into graph models to represent molecular structure data. The method also includes incorporating the graph models into a chemical reaction algorithm and training a vectorized cognitive deep learning network of the chemical reaction algorithm by using the graph models and a property of the historic chemical reaction data to produce a catalyst chemical reaction model. Further, the method includes validating the catalyst chemical reaction model by inputting the historic chemical reaction data and comparing a generated property corresponding to the catalyst chemical reaction model to the property of the historic chemical reaction data. Lastly, the method includes updating the training of the catalyst chemical reaction model.

Abstract: An example apparatus to perform a convolution on an input tensor includes a parameters generator to: generate a horizontal hardware execution parameter for a horizontal dimension of the input tensor based on a kernel parameter and a layer parameter; and generate a vertical hardware execution parameter for a vertical dimension of the input tensor based on the kernel parameter and the layer parameter; an accelerator interface to configure a hardware accelerator circuitry based on the horizontal and vertical hardware execution parameters; a horizontal Iterator controller to determine when the hardware accelerator circuitry completes the first horizontal iteration of the convolution; and a vertical Iterator controller to determine when the hardware accelerator circuitry completes the first vertical iteration of the convolution.

Abstract: A method for predicting the fluctuation of circuit path delay on the basis of machine learning, comprising the following steps: S1: selecting suitable sample characteristics by means of analyzing the relationship between circuit characteristics and path delay; S2: generating a random path by means of enumerating values of randomized parameters, acquiring the maximum path delay by means of performing Monte Carlo simulation on the random path, selecting a reliable path by means of the 3? standard, and using the sample characteristics and path delay of the reliable path as a sample set (D); S3: establishing a path delay prediction model, and adjusting parameters of the model; S4: verifying the precision and stability of the path delay prediction model; S5: obtaining the path delay.

Abstract: An accelerated life test method for a speed reducer of an industrial robot is provided. The accelerated life test method includes: setting first load stress higher than rated load stress and second load stress lower than the rated load stress; performing an accelerated life test by loading the first load stress to first speed reducer samples; calculating a service life of each of the first speed samples in the accelerated life test; performing a contrast test by loading the second load stress to second speed reducer samples; calculating a service life of each of the second speed samples in the contrast test; and calculating an acceleration coefficient, and the acceleration coefficient is equal to a ratio of the service life in the accelerated life test to the service life in the contrast test.

Abstract: A media Parameter-modified method for realizing an adaptive expression of an arbitrary discontinuous surface, comprising the following steps: importing an initial forward model, importing anisotropic parameters; and setting a space step and a time step according to the initial forward model parameters; and then starting a stepped discretization of a free surface of the initial forward model; and using a corrected constitutive relationship to correct a first level parameter of the initial forward model; and bringing the corrected constitutive relationship into a displacement stress equation, and the influence of the free surface can be introduced in the case of the anisotropic media after series of operation. The present disclosure can make an accurate numerical simulation of a wave field near the discontinuous surface, and the accurate numerical simulation will contribute to the extraction and analysis of information from the seismic data.

Abstract: A shovel includes: an arm rotatably attached to a boom rotatably attached to a revolving body; a bucket rotatably attached to the arm; a tilt mechanism configured to support the bucket that can be tilted to the arm; a bucket tilt angle sensor configured to detect a tilt angle of the bucket; and a tilt angle controller configured to control adjusting the tilt angle. The tilt angle controller adjusts the tilt angle by automatic control of the tilt mechanism so that a bucket line of the bucket becomes parallel to a target excavation surface. The automatic control of the tilt mechanism is enabled after moving the shovel and/or during rotating the shovel.

Abstract: Aspects of the disclosure provide a method for wafer result prediction. The method includes determining predictor parameters of a semiconductor process using domain knowledge that includes knowledge of the semiconductor process, a processing tool associated with the semiconductor process, a metrology tool, and/or the wafer. The method also includes removing collinearity among the predictor parameters to obtain key predictor parameters, and selecting a subset of the key predictor parameters based on metrology data of the wafer obtained from the metrology tool. The method further includes building a virtual metrology (VM) model on the subset of the key predictor parameters and may include predicting wafer results using the VM model.

Abstract: A method for adjusting a blend composition includes: receiving target blend composition data associated with a target blend composition having a target blend property; controlling blend component flow streams to cause blend components to be added to a blend tank to form a blend composition; determining a property of the blend composition; comparing the property of the blend composition with the target blend property; generating control flow instructions based on the property of the blend composition and a machine learning analysis of historical blend data; and adjusting a blend component flow stream of the blend component flow streams to form a modified blend composition in the blend tank.

Abstract: The disclosure provides a method, an apparatus, and a storage medium for controlling heating system. The method includes: establishing an objective function and constraints for estimating system parameters of the heating system, in which the heating system includes nodes, pipelines and equivalent branches, the equivalent branch is configured to represent a heating resource or a heating load in the heating system, the system parameters include a resistance coefficient of each of the pipelines and equivalent branches, and a heat dissipation coefficient of each of the pipelines; solving the objective function based on the constraints to obtain the system parameters; modeling the heating system based on the obtained system parameters to obtain control parameters of the heating system; and controlling the heating system based on the control parameters.