Abstract: A physical pipeline network is decomposed into multiple subnetworks. The subnetworks include upstream subnetworks and at least one downstream subnetwork. A network solver is executed on the upstream subnetworks in parallel to obtain a set of boundary conditions and a set of control device settings. The set of boundary conditions and a set of control device settings are then used to execute the network solver on the downstream subnetwork and obtain a result having another set of control device settings. The network solver may repeat executions until convergence is achieved. When convergence is achieved, the result is presented.

Abstract: Systems and methods are disclosed for providing at least one report relating to a wireless communications spectrum. At least one device is operable for wideband scan; to detect and measure at least one signal transmitted from at least one signal emitting device autonomously, thereby creating signal data; to analyze the signal data in near real-time, thereby creating analyzed data; generate the at least one report in near real-time; and to communicate at least a portion of the at least one report over a network to at least one remote device.

Abstract: A technique is described for extracting or constructing a three-dimensional (3D) model from multiple two-dimensional (2D) images. In an embodiment, a foreground segmentation mask or depth field may be provided as an additional supervision input with each 2D image. In an embodiment, the foreground segmentation mask or depth field is automatically generated for each 2D image. The constructed 3D model comprises a triangular mesh topology, materials, and environment lighting. The constructed 3D model is represented in a format that can be directly edited and/or rendered by conventional application programs, such as digital content creation (DCC) tools. For example, the constructed 3D model may be represented as a triangular surface mesh (with arbitrary topology), a set of 2D textures representing spatially-varying material parameters, and an environment map. Furthermore, the constructed 3D model may be included in 3D scenes and interacts realistically with other objects.

Abstract: A method for measuring indentation resistance includes: obtaining a first curve indicating a yield shear stress in a depth direction of a raceway surface of a material forming a rolling bearing in a state before the raceway surface is subjected to machining, a second curve indicating a static shear stress in the depth direction of the raceway surface in a state in which the raceway surface is subjected to the machining, and a third curve indicating a static shear stress in the depth direction of the raceway surface in a state in which rolling elements are in contact with the raceway surface and a static load is applied to the raceway surface; and obtaining a correlation between an area and an indentation depth of the raceway ring by defining a region surrounded by exceeding the first curve and the second curve and falling below the third curve as the area.

Abstract: The systems and methods described in this specification relate to generating a low frequency model of a subterranean formation for performing a seismic inversion. The systems and methods receive seismic data for a first region of the subterranean formation and well log data of one or more wells located at the first region. The systems and methods determine one or more relative layer attributes of the first region, one or more first input values for a machine learning model, and one or more second input values for the machine learning model. The systems and methods generate, a first relative low frequency model for the first region, and extrapolate, by executing the machine learning model by the processor, the first relative low frequency model to a second region of the subterranean formation.

Abstract: An NVM algorithm generator that evaluates a Liberty file characterizing an NVM module and a memory view of the NVM module that identifies ports and associated operations of the NVM module to generate a control algorithm. The control algorithm includes a read algorithm that includes an order of operations for assigning values to ports of the NVM module to assert a read condition of a strobe port, executing a memory read on the NVM module and setting values to the ports on the NVM module to assert a complement of a program condition. The control algorithm also includes a program algorithm that includes an order of operations for assigning values to ports of the NVM module to assert the program condition of the strobe port, executing a memory write and setting values to the ports on the NVM module to assert the complement of the program condition.

Abstract: A computer is configured to generate a computer model predicting the progressive creation, density, and spacing of a plurality of cracks in a filler material, such as a “noodle,” for example, disposed at a connection interface between a load-bearing composite structural component, such as a stringer or a spar, for example, and the structural framework of a vehicle on which those structural components are utilized.

Abstract: There is provided a method of monitoring a powder bed process in additive manufacturing, using at least one processor. The method including: obtaining a first image of a powder bed layer from scanning the powder bed layer in a first scanning direction using a first contact image sensor, the powder bed layer being formed by a powder re-coater arm in the powder bed process and the first contact image sensor being attached to the powder re-coater arm; determining a focus level property of the first image; and detecting non-uniformities in the powder bed layer based on the focus level property of the first image. There is also provided a corresponding system for monitoring a powder bed process.

Abstract: Embodiments of the present disclosure are directed towards a system and method for performing an inspection of an underwater environment. Embodiments may include providing an autonomous underwater vehicle (“AUV”) and performing an inspection of an underwater environment using the AUV. Embodiments may further include acquiring real-time sensor data during the inspection of the underwater environment and applying an active simultaneous localization and mapping (“SLAM”) algorithm during the inspection, wherein applying includes estimating one or more virtual landmarks based upon, at least in part, at least one past measurement and a current estimate of AUV activity.

Abstract: A method for part replacement timing optimization. The method includes training a wear estimate model. Training the model includes predicting a plurality of wear patterns for a part, each wear pattern corresponding to a degree of severity. Training images are rendered for each wear pattern. Each of the training images is labeled with the corresponding degree of severity. A neural network is then trained with the labeled training images. An image of a deployed part associated with a machine is received and fed into the trained wear estimate model. The method further includes receiving a wear estimate for the part image from the trained wear estimate model, estimating a change in performance of the machine based on the wear estimate, and determining a machine utilization pattern for the machine. The machine utilization pattern and the change in performance estimate are combined to determine an optimal time to replace the part.

Abstract: A workflow engine processes a work problem to generate solutions for the work problem comprising a plurality of related optimization problems. The work problem may comprise a second optimization problem that is dependent on a first optimization problem, such that at least one solution for the first optimization problem is to be utilized as an initial solution for the second optimization problem. The workflow engine generates and stores a branch object for each optimization problem, each branch object specifying a solver engine assigned for processing the optimization problem and dependency information indicating a dependency relationship between the optimization problem and another optimization problem. The workflow engine processes the work problem based on the branch objects by initiating each solver engine to perform optimization operations on the assigned optimization problem based on the corresponding branch object to generate one or more solutions for the assigned optimization problem.

Abstract: A method of designing/manufacturing a static-magnetic-field shimming coil system for magnetic resonance imaging, includes determining an optimal stream function, defined on a reference surface enclosing a region of interest, for each member of a cohort of magnetic resonance imaging subjects; performing a Principal Component Analysis of the stream functions; determining at least one coil wiring pattern defined on the reference surface by discretizing at least a most significant principal component of the stream functions. A static-magnetic-field shimming coil system suitable to be obtained by the method at least one hollow dielectric support element having a cavity containing the region of interest and a surface having a shape corresponding to the reference surface or, where appropriate, one the additional surface; and a set of conducting elements deposed on or affixed to the surface of the dielectric support, forming the or one the coil wiring pattern.

Abstract: Visually seamless grafting of volumetric data. In some implementations, a method includes obtaining volumetric data that represents a first volume including one or more three-dimensional objects. Planar slices of the first volume are determined and for each planar slice, a result region and an outer region are determined, the outer region located between the result region and an edge of the planar slice. A target region is determined within the result region and adjacent to an edge of the result region. The result region is modified by updating source voxels in the target region based on corresponding continuity voxels in the outer region, and the updating is weighted based on a distance of each source voxel from an associated edge of the result region. The modified result regions are grafted to a second volume at the edge of the result regions to provide a grafted volume.

Abstract: Provided is an improved method, system, and computer program product to implement simulation for photonic devices. A composite, multi-domain simulation model is disclosed, with connected domain-specific representations that allow the use of the most relevant simulator technology for a given domain. The model has external connection points either expressed as actual ports or virtual ones, embodied by simulator API calls in the model.

Abstract: A method can include accessing a depogrid generated via gridding of a structural model in a depositional space and transforming the gridded structural model to a geological space via an inverse mapping where the structural model represents structural features in a subterranean environment based at least in part on data acquired via at least one sensor; determining local u, v and w axes for a plurality of cells in the depogrid via volumetric centroids and vertices represented by coordinates in a depositional space coordinate system (u, v, w) and by coordinates in a physical coordinate system (x, y, z); defining directional geological grid properties based at least in part on the local u, v and w axes; and simulating physical phenomena of the subterranean environment via a simulator based at least in part on at least a portion of the directional geological grid properties.

Abstract: A computer-implemented method, including: capturing a nominal refractive power and/or a nominal astigmatism in a near reference point of the lens, determining a corrective value of the vertical or horizontal prism in the near reference point of the lens; modifying the nominal refractive power and/or the nominal astigmatism in the near reference point on the basis of the corrective value of the vertical or horizontal prism of the lens; determining a continuous course of the nominal refractive power or the nominal astigmatism along the main line of the lens on the basis of the modified refractive power and/or nominal astigmatism in the near reference point; and calculating or optimizing the lens on the basis of the modified nominal refractive power and/or nominal astigmatism in the near reference point and the determined course of the nominal refractive power and/or the nominal astigmatism along the main line.

Abstract: The present invention provides a novel approach to matching personality traits, as determined through observational or self-assessment reporting in combination with specific loci and identifiable variations within an individual's nucleotide sequence in the form of SNPs. The present invention further utilizes an individual's cyber footprint, in combination with SNPs and traditional assessment and self-assessment techniques, to define a testing and reinforcement mechanism for strengthening the interdependence and accuracy of each type of reporting in order to bolster the reliability of each alone and in combination.

Abstract: In a priority determination apparatus (10), a dissimilarity index calculation unit (11) calculates a dissimilarity index between a transmission/reception performance record of a first traffic flow related to a first security alert notified from a network-type intrusion detection apparatus and a transmission/reception performance record of a second traffic flow related to a second security alert notified from the network-type intrusion detection apparatus in the past, the network-type intrusion detection apparatus being configured to detect an attack on an apparatus in a network. A priority determination unit (12) determines a priority of the first security alert based on the dissimilarity index calculated by the dissimilarity index calculation unit (11).

Abstract: The present disclosure discloses a method for automatically identifying south troughs by improved Laplace and relates to the technical field of meteorology. The method includes the following steps: acquiring grid data of a geopotential height field; calculating a gradient field of the geopotential height field in an x direction; searching for a turning point where a gradient value turned from being negative to being positive, and cleaning the gradient field; calculating a divergence of the x direction to obtain an improved Laplacian numerical value L?; performing 0,1 binarization processing on the L? to obtain a black-and-white image and a plurality of targets of potential troughs, merging the black-and-white image and the plurality of targets of the potential troughs by expansion, recovering original scale through erosion, and selecting an effective target through an angle of direction of a contour and an axial ratio.

Abstract: Techniques are provided for the transfer of data (e.g. electromagnetic losses and temperature for an electro-thermal simulation) between domains (e.g. 2D regions, 3D regions) with dissimilar topologies, e.g. to represent a physical object. Meshes from 2D and 3D regions of respective simulation models involved in the data transfer are projected onto and through one another. For profile preserving (e.g., temperature, convection coefficients, mesh displacements, etc.) and conservative (e.g., force, mass, or thermal energy, etc.) data transfers, shape functions and area/volume fractions are used in mapping weight generation, respectively. These weights are later used to generate field values on the mesh of the target simulation model, using data from the mesh of the source simulation model. Related apparatus, systems, techniques and articles are also described.

Abstract: Techniques that facilitate optimization of prototype and machine design within a three-dimensional fluid modeling environment are presented. For example, a system includes a modeling component, a machine learning component, and a graphical user interface component. The modeling component generates three-dimensional model of a mechanical device based on a library of stored data elements. The machine learning component predicts one or more characteristics of the mechanical device based on a first machine learning process associated with the three-dimensional model. The machine learning component also generates physics modeling data of the mechanical device based on the one or more characteristics of the mechanical device. The graphical user interface component provides, via a graphical user interface, a three-dimensional design environment associated with the three-dimensional model and a probabilistic simulation environment associated with optimization of the three-dimensional model.

Abstract: A system for generating task schedules using an electronic device includes: a processor, the processor comprising neural networks; a memory coupled to the processor; a scheduler coupled to the processor, the scheduler is configured to: receive: a total work database configured to contain items representing work packages; a resources database configured to contain items representing resources required to fulfill items in the work packages; a constraints database configured to contain items representing constraints to fulfilling items in the work packages; and a scheduling objective database configured to designate a prime objective that is to be achieved by the optimum task schedule; provide a trained reinforcement learning engine for optimizing the task schedule based on inputs from the databases; and generate an optimum work package schedule to sequence the work packages using the trained reinforcement learning engine, wherein the optimum work package schedule maximizes the one or more prime objectives.

Abstract: Technologies are provided for determining an individual's likelihood of relapsing into prior behavior subsequent to a treatment for a mental health or addiction disorder, and in some instances predicting a likelihood time frame for such a relapse. Target subjects having a risk of addiction relapse, non-adherence to a treatment program, or absconding, may be automatically identified based on a multiplicative-regression model for relative survival (MRS) that is developed for predicting risk or likelihood of relapse or non-adherence. Further, in some embodiments, a leading indicator of near-term future abnormalities may be provided thereby proactively notifying supervisory personnel responsible for the person and providing such personnel with timely notice to enable effective corrective, preventive, or trend-modifying maneuvers to be undertaken.

Abstract: Indexing a data corpus to a set of multidimensional points, including: generating a set of points in a multidimensional space; identifying, for each sample in a plurality of samples in a data corpus, a nearest point in the set of points; and generating an index mapping each sample with the nearest point in the set of points.

Abstract: The present invention relates to methods of imaging template hybridisation for estimating cluster numbers prior to solid phase amplification and sequencing. More particularly, an initial round of imaging is carried out at the single molecule template hybridisation stage which allows a general estimation of cluster numbers prior to clusters being formed. Amplification of the signal allows single molecule imaging to be carried out using standard sequencing imaging apparatus.

Abstract: A system and method for learning human activities from video demonstrations using video augmentation is disclosed. The method includes receiving original videos from one or more data sources. The method includes processing the received original videos using one or more video augmentation techniques to generate a set of augmented videos. Further, the method includes generating a set of training videos by combining the received original videos with the generated set of augmented videos. Also, the method includes generating a deep learning model for the received original videos based on the generated set of training videos. Further, the method includes learning the one or more human activities performed in the received original videos by deploying the generated deep learning model. The method includes outputting the learnt one or more human activities performed in the original videos.

Abstract: A computing system for building a virtual factory includes database and a virtual factory building module. The database stores modeling data. The virtual factory building module builds the virtual factory in which a progress situation of a work performed from a first portion to a second portion is displayed, based on the modeling data and a time difference between an output time of a first signal and an output time of a second signal, which is calculated based on the first signal output when a product is at a first portion on one or more facilities monitored from a first location present in an outside of the one or more facilities used in a real factory and the second signal output when the product is at a second portion on the one or more facilities monitored from a second location present in the outside of the one or more facilities. The first location is spaced from the second location, and the first portion is spaced from the second portion.

Abstract: A method for analysis of complex spatio-temporal data within a dynamic system that includes spatial positions and fields, at least a portion of which are interacting, includes determining values of mean field at every spatial position, determining spatio-temporal eigenmodes in spatial-frequency space assuming interacting fields, and determining spatial and temporal interactions between the eigenmodes. The resulting display indicates space/time localization patterns that are indicative of connectivity within the dynamic system.

Abstract: A system can be provided for applying a dynamic filter to a velocity model for converting the domain of seismic data. The system can receive a velocity model for a geological area of interest. The system can apply a dynamic filter to the velocity model for smoothing an anomaly included in the velocity model. The system can apply the velocity model with the smoothed anomaly to seismic data associated with the geological area of interest for converting the domain of the seismic data.

Abstract: A movement control method, an electronic device, and a computer storage medium are provided. The method includes: acquiring a first polygonal grid map corresponding to a target work region, determining an avoidance subregion non-traversable for the autonomous mobile mowing apparatus in the target work region according to three-dimensional information of each of polygonal planes in a first polygonal grid map and parameters of an autonomous mobile mowing apparatus; deleting a polygonal plane corresponding to the avoidance subregion from the first polygonal grid map to obtain a second polygonal grid map; and controlling the autonomous mobile mowing apparatus to move according to a second polygonal grid map. Based on the method, the region non-traversable for the autonomous mobile mowing apparatus can be avoided, thereby avoiding a danger caused by an abnormal handling behavior triggered by the autonomous mobile mowing apparatus, and improving safety of movement of the autonomous mobile mowing apparatus.

Abstract: Structural health monitoring systems for building structures created by additive processes can include at least an orientation sensing subsystem, a strain sensing subsystem, and a local processor. Orientation sensors can collect data from a first set of strategic locations and strain gauges can collect data from a second set of strategic locations on a 3D-printed building component. The sensors can be embedded during or after the 3D-printing process. A simulation engine can determine the strategic locations by modeling 3D geometry and material properties and simulating results from the application of various loads to determine the likely structural failure locations of the building component. The local processor can receive sensor data, filter the data, format the data for analysis, store the data, and forward the formatted data to a remotely located processing system for analysis.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium for receiving an indication of damage to a building from a sensor network associated with the building, where the sensor network is responsive to damage to the building. Determining a location and an extent of the damage to the building based on the indication of damage. Automatically coordinating a repair for the damage in response to determining the location and the extent of the damage.

Abstract: A method for ascertaining the pose of an object. The method includes recording a first and a second camera image of the object, ascertaining a correspondence between camera pixels of the camera images and vertices of a 3D model of the object, and ascertaining the pose of the object from a set of poses by minimizing, across the set of poses, a loss function, the loss function for a pose being provided by accumulation of distance measures between projections of the object in the pose onto the respective camera image plane and the corresponding pixels of the respective camera image.

Abstract: Computer-implemented processes for precision therapeutic biomarker screening for cancer include using a model-based overlapping clustering framework to assess large numbers of possible drugs and drug combinations against patient data, including cell line responsiveness. A multivariate regression model has been developed, along with a latent overlapping cluster indicator variable. The techniques employ a new finite mixture of multivariate regression (FMMR) model and expectation-maximization (EM) algorithm for modeling. The techniques can analyze large amounts of drug data and identify complex overlapping drug clusters, as well as cluster-wise drivers that facilitate identification of new drugs for treating pathologies, such as cancer, in patients.

Abstract: A component library having a plurality of design components is received. Designs are predicted using the plurality of components using a machine learning model. The predicted designs comprise a subset of all possible designs using the plurality of components. A set of design criteria is received. At least one design solution is generated based on the set of design criteria and the predicted designs.

Abstract: Disclosed is a magnetic parameter value estimation method using deep learning, the magnetic parameter value estimation method including creating a simulated magnetic domain image corresponding to a spin configuration of a two-dimensional magnetic system created through computer simulation, modeling a deep neural network using the simulated magnetic domain image, and estimating a magnetic parameter value of an observed magnetic domain image using the modeled deep neural network.

Abstract: Electrosurgical generators having improved functionality and user interface. In an example, the user may modify therapy output parameters without interrupting therapy delivery within a therapy regimen. In an example, the display shows both therapy amplitudes and encountered impedances for a plurality of therapy pulses in different portions of a display. In an example, the electrosurgical generator is operable in a triggered mode using a cardiac signal trigger and provides the operator with an estimate of remaining time that is calculated in light of a calculated cardiac rate.

Abstract: A system for generating a fraud risk score for a third party provider (TPP) transaction. The system includes a server including an electronic processor. The electronic processor is configured to determine a frequency-recency-monetary value feature, a reputation feature, and a rule feature for a TPP transaction, using the frequency-recency-monetary value feature, the reputation feature, and the rule feature as input for a machine learning model, execute the machine learning model to generate a blended score, and, when the blended score is above a second predetermined threshold, determine that the TPP transaction is fraudulent.

Abstract: A method and a system for constructing a driving coordinate system for use in the field of smart transport. The method for constructing a driving coordinate system comprises: determining the road boundary line on one side of the road on which a current vehicle is situated as a reference line for constructing a driving coordinate system; in a vehicle coordinate system, determining the reference line point having the smallest distance between the reference line and the current vehicle position as an origin point OF of the driving coordinate system; on the basis of the origin point OF, determining the road guiding line direction as the XF axis of the driving coordinate system and determining the direction relative to the road guiding line direction according to the left-hand rule as the YF axis of the driving coordinate system; and, on the basis of the origin point OF, the XF axis, and the YF axis, forming a corresponding driving coordinate system.

Abstract: A method for simulating laser machining of a material by a laser machining system comprising the following steps: providing a central unit with: information relating to the material to be machined: delta ?, threshold fluence, incubation coefficient S, complex refractive index n+ik, information about the laser processing system: information relating to a polarization, pulse energy EP, diameter of said machining laser beam at a focal point w, order of a Gaussian p, pulse repetition rate PRR n, wavelength; determining with said central unit on the basis of the information relating to said material to be machined and the laser machining system, a machining profile in two dimensions corresponding to the simulation of a machining of said material to be machined with said laser machining system.

Abstract: Systems and methods for document analysis using model intersections are disclosed. Predictive models are built and trained to predict whether a given document is in class with respect to a given model. Each predictive model may be associated with a subcategory of an identified technology. Documents that are determined to be in class by multiple ones of the predictive models may be identified and grouped into subsets. These subsets of documents may be identified as relevant to the technology in question.

Abstract: A method of smoothing spectral data recorded by a spectrometer including successively fitting a plurality of spline curves to the spectral data, each spline curve having a different number of knots. A knot position of each knot, other than end point knots, in each spline curve is determined based upon a measure of fit of points of a previously fitted one of the spline curves having fewer knots to the spectral data. The method further includes selecting one of the spline curves as a smoothed data curve of the spectral data based upon a model selection criterion.

Abstract: A method includes obtaining a plurality of data sets, where each data set of the plurality of data sets includes multivariate time series data for a respective sample period of a plurality of sample periods. The method also includes, for each data set of the plurality of data sets, determining recurrence data indicative of recurrent states in the data set and determining, based on the recurrence data, determinism values of a determinism metric and laminarity values of a laminarity metric. The method further includes determining that a particular data set of the plurality of data sets includes data representing an anomalous state based on a determinism-laminarity curve representing the particular data set, where the determinism-laminarity curve is based on the determinism values of the particular data set and the laminarity values of the particular data set. The method also includes generating output data indicating the anomalous state.

Abstract: Described is a system for training a neural network for estimating surface normals for use in operating an autonomous platform. The system uses a parallelizable k-nearest neighbor sorting algorithm to provide a patch of points, sampled from the point cloud data, as input to the neural network model. The points are transformed from Euclidean coordinates in a Euclidean space to spherical coordinates. A polar angle of a surface normal of the point cloud data is estimated in the spherical coordinates. The trained neural network model is utilized on the autonomous platform, and the estimate of the polar angle of the surface normal is used to guide operation of the autonomous platform within the environment.

Abstract: Disclosed is a method for evaluating computational fluid dynamic simulation results. The method includes: performing at least two baseline runs of a simulated area or volume containing a first vehicle body shape using a set of initial conditions, performing a change run using a second vehicle body using the set of initial conditions, creating a noise map based on differences between the second baseline run and the first baseline run, creating a change map based on differences between the change run and a selected baseline run, and comparing the change map to the noise map.

Abstract: The external heterogeneity in the Discrete Event System Specification (DEVS) for simulators refers to the ability to incorporate different types of models, each with potentially different behaviors, into a single simulation environment. In the DEVS framework, a system is composed of multiple individual models, each representing a component of the system. These models can be either atomic (cannot be decomposed further) or coupled (composed of other models). This gives DEVS its hierarchical nature. The atomic or coupled models can in DEVS Markov models be fundamentally different from each other. For example, one model might represent a deterministic rule-based decision process, while another model might represent a probabilistic random variable generator. These models have different state variables, different event sets, and different transition functions, but they can still interact with each other within the same simulation.

Abstract: A method and three-dimensional (3D) modeling engine for managing modeling data during 3D modeling includes generating, by an editable mesh module, a data search list. The method and engine further includes searching, by the editable mesh module, for connection information of vertices, edges, and faces of a 3D model on the basis of the data search list.

Abstract: Techniques are described for training neural networks on variable length datasets. The numeric representation of the length of each training sample is randomly perturbed to yield a pseudo-length, and the samples sorted by pseudo-length to achieve lower zero padding rate (ZPR) than completely randomized batching (thus saving computation time) yet higher randomness than strictly sorted batching (thus achieving better model performance than strictly sorted batching).

Abstract: A method for partitioning a search direction when using least squares reverse time migration (LSRTM) is provided. LSRTM may be used iteratively in order to improve imaging accuracy. As part of LSRTM, multiple local line searches may be performed. In particular, image space may be partitioned, such as by using a set of masks. The search direction, such as the gradient, may be partitioned using the set of masks. Local line searches may be performed for each partition of the search direction, resulting in finding respective line search constants. The respective line search constants may then be used for iterating the model in order to improve imaging accuracy.

Abstract: An integrated system and method for personalized stratification and prediction of neurodegenerative disease state and progression rate. Homogenous patient clusters are identified among heterogeneous patient data. Each patient cluster is characterized by specific disease factors that are used to predict disease progression state and rate for patients assigned to a particular patient cluster in accordance with his disease profile.