Abstract: A computer implemented method for creating a tree of database states including accessing a database having at least one branch of database states, receiving at the database one or more write events that are applied to an identified state of the database, recovering the identified database state from the database, creating a new branch by creating a new patch as alternative state to the identified database state with a reference to the identified state.

Abstract: A computer implemented method for improving search engine queries including receiving a text corpus, determining a list of n-gram candidates, each being a series of consecutive words of said text corpus, the number of said consecutive words within said series being an integer n superior or equal to two, modifying at least partially said text corpus based on said list of n-gram candidates, performing a machine learning embedding on the resulting text corpus, for each element in said list of n-gram candidates, computing a score based on the embedding of said element and the embeddings of the words making up said element, adding one or more of the n-gram candidates to a search engine queries items list based on their respective scores.

Abstract: A computer implemented method for designing a 3D object in a scene including obtaining a 3D grid of cubes in the scene, said 3D grid of cubes controlling a subdivision surface, said subdivision surface modeling the 3D object, receiving a user stroke of a curve on at least one external face of at least a cube of the grid of cubes, determining a first set of cubes which intersect with the curve on the external face, a second set of cubes which is adjacent to the first set of cubes, perpendicularly to the external face, and a third set of cubes, called intersected cubes, comprising the first set of cubes and the second set of cubes, and for each intersected cube, deforming the intersected cube by moving at least one vertex of said intersected cube so as to fit the curve thereby deforming the subdivision surface.

Abstract: A computer-implemented method for storing a database state. The method comprises providing a database, receiving by the database one or more write events, logging each write event, each logged write event thus forming a new state on the database, buffering pages modified or created by the write events, and creating a patch by flushing to a database storage the buffered pages if a threshold has been met.

Abstract: It is proposed a method for factory operation. The method includes providing manufacturing tasks each represented by a law describing a manufacturing of a product by one or more manageable machines. The method includes obtaining one or more manufacturing constraints and one or more manufacturing events. The method includes determining an operating mode of the factory based on the one or more manufacturing constraints and on one or more product constraints. The determining includes one or more iterations. Each iteration computes a respective propensity of each manufacturing task representing a frequency with which the task is chosen for manufacturing the product given the constraints and/or a previous event(s) occurrence. The iteration ranks the tasks according to a propensity descending order. The iteration visits the tasks according to the ranking and affecting to each task one or more manageable machines and resources. The iteration executes the tasks until an event(s).

Abstract: A computer-implemented method of machine-learning for learning a neural network that encodes a super-point of a 3D point cloud into a latent vector. The method including obtaining a dataset of super-points. Each super-point is a set of points of a 3D point cloud. The set of points represents at least a part of an object. The method further includes learning the neural network based on the dataset of super-points. The learning includes minimizing a loss. The loss penalizes a disparity between two super-points. This constitutes improved machine-learning for 3D object detection.

Abstract: A computer-implemented method is disclosed that includes receiving content associated with a heap dump of a computer application, generating a plurality of files based on the heap dump content, and loading the files into the graph database. The files so generated are compatible with the graph database. In some implementations, additional analysis and route finding (e.g., finding the relationship between two nodes) may be performed on the resulting object graph.

Abstract: A computer-implemented method computes an unfolded part of a modeled bended 3D object in a 3D scene of a computer-aided design system. The method a) provides the 3D object; b) selects a fixed portion (FP) of the 3D object; c) selects a mobile portion (MP) of the 3D object; d) determines a 1D interface (INT) forming an intersection between the fixed portion (FP) and the mobile portion; e) computes a transformed portion resulting from a linear transformation of the mobile portion (MP) according to an drawing direction (DD); f) trims the transformed portion in the vicinity of the 1D interface (INT), thereby forming a trimmed transformed portion (TTP); g) creates a fillet (FI) between the 1D interface (INT) and the trimmed transformed portion (TTP); and h) defines the unfolded part as an union of the fixed portion (FP), the trimmed transformed portion (TTP) and the created fillet (FI).

Abstract: A computer-implemented method for generating a color of an object displayed on a GUI. The method includes displaying on a graphical user interface a set of icons, each icon of the set being associated with a color, detecting a first user interaction on a first icon of the set, detecting a second user interaction that comprises at least a slide, modifying a value of a parameter of a first color associated with the first icon, the modification of the value being performed with the second user interaction, and computing a first new color that is the first color with the modified value of a parameter.

Abstract: A methods and computer systems can automatically identify and fill gaps in a computer aided design. One method includes identifying a first set of points on a first solid in a CAD design. The method includes identifying a second set of points on the second solid in the CAD design. The method also includes determining a volume of the gap between the first solid and the second solid based on a Delaunay tetrahedralization of the first set of points and the second set of points.

Abstract: A 3D reconstruction method including obtaining a first open triangulated surface consisting of triangles of a tetrahedral meshing of a point cloud and determining a second open triangulated surface. The determining explores candidate open triangulated surfaces each being a set of triangles of the meshing and penalizes a high rank of the candidates according to a lexicographic order based on a triangle order and ordering a candidate having triangles decreasingly ordered according to a triangle order penalizing triangle size, relative to another candidate having triangles decreasingly ordered according to the triangle order. The second surface violates consistency of a labelling of the meshing with two labels. A triangle respects labelling consistency when it belongs to the first surface and separates two tetrahedrons having different labels, or when it does not belong to the first surface and separates two tetrahedrons having a same label.

Abstract: Methods and systems identify frequently-used CAD components and apply machine learning techniques to predict mateable entities and corresponding mate types for those components to automatically add components to a CAD model. An example method includes accessing information regarding CAD model parts and related mate information stored in a computer database, and dividing parts into a plurality of clusters having parts with similar global shape signatures. In response to a new part being added, contextual signatures of entities of the new part are input into a mateability predictor neural network to determine a mateable entity of the new part. Input into a mate-type predictor neural network is (i) a contextual signature of the mateable entity and (ii) a contextual signature of an entity of another part of the CAD model to determine a mate type between the entities. A mate between the new part and the other part is automatically added based on the determined mate type.

Abstract: A method preserves shapes in a solid model when distributing material during topological optimization. A 3D geometric model of a part having a boundary shape is received. The geometric model is pre-processed to produce a variable-void distance field and to produce a frozen distance field representing the boundary shape. The geometric model is apportioned into a plurality of voxels, and a density value is adjusted for each voxel according to an optimization process. An iso-surface mesh is extracted from the voxel data, and an iso-surface distance field is generated from the extracted iso-surface mesh. A distance field intersection is derived between the iso-surface distance field and the variable-void distance field. A distance field union is performed between the distance field intersection and the frozen distance field, and a result iso-surface mesh is produced from the distance field union.

Abstract: A computer-implemented method for classifying three-dimensional (3D) objects including obtaining a set of 3D objects. Each 3D object of the set has a signature representative of the morphology of the 3D object. The method also includes computing a multi-level clustering of the set of 3D objects. The multi-level clustering is a hierarchical tree structure of clusters of 3D objects of the set and has N hierarchical levels. The method also includes selecting, automatically or upon user interaction, one of the computed clusters of a level of the multi-level clustering thereby defining a current level. The method comprises displaying, to a user, 3D objects of the selected cluster in a first part of a display. The method further includes classifying, upon user interaction, the displayed 3D objects. The computer-implemented method improves the classification of 3D objects.

Abstract: A computer implemented method for comparing unsupervised embedding methods for a similarity based industrial component model requesting system including obtaining a text corpus relating to industrial component models and a list of testing words, modifying by altering some of the occurrences of each testing word, the modified text corpus containing, for each testing word, occurrences of a first version of each testing word, and occurrences of a second version of each testing word, running an unsupervised embedding method on the modified text corpus and obtaining vector representations, determining a scoring value, by comparing, for at least some of the testing words, the vector representations of the first version of these testing words, and the vector representations the second version of these testing words, running the obtaining, modifying with the text corpus and the list of testing words with another unsupervised embedding method and returning the respective scoring values.

Abstract: The invention notably relates to a computer-implemented method for updating a model of a machine learning system. The method comprises providing a first set of observations of similar events, each observation being associated with one or more variables, each variable being associated with a value, and with a target value; indexing each observation of the first set with its corresponding one or more variables and target value; receiving, on the index, a query allowing a selection of a subset of the first set of observations; returning, as a result of the query, a subset of the first set of observations; providing a second model; training the provided second model with the returned subset of the first set of observations; and loading the trained second model.

Abstract: The disclosure notably relates to a computer-implemented method for designing, with a CAD system, a 3D modeled object representing a mechanical part. The method includes providing a B-rep representing the mechanical part. The B-rep has faces, edges and vertices. The method includes providing a sharp edge. The method further includes, automatically by the CAD system, identifying a set of edges. The set of edges includes the provided sharp edge. Each first edge of the set of edges is directed similarly to at least one second edge of the set of edges, the first edge and the second edge sharing a face. The method further includes, automatically by the CAD system, selecting sharp edges within the set of edges. Such a method constitutes an improved method for designing a mechanical part.

Abstract: A computer-implemented method for training a deep-learning generative model configured to output 3D modeled objects each representing a mechanical part or an assembly of mechanical parts. The method comprises obtaining a dataset of 3D modeled objects and training the deep-learning generative model based on the dataset. The training includes minimization of a loss. The loss includes a term that penalizes, for each output respective 3D modeled object, one or more functional scores of the respective 3D modeled object. Each functional score measures an extent of non-respect of a respective functional descriptor among one or more functional descriptors, by the mechanical part or the assembly of mechanical parts. This forms an improved solution with respect to outputting 3D modeled objects each representing a mechanical part or an assembly of mechanical parts.

Abstract: Unlike existing methods that rely on a manual procedure for setting conditions for performing computer-based simulations, embodiments automatically set conditions for a simulation of a real-world object represented by a computer aided design (CAD) model. In one such embodiment, the morphology of a CAD mode is analyzed to identify a function of an element of the CAD model. In turn, conditions for a simulation are defined based upon one or more rules corresponding to the identified function of the element of the CAD model, where said defining includes automatically setting conditions in a simulation of the real-world physical object.

Abstract: The disclosure notably relates to a computer-implemented method for displaying a simulation. The method includes computing a full simulation. The full simulation includes states. The method further includes computing a reduced model of the computed full simulation. The reduced model includes a basis with elements. Each state of the full simulation is represented by a respective linear combination of basis elements. The method further includes displaying, for at least one state of the full simulation, a part of the respective linear combination. This constitutes an improved method for displaying a simulation.