Abstract: There is provided a method for a computer implemented method for generating a 3D object. The method comprises training a machine learning system to learn design parameter values that give rise to an optimally performing version of the 3D object; and processing, using the machine learning system, input data relating to the 3D object, in an unsupervised manner such that it can be used for generative purposes, such as the creation of novel geometries or other parameters of the 3D object.

Abstract: A method and associated system. Multiple virtual triples for an entity of multiple entities identified within a first data source are generated. Each virtual triple consists of a subject, a predicate, and an object. The subject is the entity. The predicate is a relationship between the entity and other entities identified within the first data source. The object is associated with an attribute of the entity. The subject, the predicate, and the object are each identified within the first data source. A degree of similarity between two entities of the two or more entities is identified by comparing the respective frequency metrics of the two entities. The two entities within the data structure are associated in response to a determination that an identified degree of similarity between the two entities exceeds a first predetermined threshold.

Abstract: A method for extracting structure from networks includes receiving an edge list, where the edge list defines a network including nodes and edges connecting the nodes to each other, where the edges define a strength of a relationship between connected nodes and filtering nodes from the edge list based on a predetermined filter parameter, thereby forming a filtered network. The method further includes identifying distinct connected components within the filtered network, analyzing each of the distinct connected components of the filtered network for the presence of additional structures within the distinct connected components, where the additional structures are decomposed into additional distinct connected components.

Abstract: A method and associated system. Multiple virtual triples for an entity of multiple entities identified within a first data source are generated. Each virtual triple consists of a subject, a predicate, and an object. The subject is the entity. The predicate is a relationship between the entity and other entities identified within the first data source. The object is associated with an attribute of the entity. The subject, the predicate, and the object are each identified within the first data source. A degree of similarity between two entities of the two or more entities is identified by comparing the respective frequency metrics of the two entities. The two entities within the data structure are associated in response to a determination that an identified degree of similarity between the two entities exceeds a first predetermined threshold.

Abstract: A method and associated system. Entities within a first data source are identified. For each entity identified within the first data source, attributes of the entity identified within the first data source and/or relationships between the entity identified within the first data source and other entities identified within the first data source are identified. The attributes and/or relationships identified within the first data source are associated with a first entity identified within a data structure. For each entity identified within the first data source, a frequency metric characterizing the entity identified within the first data source is generated. The frequency metric is based on a frequency at which each attribute and/or relationship identified within the first data source is associated with the entity identified within the first data source. A degree of similarity between two entities of the entities is identified, by comparing the frequency metrics of the two entities.

Abstract: A method to search for at least one relationship pattern in a plurality of runtime artifacts is provided. The method may include detecting at least one data manipulation statement in the plurality of runtime artifacts. The method may also include extracting at least one relationship clause from the detected at least one data manipulation statement. The method may further include parsing the extracted at least one relationship clause. The method may include generating at least one normalized syntax tree based on the parsed at least one relationship clause. The method may also include performing a classification and a snippet discovery on the generated at least one normalized syntax tree.

Abstract: A method for extracting structure from networks includes receiving an edge list, where the edge list defines a network including nodes and edges connecting the nodes to each other, where the edges define a strength of a relationship between connected nodes and filtering nodes from the edge list based on a predetermined filter parameter, thereby forming a filtered network. The method further includes identifying distinct connected components within the filtered network, analyzing each of the distinct connected components of the filtered network for the presence of additional structures within the distinct connected components, where the additional structures are decomposed into additional distinct connected components.

Abstract: A method to search for at least one relationship pattern in a plurality of runtime artifacts is provided. The method may include detecting at least one data manipulation statement in the plurality of runtime artifacts. The method may also include extracting at least one relationship clause from the detected at least one data manipulation statement. The method may further include parsing the extracted at least one relationship clause. The method may include generating at least one normalized syntax tree based on the parsed at least one relationship clause. The method may also include performing a classification and a snippet discovery on the generated at least one normalized syntax tree.

Abstract: A method to search for at least one relationship pattern in a plurality of runtime artifacts is provided. The method may include detecting at least one data manipulation statement in the plurality of runtime artifacts. The method may also include extracting at least one relationship clause from the detected at least one data manipulation statement. The method may further include parsing the extracted at least one relationship clause. The method may include generating at least one normalized syntax tree based on the parsed at least one relationship clause. The method may also include performing a classification and a snippet discovery on the generated at least one normalized syntax tree.

Abstract: A method and associated system. Entities within a first data source are identified. For each entity identified within the first data source, attributes of the entity identified within the first data source and/or relationships between the entity identified within the first data source and other entities identified within the first data source are identified. The attributes and/or relationships identified within the first data source are associated with a first entity identified within a data structure. For each entity identified within the first data source, a frequency metric characterizing the entity identified within the first data source is generated. The frequency metric is based on a frequency at which each attribute and/or relationship identified within the first data source is associated with the entity identified within the first data source. A degree of similarity between two entities of the entities is identified, by comparing the frequency metrics of the two entities.

Abstract: A method to search for at least one relationship pattern in a plurality of runtime artifacts is provided. The method may include detecting at least one data manipulation statement in the plurality of runtime artifacts. The method may also include extracting at least one relationship clause from the detected at least one data manipulation statement. The method may further include parsing the extracted at least one relationship clause. The method may include generating at least one normalized syntax tree based on the parsed at least one relationship clause. The method may also include performing a classification and a snippet discovery on the generated at least one normalized syntax tree.

Abstract: A lift truck has front and rear sections pivotally connected for the front section to turn 90° to the rear section from the straight ahead state of the truck. The front and rear sections can each have a pair of wheels or one section can have a pair of wheels and the other section only a single wheel. All the wheels are drivable. In one aspect drive to a wheel is in proportion to the degree of articulation between the front and rear sections. In a second aspect drive to a wheel is controlled when said articulation exceeds a predetermined value, and in a third aspect a rear wheel or one or both of a pair of rear wheels can be undriven, i.e. freely rotatable in either direction of rotation.