Abstract: A computer-implemented method for navigating between sections in a display space is furnished. The sections in the display space are each assigned to a particular location of the display space, and representatives are provided which are each assigned to a particular section in the display space using an unambiguous relation. The method for navigating includes the following steps: selecting at least one representative that is assigned to a particular section in the display space with the aid of the unambiguous relation; and navigating to the particular section in the display space with the aid of the unambiguous relation with the particular section in the display space.

Abstract: An analysis system analyzes and measures patterns present in the pixel values of digital images using a computer-implemented network structure that includes a process hierarchy, a class network and a data network. The data network includes image layers, thematic layers and object networks. Various types of processing are performed depending on whether the data of the digital images is represented in the image, thematic or object layers. Pixel-oriented and object-oriented processing is combined so that fewer computations and less memory are used to analyze the digital images. Pixel-oriented processes, such as filtering, are selectively performed only at pixel locations that are assigned to a specified thematic class of a thematic layer or that are linked to a particular object of the object network. Similarly, object-oriented processing is performed at pixel locations linked to objects generated using thematic layers or using image layers on which pixel-oriented processes have already been performed.

Abstract: A method for the use of fractal semantic networks is disclosed, wherein the fractal semantic network contains both semantic units that possess respective information contents as well as link units that describe a relation content that respectively links two semantic units such that the mutual relationship of the two linked semantic units is determined through the relation content. In that case, a knowledge network consists of category units and, as the case may be, additionally of instance units and/or Janus units. For the querying of information, classification and/or selecting of semantic sub-networks in this knowledge network, the networking of semantic units taking into consideration the type, content, composition and/or distance of other semantic units in the respective network environment can be employed. Furthermore, Janus functionality can be employed for the local classification or for the local alteration of the networking of a semantic unit.

Abstract: A method for processing data structures with the aid of networked semantic units includes: acquiring a data structure, and generating, modifying, deleting and storing semantic structure units and networking them on the basis of the acquired data structure while using a knowledge base comprised of a network of semantic knowledge units. Semantic structure units and their network are classified in iterative steps. Based on this classification, a specific processing is activated which modifies a respective semantic structure unit and a particular partial network.

Abstract: A computer-implemented network structure includes a semantic network machine comprised of nodes containing informational contents and links containing relational contents. Relational contents describe the relationship between linked nodes. Some of the nodes are semantic Janus units. Based on time-variable states of each semantic Janus unit, the semantic Janus units perform operations on nodes and links. The operations are focused on selected portions of the semantic network machine such that each semantic Janus unit need not deal with all possible informational and relational contents within the semantic network machine. The computational resources of the computer network are thereby efficiently managed, and artificial intelligence tasks such as inferential retrieval are performed quicker. The amount of data that is processed is substantially reduced by focusing on bundled information.

Abstract: A computer-implemented method for navigating between sections in a display space is furnished. The sections in the display space are each assigned to a particular location of the display space, and representatives are provided which are each assigned to a particular section in the display space using an unambiguous relation. The method for navigating includes the following steps: selecting at least one representative that is assigned to a particular section in the display space with the aid of the unambiguous relation; and navigating to the particular section in the display space with the aid of the unambiguous relation with the particular section in the display space.

Abstract: What is disclosed is a computer-implemented method for finding objects which are based on data structures, the method comprising the following steps: announcing a selection of objects; generating and/or invalidating a characterization of one object or several objects of the selection, with characterization being effected by means of an item of characterization information; calculating weights of the objects of the selection and/or of objects located in a vicinity of the characterized objects based on the characterization information, weights already calculated, and/or weights already stored; and modifying the selection and continuing the method from the first step until objects to be found are contained in the selection, until the method is interrupted, or until a given or calculated number of method steps has been carried out, with the possibility of terminating or interrupting the method after any one of the preceding steps.

Abstract: A method is disclosed for generating an application that analyzes image data, such as from satellite and microscope pictures. The method uses a graphical user interface to add a new processing object to a processing object network. The processing object network includes a parent processing object and a child processing object. A user can append a new processing object to the child processing object or can add the new processing object as a subprocess to the parent processing object. The user selects a data domain and an algorithm from selection lists on the graphical user interface and adds them to the new processing object. The application uses a semantic cognition network to process data objects that are generated by segmenting the image data. The application then uses the new processing object to identify portions of the image that are to be highlighted on the graphical user interface.

Abstract: A method for processing data structures with the aid of networked semantic units. The method includes acquiring a data structure, and generating, modifying, deleting and/storing semantic structure units and/networking them on the basis of the acquired data structure. The method uses a knowledge base comprised of a network of semantic knowledge units. Semantic structure units and/their network are classified in iterative steps. Based on this classification, a specific processing is activated which modifies a respective semantic structure unit and/a particular partial network.

Abstract: A method is disclosed for extracting information from input data comprising mapping of the input data into a data object network. The method uses a semantic cognition network comprised of the data object network, a class object network and a processing object network. The semantic cognition network uses a set of algorithms to process the semantic units. The semantic cognition network defines a processing object in the processing object network by selecting a data domain in the data object network, a class domain in the class object network and an algorithm from the set of algorithms. The processing object comprises the data domain, the class domain and the algorithm. The processing object is used in the processing object network to process the semantic units.

Abstract: Disclosed is a computer-implemented method for characterizing a complex system, wherein said complex system consists of a plurality of objects and wherein relations are present between said objects, said method comprising the steps of (a) forming a hierarchical structure having a plurality of hierarchical levels, wherein super ordinate objects of a respective higher hierarchical level of the hierarchical structure are combinations of objects of a respective lower hierarchical level of the hierarchical structure, wherein a characteristic and a boundary condition is assigned to each of said objects within the hierarchical structure; (b) forming groups of objects which belong to the same superordinate object of a respective higher hierarchical level; determining relations between objects in each respective group by taking into account the respective boundary conditions of the objects within the respective group; (d) determining at least one characteristic for each group based on the determined relations between

Abstract: The present invention relates to a method for segmentation of a digital picture consisting of a multiplicity of single picture elements comprising determining if one of one and several features relating to contiguous picture objects comprising picture elements and picture segments are conforming or not conforming based on a specific homogeneity criterion by means of referencing a predetermined tolerance for each feature as a termination criterion, within which feature values relating to the contiguous picture objects in question may differ; if one of one feature and several features relating to the contiguous picture objects are determined to be conforming then merging the conforming picture objects; and repeating the resulting segmentation until the resulting segmentation converges in a stable or approximately stable condition in which no further contiguous picture objects are determined to be conforming.

Abstract: A method for fractal-darwinian object generation consists of the steps of: preparing a fractal object library including predetermined objects and associated rules of property and context, forming objects and comparing the formed objects with the objects in the fractal object library. By using the property rules, a local classification likelihood is allocated to each formed object. Thereupon, by using the context rules for each object, a respective fractal classification likelihood is formed. For optimisation of the fractal classification likelihood, alteration rules are applied to the objects. The above method is carried out iteratively, whereby a process of gradual optimisation takes place.

Abstract: The invention relates to a method for dynamically obtaining relevant traffic information and/or for dynamically optimizing a route followed by a first vehicle which belongs to a self-organizing traffic information and/or traffic guidance system to which other vehicles belong as well. Said method consists of the following steps: generating own data by means of vehicle-mounted sensors and/or other information sources in the first vehicle; transmitting data relevant to the first vehicle or other vehicles; receiving data transmitted by other vehicles; storing data obtained from received and/or own data; generating and transmitting requests regarding data which can possibly be provided by other vehicles; and potential relaying received data by retransmitting said data in processed or unprocessed form.