Carlos Hernando, Borja

The invention relates to a buccal scan positioning pin and digital workflow method in the implantation of dental prostheses, related, on one hand, to a buccal scan positioning pin, intended to be located in the buccal cavity of a patient, and on the other hand, to a digital workflow method in the implantation of dental prostheses to achieve a precise fit between an original anatomical situation of the buccal cavity and a restored situation of said buccal cavity after a surgical process for the implantation of at least one implant, providing greater precision and a better appearance in the final dental prosthesis obtained after the procedure.

An angled abutment with direct luting, relating to a device used as a connection between an implant and a dental prosthesis and which main purpose is to solve problems associated with the height and angulation of the prosthesis fixed directly on the abutment. Preferably, the angled abutment is made of biocompatible material and, after installation, is solidly anchored to the dental implant.

The invention relates to a distraction device for palatal expansion, specifically for the expansion of the palatal suture, relates to a distraction device with an expanding element having different structural modifications with respect to distraction devices in the prior art. One modification comprises a structural configuration to increase expansion capacity with respect to known devices in the prior art, another modification introduces safety mechanisms that prevent the uncoupling of the components of the device during use, and another modification optimises the design, facilitating the assembly of the expansion device on a personalised sintered CAD/CAM structure, used to fix the device or expander to the patient's palate or teeth without the need to use welds.

A method, orchestrator, and computer programs for workload management across cloud and edge computing environments are provided. The method comprises performing a microservice topology mapping and application-specific microservice dependencies profiling by analyzing how different microservices hosted on datacenters and/or edge centers interact and depend on each other; profiling and translating datacenter's and/or edge center's incoming application traffic data into resource utilization; estimating future incoming application traffic data patterns of the datacenters and/or edge centers; detecting anomalies in resource utilization or workload performance in the datacenters and/or edge centers; determining whether a workload should be migrated to another datacenter and/or edge center by performing a multi-objective customizable optimization process comprising executing a weighted scoring function on different metrics including resource utilization, carbon footprint reduction, latency minimization, cost efficiency and anomaly management.

A method, system and computer program for deepfake detection in video digital content are provided. Comprises obtaining a video digital content of a user; extracting the audio and video thereof; performing a verbal speech-based detection analysis by transcribing the extracted audio into text and checking whether a speech content is coherent, contextually relevant and/or aligns with an expected topic; performing a voice tonality detection analysis by generating a spectrogram of the extracted audio and identifying irregularities or artifacts characteristics of manipulated or synthesized voice in the spectrogram; performing a facial cue detection analysis by analyzing expression or mouth movements of the user by identifying and dynamically tracking a landmark of the user and verifying whether the analyzed expression or mouth movements temporally and contextually align with speech phonetics; and determining that the obtained video digital content comprises deepfake content based on the performed verbal speech-based detection, voice tonality detection, and facial cue detection analysis.

A method, system and computer program for anomaly detection in mobile cellular networks are provided. The method comprises generating a graph representation of a plurality of cells; selecting one of the cells of the graph as a target cell; obtaining monitored KPIs of connected neighboring cells of the target cell and of the target cell; predicting expected KPI values in the target cell over a predicting sliding window using the graph representation and the KPIs by a ML context-based predictor; making context-based predictions on the monitored KPIs of the target cell by training the ML context-based predictor using the predicted expected KPI values; calculating an anomaly score by comparing the predicted expected KPI values in the target cell over the predicting sliding window with actual values measured in the target cell over the same period; and determining that an anomaly occurs when the calculated anomaly score exceeds a predefined threshold.

A method and an ALTO server method for advanced processing and exposure of network information are proposed. The method comprises providing an ALTO server formed by modular entities including an exposure module, an ALTO core, ALTO applications, and reading modules; periodically monitoring, by the reading modules, a transport network by generating network status information based on network information collected from network domains; processing, by the core, the generated network status information using a processing functionality of the core, obtaining a network view; receiving, by the exposure module, an advanced network information request from an ALTO client; routing the advanced network information request to one of the applications; providing, by the core, the obtained network view to the application; applying, by the application, an application functionality to the network view, obtaining a response to the advanced network information request; and routing the response to the advanced network information request back to the client.

A method, system and computer programs for securely and efficiently measuring available bandwidth of network paths of an SDN-based network are proposed. The network comprises an SDN controller and a plurality of programmable network devices. The method comprises including a bandwidth monitoring element on the SDN controller and/or on the plurality of programmable network devices of the SDN-based network; executing, by one of the bandwidth monitoring elements, within a measurement round, a real-time available bandwidth measurement of a network path between any two of the plurality of programmable devices by embedding a security mechanism into the probing packets shared between the two programmable network devices based on a data plane protocol relying on cryptographic methods and measuring the available bandwidth of the network path by considering reception time-based information of the probing packets using a single clock.

A method, system and computer program for computing radio coverage maps. The method comprises generating a geographic area scene including an antenna, several buildings surrounding the antenna, and receivers; obtaining a 3D coverage map for the scene using a neural network that converts the geographic area scene to a point cloud with different types of points, including a point for the antenna, coverage points covering the scene and building points capturing the buildings' location and dimensions; converts each point into a node, providing an antenna node, building nodes, and coverage nodes; connects the single antenna node and the coverage nodes to all the building nodes; encodes each node type and records an orientation of each node using both an alpha and beta angle; and defines edges of the 3D coverage map using different features capturing a relationship between connected nodes.

A method, system and computer program for system log compression are provided. The method comprises: obtaining at least one first batch of complete and untampered system log entries; representing the system log entries as a provenance graph, with nodes of the graph representing system entities and edges representing relationships between the system entities, wherein each node and edge of the graph is assigned a set of features; embedding the system entities and relationships within the provenance graph into a continuous multidimensional vector space using an embedding algorithm; identifying expected behavior deviations of the system log entries using the embedded continuous vector space; comparing the identified system log entries that deviate from an expected behavior with a given threshold; and labeling system log entries as anomalous if their deviation is different to or falls outside the given threshold, and compressing the system log entries by discarding those are not labeled as anomalous.