An apparatus for analysing the condition of a machine having a part rotating with a speed of rotation (f.sub.ROT), comprising: a first sensor (10) adapted to generate an analogue electric measurement signal (S.sub.EA) dependent on mechanical vibrations (V.sub.MD) emanating from rotation of said part; an analogue-to-digital converter (40, 44) adapted to sample said analogue electric measurement signal (S.sub.EA) at an initial sampling frequency (fs) so as to generate a digital measurement data signal (SMD, .sub.SENV) in response to said received analogue electric measurement signal (S.sub.EA); a device (420) for generating a position signal (Ep) having a sequence of position signal values (P.sub.(i)) for indicating momentary rotational positions of said rotating part; and a speed value generator (601) being adapted for recording a time sequence of said position signal values (P.sub.(i)) such that there are angular distances (delta-FI.sub.p1-p2, delta-FI.sub.p2-p3) and corresponding durations (delta-T.sub.p1-p2; delta-T.sub.p2-p3) between at least three consecutive position signals (P1, P2, P3) wherein the speed value generator (601) operates to establish at least two momentary speed values (VT1; VT2) based on said angular distances (delta-FI.sub.p1-p2, delta-FI.sub.p2-p3) and said corresponding durations (delta-T.sub.p1-p2; delta-T.sub.p2-p3), and wherein further momentary speed values for the rotational part (8) are established by interpolation between the at least two momentary speed values (VT1, VT2).

An apparatus for analysing the condition of a machine having a part rotating with a speed of rotation (f.sub.ROT), comprising: a first sensor (10) adapted to generate an analogue electric measurement signal (S.sub.EA) dependent on mechanical vibrations (V.sub.MD) emanating from rotation of said part; an analogue-to-digital converter (40, 44) adapted to sample said analogue electric measurement signal (S.sub.EA) at an initial sampling frequency (fs) so as to generate a digital measurement data signal (SMD, .sub.SENV) in response to said received analogue electric measurement signal (S.sub.EA); a device (420) for generating a position signal (Ep) having a sequence of position signal values (P.sub.(i)) for indicating momentary rotational positions of said rotating part; and a speed value generator (601) being adapted for recording a time sequence of said position signal values (P.sub.(i)) such that there are angular distances (delta-FI.sub.p1-p2, delta-FI.sub.p2-p3) and corresponding durations (delta-T.sub.p1-p2; delta-T.sub.p2-p3) between at least three consecutive position signals (P1, P2, P3) wherein the speed value generator (601) operates to establish at least two momentary speed values (VT1; VT2) based on said angular distances (delta-FI.sub.p1-p2, delta-FI.sub.p2-p3) and said corresponding durations (delta-T.sub.p1-p2; delta-T.sub.p2-p3), and wherein further momentary speed values for the rotational part (8) are established by interpolation between the at least two momentary speed values (VT1, VT2).

Technologies for generating manifest data for a sled include a sled to generate manifest data indicative of one or more characteristics of the sled (e.g., hardware resources, firmware resources, a configuration of the sled, or a health of sled components). The sled is also to associate an identifier with the manifest data. The identifier uniquely identifies the sled from other sleds. Additionally, the sled is to send the manifest data and the associated identifier to a server. The sled may also detect a change in the hardware resources, firmware resources, the configuration, or component health of the sled. The sled may also generate an update of the manifest data based on the detected change, where the update specifies the detected change in the hardware resources, firmware resources, the configuration, or component health of the sled. The sled may also send the update of the manifest data to the server.

Technologies for generating manifest data for a sled include a sled to generate manifest data indicative of one or more characteristics of the sled (e.g., hardware resources, firmware resources, a configuration of the sled, or a health of sled components). The sled is also to associate an identifier with the manifest data. The identifier uniquely identifies the sled from other sleds. Additionally, the sled is to send the manifest data and the associated identifier to a server. The sled may also detect a change in the hardware resources, firmware resources, the configuration, or component health of the sled. The sled may also generate an update of the manifest data based on the detected change, where the update specifies the detected change in the hardware resources, firmware resources, the configuration, or component health of the sled. The sled may also send the update of the manifest data to the server.

A computer system for identifying execution paths of analytic elements comprises computer-executable instructions that configure the computer system to identify an orphan analytic element and a second analytic element associated with a network-connected software application. The system can also be configured to identify, with a computer processor, one or more common attributes associated with the orphan analytic element and the second analytic element. Based upon the one or more common attributes, the computer system can identify an execution path for the orphan analytic element. Additionally, the system can be configured to execute, at the one or more computer processors, the network-connected software application, capture network communications generated by the network-connected software application, and generate observed execution paths based on the captured network communications. The system can additionally generate a report indicating the frequency of analytic element execution paths associated with the network-connected software application.

Media items associated with status values are stored using a server in a protected environment. A device outside the protected environment requests sending media items to a client device that is also outside. Using machine learning systems that can be trained using attribute values associated with personal data records to output the existence of a status value, the server computer trains a particular machine learning system in the protected environment only if specified data meets specified criteria, then sends the resulting trained ML system to the requesting device. That device evaluates the trained ML system to determine which media items to deliver to the client device in the manner set forth in the claims.

A method of fault criticality assessment using a k-tier graph convolution network (GCN) framework, where k≥2, includes generating a graph from a netlist of a processing element implementing a target hardware architecture having an applied domain-specific use-case, wherein a logic gate is represented in the graph as a node and a signal path between two logic gates is represented in the netlist-graph as an edge; evaluating functional criticality of unlabeled nodes of the graph using a trained first GCN, and evaluating nodes classified as benign by the trained first GCN using a trained second GCN to identify misclassified nodes.

A method of fault criticality assessment using a k-tier graph convolution network (GCN) framework, where k≥2, includes generating a graph from a netlist of a processing element implementing a target hardware architecture having an applied domain-specific use-case, wherein a logic gate is represented in the graph as a node and a signal path between two logic gates is represented in the netlist-graph as an edge; evaluating functional criticality of unlabeled nodes of the graph using a trained first GCN, and evaluating nodes classified as benign by the trained first GCN using a trained second GCN to identify misclassified nodes.

Technologies for dividing work across one or more accelerator devices include a compute device. The compute device is to determine a configuration of each of multiple accelerator devices of the compute device, receive a job to be accelerated from a requester device remote from the compute device, and divide the job into multiple tasks for a parallelization of the multiple tasks among the one or more accelerator devices, as a function of a job analysis of the job and the configuration of each accelerator device. The compute engine is further to schedule the tasks to the one or more accelerator devices based on the job analysis and execute the tasks on the one or more accelerator devices for the parallelization of the multiple tasks to obtain an output of the job.

Technologies for dividing work across one or more accelerator devices include a compute device. The compute device is to determine a configuration of each of multiple accelerator devices of the compute device, receive a job to be accelerated from a requester device remote from the compute device, and divide the job into multiple tasks for a parallelization of the multiple tasks among the one or more accelerator devices, as a function of a job analysis of the job and the configuration of each accelerator device. The compute engine is further to schedule the tasks to the one or more accelerator devices based on the job analysis and execute the tasks on the one or more accelerator devices for the parallelization of the multiple tasks to obtain an output of the job.