Abstract: A computer-implemented method for facilitating a virtual meet-and-greet between a first client device, a second client device, and at least a third client device is provided. The method involves establishing a first private one-on-one video chat between the first client device and the second client device. The method also involves transmitting a request to the third client device to carry out one or more preloading operations to test the operation of one or more hardware and/or software elements of the third client device. The method further involves establishing a second private one-on-one video chat between the first client device and the third client device based at least in part on the third client device have successfully completed the preloading operations and being ready to establish a private one-on-one video chat.

Abstract: A computer-implemented method for facilitating a virtual meet-and-greet between a first client device, a second client device, and at least a third client device is provided. The method involves establishing a first private one-on-one video chat between the first client device and the second client device. The method also involves transmitting a request to the third client device to carry out one or more preloading operations to test the operation of one or more hardware and/or software elements of the third client device. The method further involves establishing a second private one-on-one video chat between the first client device and the third client device based at least in part on the third client device have successfully completed the preloading operations and being ready to establish a private one-on-one video chat.

Abstract: A system and method including receiving vibration spectrum data from a plurality of different assets; determining, based on a shape of the vibration spectrum data for each of the plurality of assets, clusters for the plurality of assets, assets being grouped in a same cluster having vibration spectrum data of a similar spectral shape; determining for each of the clusters, based on an application of domain derived pattern recognition rules for the vibration spectrum data, one of a plurality of fault classifications; generating an output including an association of each of the plurality of assets with the fault classification of the cluster in which the particular asset is grouped; and saving a record of the output.