Abstract: A method is provided of forming a neural network for detecting surface defects in aircraft engine components. The method includes: providing (i) a pre-trained deep learning network and (ii) a learning machine network; providing a set of pixelated training images of aircraft engine components exhibiting examples of different classes of surface defect; training the trainable weights of the learning machine network on the set of training images.

Abstract: A method is provided of forming a neural network for detecting surface defects in aircraft engine components. The method includes: providing (i) a pre-trained deep learning network and (ii) a learning machine network; providing a set of pixelated training images of aircraft engine components exhibiting examples of different classes of surface defect; training the trainable weights of the learning machine network on the set of training images.

Abstract: A method for predicting fault occurrence in a mechanical system and an electrical system. The method comprises: receiving a first dataset of mechanical system condition data, the first dataset being imbalanced by having more data points in a first category than in a second category; generating a plurality of chromosomes from the second category data points in the first dataset; the plurality of chromosomes including information to enable the creation of new datasets; generating a second dataset using the plurality of chromosomes and an evolutionary algorithm, the second dataset being less imbalanced than the first dataset; and predicting fault occurrence in the mechanical system using the second dataset and a machine learning algorithm.

Abstract: A system in which computer content is encoded at low latency and distributed to one or more client devices and in which user gestures on the client device are translated into a digital representation of the computer's native input format, thereby allowing the client device to control the computer. A method of capturing screen data on a desktop system, packaging the captured content, streaming the content to one or more client device, decoding the content on the client-side, displaying the decoded content on the client device, accepting user input, transmitting the user input to the desktop system, translating the input into a native format, and controlling the desktop system using the translated user input.

Abstract: Mechanisms are provided that improve the usability of remote access between different devices or with different platforms by predicting user intent and, based in part on the prediction, offering the user appropriate interface tools or modifying the present interface accordingly. Mechanisms for creating and using gesture maps that improve usability between cross-device user interfaces are also provided.

Abstract: A system in which computer content is encoded at low latency and distributed to one or more client devices and in which user gestures on the client device are translated into a digital representation of the computer's native input format, thereby allowing the client device to control the computer. A method of capturing screen data on a desktop system, packaging the captured content, streaming the content to one or more client device, decoding the content on the client-side, displaying the decoded content on the client device, accepting user input, transmitting the user input to the desktop system, translating the input into a native format, and controlling the desktop system using the translated user input.