Abstract: A brain machine interface system for use with an electroencephalogram to identify a behavioral intent of a person is disclosed. The system includes an electroencephalogram configured to sense electromagnetic signals generated by a brain of a person. The electromagnetic signals include a time component and a frequency component. A monitor monitors a response of the person to a stimulus and a characteristic of the stimulus. A synchronization module synchronizes the sensed electromagnetic signals with the response and the characteristic to determine a set of electromagnetic signals corresponding to the monitored response and the characteristic. A processor processes the set of electromagnetic signals and extracts feature vectors. The feature vectors define a class of behavioral intent. The processor determines the behavioral intent of the person based on the feature vectors. A brain machine interface and a method for identifying a behavioral intent of a person is also disclosed.

Abstract: Various examples are related to bioimpedance measurements. In one example, a wearable monitoring system includes electrodes and processing circuitry configured for bioimpedance sensing. The electrodes can include a current source electrode, a current sink electrode, and voltage measurement electrodes aligned between the current source and sink electrodes. The processing circuitry can sense bioimpedance based upon excitation current applied through the current source and sink electrodes and measured voltage obtained through the voltage measurement electrodes across a range of excitation frequencies. The electrodes can be conformal and stretchable.

Abstract: A brain machine interface system for use with an electroencephalogram to identify a behavioral intent of a person is disclosed. The system includes an electroencephalogram configured to sense electromagnetic signals generated by a brain of a person. The electromagnetic signals include a time component and a frequency component. A monitor monitors a response of the person to a stimulus and a characteristic of the stimulus. A synchronization module synchronizes the sensed electromagnetic signals with the response and the characteristic to determine a set of electromagnetic signals corresponding to the monitored response and the characteristic. A processor processes the set of electromagnetic signals and extracts feature vectors. The feature vectors define a class of behavioral intent. The processor determines the behavioral intent of the person based on the feature vectors. A brain machine interface and a method for identifying a behavioral intent of a person is also disclosed.

Abstract: A method of detecting a dynamic weather event includes the steps of: (a) receiving video images of a scene from a camera; (b) dividing each of the video images into multiple regions, in which a region is defined by a range of distances from the camera to objects in the scene; (c) selecting a region; and (d) segmenting the selected region into a plurality of three-dimensional (3D) image patches, in which each 3D image patch includes a time-sequence of T patches, with each patch comprised of N×M pixels, wherein N, M and T are integer numbers. The method also includes the following steps: measuring an image intensity level in each of the 3D image patches; masking 3D image patches containing image intensity levels that are above a first threshold level, or below a second threshold level; and extracting features in each 3D image patch that is not discarded by the masking step. Based on the extracted features, the method makes a binary decision on detecting a dynamic weather event.

Abstract: A method of detecting a dynamic weather event includes the steps of: (a) receiving video images of a scene from a camera; (b) dividing each of the video images into multiple regions, in which a region is defined by a range of distances from the camera to objects in the scene; (c) selecting a region; and (d) segmenting the selected region into a plurality of three-dimensional (3D) image patches, in which each 3D image patch includes a time-sequence of T patches, with each patch comprised of N×M pixels, wherein N, M and T are integer numbers. The method also includes the following steps: measuring an image intensity level in each of the 3D image patches; masking 3D image patches containing image intensity levels that are above a first threshold level, or below a second threshold level; and extracting features in each 3D image patch that is not discarded by the masking step. Based on the extracted features, the method makes a binary decision on detecting a dynamic weather event.

Abstract: A computer-assisted software engineering system facilitates the design, implementation, and execution of applications in cooperative processing environments. Design tools create, store, retrieve, and edit system specifications in a repository. Construction tools generate applications from the systems specification created by the design tools. A run-time execution architecture is provided for executing the applications on a plurality of computer hardware platforms. The run-time execution architecture includes pre-programmed presentation services for interacting with the user and pre-programmed distribution services for routing and transferring messages.

Abstract: A method of and apparatus for joining a small diameter tube to a large diameter tube. An indentation tool is used to inwardly deform the wall of a tube from the outside into the internal bore of the tube. The resulting indentation formed has an open end sized to receive the small diameter tube. The small diameter tube is then located within the indentation and mechanically joined by brazing or soldering such that the axis of the portion of the small diameter tube within the large diameter tube is roughly parallel to the axis of the large diameter tube.