Luminus Devices, Inc.

Rayvio Corporation

3newable LLC

Milan Singh Minsky

Alexei A Erchak

John W Graff

Scott W Duncan

Michael Hong Lim

Michael Gregory Brown

Henry Bowdoin Minsky

Max Carlson

Cyrus Shaoul

Matthew Weig

Julie Elizabeth Fouquet

Elefterios Lidorikis

Michael J Prichard

Robert C Walker

Nikolay I Nemchuk

Steven J Kommrusch

Alexander L Pokrovskiy

Lars Elof Rosenblad

A method for training a learning system to identify components of time-based data streams includes processing, by a machine vision component in communication with a learning system, a video file to detect at least one object in the video file. The method includes generating by the machine vision component an output including data relating to the at least one object and the video file. The method includes analyzing, by a learning system, the output. The method includes identifying, by the learning system, an unidentified object in the processed video file.

Methods and systems for training and execution of improved learning systems for identification of components in time-based data streams

A computer vision learning system and corresponding computer-implemented method extract meaning from image content. The computer vision learning system comprises at least one image sensor that transforms light sensed from an environment of the computer vision learning system into image data representing a scene of the environment. The computer vision learning system further comprises a digital computational learning system that includes a network of actor perceiver predictor (APP) nodes and a library of visual methods available to the APP nodes for applying to the image data. The digital computational learning system employs the network in combination with the library to determine a response to a query and outputs the response determined. The query is associated with the scene. The computer vision learning system is capable of answering queries not just about what is happening in the scene, but what would happen based on the scene in view of hypothetical conditions and/or actions.

Computer vision learning system

A wave energy converter comprises a power generator, characterized by an axial length along a longitudinal axis; the power generator being configured to tilt about a horizontal axis perpendicular to the longitudinal axis. The tilt results in a conversion of kinetic energy, present in a group of water waves causing the tilt, to electrical energy. The axial length is less than approximately one quarter of the average wavelength expected to be encountered in a dominant sub-group of waves within the group of waves. The power generator generates power independent of whether or not the wave energy converter is tethered to any solid object at a position that is fixed independent of water motion.

Compact wave energy converter

A portable water purification device comprises a portable power supply, an ultraviolet light source coupled to the portable power supply, wherein the ultraviolet light source is configured to output ultraviolet light, a container coupled to the ultraviolet light source, wherein the container is configured to hold water, and wherein the container is configured to reflect ultraviolet light, and an indicator configured to output a visual indication when the ultraviolet light source is outputting ultraviolet light.

Portable UV-LED water purification system

Light-emitting devices (e.g., LEDs) and methods associated with such devices are provided. In some embodiments, the device includes a distribution of light-generating portions (including active regions) that are spatially localized and separated (e.g., horizontally or vertically) from one or more patterned light extraction portions. This arrangement can allow light generated by the device to propagate and pass through regions of low absorption (e.g., light-extraction portions) rather than in regions of high absorption (e.g., light-generating portions), which can enhance light emission.

Spatial localization of light-generating portions in LEDs

Light-emitting device methods are disclosed.

Light emitting device methods

Electronic devices involving contact structures, and related components, systems and methods associated therewith are described. Contact structures (also referred to as electrical contact structures or electrodes) are features on a device that are electrically connected to a power source. The power source can provide current to the device via the contact structures. The contact structures can be designed to improve current distribution in electronic devices. For example, the contact resistance of the contacts may be modified to improve current distribution (e.g., by controlling the shape and/or structure and/or composition of the contacts). The contact structures may include an intervening layer (e.g., a non-ohmic layer) positioned between a surface of the device and a conductive portion extending from a conductive pad. The intervening layer and/or conductive portions may be designed to have certain shapes (e.g., non-linear shapes) that promote current flow from the conductive pad towards the ends of the contacts to increase current spreading. The intervening layer can also reduce light generation underneath the light absorbing contacts to allow a greater percentage of the generated light to emerge from the surface of the device. Advantageously, devices including contact structures of the invention can increase uniformity of light emission and/or otherwise improve performance. As such, these contact structures are particularly suitable for use in a variety of light-emitting devices, including LEDs.

Electronic device contact structures

Light-emitting devices, and related components, processes, systems and methods are disclosed.

Light emitting device processes

A method includes disposing a planarization layer on a surface of a layer of semiconductor material and disposing a lithography layer on a surface of the planarization layer. The method also includes performing nanolithography to remove at least a portion of the planarization layer, at least a portion of the lithography layer and at least a portion of the layer of semiconductor material, thereby forming a dielectric function in the surface of the layer of semiconductor material that varies spatially according to a pattern.

Growing community of inventors

Newton, MA, United States of America

Milan Singh Minsky