Abstract: The various implementations described herein include methods, devices, and systems for automatic audio equalization. In one aspect, a method is performed at an electronic device that includes speakers, microphones, processors and memory. The electronic device outputs audio user content from the speakers and automatically equalizes subsequent audio output of the device without user input. The automatic equalization includes: (1) obtaining audio content signals, including receiving outputted audio content at each microphone; (2) determining from the audio content signals phase differences between microphones; (3) obtaining a feature vector based on the phase differences; (4) obtaining a frequency correction from a correction database based on the obtained feature vector; and (5) applying the obtained frequency correction to the subsequent audio output.

Abstract: Disclosed is apparatus and method for motion tracking of a subject in medical brain imaging. The method comprises providing a light projector and a first camera; projecting a first pattern sequence (S1) onto a surface region of the subject with the light projector, wherein the subject is positioned in a scanner borehole of a medical scanner, the first pattern sequence comprising a first primary pattern (P1,1) and/or a first secondary pattern (P1,2); detecting the projected first pattern sequence (S1?) with the first camera; determining a second pattern sequence (S2) comprising a second primary pattern (P2,1) based on the detected first pattern sequence (S1?); projecting the second pattern sequence (S2) onto a surface region of the subject with the light projector; detecting the projected second pattern sequence (S2?) with the first camera; and determining motion tracking parameters based on the detected second pattern sequence (S2?).

Abstract: The various implementations described herein include methods, devices, and systems for automatic audio equalization. In one aspect, a method is performed at an electronic device that includes speakers, microphones, processors and memory. The electronic device outputs audio user content from the speakers and automatically equalizes subsequent audio output of the device without user input. The automatic equalization includes: (1) obtaining audio content signals, including receiving outputted audio content at each microphone; (2) determining from the audio content signals phase differences between microphones; (3) obtaining a feature vector based on the phase differences; (4) obtaining a frequency correction from a correction database based on the obtained feature vector; and (5) applying the obtained frequency correction to the subsequent audio output.

Abstract: A method and apparatus for surface scanning in medical imaging is provided. The surface scanning apparatus comprises an image source, a first optical fiber bundle comprising first optical fibers having proximal ends and distal ends, and a first optical coupler for coupling an image from the image source into the proximal ends of the first optical fibers, wherein the first optical coupler comprises a plurality of lens elements including a first lens element and a second lens element, each of the plurality of lens elements comprising a primary surface facing a distal end of the first optical coupler, and a secondary surface facing a proximal end of the first optical coupler.

Abstract: The various implementations described herein include methods, devices, and systems for automatic audio equalization. In one aspect, a method is performed at an electronic device that includes speakers, microphones, processors and memory. The electronic device outputs audio user content from the speakers and automatically equalizes subsequent audio output of the device without user input. The automatic equalization includes: (1) obtaining audio content signals, including receiving outputted audio content at each microphone; (2) determining from the audio content signals phase differences between microphones; (3) obtaining a feature vector based on the phase differences; (4) obtaining a frequency correction from a correction database based on the obtained feature vector; and (5) applying the obtained frequency correction to the subsequent audio output.

Abstract: A method and apparatus for surface scanning in medical imaging is provided. The surface scanning apparatus comprises an image source, a first optical fiber bundle comprising first optical fibers having proximal ends and distal ends, and a first optical coupler for coupling an image from the image source into the proximal ends of the first optical fibers, wherein the first optical coupler comprises a plurality of lens elements including a first lens element and a second lens element, each of the plurality of lens elements comprising a primary surface facing a distal end of the first optical coupler, and a secondary surface facing a proximal end of the first optical coupler.

Abstract: The various implementations described herein include methods, devices, and systems for automatic audio equalization. In one aspect, a method is performed at an electronic device that includes speakers, microphones, processors and memory. The electronic device outputs audio user content from the speakers and automatically equalizes subsequent audio output of the device without user input. The automatic equalization includes: (1) obtaining audio content signals, including receiving outputted audio content at each microphone; (2) determining from the audio content signals phase differences between microphones; (3) obtaining a feature vector based on the phase differences; (4) obtaining a frequency correction from a correction database based on the obtained feature vector; and (5) applying the obtained frequency correction to the subsequent audio output.

Abstract: Disclosed is apparatus and method for motion tracking of a subject in medical brain imaging. The method comprises providing a light projector and a first camera; projecting a first pattern sequence (S1) onto a surface region of the subject with the light projector, wherein the subject is positioned in a scanner borehole of a medical scanner, the first pattern sequence comprising a first primary pattern (P1,1) and/or a first secondary pattern (P1,2); detecting the projected first pattern sequence (S1?) with the first camera; determining a second pattern sequence (S2) comprising a second primary pattern (P2,1) based on the detected first pattern sequence (S1?); projecting the second pattern sequence (S2) onto a surface region of the subject with the light projector; detecting the projected second pattern sequence (S2?) with the first camera; and determining motion tracking parameters based on the detected second pattern sequence (S2?).

Abstract: Disclosed is apparatus and method for motion tracking of a subject in medical brain imaging. The method comprises providing a light projector and a first camera; projecting a first pattern sequence (S1) onto a surface region of the subject with the light projector, wherein the subject is positioned in a scanner borehole of a medical scanner, the first pattern sequence comprising a first primary pattern (P1,1) and/or a first secondary pattern (P1,2); detecting the projected first pattern sequence (S1?) with the first camera; determining a second pattern sequence (S2) comprising a second primary pattern (P2,1) based on the detected first pattern sequence (S1?); projecting the second pattern sequence (S2) onto a surface region of the subject with the light projector; detecting the projected second pattern sequence (S2?) with the first camera; and determining motion tracking parameters based on the detected second pattern sequence (S2?).

Abstract: The various implementations described herein include methods, devices, and systems for automatic audio equalization. In one aspect, a method is performed at an electronic device that includes speakers, microphones, processors and memory. The electronic device outputs audio user content from the speakers and automatically equalizes subsequent audio output of the device without user input. The automatic equalization includes: (1) obtaining audio content signals, including receiving outputted audio content at each microphone; (2) determining from the audio content signals phase differences between microphones; (3) obtaining a feature vector based on the phase differences; (4) obtaining a frequency correction from a correction database based on the obtained feature vector; and (5) applying the obtained frequency correction to the subsequent audio output.

Abstract: The various implementations described herein include methods, devices, and systems for automatic audio equalization. In one aspect, a method is performed at an electronic device that includes speakers, microphones, processors and memory. The electronic device outputs audio user content from the speakers and automatically equalizes subsequent audio output of the device without user input. The automatic equalization includes: (1) obtaining audio content signals, including receiving outputted audio content at each microphone; (2) determining from the audio content signals phase differences between microphones; (3) obtaining a feature vector based on the phase differences; (4) obtaining a frequency correction from a correction database based on the obtained feature vector; and (5) applying the obtained frequency correction to the subsequent audio output.

Abstract: Implementations include systems and methods for scoring candidates for set recommendation problems. An example method includes repeating, for each code in code arrays for items in a set of items, determining a most common value for the code. In some implementations, the method includes determining that the most common value occurs with a frequency that meets an occurrence threshold and adding the code and the most common value to set-inclusion criteria. In other implementations, the method includes determining a value for the code from a code array for a seed item and adding the code and the most common value to set-inclusion criteria when the value for the code from the code array for the seed item matches the most common value. The method may also include evaluating a similarity with a candidate item based on the set-inclusion criteria and basing a recommendation regarding the candidate item on the similarity.

Abstract: Implementations include systems and methods for scoring candidates for set recommendation problems. An example method includes repeating, for each code in code arrays for items in a set of items, determining a most common value for the code. In some implementations, the method includes determining that the most common value occurs with a frequency that meets an occurrence threshold and adding the code and the most common value to set-inclusion criteria. In other implementations, the method includes determining a value for the code from a code array for a seed item and adding the code and the most common value to set-inclusion criteria when the value for the code from the code array for the seed item matches the most common value. The method may also include evaluating a similarity with a candidate item based on the set-inclusion criteria and basing a recommendation regarding the candidate item on the similarity.

Abstract: A method and apparatus for surface scanning in medical imaging is provided. The surface scanning apparatus comprises an image source, a first optical fiber bundle comprising first optical fibers having proximal ends and distal ends, and a first optical coupler for coupling an image from the image source into the proximal ends of the first optical fibers, wherein the first optical coupler comprises a plurality of lens elements including a first lens element and a second lens element, each of the plurality of lens elements comprising a primary surface facing a distal end of the first optical coupler, and a secondary surface facing a proximal end of the first optical coupler.

Abstract: Disclosed is apparatus and method for motion tracking of a subject in medical brain imaging. The method comprises providing a light projector and a first camera; projecting a first pattern sequence (S1) onto a surface region of the subject with the light projector, wherein the subject is positioned in a scanner borehole of a medical scanner, the first pattern sequence comprising a first primary pattern (P1,1) and/or a first secondary pattern (P1,2); detecting the projected first pattern sequence (S1?) with the first camera; determining a second pattern sequence (S2) comprising a second primary pattern (P2,1) based on the detected first pattern sequence (S1?); projecting the second pattern sequence (S2) onto a surface region of the subject with the light projector; detecting the projected second pattern sequence (S2?) with the first camera; and determining motion tracking parameters based on the detected second pattern sequence (S2?).

Abstract: Novel food-grade cloning vectors comprising a nonsense mutation suppressor-encoding gene, which vector, when it is present in a lactic acid bacterial strain, permits such a strain to have an industrially appropriate growth rate and metabolic activity. The cloning vectors are useful when present in lactic acid bacteria used as starter cultures in the preparation of food or feed products, or a dairy flavor.

Abstract: A process and apparatus for allocating bits between the stages of a multi-stage digital image compression scheme with quantizer feedback is disclosed. The process selects a quantization schedule (from a finite number of possibilities) for all stages that minimizes an estimate of total distortion while keeping total bit demand below a constraint; uses said schedule to actually quantize one stage of the compression scheme; selects a new quantization schedule for the remaining stages using estimates for distortion and bit demand that are updated to reflect the quantization of the previous stage; actually quantizes the next stage according to the new quantization schedule; and continues recursively until it has chosen an actual quantization scale for every stage of the compression scheme.

Abstract: The invention relates to imaging methods for assessing quality or quantity parameters of particles in a sample, wherein the particles contain less than 106 analyte detectable positions. The method comprises 1) mixing the sample with a targeting species capable of binding an analyte position and a labelling agent, 2) arranging the sample in an exposing domain, allowing electromagnetic signals from the sample to pass to the exterior, 3) exposing a representation of said signals onto an array of detection elements, wherein the representation is subject to a linear enlargement, so that the ratio of the image of a linear dimension on the array of detection elements to the original linear dimension in the exposing domain is smaller than 20:1, 4) detecting the representation as intensities by said detection elements, 5) processing the intensities to identify the particles, and 6) obtaining the quality or quantity parameter.

Abstract: The invention relates to the field of detecting and optionally collecting and isolating rare event particles. The method according to the invention is based on relatively simple optical equipment, which requires a few and uncomplicated decisions for the user of the system. The method is based on the acquisition of an image of relatively low resolution and magnification of a large volume of sample and detecting the presence or absence of the rare event particle. The method is then repeated with at least one further volume of sample. The method is particularly adapted for detection of white blood cells in leuko-depleted blood.

Abstract: A process and apparatus for allocating bits between the stages of a multi-stage digital image compression scheme with quantizer feedback is disclosed. The process selects a quantization schedule (from a finite number of possibilities) for all stages that minimizes an estimate of total distortion while keeping total bit demand below a constraint; uses said schedule to actually quantize one stage of the compression scheme; selects a new quantization schedule for the remaining stages using estimates for distortion and bit demand that are updated to reflect the quantization of the previous stage; actually quantizes the next stage according to the new quantization schedule; and continues recursively until it has chosen an actual quantization scale for every stage of the compression scheme.