Abstract

A method of manufacturing a porous part includes controlled freeze casting of a slurry. After freezing, a solvent in the slurry is removed by sublimation and the remaining material is sintered to form the porous part. Spatial and temporal control of thermal conditions at the boundary and inside of the mold can be controlled to create parts with controlled porosity, including size, distribution, and directionality of the pores. Porous parts with near-net-shape from ceramics, metals, polymers and other materials and their combinations can be created.

IPC Classes  ?

• B22F 3/11 - Making porous workpieces or articles
• B22F 1/107 - Metallic powder containing lubricating or binding agents; Metallic powder containing organic material containing organic material comprising solvents, e.g. for slip casting
• B22F 3/22 - Manufacture of workpieces or articles from metallic powder characterised by the manner of compacting or sintering; Apparatus specially adapted therefor for producing castings from a slip
• B28B 1/00 - Producing shaped articles from the material
• B29C 39/02 - Shaping by casting, i.e. introducing the moulding material into a mould or between confining surfaces without significant moulding pressure; Apparatus therefor for making articles of definite length, i.e. discrete articles
• B29C 39/38 - Heating or cooling
• B29C 39/44 - Measuring, controlling or regulating

Abstract

A tactile sensor utilizes a magnet embedded in an elastomer and a magnetometer for measuring a strength of a magnetic field emitted by the magnet. The elastomer may include two layers, with a first layer having a lower modulus than the second layer. When two layers are used, the magnet can be positioned at an interface between the layers. The use of a softer outer layer increases the sensitivity of the sensor. Sensitivity can be further increased by including features or a pattern of features on the surface of the elastomer. The features, which can be similar to fingerprints on a human hand, are adapted to provide vibrational information caused by the surface roughness of a material. The sensor provides material characterization and can be used to identify the material in contact with the sensor. The sensor can be fabricated using molding techniques.

Abstract

Disclosed herein is a system and method for the automatic detection of persons engaged in the open carry of firearms at a venue. The system and method comprise strategically placed cameras at the venue which are connected to edge devices which extract frames from video generated by the cameras. The video frames are sent to a server for analysis by an AI/ML model trained to detect firearms and, specifically, to detect persons carrying firearms. If a person wielding a firearm is detected in any image, an alert is raised and local authorities are automatically contacted. The system is designed to run continuously such as to be able to quickly detect a person in a venue carrying a firearm.

IPC Classes  ?

• G06V 20/52 - Surveillance or monitoring of activities, e.g. for recognising suspicious objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G08B 21/02 - Alarms for ensuring the safety of persons

Abstract

Disclosed herein is a system and method for data augmentation for general object recognition which preserves the class identity of the augmented data. The system comprises an image recognition network an image generation network that take as input ground truth images and classes respectively and which generates a predicted class and an augmented image. A discriminator evaluates the predicted class and augmented image and provides feedback to the image recognition network and the image generation network.

IPC Classes  ?

• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06V 40/16 - Human faces, e.g. facial parts, sketches or expressions

Abstract

Disclosed herein is an Overmoded Bulk Acoustic Resonator (OBAR) and a solidly-mounted OBAR (SBAR), which operate in a partially transduced 2nd overtone split between piezoelectric and electrode layers using dual all metal Bragg mirrors. The devices may be deployed in a series configuration. The devices have arbitrarily thick electrodes to minimize ohmic loss and bandwidths high enough to meet filtering requirements of 5G networks. The devices provide sharp filtering which can be performed directly at each antenna element in a form factor much smaller than the half-wavelength separation between adjacent antenna elements required when using electromagnetic resonators.

IPC Classes  ?

• H03H 9/17 - Constructional features of resonators consisting of piezoelectric or electrostrictive material having a single resonator
• H03H 9/02 - Networks comprising electromechanical or electro-acoustic elements; Electromechanical resonators - Details
• H03H 9/56 - Monolithic crystal filters

Abstract

Disclosed herein is a framework for the modeling and design of materials based on differentiable programming, where the models can be trained by gradient-based optimization. Within this framework, all the components are differentiable and can be seamlessly integrated and unified with deep learning. The framework can design and optimize materials for a variety of applications.

IPC Classes  ?

• G06F 30/27 - Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model

Abstract

A computer-implemented method of learning a policy for an agent. The method includes: receiving an initialized first neural network, in particular a Q-functionor value-function, an initialized second neural network, auxiliary parameters, and the initialized policy; repeating the following steps until a termination condition is fulfilled: sampling a plurality of pairs of states, actions, rewards and new states from a storage. Sampling actions for the current states, and actions for the new sampled states; computing features from a penultimate layer of the first neural network based on the sampled states and actions and updating the second neural network and the auxiliary parameters as well as updating parameters the first neural network using a re-weighted loss.

IPC Classes  ?

• G06N 3/092 - Reinforcement learning

Abstract

The present disclosure relates to structures and methods of use of textiles for protection, and more particularly. relates to single layer knitted structures that can be worn as garments to block mosquito bites. The knit structures of the present embodiments can include single layer structures having a unique geometric combination of yarn properties and textiles to block mosquito bites in a single. comfortable layer of fabric. The knit structures can include one or more controllable parameters that can be adjusted to increase and/or decrease the bite blocking ability of the knit structure.

IPC Classes  ?

• D04B 1/18 - Other fabrics or articles characterised primarily by the use of particular thread materials elastic threads
• A01M 29/00 - Scaring or repelling devices, e.g. bird-scaring apparatus
• A41D 27/00 - OUTERWEAR; PROTECTIVE GARMENTS; ACCESSORIES - Details of garments or of their making
• D04B 1/16 - Other fabrics or articles characterised primarily by the use of particular thread materials synthetic threads

Abstract

Disclosed herein is a system and method for reducing false positives in object detection frameworks. A human form view of objects detected by the object detection framework and indicates the object is a false positive. When an indication of a false positive been received, a feature representation of displayed object stored in the gallery. During an inference or testing phase, the gallery is searched for a feature representation matching the feature representation of the detected objects, and, if a match is found, the detected object is deemed to be a false positive and is not displayed to the user.

IPC Classes  ?

• G06V 10/778 - Active pattern-learning, e.g. online learning of image or video features
• G06V 10/75 - Image or video pattern matching; Proximity measures in feature spaces using context analysis; Selection of dictionaries

Abstract

A system includes an inertial sensing device having an inertial sensor and plurality of stress sensors configured to measure stress applied to the inertial sensing device, and at least one computing device configured to: receive sensor data from the inertial sensor and the plurality of stress sensors; and determine a drift compensation of the inertial sensor based on the sensor data. Other systems, methods, and devices are disclosed.

IPC Classes  ?

• G01D 3/036 - Measuring arrangements with provision for the special purposes referred to in the subgroups of this group mitigating undesired influences, e.g. temperature, pressure on measuring arrangements themselves
• B81B 7/02 - Microstructural systems containing distinct electrical or optical devices of particular relevance for their function, e.g. microelectro-mechanical systems (MEMS)
• G01P 15/02 - Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration by making use of inertia forces
• G01P 21/00 - Testing or calibrating of apparatus or devices covered by the other groups of this subclass
• G06N 3/08 - Learning methods

Abstract

Disclosed herein is a system and method using an equivariant neural network for predicting quantum mechanical charge density. The equivariant neural network serves as a surrogate for the density-functional theory used to calculate a selfconsistent field and predicts the central observable charge density, which, in addition to enabling force calculations, can also accelerate DFT itself and compute a full range of chemical properties.

IPC Classes  ?

• G16C 20/30 - Prediction of properties of chemical compounds, compositions or mixtures
• G16C 20/70 - Machine learning, data mining or chemometrics

Abstract

A near-field probe (and associated method) compatible with near-infrared electromagnetic radiation and high temperature applications above 300°° C. (or 500° C. in some applications) includes an optical waveguide and a photonic thermal emitting structure comprising a near-field thermally emissive material coupled to or part of the optical waveguide. The photonic thermal emitting structure is structured and configured to emit near-field energy responsive to at least one environmental parameter of interest, and the near-field probe is structured and configured to enable extraction of the near-field energy to a far-field by coupling the near-field energy into one or more guided modes of the optical waveguide.

IPC Classes  ?

• G01J 1/04 - Optical or mechanical part
• G02B 6/42 - Coupling light guides with opto-electronic elements

Abstract

A method for learning a representation of a sequence of frames includes encoding, via an encoder network, the sequence of frames to obtain a set of feature maps and extracting, a motion-guided slot learning mechanism, mid-level features from the set of feature maps. The method further includes quantizing the mid-level features via a vector quantization process to obtain a set of tokens, and decoding, via a decoder network, the tokens to obtain a reconstructed sequence of frames. The method still further includes optimizing a combination of a reconstruction loss and a motion loss to train the encoder and decoder networks.

IPC Classes  ?

• G06T 7/246 - Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
• G06V 20/58 - Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads

Abstract

Disclosed herein is a system architecture that structures commodity heterogeneous interconnected computing platforms around universal object abstractions, which are a fundamental system abstraction and building block that provides practical and provable end-to-end guarantees of security, correctness, and timeliness for the platform.

IPC Classes  ?

• G06F 21/44 - Program or device authentication
• G06F 9/48 - Program initiating; Program switching, e.g. by interrupt
• G06F 11/36 - Preventing errors by testing or debugging of software
• G06F 21/60 - Protecting data

Abstract

In an example, a method may include deforming a first ray associated with a dynamic object at a first time using a first neural network and a latent code to obtain a deformed ray. The method may also include obtaining a hyperspace code associated with the first ray by inputting the first ray, the first time, and the latent code into a second neural network. The method may further include sampling one or more points from the deformed ray. The method may also include combining the sampled points and the hyperspace code into a network input. The method may further include inputting the network input into a third neural network to obtain RGB values for rendering images of a three-dimensional scene representative of the dynamic object at a second time.

IPC Classes  ?

• G06T 13/40 - 3D [Three Dimensional] animation of characters, e.g. humans, animals or virtual beings
• G06T 3/40 - Scaling of a whole image or part thereof
• G06T 15/06 - Ray-tracing

Abstract

A method for sequential point cloud forecasting is described. The method includes training a vector-quantized conditional variational autoencoder (VQ-CVAE) framework to map an output to a closest vector in a discrete latent space to obtain a future latent space. The method also includes outputting, by a trained VQ-CVAE, a categorical distribution of a probability of V vectors in a discrete latent space in response to an input previously sampled latent space and past point cloud sequences. The method further includes sampling an inferred future latent space from the categorical distribution of the probability of the V vectors in the discrete latent space. The method also includes predicting a future point cloud sequence according to the inferred future latent space and the past point cloud sequences. The method further includes denoising, by a denoising diffusion probabilistic model (DDPM), the predicted future point cloud sequences according to an added noise.

IPC Classes  ?

• G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

Computer-based systems and methods for discovering neighborhood clusters in a geographic region, where the clusters have a mix of venues and are determined based on venue check-in data. The mix of venues for the clusters may be based on the social similarity between pairs of venues; or emblematic of certain neighborhood typologies; or emblematic of temporal check-in pattern types; or combinations thereof. The neighborhood clusters that are so discovered through venue-check in data could be used for many commercial and civic purposes.

IPC Classes  ?

• G06Q 30/0204 - Market segmentation

Abstract

Disclosed herein is a method for optimizing electrode placement that directly exploits the thresholding phenomenon of neurons. The method employs a loss function which only becomes non-zero when the electric field is above a user-specified threshold in the cancel region, thereby allowing for fields which can have significant non-zero current in the cancel region, but still provide more focused neural activation.

IPC Classes  ?

• A61N 1/36 - Applying electric currents by contact electrodes alternating or intermittent currents for stimulation, e.g. heart pace-makers
• A61N 1/04 - Electrodes

Abstract

Methods and systems are for generating a process map for forming a structure, the process map usable for controlling additive manufacturing with the structure. The methods and systems are configured for obtaining a value of at least one process parameter for controlling thermo-fluid dynamics of the structure for melting material; heating, in accordance with the value of the at least one process parameter, the structure; obtaining a high-speed imaging of a melt pool; determining changes in a topological shape of the melt pool from the imaging; determining an absence or a presence of a defect in the structure representing whether the material is successful added to the structure; and generating a process map that correlates the value of the at least one process parameter to the absence or the presence of the defect in the structure.

IPC Classes  ?

• B22F 10/85 - Data acquisition or data processing for controlling or regulating additive manufacturing processes
• B22F 12/90 - Means for process control, e.g. cameras or sensors
• B29C 64/393 - Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes
• B33Y 50/02 - Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes
• B22F 10/36 - Process control of energy beam parameters
• G06T 7/00 - Image analysis
• G06N 3/0499 - Feedforward networks

Abstract

Provided are systems, methods, and apparatuses for passive light interferometry. A system includes a mirror, a first sensor arranged to capture light from a light source reflected by the mirror, a controller in communication with the first sensor, the controller configured to cause rotation of the mirror based on movement of the light, an interferometer arranged in an optical path of the light source reflected by the mirror, and a beam splitter arranged in an optical path between the mirror and the interferometer.

IPC Classes  ?

• G01N 21/35 - Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light

Abstract

Lipid-containing particles and formulations containing the lipid-containing particles are provided. Methods of delivery of therapeutic agents to the pancreas using the lipid-containing particles are provided.

IPC Classes  ?

• A61K 9/127 - Liposomes
• A61K 9/51 - Nanocapsules
• A61K 31/711 - Natural deoxyribonucleic acids, i.e. containing only 2'-deoxyriboses attached to adenine, guanine, cytosine or thymine and having 3'-5' phosphodiester links

Abstract

A method for detecting an application progress and handling an application failure in a distributed system. The method includes: monitoring an interaction between modules of at least one application, the at least one application being deployed across different physical nodes, the interaction being carried out by exchanging messages between the modules using a message broker, the monitoring being carried out at least partially using the message broker; detecting the application progress based on the monitoring; initiating a failure handling based on the detecting.

IPC Classes  ?

• G07C 5/00 - Registering or indicating the working of vehicles

Abstract

A method for providing a secondary backup application as a backup for a primary application, particularly for a predictive standby in distributed systems. The method includes the following steps are carried out by a predictive standby manager: receiving application-specific state data, the application-specific state data being obtained from monitoring a state of the primary application; receiving platform-specific state data, the platform-specific state data being obtained from monitoring a state of at least one platform that executes the primary application; initiating a backup process for using the secondary backup application based on the received application-specific state data and the platform-specific state data.

IPC Classes  ?

• G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result

Abstract

A system and method can be used by blind and low-vision users to navigate and interact in an environment using conversational speech. The system and method integrate object detection, spatial anchors, and conversation to support both independent navigation and interaction. Object detection can be accomplished by capturing data from sensors on an electronic device carried by the user. Spatial anchors can include information relevant to requests from the user. The use of conversational speech permits an exchange of information that is not cognitively overwhelming.

IPC Classes  ?

• G01C 21/20 - Instruments for performing navigational calculations
• G06F 3/16 - Sound input; Sound output
• G10L 13/027 - Concept to speech synthesisers; Generation of natural phrases from machine-based concepts

Abstract

Cationic compounds and methods of making and using same. A cationic compound comprises one or more norborenyl group(s) and one or more cationic group(s). The cationic groups(s) is/are chosen from phosphonium groups, imidazolium groups, cyclic ammonium groups, and the like, and any combination thereof. The cationic group(s) is/are independently covalently linked or covalently linked via a linking group to the norbornene ring of a norborenyl group. In various examples, one or more cationic compound(s) is/are used as a monomer or monomers in a polymerization, such as, for example, a direct insertion polymerization or the like, to form a cationic polymer. In various examples, an anionic exchange membrane, which may be used in a device, such as, for example, in a sensor, an actuator, an energy-storage device, or an energy-generating device, or the like, comprising one or more cationic polymer(s).

IPC Classes  ?

• C07F 9/54 - Quaternary phosphonium compounds
• C07D 295/02 - Heterocyclic compounds containing polymethylene-imine rings with at least five ring members, 3-azabicyclo [3.2.2] nonane, piperazine, morpholine or thiomorpholine rings, having only hydrogen atoms directly attached to the ring carbon atoms containing only hydrogen and carbon atoms in addition to the ring hetero elements

Abstract

Materials and methods for labeling and isolating particular cell types from mixed cell populations are provided herein. Also provided herein are methods for generating data representing a synthetic genetic sequence configured for labeling at least one cell type by causing expression of a marker in the at least one cell type.

IPC Classes  ?

• G16B 20/00 - ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• G16B 30/10 - Sequence alignment; Homology search
• G16B 30/20 - Sequence assembly
• G16B 35/20 - Screening of libraries
• G16B 40/10 - Signal processing, e.g. from mass spectrometry [MS] or from PCR
• G16B 40/30 - Unsupervised data analysis
• C40B 40/08 - Libraries containing RNA or DNA which encodes proteins, e.g. gene libraries
• G06N 20/00 - Machine learning

Abstract

Methods are provided for rapid processing of tissue samples, including thick tissue, organs, and organisms, for expansion microscopy.

IPC Classes  ?

• G01N 1/28 - Preparing specimens for investigation
• G01N 1/36 - Embedding or analogous mounting of samples
• G02B 21/36 - Microscopes arranged for photographic purposes or projection purposes

Abstract

The invention relates to a method (100) for embedding at least one application (20) into a real-time environment, the real-time environment being provided by a memory-programmable controller (31), and the method having the following steps: - receiving (101) the at least one application (20), said at least one application (20) being received as an intermediate representation, - providing (102) a sandbox (80) for the at least one received application (20), and - running (103) the at least one application (21), which is run in the sandbox, wherein the step of running (103) the application is carried out on the basis of an interpretation of the at least one application (21) run in the sandbox using a virtualization runtime (35) of the real-time environment. The intermediate representation is expanded by the runtime (35) in order to provide at least one real-time and/or security function for the at least one application (21) run in the sandbox.

IPC Classes  ?

• G06F 21/53 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure by executing in a restricted environment, e.g. sandbox or secure virtual machine
• G06F 21/54 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure by adding security routines or objects to programs

Abstract

Electrochemical devices, and associated materials and methods, are generally described. In some embodiments, an electrochemical device comprises an electroactive material. The electroactive material may comprise an alloy having a solid phase and a liquid phase that co-exist with each other. As a result, such a composite electrode may have, in some cases, the mechanical softness to permit both high energy densities and an improved current density as compared to, for example, a substantially pure metal electrode.

IPC Classes  ?

• H01M 4/40 - Alloys based on alkali metals
• H01M 10/0525 - Rocking-chair batteries, i.e. batteries with lithium insertion or intercalation in both electrodes; Lithium-ion batteries
• H01M 10/36 - Accumulators not provided for in groups
• H01M 10/44 - Methods for charging or discharging

Abstract

Methods and materials for making and using apical-out ciliated organoids (e.g., apical-out airway organoids) are provided herein.

IPC Classes  ?

• C12N 5/071 - Vertebrate cells or tissues, e.g. human cells or tissues
• C12M 1/32 - Inoculator or sampler multiple field or continuous type
• G01N 33/50 - Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing

Abstract

Provided is a system, method, and apparatus for steering light. The system includes a medium arranged in a path of at least one light beam and at least one controller configured to steer the at least one light beam by modulating a sonic waveform in the medium.

IPC Classes  ?

• G02B 1/06 - Optical elements characterised by the material of which they are made; Optical coatings for optical elements made of fluids in transparent cells
• G02F 1/33 - Acousto-optical deflection devices
• B06B 1/06 - Processes or apparatus for generating mechanical vibrations of infrasonic, sonic or ultrasonic frequency making use of electrical energy operating with piezoelectric effect or with electrostriction
• B06B 1/20 - Processes or apparatus for generating mechanical vibrations of infrasonic, sonic or ultrasonic frequency making use of a vibrating fluid
• G01H 9/00 - Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by using radiation-sensitive means, e.g. optical means

Abstract

Disclosed herein is a system and method implementing a trusted IoT security gateway architecture, based on a microhypervisor, that provides a guarantee that the correct security protections are applied to each IoT device's network traffic at all times, including when under attack. The disclosed architecture provides robust trust properties to a broad range of legacy hardware platforms utilizing existing software with a reasonable performance overhead.

IPC Classes  ?

• H04W 12/108 - Source integrity
• H04W 12/106 - Packet or message integrity
• H04W 84/18 - Self-organising networks, e.g. ad hoc networks or sensor networks

Abstract

Disclosed herein is a formalized programming framework using memory compartmentalization and other properties of certified compilers to provide that security guarantees verified at the source level also hold on the compiled code. A trusted execution environment formulated as a collection of objects that access separate memory locations and conform to a public interface.

IPC Classes  ?

• G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
• G06F 9/30 - Arrangements for executing machine instructions, e.g. instruction decode
• G06F 9/448 - Execution paradigms, e.g. implementations of programming paradigms
• G06F 11/36 - Preventing errors by testing or debugging of software
• G06F 21/12 - Protecting executable software

Abstract

Disclosed herein is a novel system that enables focus tunability with spatial selectivity, in which the lens appears to have different focal lengths over different parts of the display. This is achieved with an improved and modified version of a Lohmann lens that enables spatial selectivity, while replacing mechanical motion with optical translation using a phase spatial light modulator.

IPC Classes  ?

• G02F 1/015 - Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics for the control of the intensity, phase, polarisation or colour based on semiconductor elements with at least one potential jump barrier, e.g. PN, PIN junction
• G06F 3/048 - Interaction techniques based on graphical user interfaces [GUI]

Abstract

A novel method for using the widely-used electroencephalography (EEG) systems to detect and localize silences in the brain is disclosed. The method detects the absence of electrophysiological signals, or neural silences, using noninvasive scalp electroencephalography (EEG) signals. This method can also be used for reduced activity localization, activity level mapping throughout the brain, as well as mapping activity levels in different frequency bands. By accounting for the contributions of different sources to the power of the recorded signals and using a hemispheric baseline approach and a convex spectral clustering framework, the method permits rapid detection and localization of regions of silence in the brain using a relatively small amount of EEG data.

IPC Classes  ?

• A61B 5/372 - Analysis of electroencephalograms
• A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging

Abstract

Disclosed herein is a system and method for training a subject to self-regulate neural variability. The system and method implements a prefrontal cortex brain-computer interface (BCI) and a method that allows subjects to use neurofeedback to produce a desired neural activity by regulation of their arousal levels to stabilize their neural activity across a timescale of seconds or minutes. The system comprises a prefrontal cortex brain-computer interface (BCI) to train subjects to use neurofeedback to produce desired neural activity. Subjects used the disclosed system and method, which includes BCI feedback, to self-regulate their arousal levels and successfully stabilize their neural activity.

IPC Classes  ?

• A61B 5/378 - Visual stimuli
• A61B 5/16 - Devices for psychotechnics; Testing reaction times
• A61N 5/06 - Radiation therapy using light

Abstract

Provided are systems, methods, and computer program products for extracting features from imaging biomarkers with machine-learning models. The method includes training a first artificial intelligence (AI) model based on first training data including images labeled with imaging biomarkers, the first AI model trained to identify a plurality of imaging biomarker features in at least one image, training a second AI model based on second training data including sets of imaging biomarker features associated with task-specific labels, the second AI model trained to identify at least one task-specific feature based at least partially on a set of imaging biomarker features, processing at least one input image with the first AI model to generate a first AI model output, and processing the first AI model output with the second AI model to generate a second AI model output.

IPC Classes  ?

• G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
• G06T 7/00 - Image analysis
• G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

A method of forming a microneedle array can include forming a sheet of material having a plurality of layers and micromilling the sheet of material to form a microneedle array. At least one of the plurality of layers can include a bioactive component, and the microneedle array can include a base portion and plurality of microneedles extending from the base portion.

IPC Classes  ?

• A61L 31/14 - Materials characterised by their function or physical properties
• A61L 31/04 - Macromolecular materials
• A61L 31/06 - Macromolecular materials obtained otherwise than by reactions only involving carbon-to-carbon unsaturated bonds
• A61L 31/16 - Biologically active materials, e.g. therapeutic substances
• A61M 37/00 - Other apparatus for introducing media into the body; Percutany, i.e. introducing medicines into the body by diffusion through the skin
• B23C 3/00 - Milling particular work; Special milling operations; Machines therefor

Abstract

Disclosed here are various techniques for improving the testing and training of datasets comprising sequences of skeletal representations performing various actions. The dataset can be denoised by applying various techniques to determine noisy frames within each sequence and eliminating the sequences from the dataset when the number of noisy frames in the sequence is too large. In addition, the dataset may be augmented by various data augmentation techniques to manipulate the skeletal representations, after denoising.

IPC Classes  ?

• G06T 5/00 - Image enhancement or restoration
• G06T 3/40 - Scaling of a whole image or part thereof
• G06T 3/60 - Rotation of a whole image or part thereof
• G06T 5/20 - Image enhancement or restoration by the use of local operators
• G06T 7/20 - Analysis of motion
• G06T 7/60 - Analysis of geometric attributes

Abstract

Disclosed herein is a method of reducing the complexity of a neural network using PRC-NPTN layers by applying a pruning technique to remove a subset of filters in the network based on the importance of individual filters to the accuracy of the network, which is determined by the frequency with which the response of the filter is activated.

IPC Classes  ?

• G06N 3/082 - Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections
• G06N 3/04 - Architecture, e.g. interconnection topology

Abstract

Disclosed herein is a system and method implementing a battery avionics system for integrating battery monitoring, control, and management functions with an avionics system of an aircraft. The system uses a model implementing a battery pack digital twin, which is a continuous simulation of the operation of the battery pack within the aircraft, receives data regarding the battery pack generated by the digital twin model and provides optimized parameters to the battery avionics system. The system enables high precision, cell-level resolution control of the battery pack. The system estimates the state of charge, state of health, state of safety, and state of function of the cells and the battery pack as a whole and uses this information to manage the battery pack, given a particular flight profile of the aircraft.

IPC Classes  ?

• B60L 58/18 - Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries of two or more battery modules
• B64D 27/357 - using batteries
• G06F 30/20 - Design optimisation, verification or simulation
• H01M 10/42 - Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
• H02J 7/00 - Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries

Abstract

A method for carrying out a decision for upgrading and/or deploying software on multiple heterogenous devices. The method includes: receiving a request to upgrade and/or deploy software on at least one of the devices; initiating a connection to the at least one of the devices; initiating a process for determining at least one capability of the at least one connected device for executing the software, the initiating being carried out via the connection, the process being initiated for being executed by the at least one connected device; receiving a result of the initiated process; and carrying out the decision for the upgrade and/or deployment of the software based on the received result.

IPC Classes  ?

• G06F 8/65 - Updates

Abstract

Provided herein are methods of preparing gamma-peptide nucleic acid monomers, and methods of synthesizing gamma-peptide nucleic acid oligomers.

IPC Classes  ?

• C07K 14/00 - Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof

Abstract

Provided herein is a method of mounting tissue or cell sample for microscopic analysis, a kit for the preparation of a microscope slide assembly, and microscope slide assemblies. The tissue or cell samples can be expanded tissue or cell samples embedded in a swelled polymer.

IPC Classes  ?

• G01N 1/36 - Embedding or analogous mounting of samples
• G01N 1/28 - Preparing specimens for investigation
• G02B 21/00 - Microscopes

Abstract

A photonic crystal for detection of an analyte includes: a first layer including a first material with a first refractive index; a second layer over the first layer and including a second material with a second refractive index that is higher than the first refractive index; where the second layer includes a hole, the hole including: a first diameter from an outer surface of the second layer to a first hole depth; a second diameter from the first hole depth to a second hole depth; where the first diameter is larger than the second diameter; and a member of a binding pair with the analyte linked to a surface of the hole.

IPC Classes  ?

• G01N 21/77 - Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated by observing the effect on a chemical indicator
• G01N 21/35 - Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
• G01N 21/3577 - Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing liquids, e.g. polluted water
• G01N 21/47 - Scattering, i.e. diffuse reflection
• G01N 33/543 - Immunoassay; Biospecific binding assay; Materials therefor with an insoluble carrier for immobilising immunochemicals

Abstract

Provided is a system, method, and computer program product for training a machine-learning model. The method includes labeling each object of a plurality of objects with a probabilistic confidence label including a probability classification score for each class of at least two classes, resulting in a plurality of probabilistic confidence labels associated with the plurality of objects, and training, with at least one computing device, the machine-learning model based on the plurality of objects and the plurality of probabilistic confidence labels.

IPC Classes  ?

• G06N 3/08 - Learning methods
• G06N 3/048 - Activation functions

Abstract

Provided are systems, methods, and computer program products for segmenting an image. A method includes segmenting each image in a sequence of images including a needle into a needle and at least one needle artifact based on processing each image with a first machine-learning model trained with a plurality of hard labels for a plurality of images, resulting in a plurality of hard-labeled images, transforming each hard-labeled image of the plurality of hard-labeled images into a soft-labeled image including pixel values corresponding to an effect of the at least one needle artifact, resulting in a plurality of soft-labeled images, and segmenting at least one image of the sequence of images based on processing the at least one image with a second machine-learning model trained at least partially with the plurality of soft-labeled images.

IPC Classes  ?

• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G06T 7/10 - Segmentation; Edge detection
• G06V 10/762 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using clustering, e.g. of similar faces in social networks

Abstract

Disclosed herein is a system providing a mixed reality combination system that pairs augmented reality technology and an inertial measurement unit sensor with 3D printed objects such that user motions tracked by the inertial measurement unit as the user interacts with the 3D printed object is reflected in a virtual environment display of dynamic 3D imagery and augmented reality imagery.

IPC Classes  ?

• G06T 19/00 - Manipulating 3D models or images for computer graphics
• A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
• G02B 27/01 - Head-up displays
• G06F 30/23 - Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
• G06V 10/10 - Image acquisition
• G06V 40/20 - Movements or behaviour, e.g. gesture recognition

Abstract

Provided are methods including the steps of receiving, with at least one computing device, an image of a portion of a subject, assigning: with the at least one computing device and based on a machine-learning model, a label to one or more pixels of the image to generate a diagnostically segmented image: and classifying, with the at least one computing device and based on a machine-learning model, the diagnostically segmented image and the one or more pixels into at least one class to generate a classified image, wherein the classified image includes a classification label indicating a clinical assessment of the portion of the subject and wherein the one or more pixels include a clinical label indicating a diagnosis of a portion of a subject contained within each pixel, based on the diagnostically segmented image having labels assigned to each pixel of the segmented image.

IPC Classes  ?

• G06V 10/26 - Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
• G06T 7/00 - Image analysis
• G06T 7/11 - Region-based segmentation
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06V 20/70 - Labelling scene content, e.g. deriving syntactic or semantic representations

Abstract

Ruggedized particles or live cells are provided. The particles or cells comprise a cross-linked matrix of nucleic acid and/or nucleic acid analog nanostructures forming a shell about the particle or cell. Methods of making and using the ruggedized particles or live cells are provided. The ruggedized particles or cells may be decorated with environmental sensors, for example, which are prepared from nucleic acid and/or nucleic acid analog nanostructures and may include a FRET pair.

IPC Classes  ?

• C12N 5/00 - Undifferentiated human, animal or plant cells, e.g. cell lines; Tissues; Cultivation or maintenance thereof; Culture media therefor
• C12N 5/074 - Adult stem cells

Abstract

Disclosed herein is a system and method for controlling a high-density storage system comprising a plurality of layers, each layer comprising a plurality of rows for storing a plurality of coupled totes and one or more carriers located on opposite ends of each layer, each carrier being multiple rows wide, each carrier capable of retrieving totes from a row in the layer, depositing a tote into a row in the layer and shifting totes from one row to another within the layer.

IPC Classes  ?

• B25J 9/16 - Programme controls
• B65G 1/04 - Storage devices mechanical
• B65G 47/90 - Devices for picking-up and depositing articles or materials
• G06Q 10/087 - Inventory or stock management, e.g. order filling, procurement or balancing against orders

Abstract

Disclosed herein is a mobile high-density storage system comprising a storage structure deployed in a mobile container, for example, a tractor-trailer or a delivery van. The mobile storage structure optimizes the arrangement of totes within the structure while mobile such that the totes required for the next delivery are able to be easily accessed, for example, by moving the totes required for the next delivery to a location near and open end of the mobile container. In some embodiments, the mobile storage structure may interface with a storage structure deployed in a warehouse to automatically transfer totes from the mobile storage structure to the stationary storage structure.

IPC Classes  ?

• B65G 67/02 - Loading or unloading land vehicles
• B60P 3/00 - Vehicles adapted to transport, to carry or to comprise special loads or objects

Abstract

Disclosed herein are various configurations of a high-density storage system comprising a plurality of layers, each layer comprising a plurality of rows for storing a plurality of coupled totes and one or more robotic carriers located on opposite ends of each layer, each carrier being multiple rows wide, each carrier capable of retrieving totes from a row in the layer, depositing a tote into a row or oral in a layer and shifting totes from one row to another within the layer.

IPC Classes  ?

• B65G 35/06 - Mechanical conveyors not otherwise provided for comprising a load-carrier moving along a path, e.g. a closed path, and adapted to be engaged by any one of a series of traction elements spaced along the path
• B65G 1/133 - Storage devices mechanical with article supports or holders movable in a closed circuit to facilitate insertion or removal of articles the circuit being confined in a horizontal plane
• B65G 1/137 - Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed
• G06Q 10/087 - Inventory or stock management, e.g. order filling, procurement or balancing against orders

Abstract

In one aspect, the disclosure relates to detection of pore defects in laser powder bed fusion additive manufacturing. A convolutional neural network is trained based upon a training data set. The training data set can be generated using simulations or experiments performed on a metal sample by capturing side-view x-ray imagery as well as top-view thermal imagery of the metal sample as it is formed with a laser. This abstract is intended as a scanning tool for purposes of searching in the particular art and is not intended to be limiting of the present disclosure.

IPC Classes  ?

• B22F 10/28 - Powder bed fusion, e.g. selective laser melting [SLM] or electron beam melting [EBM]
• B29C 64/153 - Processes of additive manufacturing using only solid materials using layers of powder being selectively joined, e.g. by selective laser sintering or melting
• B22F 3/105 - Sintering only by using electric current, laser radiation or plasma
• G01N 29/44 - Processing the detected response signal

Abstract

Provided is a system, method, and computer program product for determining a needle injection site. The method includes segmenting, with at least one computing device, an image of a sequence of images into at least one object based on a machine-learning model configured to estimate its uncertainty for each segmentation, generating, with the at least one computing device, a 3D model of the at least one object, and determining, with the at least one computing device, an insertion location of the at least one object based at least partially on an output of the machine-learning model.

IPC Classes  ?

• G06T 17/00 - 3D modelling for computer graphics
• A61B 17/34 - Trocars; Puncturing needles
• G06T 7/10 - Segmentation; Edge detection
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

A hierarchical deep-learning object detection framework provides a method for identifying objects of interest in high-resolution, high pixel count images, wherein the objects of interest comprise a relatively a small pixel count when compared to the overall image. The method uses first deep-learning model to analyze the high pixel count images, in whole or as a patchwork, at a lower resolution to identify objects, and a second deep-learning model to analyze the objects at a higher resolution to classify the objects.

IPC Classes  ?

• G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts
• G06F 18/10 - Pre-processing; Data cleansing
• G06F 18/2135 - Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods based on approximation criteria, e.g. principal component analysis
• G06F 18/214 - Generating training patterns; Bootstrap methods, e.g. bagging or boosting
• G06F 18/241 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
• G06F 18/2415 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate
• G06T 7/00 - Image analysis

Abstract

Provided is a system, method, and computer program product for tracking a needle. The method includes determining a visibility of the needle being inserted into a subject in an image of a sequence of images, in response to determining that the visibility satisfies a visibility threshold, detecting a location of the needle based on at least one first algorithm and a detected curvature of the needle, in response to determining that the visibility does not satisfy the visibility threshold, detecting the location of the needle being inserted based on at least one second algorithm, and tracking the location of the needle in the sequence of images based on locations detected with the at least one first algorithm and the at least one second algorithm.

IPC Classes  ?

• A61B 8/08 - Detecting organic movements or changes, e.g. tumours, cysts, swellings
• A61B 17/34 - Trocars; Puncturing needles
• A61B 34/20 - Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis
• G06T 7/246 - Analysis of motion using feature-based methods, e.g. the tracking of corners or segments

Abstract

An extracorporeal system for lung assist includes a housing having a blood flow inlet in fluid connection with a pressurizing stator compartment within the housing. A fiber bundle compartment within the housing is above and in fluid connection with the pressurizing stator compartment via a flow channel formed within the housing and extending from the pressurizing stator compartment to an inlet manifold of the fiber bundle compartment. A blood flow outlet in is fluid connection with an outlet man fold of the fiber bundle compartment. The blood flow inlet extends through the housing parallel to a plane of rotation of an impeller in the pressurizing stator compartment. The blood flow inlet turns to deliver blood into a central portion of the impeller. A has inlet is in fluid connection with the housing and in fluid connection with inlets of the plurality of hollow gas permeable fibers of a cylindrical fiber bundle positioned within the fiber bundle compartment. A gas outlet is in fluid connection with the housing and in fluid connection with outlets of the plurality of hollow gas permeable fibers.

IPC Classes  ?

• A61M 1/36 - Other treatment of blood in a by-pass of the natural circulatory system, e.g. temperature adaptation, irradiation
• A61M 1/16 - Dialysis systems; Artificial kidneys; Blood oxygenators with membranes
• A61M 60/113 - Extracorporeal pumps, i.e. the blood being pumped outside the patient’s body incorporated within extracorporeal blood circuits or systems in other functional devices, e.g. dialysers or heart-lung machines
• A61M 60/232 - Centrifugal pumps
• A61M 60/38 - Blood oxygenation
• A61M 60/419 - Blood pumps; Devices for mechanical circulatory actuation; Balloon pumps for circulatory assistance - Details relating to driving for non-positive displacement blood pumps the force acting on the blood contacting member being permanent magnetic, e.g. from a rotating magnetic coupling between driving and driven magnets
• A61M 60/422 - Blood pumps; Devices for mechanical circulatory actuation; Balloon pumps for circulatory assistance - Details relating to driving for non-positive displacement blood pumps the force acting on the blood contacting member being electromagnetic, e.g. using canned motor pumps
• A61M 60/82 - Magnetic bearings
• A61M 60/824 - Hydrodynamic or fluid film bearings
• A61M 60/825 - Contact bearings, e.g. ball-and-cup or pivot bearings

Abstract

Disclosed herein are training strategies for query-based object detectors, referred to herein as Query Recollection (QR). In one variation or QR, dense query recollection, every intermediate query is collected and independently forwarded to every downstream stage. In a second variation or QR, selective query recollection, intermediate queries are collected from the two nearest previous stages and forwarded to the next downstream stage. This eliminates the phenomena wherein intermediate stages of the decoder produce more accurate results than later stages of the decoder.

IPC Classes  ?

• G06V 10/774 - Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting

Abstract

In an example, a method may include obtaining, from a data source, first data including multiple frames each including a human face. The method may include automatically detecting, in each of the multiple frames, one or more facial landmarks and one or more action units (AUs) associated with the human face. The method may also include automatically generating one or more semantic masks based at least on the one or more facial landmarks, the one or more semantic masks individually corresponding to the human face. The method may further include obtaining a facial hyperspace using at least the first data, the one or more AUs, and the semantic masks. The method may also include generating a synthetic image of the human face using a first frame of the multiple frames and one or more AU intensities individually associated with the one or more AUs.

IPC Classes  ?

• G06T 13/40 - 3D [Three Dimensional] animation of characters, e.g. humans, animals or virtual beings
• G06T 17/00 - 3D modelling for computer graphics
• G06V 40/16 - Human faces, e.g. facial parts, sketches or expressions

Abstract

Disclosed herein is a novel pseudoinverse estimation system and method that adapts regression techniques to directly estimate one or more pseudoinverses of a neuromodulation pathway, thereby circumventing the need of inverting an estimated forward model. This is accomplished by the learning of a restricted domain that restricts the potential stimuli required to produce a desired neuro response.

IPC Classes  ?

• A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
• G06F 18/213 - Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
• G06F 18/2415 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate
• G06N 3/08 - Learning methods
• G06T 5/60 - using machine learning, e.g. neural networks
• G06T 7/00 - Image analysis
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

ex vivoex vivoex vivo perfusion prior to transplantation.

IPC Classes  ?

• C12Q 1/6872 - Methods for sequencing involving mass spectrometry
• G01N 33/68 - Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
• G16B 20/40 - Population genetics; Linkage disequilibrium

Abstract

Disclosed herein is a novel method for improving transductive fine-tuning for few-shot learning using margin-based uncertainty weighting and probability regularization. Margin-based uncertainty is designed to assign low loss weights for wrongly predicted samples and high loss weights for the correct ones. Probability regularization provides for the probability of each testing sample being adjusted by a scale vector, which quantifies the difference between the class marginal distribution and the uniform.

IPC Classes  ?

• G06N 7/01 - Probabilistic graphical models, e.g. probabilistic networks
• G06N 20/00 - Machine learning

Abstract

Disclosed herein is a method for skeleton-based action recognition using handcrafted features. The input of the model is keypoint data of one or more skeletons from the frames of a video clip. Several histogram features are used to describe the spatial and temporal patterns of the corresponding body. These features are concatenated and sent to a linear classifier to predict the category of the actions.

IPC Classes  ?

• G06V 40/20 - Movements or behaviour, e.g. gesture recognition
• G06V 10/20 - Image preprocessing
• G06V 10/50 - Extraction of image or video features by summing image-intensity values; Projection analysis
• G06V 10/771 - Feature selection, e.g. selecting representative features from a multi-dimensional feature space
• G06T 7/246 - Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
• G06T 7/292 - Multi-camera tracking

Abstract

A wearable device has a plurality of sensors surrounding a user's arm or wrist and provides depth information about the user's environment. Each sensor in the plurality of sensors has a field-of-view that may include the user's arm, torso, and surrounding environment. A controller receives data from the plurality of sensors and merges the data to create a composite image or depth point cloud. The device utilizes low-resolution sensors, with the composite image having a greater resolution and field-of-view than any individual sensor. The device is worn on the user's arm or wrist and can be used for static or continuous hand pose estimation, whole-arm pose estimation, and object detection, among other applications.

IPC Classes  ?

• G06V 40/20 - Movements or behaviour, e.g. gesture recognition
• G06T 7/55 - Depth or shape recovery from multiple images

Abstract

Provided is a method for locating an epilepsy seizure onset zone and prediction of seizure outcome including receiving interictal electroencephalographs from two or more points in a patient's cerebral cortex. The interictal electroencephalographs are used to determine directional information flow values which indicate dominant information flow from a non-seizure zone to a seizure onset zone. The directional informational flow values may be input into a classification model trained to predict whether the two or more points in the patient's cerebral cortex are a seizure onset zone and/or classify the patient's predicted post-treatment seizure outcome after epilepsy treatment based on the directional information flow values. An output from the classification model may indicate a location of seizure onset zone in the patient's cerebral cortex and/or the patient's predicted post-treatment seizure outcome after epilepsy treatment. Systems and computer program products are also provided.

IPC Classes  ?

• A61B 5/374 - Detecting the frequency distribution of signals, e.g. detecting delta, theta, alpha, beta or gamma waves
• A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
• A61B 5/291 - Bioelectric electrodes therefor specially adapted for particular uses for electroencephalography [EEG]
• G16H 20/40 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture

Abstract

Additive manufacturing methods, additive manufacturing systems, and products thereof are provided. The method comprises depositing a bioink into a support material based on a first computer model of an object, thereby forming a first portion of an object in the support material. The bioink comprises cells. The method comprises depositing a structure material into the support material based on the first computer model of an object, thereby forming a first portion of a scaffold for the object. The structure material is different from the bioink and the structure material comprises a polymer. The method comprises repeating the depositing of the bioink and the structure material as necessary to additively form the object and the scaffold within the object.

IPC Classes  ?

• B29C 64/106 - Processes of additive manufacturing using only liquids or viscous materials, e.g. depositing a continuous bead of viscous material
• B29C 64/209 - Heads; Nozzles
• B29C 64/336 - Feeding of two or more materials
• B33Y 10/00 - Processes of additive manufacturing
• B33Y 30/00 - ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING - Details thereof or accessories therefor
• B33Y 80/00 - Products made by additive manufacturing

Abstract

A method of synthesizing a polynucleotide composition includes performing a synthesis of the polynucleotide composition via phosphoramidite chemistry, solid-phase supported synthesis, to create polynucleotide chain. During at least one cycle of the synthesis, coupling an RDRP-phophoramidite reagent in a growing chain of the polynucleotide composition. The RDRP -phophoramidite reagent, includes a phosphoramidite compound conjugated to an RDRP initiator or a chain transfer agent for RDRP via a moiety comprising a protected hydroxyl group. A hydroxyl protecting group of the protected hydroxyl group is stable to polynucleotide synthesis conditions.

IPC Classes  ?

• B01J 19/00 - Chemical, physical or physico-chemical processes in general; Their relevant apparatus
• C07H 21/04 - Compounds containing two or more mononucleotide units having separate phosphate or polyphosphate groups linked by saccharide radicals of nucleoside groups, e.g. nucleic acids with deoxyribosyl as saccharide radical
• C12Q 1/68 - Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
• C40B 50/08 - Liquid phase synthesis, i.e. wherein all library building blocks are in liquid phase or in solution during library creation; Particular methods of cleavage from the liquid support

Abstract

A bipedal walking robot uses a quasi-passive control scheme and a simplified mechanical design. The walking robot has a pair of legs connected to a body through a passive hip joint, which is offset from a center of gravity of the walking robot. A nonconcentric, curved foot is attached at to each leg by a prismatic joint. Extension and retraction of the prismatic joint initiates the walking sequence of the robot, with each foot retracted during the swing phase and extended during the stance phase. Directional changes are controlled by changing a phase offset in the actuation of each foot.

IPC Classes  ?

• B25J 9/16 - Programme controls
• B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid

Abstract

A method of modifying a polynucleotide includes reacting the polynucleotide with one or more molecules of an acylating reagent. The acylating reagent includes an acylating compound conjugated to (i) an initiator compound for reversible deactivation radical polymerization; (ii) a chain transfer agent for reversible deactivation radical polymerization or (iii) a compound comprising a polymerizable group to form a modified polynucleotide.

IPC Classes  ?

• C07H 21/02 - Compounds containing two or more mononucleotide units having separate phosphate or polyphosphate groups linked by saccharide radicals of nucleoside groups, e.g. nucleic acids with ribosyl as saccharide radical
• C07H 21/04 - Compounds containing two or more mononucleotide units having separate phosphate or polyphosphate groups linked by saccharide radicals of nucleoside groups, e.g. nucleic acids with deoxyribosyl as saccharide radical
• C08F 2/04 - Polymerisation in solution
• C08F 2/48 - Polymerisation initiated by wave energy or particle radiation by ultraviolet or visible light
• C08J 3/18 - Plasticising macromolecular compounds

Abstract

Disclosed herein is a system and method implementing a processing and detection pipeline to detect spreading depolarization waves in a brain occurring after a traumatic brain injury. The method relies solely on EEG data collected by a standard EEG machine.

IPC Classes  ?

• A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
• A61B 6/02 - Devices for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis

Abstract

Systems and methods for generating new images for training a machine-learning model are disclosed. Image data is produced regarding an image captured by an image sensor. The image data is altered such that the style of the image (e.g., color, shading, orientation, etc.) is altered. The altered image data is encoded into a first latent space. An image from a database is selected based on its similarity to the altered image and a decoding of the first latent space. Style encodings of the first latent space are extracted to classify a style of the altered image data in a second latent space. New images are then generated utilizing a reconstructor model that combines the two latent spaces. These new images can be used to train an image-recognition model.

IPC Classes  ?

• G06V 10/774 - Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
• G06F 16/532 - Query formulation, e.g. graphical querying
• G06T 11/00 - 2D [Two Dimensional] image generation
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06V 20/58 - Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads

Abstract

This document describes a process of producing gel microparticles, which are consistent in size and morphology. Through the process of coacervation, large volumes of gel microparticle slurry can be produced by scaling up reactor vessel size. Particles can be repeatedly dehydrated and rehydrated in accordance to their environment, allowing for the storage of particles in a non-solvent such as ethanol. Gel slurries exhibit a Bingham plastic behavior in which the slurry behaves as a solid at shear stresses that are below a critical value. Upon reaching the critical shear stress, the slurry undergoes a rapid decrease in viscosity and behaves as a liquid. The rheological behavior of these slurries can be adjusted by changing the compaction processes such as centrifugation force to alter the yield-stress. The narrower distribution and reduced size of these particles allows for an increase in FRESH printing fidelity.

IPC Classes  ?

• C08J 3/075 - Macromolecular gels
• B33Y 70/00 - Materials specially adapted for additive manufacturing
• C09D 11/04 - Printing inks based on proteins

Abstract

Disclosed herein are devices comprising stretchable 3D circuits and methods for fabricating the circuits. The fabrication process includes providing in the elastomeric polymer as a substrate and providing conductive interconnects within the substrate encased in an insulating polymer, such as polyimide, to provide a stiffness gradient between the conductive interconnects and the flexible elastomeric substrate. The circuit may be fabricated as a multilayer construction using three-dimensional pillars as vias and as external interconnects to the circuit.

IPC Classes  ?

• H05K 3/00 - Apparatus or processes for manufacturing printed circuits
• H05K 1/03 - Use of materials for the substrate
• H05K 3/40 - Forming printed elements for providing electric connections to or between printed circuits

Abstract

Methods for assisting one or more users in organizing content-items, such as location information (e.g., URLs) for online information resources (e.g., webpages) and clips taken from information resources, accessed via content-access software, such as one or more web browsers, using a content item-bundle primitive that allows users to create, build, manipulate, and/or populate their own content-item bundles according to their information investigation and collection desires/needs. In some embodiments, the methods include automatically bundling content items into suggested content-item bundles based on learned relationships among various content items. In some embodiments, the methods can be implemented to provide bundle-based task managers that allow users to not only organize their content items but also define tasks and/or projects rooted in the content-item-bundle primitive. Further embodiments are disclosed, as is software for executing disclosed methods.

IPC Classes  ?

• G06F 3/0486 - Drag-and-drop
• G06F 3/0483 - Interaction with page-structured environments, e.g. book metaphor
• G06Q 10/0631 - Resource planning, allocation, distributing or scheduling for enterprises or organisations

Abstract

In one aspect, a method includes providing support material within which the structure is fabricated, depositing, into the support material, structure material to form the fabricated structure, and removing the support material to release the fabricated structure from the support material. The provided support material is stationary at an applied stress level below a threshold stress level and flows at an applied stress level at or above the threshold stress level during fabrication of the structure. The provided support material is configured to mechanically support at least a portion of the structure and to prevent deformation of the structure during the fabrication of the structure. The deposited structure material is suspended in the support material at a location where the structure material is deposited. The structure material comprises a fluid that transitions to a solid or semi-solid state after deposition of the structure material.

IPC Classes  ?

• A61L 27/54 - Biologically active materials, e.g. therapeutic substances
• A61L 27/04 - Metals or alloys
• A61L 27/10 - Ceramics or glasses
• A61L 27/14 - Macromolecular materials
• A61L 27/18 - Macromolecular materials obtained otherwise than by reactions only involving carbon-to-carbon unsaturated bonds
• A61L 27/20 - Polysaccharides
• A61L 27/22 - Polypeptides or derivatives thereof
• A61L 27/24 - Collagen
• A61L 27/38 - Animal cells
• A61L 27/52 - Hydrogels or hydrocolloids
• B29C 64/112 - Processes of additive manufacturing using only liquids or viscous materials, e.g. depositing a continuous bead of viscous material using individual droplets, e.g. from jetting heads
• B29C 64/118 - Processes of additive manufacturing using only liquids or viscous materials, e.g. depositing a continuous bead of viscous material using filamentary material being melted, e.g. fused deposition modelling [FDM]
• B29C 64/40 - Structures for supporting 3D objects during manufacture and intended to be sacrificed after completion thereof
• B33Y 10/00 - Processes of additive manufacturing
• B33Y 70/00 - Materials specially adapted for additive manufacturing

Abstract

A system for classifying structured medical data, with each item of structured medical data, the system comprising a processing module that parses items of structured medical data to retrieve values of respective fields of the one or more items of structured medical data, the one or more retrieved values representing a set of medical attributes; a classification module that selects a classifier based at least one of the attributes in the set and applies the classifier to the set of attributes to classify one or more items of structured medical data into a particular risk profile; a user interface that renders one or more controls for input data that confirms one or more of the risk factors of the risk profile; and a transmitter to transmit to a remote medical device, an alert that specifies confirmation of the one or more of the risk factors.

IPC Classes  ?

• G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
• A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
• G06F 9/451 - Execution arrangements for user interfaces
• G06F 16/901 - Indexing; Data structures therefor; Storage structures
• G06N 5/02 - Knowledge representation; Symbolic representation
• G06N 20/00 - Machine learning
• G16H 10/20 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
• G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment

Abstract

A high-density storage system for goods is described in which totes carrying the goods are storage in a storage structure and stored and retrieved by robotic carriers. The carriers move laterally and/or longitudinally along the exterior of the support structure and retrieve totes from the interior of the structure by manipulating rows of coupled totes. Totes at the ends of rows are quickly removed and stored in another row until the desired tote appears at the end of the row, at which point the carrier proceeds with the tote to the exit point of the storage system. Storing totes is also a quick action by pushing them into any row. As a tote is pushed into the row, it will automatically couple with a tote inside the row that it comes into contact with.

IPC Classes  ?

• B65G 1/04 - Storage devices mechanical
• B65D 21/02 - Containers specially shaped, or provided with fittings or attachments, to facilitate nesting, stacking, or joining together

Abstract

A high-density storage system for goods is described in which totes carrying the goods are stored in a storage structure and stored and retrieved via stationary or mobile conveyors running along opposite ends of each layer of the storage structure. The totes may be moved to or from the conveyors as the rows move at a constant velocity toward or away from the conveyors. Totes at the ends of rows are quickly moved and stored in another row until the desired tote appears at the end of the row, at which point the desired tote is carried to an exit point of the storage structure by one of the conveyors.

IPC Classes  ?

• B65G 1/04 - Storage devices mechanical
• B65D 21/02 - Containers specially shaped, or provided with fittings or attachments, to facilitate nesting, stacking, or joining together

Abstract

Disclosed herein is a system and method for increasing the confidence of a match between the test image and an image stored in a library database. Features are extracted from the test image and compared to features stored in the image database and, if a match is determined, one or more transformations are performed on the test image to generate pose-altered images. Features are then extracted from the pose-altered images and matched with pose-altered images in the database. The scores for the subsequent matchings can be aggregated to determine an overall probability of a match between the test image in an image in the library database.

IPC Classes  ?

• G06V 10/74 - Image or video pattern matching; Proximity measures in feature spaces
• G06T 3/60 - Rotation of a whole image or part thereof
• G06T 19/20 - Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
• G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
• G06V 10/56 - Extraction of image or video features relating to colour
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06V 20/68 - Food, e.g. fruit or vegetables

Abstract

Disclosed herein is a system and method for generating quadrilateral bonding boxes which tightly cover the most representative faces of retail products having arbitrary poses. The quadrilateral boxes do not include unnecessary background information or miss parts of the objects, as would the axis-aligned bounding boxes produced by prior art detectors. A simple projection transformation can correct the pose of products for downstream tasks.

IPC Classes  ?

• G06T 7/70 - Determining position or orientation of objects or cameras
• G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
• G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects

Goods & Services

Consulting services, namely, investigation, namely, computer software design for others, and analysis, and testing of computer software architecture relative to software quality attributes and business goals and providing materials relating thereto

Abstract

Disclosed herein is a method for efficiently reducing the computational footprint of any AI-based object detection model, so as to enable its real-time deployment on computing resource-limited (i.e., low-power, embedded) devices. The disclosed method provides a step-by-step framework using an optimized combination of compression techniques to effectively compress any given AI-based object detection model.

IPC Classes  ?

• G06V 10/70 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning
• G06N 3/082 - Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections
• G06V 10/774 - Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

Disclosed herein is a system and method for novel neural architecture search using a random graph network backbone to facilitate the creation of an efficient network structure. The method utilizes reinforcement learning algorithms to build a complex relationship between intra-connections (i.e., links between blocks in a random graph network) and extra-connections (i.e., links among blocks across the random graphs network) for discovering an efficient random neural architecture.

IPC Classes  ?

• G06N 3/08 - Learning methods

Abstract

A system comprises a IoT resource and a computing device of a user. The computing device comprises a processor that executes a personal privacy app that receives data about the IoT resource and communicates a preference setting for the user with respect to the IoT device. The preference setting is based on the data received about the IoT resource.

IPC Classes  ?

• G06F 21/60 - Protecting data
• G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
• G06N 7/00 - Computing arrangements based on specific mathematical models
• G06N 20/00 - Machine learning
• H04L 9/40 - Network security protocols
• H04L 67/306 - User profiles

Abstract

Disclosed herein is a system and method for evolving a deep neural network model by searching for hidden sub-networks within the model. The model is evolved by adding convolutional layers to the model, then pruning the model to remove redundant filters. The model is exposed to training samples of increasing complexity each time the model is evolved, until a desired level of performance is achieved, at which time, the model is exposed to all available training data.

IPC Classes  ?

• G06N 3/08 - Learning methods

Abstract

A process for micro-tissue encapsulation of cells includes coating a tissue scaffold stamp with an extracellular matrix compound. The process includes depositing the tissue scaffold stamp onto a thermoresponsive substrate and seeding the tissue scaffold stamp with a cell culture. A cell culture forms a cell patch that is attached to the extracellular matrix compound. A monolayer on the tissue scaffold stamp for which borders of the monolayer maintain expressions for cell-cell junctions, wherein the cell-cell junctions of the monolayer are configured to express tension forces. The process includes removing the thermoresponsive substrate. The process includes folding the micro-tissue structure by suspending the micro-tissue in the solvent. The folded micro-tissue structure is collected from the solvent and administered to an organism.

IPC Classes  ?

• A61F 9/00 - Methods or devices for treatment of the eyes; Devices for putting in contact-lenses; Devices to correct squinting; Apparatus to guide the blind; Protective devices for the eyes, carried on the body or in the hand
• A61K 35/30 - Nerves; Brain; Eyes; Corneal cells; Cerebrospinal fluid; Neuronal stem cells; Neuronal precursor cells; Glial cells; Oligodendrocytes; Schwann cells; Astroglia; Astrocytes; Choroid plexus; Spinal cord tissue
• A61L 27/18 - Macromolecular materials obtained otherwise than by reactions only involving carbon-to-carbon unsaturated bonds
• A61L 27/34 - Macromolecular materials
• A61L 27/36 - Materials for prostheses or for coating prostheses containing ingredients of undetermined constitution or reaction products thereof
• A61L 27/38 - Animal cells
• A61L 27/50 - Materials characterised by their function or physical properties
• C12N 5/079 - Neural cells

Abstract

Disclosed herein is a novel method for modelling and simulating urban solar harvesting by modeling the components of solar radiation using a modelling framework with modules related to view factors, transmittance, beam and diffuse shadow modeling, heat transfer equilibrium, and a virtual environment that emulates urban infrastructure and receives weather and radiation data as inputs. Also disclosed herein are various approaches for modelling diffuse shadows, which are a component of the integrated modelling framework. The various modules are integrated and optimized to compose several versions of modeling and simulation tools, which can estimate the temperature, power, and energy output of dense groups of freely-defined dynamic solar harvesting surfaces in urban and other intricate scenarios characterized by high three-dimensionality.

IPC Classes  ?

• G06T 15/60 - Shadow generation
• G06T 15/06 - Ray-tracing
• G06T 15/55 - Radiosity
• G06F 17/18 - Complex mathematical operations for evaluating statistical data
• G06F 30/20 - Design optimisation, verification or simulation

Abstract

Disclosed herein is a co-designed compiler and CGRA architecture that achieves both high programmability and extreme energy efficiency. The architecture includes a rich set of control-flow operators that support arbitrary control flow and memory access on the CGRA fabric. The architecture is able to realize both energy and area savings over prior art implementations by offloading most control operations into a programmable on-chip network where they can re-use existing network switches.

IPC Classes  ?

• G06F 9/30 - Arrangements for executing machine instructions, e.g. instruction decode
• G06F 5/00 - Methods or arrangements for data conversion without changing the order or content of the data handled
• G06F 8/41 - Compilation
• G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]

Abstract

Disclosed herein is a system and method for selecting a battery for a particular application, for example, batteries used in portable electronics, electric vehicles, satellites, etc. The method uses an end-to-end differentiable modeling approach that allows the selection of batteries directly from the parameters of the battery and a specification of the particular application for which the batteries are being selected.

IPC Classes  ?

• G01R 31/36 - Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
• G01R 31/367 - Software therefor, e.g. for battery testing using modelling or look-up tables

Abstract

Provided is a system, method, and device for automated energy remediation. The system includes at least one processor programmed or configured to: store energy usage data for a plurality of households, store environmental data associated with the plurality of households, the environmental data including outdoor temperature measurements, determine an inflection temperature for each household of the plurality of households based on a nonlinear regression model, determine a gap metric value based on a maximum median inflection temperature and a minimum inflection temperature from the plurality of households, form a plurality of groups based on the plurality of households and household data associated with each household, each group including a subset of households of the plurality of households, determine at least one group of the plurality of groups, and automatically initiate at least one energy protocol for households in the at least one group.

IPC Classes  ?

• H02J 13/00 - Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
• H02J 3/00 - Circuit arrangements for ac mains or ac distribution networks

Abstract

Disclosed herein is a methodology for refining novel-class features in a few-shot learning scenario by fine-tuning the feature extractor by reducing both class-agnostic biases and class-specific biases. A distribution calibration module is used to reduce the class-agnostic bias by normalizing the overall feature distribution for novel classes and further reshaping the feature manifold for fast adaptation during fine-tuning. Selected sampling is used to reduce class-specific bias by augmenting more data for better estimation.

IPC Classes  ?

• G06V 10/77 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/771 - Feature selection, e.g. selecting representative features from a multi-dimensional feature space

Abstract

Provided is a system, method, and computer program product for tracking an object based on skin images. A method includes capturing, with at least one computing device, a sequence of images with a stationary or movable camera unit arranged in a room, the sequence of images including the subject and an object moving relative to the subject, and determining, with at least one computing device, the pose of the object with respect to the subject in at least one image of the sequence of images based on computing or using a prior surface model of the subject, a surface model of the object, and an optical model of the stationary or movable camera unit.

IPC Classes  ?

• A61B 5/06 - Devices, other than using radiation, for detecting or locating foreign bodies
• A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
• G06T 7/246 - Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
• G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods

Abstract

Disclosed herein is a method of soft anchor-point detection (SAPD), which implements a concise, single-stage anchor-point detector with both faster speed and higher accuracy. Also disclosed is a novel training strategy with two softened optimization techniques: soft-weighted anchor points and soft-selected pyramid levels.

IPC Classes  ?

• G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
• G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
• G06V 10/74 - Image or video pattern matching; Proximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects

Abstract

Disclosed herein is a system and method for performing pose-correction on images containing objects within a scene, or the entire scene, to compensate for off-centered camera views. The system and method generates a more frontal view of the object or scene by applying planar homography by identifying corner endpoints of the object or the scene and repositioning the corner endpoints to provide a more frontal view. The pose-corrected scene may then be input to an object detector to determine a location of a bounding box of an object-of-interest which would be more accurate than a bounding box from the original off-centered image.

IPC Classes  ?

• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
• G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 20/50 - Context or environment of the image

Abstract

Disclosed herein is a system and method for pooling local features for fine-grained image classification. The deep features learned by the deep network are augmented with low level local landmark features by learning a pooling strategy that pools landmark features from earlier layers of the deep network. These low level landmark features are combined with the deep features and sent to the classifier.

IPC Classes  ?

• G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06V 10/77 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
• G06V 10/46 - Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features

Abstract

Disclosed herein is a method to disentangle linear-encoded facial semantics from facial images without external supervision. The method uses linear regression and sparse representation learning concepts to make the disentangled latent representations easily interpreted and manipulated. Generated facial images are decomposed into multiple semantic features and latent representations are extracted to capture interpretable facial semantics. The semantic features may be manipulated to synthesize photorealistic facial images by sampling along vectors representing the semantic features, thereby changing the associate semantics.

IPC Classes  ?

• G06T 11/60 - Editing figures and text; Combining figures or text
• G06T 9/00 - Image coding
• G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
• G06V 40/16 - Human faces, e.g. facial parts, sketches or expressions

Abstract

A MEMS/NEMS actuator based on a phase change material is described in which the volumetric change observed when the phase change material changes from a crystalline phase to an amorphous phase is used to effectuate motion in the device. The phase change material may be changed from crystalline phase to amorphous phase by heating with a heater or by passing current directly through the phase change material, and thereafter quenched quickly by dissipating heat into a substrate. The phase change material may be changed from the amorphous phase to a crystalline phase by heating at a lower temperature. An application of the actuator is described to fabricate a phase change nano relay in which the volumetric expansion of the actuator is used to push a contact across an airgap to bring it into contact with a source/drain.

IPC Classes  ?

• H01H 37/36 - Thermally-sensitive members actuated due to expansion or contraction of a fluid with or without vaporisation
• H01H 1/00 - Contacts

Abstract

Provided is a method for classification of diseases including receiving image data associated with an image at a first resolution. The image may be processed, for example by removing a background from the image, deconstructing the image into separate layers, and segmenting the image to define a plurality of single-cell images. A single-cell image may be processed, for example, by applying a filter to the single-cell image to decrease a resolution of the single-cell image as compared to the first resolution, to a second resolution. A label may be assigned to the single-cell image. A machine learning model is trained to predict a classification of the single-cell image based on inputting a plurality of single-cell images into the model. The trained machine learning model may be used to predict the outcome of a treatment. Systems and computer program products are also provided.

IPC Classes  ?

• G06T 7/00 - Image analysis
• G06T 7/194 - Segmentation; Edge detection involving foreground-background segmentation
• G06T 7/11 - Region-based segmentation
• G06V 10/774 - Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
• G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts
• G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
• G06V 20/70 - Labelling scene content, e.g. deriving syntactic or semantic representations
• G06V 10/776 - Validation; Performance evaluation
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06T 3/40 - Scaling of a whole image or part thereof
• G16H 20/40 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture

Abstract

Disclosed herein an effective detach strategy which suppresses the flow of gradients from context sub-networks through the detection backbone path to obtain a more discriminative context by forcing the representation of context sub-network to be dissimilar from the detection network. A sub-network is defined to generate the context information from early layers of the detection backbone. Because instance and context focus on perceptually different parts of an image, the representations from either of them should also be discrepant. In addition, a stacked complementary loss is generated to and backpropagated to the detection network.

IPC Classes  ?

• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06V 10/77 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation