Abstract: Systems and methods to detect a scratch are provided. The method includes identifying, via an OPTICS technique, a cluster of points on an image. The method also includes utilizing a principal curves technique to identify a curve that approximates one or more points of the cluster of points as a smooth curve. The method further includes determining one or more characteristics of the curve. The method further includes determining one or more characteristics of the cluster. The method further includes identifying a scratch based on at least one of the one or more characteristics of the curve and the one or more characteristics of the cluster.

Abstract: Systems, apparatus, and methods are described for additive manufacturing or three dimensional (3D) printing of objects using a set of physical masks. An additive manufacturing device can include one or more light sources, a vessel containing a volume of print material and a transparent base through which light can enter the vessel to cure a portion of the volume of print material, and a set of masks defining a series of patterns associated with layers of a 3D object that are each positionable between the light source and the transparent base to control a pattern of the light that is received through the transparent base and therefore the pattern of the cured portion of print material.

Abstract: An apparatus and a method of additive manufacturing is provided. The apparatus includes a light source configured to emit light between 0 and 500 nm in wavelength. At least one vessel is provided that includes a chamber and a transparent base. The chamber contains a volume of liquid print material. The transparent base being made of Fluorinated ethylene propylene (FEP) or Polydimethylsiloxane (PDMS) through which the relevant wavelength can be received into the chamber to cure a portion of the volume of print material through at least one mask, the at least one mask being made of paper, polymer, glass, metal, composites, or laminated substrates, the at least one mask defining a series of patterns associated with layers of a three-dimensional (3D) object, the at least one mask being position-able between the light source and the transparent base, via a mechanism, wherein the at least one mask defines the pattern of the light that is received through the transparent base and into the print material.

Abstract: Today, artificial neural networks are trained on large sets of manually tagged images. Generally, for better training, the training data should be as large as possible. Unfortunately, manually tagging images is time consuming and susceptible to error, making it difficult to produce the large sets of tagged data used to train artificial neural networks. To address this problem, the inventors have developed a smart tagging utility that uses a feature extraction unit and a fast-learning classifier to learn tags and tag images automatically, reducing the time to tag large sets of data. The feature extraction unit and fast-learning classifiers can be implemented as artificial neural networks that associate a label with features extracted from an image and tag similar features from the image or other images with the same label. Moreover, the smart tagging system can learn from user adjustment to its proposed tagging. This reduces tagging time and errors.

Abstract: Today, artificial neural networks are trained on large sets of manually tagged images. Generally, for better training, the training data should be as large as possible. Unfortunately, manually tagging images is time consuming and susceptible to error, making it difficult to produce the large sets of tagged data used to train artificial neural networks. To address this problem, the inventors have developed a smart tagging utility that uses a feature extraction unit and a fast-learning classifier to learn tags and tag images automatically, reducing the time to tag large sets of data. The feature extraction unit and fast-learning classifiers can be implemented as artificial neural networks that associate a label with features extracted from an image and tag similar features from the image or other images with the same label. Moreover, the smart tagging system can learn from user adjustment to its proposed tagging. This reduces tagging time and errors.

Abstract: An additive manufacturing device can include a light source configured to emit light; a vessel configured to container a photopolymer, a bed having a surface disposed at least partially within the vessel. The surface is movable in a first direction relative to the light source. A mask carrier is configured to support a mask and is movable during operation in a plane parallel with the surface. The mask has a plurality of orifices formed thereon that are configured to transmit the light therethrough.

Abstract: An additive manufacturing system is provided including a light source configured to emit light, a vessel configured to contain a photopolymer, and a bed having a surface disposed at least partially within the vessel. The surface is movable in a first direction relative to the light source. A membrane is fixed to the vessel and is positioned between the light source and the photopolymer. A movable carrier is disposed between the light source and the membrane. The light source is operably coupled to the movable carrier.

Abstract: An apparatus and a method of additive manufacturing is provided. The apparatus includes a light source configured to emit light between 0 and 500 nm in wavelength. At least one vessel is provided that includes a chamber and a transparent base. The chamber contains a volume of liquid print material. The transparent base being made of Fluorinated ethylene propylene (FEP) or Polydimethylsiloxane (PDMS) through which the relevant wavelength can be received into the chamber to cure a portion of the volume of print material through at least one mask, the at least one mask being made of paper, polymer, glass, metal, composites, or laminated substrates, the at least one mask defining a series of patterns associated with layers of a three-dimensional (3D) object, the at least one mask being position-able between the light source and the transparent base, via a mechanism, wherein the at least one mask defines the pattern of the light that is received through the transparent base and into the print material.

Abstract: Systems, apparatus, and methods are described for additive manufacturing or three dimensional (3D) printing of objects using a set of physical masks. An additive manufacturing device can include one or more light sources, a vessel containing a volume of print material and a transparent base through which light can enter the vessel to cure a portion of the volume of print material, and a set of masks defining a series of patterns associated with layers of a 3D object that are each positionable between the light source and the transparent base to control a pattern of the light that is received through the transparent base and therefore the pattern of the cured portion of print material.

Abstract: An additive manufacturing system is provided including a light source configured to emit light, a vessel configured to contain a photopolymer, and a bed having a surface disposed at least partially within the vessel. The surface is movable in a first direction relative to the light source. A membrane is fixed to the vessel and is positioned between the light source and the photopolymer. A movable carrier is disposed between the light source and the membrane. The light source is operably coupled to the movable carrier.

Abstract: Today, artificial neural networks are trained on large sets of manually tagged images. Generally, for better training, the training data should be as large as possible. Unfortunately, manually tagging images is time consuming and susceptible to error, making it difficult to produce the large sets of tagged data used to train artificial neural networks. To address this problem, the inventors have developed a smart tagging utility that uses a feature extraction unit and a fast-learning classifier to learn tags and tag images automatically, reducing the time to tag large sets of data. The feature extraction unit and fast-learning classifiers can be implemented as artificial neural networks that associate a label with features extracted from an image and tag similar features from the image or other images with the same label. Moreover, the smart tagging system can learn from user adjustment to its proposed tagging. This reduces tagging time and errors.

Abstract: A wearable modular electronic device to maintain an electronic module proximate to a wearer may be configured to attach to a wearable accessory such as, without limitation jewelry (e.g., necklace/pendant, finger ring, earring, body piercing, brooch, wrist bracelet, and/or wristwatch), a money clip, a belt buckle, a handbag, and/or an article of clothing. A wearable modular electronic device may be configured as a clasp assembly for a wristwatch, which may be configured to replace an existing clasp of a wristwatch, and which may be configurable for multiple types of wristbands (e.g., strap-type and/or metal). An electronic module may include a battery and/or sensor, such as a biometric sensor, and the wearable modular electronic device or a surface thereof may be contoured to coincide with a body part of a wearer and/or otherwise configured to maintain the biometric sensor proximate to the wearer.

Abstract: A wearable modular electronic device to maintain an electronic module proximate to a wearer may be configured to attach to a wearable accessory such as, without limitation jewelry (e.g., necklace/pendant, finger ring, earring, body piercing, brooch, wrist bracelet, and/or wristwatch), a money clip, a belt buckle, a handbag, and/or an article of clothing. A wearable modular electronic device may be configured as a clasp assembly for a wristwatch, which may be configured to replace an existing clasp of a wristwatch, and which may be configurable for multiple types of wristbands (e.g., strap-type and/or metal). An electronic module may include a battery and/or sensor, such as a biometric sensor, and the wearable modular electronic device or a surface thereof may be contoured to coincide with a body part of a wearer and/or otherwise configured to maintain the biometric sensor proximate to the wearer.

Abstract: A method for simultaneously isolating the flow of blood in a nasal cavity and withdrawing the blood from the nasal cavity is disclosed. The method comprises the steps of inserting a catheter into the nasal cavity. The catheter is composed of a tube and a duct and a forward end capable of being enlarged to form a balloon. Once the catheter is positioned in the nasal passage, air is pumped into the catheter through the tube to inflate the balloon. The inflated balloon forms a seal within the nasal cavity that prevents the flow of blood beyond the seal.Simultaneously, blood is drawn into the catheter by applying a suction force to the duct. Suction may be accomplished by attaching a vacuum at the opposite end of the catheter and connecting it to the duct. The blood is drawn into the duct through a plurality of holes that connect the periphery of the catheter with the duct. The blood thus drawn into the duct is removed from the nasal cavity and disposed away from it.