Abstract: Disclosed here is a method of generating a dental recommendation based on image processing. Further, the method may include receiving at least one patient data comprising at least one image from at least one patient device. Further, the method may include retrieving at least one dental dataset. Further, the method may include analyzing the at least one patient data and the at least one dental dataset. Further, the method may include generating at least one landmark based on the analyzing. Further, the method may include retrieving at least one dental reference dataset. Further, the method may include processing the at least one landmark and the at least one dental reference dataset, determining at least one dental recommendation based on the processing, transmitting the at least one dental recommendation to at least one external device and storing the at least one dental recommendation.

Abstract: A computer-implemented system for managing, processing, refurbishing of electronic devices, is disclosed.

Abstract: Bone level measurements on dental images with machine learning algorithms is described. In an example scenario, a computer processor and memory receives a dental image. The dental image is processed with a heuristic periapical bitewing algorithm to classify the dental image. The dental image is then processed with a machine learning (ML) cementoenamel junction (CEJ) algorithm, a ML first intersection of coronal alveolar bone and tooth algorithm, a ML apex of root algorithm to produce an identified CEJ, an identified first intersection of coronal alveolar bone and tooth, an identified apex of root. The algorithm is configured to calculate the shortest contiguous distance from the identified CEJ to the identified first intersection of coronal alveolar bone and tooth (numerator) divided by the shortest contiguous distance from the identified CEJ to the identified apex of root (denominator) to produce a bone level percentage measurement which is associated with the dental image.

Abstract: The field of the invention relates to a system to provide machine learning of a dental image for expediting insurance claim approvals and to assist insurance companies in identifying insurance fraud. The dental image or image (received from a source such as an x-ray, a camera, or an image capturing device) may be matched to a known computer stored dental image dataset. Anatomic variances on a dental x-ray, such as impacted wisdom teeth can be matched and identified to a known insurance datasets to produce at least one of; an insurance approval, an insurance denial, an automated insurance approval, a fraud alert, an insurance claim for human review.

Abstract: The field of the invention relates to a system to provide artificial intelligence processing of a dental image for determining a relative health risk, i.e. the probability of getting a human disease based on dental x-ray pathologies. The dental image or image (received from a source such as an x-ray, a camera, or an image capturing device) may be matched to a known computer stored genomic pathology dataset, such as a DNA dataset or a RNA dataset. Anatomic variances on a dental x-ray, such as periodontitis (bone disease associated with teeth), can be matched and identified to a known genomic pathology dataset, such as a diabetes DNA dataset, by an artificial intelligence system to produce at least one of: a relative pathology health risk, a treatment recommendation, a product recommendation for an individual patient.

Abstract: Disclosed here is a method of generating a dental recommendation based on image processing. Further, the method may include receiving at least one patient data comprising at least one image from at least one patient device. Further, the method may include retrieving at least one dental dataset. Further, the method may include analyzing the at least one patient data and the at least one dental dataset. Further, the method may include generating at least one landmark based on the analyzing. Further, the method may include retrieving at least one dental reference dataset. Further, the method may include processing the at least one landmark and the at least one dental reference dataset, determining at least one dental recommendation based on the processing, transmitting the at least one dental recommendation to at least one external device and storing the at least one dental recommendation.

Abstract: Deep learning of dental images for national security is described. A computer may receive dental images of a patient from a dental provider. The computer is configured to match dental images to law enforcement databases such as a terrorist database. The process begins with matching a dental image to an anatomy probability dataset and a pathology probability dataset, then correlating it with a patient database to identify a person of interest. With different resolutions each neural network deep learns to probability map and detect different dental object probabilities to authenticate an individual. Further, the dental images will be associated with GPS coordinates to track movements of an individual. The datasets will be provided to e-commerce providers, e-commerce consumers, e-commerce administrators, machine learning entities, government entities and law enforcement entities which may exchange or transfer the data over a communication network such as the internet to locate a person of interest.

Abstract: Deep learning of dental images for national security is described. A computer may receive dental images of a patient from a dental provider. The computer is configured to match dental images to law enforcement databases such as a terrorist database. The process begins with matching a dental image to an anatomy probability dataset and a pathology probability dataset, then correlating it with a patient database to identify a person of interest. With different resolutions each neural network deep learns to probability map and detect different dental object probabilities to authenticate an individual. Further, the dental images will be associated with GPS coordinates to track movements of an individual. The datasets will be provided to e-commerce providers, e-commerce consumers, e-commerce administrators, machine learning entities, government entities and law enforcement entities which may exchange or transfer the data over a communication network such as the internet to locate a person of interest.

Abstract: Dental images processed with artificial intelligence for e-commerce is described. In an example scenario, a processing device receives a dental image. The dental image is processed with a deep neural network and matched to anatomy and pathology datasets in real time. The matched and identified dental image is matched to a dental treatment recommendation dataset to further produce a real time dental product recommendation for a patient. One or more artificial intelligence entities may provide in real time dental treatment recommendations and/or real time dental product recommendations to a dental professional and/or an individual. The process may also produce a diagnostic treatment aid and/or a product recommendation such as an orthodontic aligner.

Abstract: A Metal-Clad (MC) cable assembly includes a core having a plurality of power conductors cabled with a subassembly, each of the plurality of power conductors and the subassembly including an electrical conductor, a layer of insulation, and a jacket layer. The MC cable assembly further includes an assembly jacket layer disposed over the subassembly, and a metal sheath disposed over the core. In one approach, the subassembly is a cabled set of conductors (e.g., twisted pair) operating as class 2 or class 3 circuit conductors in accordance with Article 725 of the National Electrical Code®. In another approach, the MC cable assembly includes a protective layer disposed around the jacket layer of one or more of the plurality of power conductors and the subassembly. In yet another approach, a bonding/grounding conductor is cabled with the plurality of power conductors and the subassembly.

Abstract: Machine learning of a dental image for e-commerce is described. An aggregator server may receive dental images of an e-commerce consumer from an e-commerce provider. The dental images are matched to a probability dataset and correlated with an e-commerce consumer dataset to produce an e-commerce dataset. With different resolutions each neural network machine learns to probability map and detect different dental object probabilities.

Abstract: A Metal-Clad (MC) cable assembly includes a core having a plurality of power conductors cabled with a subassembly, each of the plurality of power conductors and the subassembly including an electrical conductor, a layer of insulation, and a jacket layer. The MC cable assembly further includes an assembly jacket layer disposed over the subassembly, and a metal sheath disposed over the core. In one approach, the subassembly is a cabled set of conductors (e.g., twisted pair) operating as class 2 or class 3 circuit conductors in accordance with Article 725 of the National Electrical Code®. In another approach, the MC cable assembly includes a protective layer disposed around the jacket layer of one or more of the plurality of power conductors and the subassembly. In yet another approach, a bonding/grounding conductor is cabled with the plurality of power conductors and the subassembly.

Abstract: A Metal-Clad (MC) cable assembly includes a core having a plurality of power conductors cabled with a subassembly, each of the plurality of power conductors and the subassembly including an electrical conductor, a layer of insulation, and a jacket layer. The MC cable assembly further includes an assembly jacket layer disposed over the subassembly, and a metal sheath disposed over the core. In one approach, the subassembly is a cabled set of conductors (e.g., twisted pair) operating as class 2 or class 3 circuit conductors in accordance with Article 725 of the National Electrical Code®. In another approach, the MC cable assembly includes a protective layer disposed around the jacket layer of one or more of the plurality of power conductors and the subassembly. In yet another approach, a bonding/grounding conductor is cabled with the plurality of power conductors and the subassembly.

Abstract: A lightweight and efficient electrical machine element including a method of manufacture providing a stator winding for an electric machine which has a large portion of its volume containing electrically conductive strands and a small portion of its volume containing of an encapsulant material. The stator winding includes winding of a first phase by shaping a portion of a bundle of conductive strands into an overlapping, multi-layer arrangement. Winding of successive phases occurs with further bundles of conductor strands around the preceding phases constructed into similar overlapping, multi-layer arrangements. The multiple phases are impregnated with the encapsulant material using dies to press the bundles into a desired form while expelling excess encapsulant prior to the curing of the encapsulant material. The encapsulated winding is removed from the dies after the encapsulant has cured. The encapsulant coating on the strands may be activated using either heat or solvent.

Abstract: A Metal-Clad (MC) cable assembly includes a core having a plurality of power conductors cabled with a subassembly, each of the plurality of power conductors and the subassembly including an electrical conductor, a layer of insulation, and a jacket layer. The MC cable assembly further includes an assembly jacket layer disposed over the subassembly, and a metal sheath disposed over the core. In one approach, the subassembly is a cabled set of conductors (e.g., twisted pair) operating as class 2 or class 3 circuit conductors in accordance with Article 725 of the National Electrical Code®. In another approach, the MC cable assembly includes a protective layer disposed around the jacket layer of one or more of the plurality of power conductors and the subassembly. In yet another approach, a bonding/grounding conductor is cabled with the plurality of power conductors and the subassembly.

Abstract: An axial flux brushless permanent magnet electrical machine having a stator and at least one rotor. The rotor includes a Halbach array of magnets with at least four magnets per magnetic cycle. The rotor magnets are contained within pockets in the rotor. The pockets are formed with magnet pocket walls being radial walls, active surface walls, and/or inactive surface walls where the walls retain the magnets within the pockets.

Abstract: Data mining of a dental image is described. In an example scenario, an aggregator service receives a dental image of a patient from a dental image provider. The dental image is processed with a machine learning (ML) anatomy dataset. An anatomy from the ML anatomy dataset is identified and matched to the dental image. The dental image is next matched and identified with a ML pathology and treatment dataset. A pathology and a treatment from the ML pathology and treatment dataset are matched to the dental image. Next, the dental image and the anatomy, the pathology, and the treatment associated with the dental image are inserted to a patient dataset associated with the patient. A cluster analysis of the patient dataset is performed with a cluster dataset to produce a correlated dental image information. The correlated dental image information is provided to a data mining entity and to compile a diagnostic aid for a user.

Abstract: A Metal-Clad (MC) cable assembly includes a core having a plurality of power conductors cabled with a subassembly, each of the plurality of power conductors and the subassembly including an electrical conductor, a layer of insulation, and a jacket layer. The MC cable assembly further includes an assembly jacket layer disposed over the subassembly, and a metal sheath disposed over the core. In one approach, the subassembly is a cabled set of conductors (e.g., twisted pair) operating as class 2 or class 3 circuit conductors in accordance with Article 725 of the National Electrical Code®. In another approach, the MC cable assembly includes a protective layer disposed around the jacket layer of one or more of the plurality of power conductors and the subassembly. In yet another approach, a bonding/grounding conductor is cabled with the plurality of power conductors and the subassembly.

Abstract: An axial flux brushless permanent magnet electrical machine having a stator and at least one rotor. The rotor includes a Halbach array of magnets with at least four magnets per magnetic cycle. The rotor magnets are contained within pockets in the rotor. The pockets are formed with magnet pocket walls being radial walls, active surface walls, and/or inactive surface walls where the walls retain the magnets within the pockets.

Abstract: An axial flux brushless permanent magnet electrical machine having a stator and at least one rotor. The rotor includes a Halbach array of magnets with at least four magnets per magnetic cycle. The rotor magnets are contained within pockets in the rotor. The pockets are formed with magnet pocket walls being radial walls, active surface walls, and/or inactive surface walls where the walls retain the magnets within the pockets.