Abstract: The subject technology is related to methods and apparatus for training a set of regression machine learning models with a training set to produce a set of predictive values for a pending manufacturing request, the training set including data extracted from a set of manufacturing transactions submitted by a set of entities of a supply chain. A multi-objective optimization model is implemented to (1) receive an input including the set of predictive values and a set of features of a physical object, and (2) generate an output with a set of attributes associated with a manufacture of the physical object in response to receiving the input, the output complying with a multi-objective condition satisfied in the multi-objective optimization model.

Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.

Abstract: The subject technology is related to methods and apparatus for training a set of regression machine learning models with a training set to produce a set of predictive values for a pending manufacturing request, the training set including data extracted from a set of manufacturing transactions submitted by a set of entities of a supply chain. A multi-objective optimization model is implemented to (1) receive an input including the set of predictive values and a set of features of a physical object, and (2) generate an output with a set of attributes associated with a manufacture of the physical object in response to receiving the input, the output complying with a multi-objective condition satisfied in the multi-objective optimization model.

Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.

Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.

Abstract: The subject technology is related to methods and apparatus for training a set of regression machine learning models with a training set to produce a set of predictive values for a pending manufacturing request, the training set including data extracted from a set of manufacturing transactions submitted by a set of entities of a supply chain. A multi-objective optimization model is implemented to (1) receive an input including the set of predictive values and a set of features of a physical object, and (2) generate an output with a set of attributes associated with a manufacture of the physical object in response to receiving the input, the output complying with a multi-objective condition satisfied in the multi-objective optimization model.

Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.

Abstract: The subject technology is related to methods and apparatus for training a set of regression machine learning models with a training set to produce a set of predictive values for a pending manufacturing request, the training set including data extracted from a set of manufacturing transactions submitted by a set of entities of a supply chain. A multi-objective optimization model is implemented to (1) receive an input including the set of predictive values and a set of features of a physical object, and (2) generate an output with a set of attributes associated with a manufacture of the physical object in response to receiving the input, the output complying with a multi-objective condition satisfied in the multi-objective optimization model.

Abstract: A stator angle is determined to correct a value measured by a wheel force transducer. A mounting bracket is rigidly attached to a vehicle and supports a housing within which a rotary encoder is mounted. A stator rod retainer is aligned with a rotational axis of the rotary encoder and has a through-bore extending perpendicular to the rotational axis. The stator rod retainer rotates relative to a stationary portion of the rotary encoder using at least one bearing, and the stator rod retainer supports a first end of a stator rod for substantially free movement through the through-bore. A controller determines, when the second end of the stator rod is fixedly attached to an encoder stator attached to a wheel, a stator angle of the stator rod used for adjusting at least one value associated with the wheel that is measured using the encoder stator.

Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.

Abstract: A barrier material for a containment system comprising: a first portion of polymeric material having an open structure defined by a plurality of small openings to function as a fine screen, the first portion of polymeric material being formed from a plurality of fibrous materials and being configured to form a static structure having a display surface; and a second portion attached to a second surface of the first portion, the second portion having an open structure defined by a plurality openings to function as a reinforcing member for the first portion; wherein the display surface of the first portion is configured to receive and retain a printed image thereon.

Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.

Abstract: The subject technology is related to methods and apparatus for training a set of regression machine learning models with a training set to produce a set of predictive values for a pending manufacturing request, the training set including data extracted from a set of manufacturing transactions submitted by a set of entities of a supply chain. A multi-objective optimization model is implemented to (1) receive an input including the set of predictive values and a set of features of a physical object, and (2) generate an output with a set of attributes associated with a manufacture of the physical object in response to receiving the input, the output complying with a multi-objective condition satisfied in the multi-objective optimization model.

Abstract: A stator angle is determined to correct a value measured by a wheel force transducer. A mounting bracket is rigidly attached to a vehicle and supports a housing within which a rotary encoder is mounted. A stator rod retainer is aligned with a rotational axis of the rotary encoder and has a through-bore extending perpendicular to the rotational axis. The stator rod retainer rotates relative to a stationary portion of the rotary encoder using at least one bearing, and the stator rod retainer supports a first end of a stator rod for substantially free movement through the through-bore. A controller determines, when the second end of the stator rod is fixedly attached to an encoder stator attached to a wheel, a stator angle of the stator rod used for adjusting at least one value associated with the wheel that is measured using the encoder stator.

Abstract: The subject technology is related to methods and apparatus for training a set of regression machine learning models with a training set to produce a set of predictive values for a pending manufacturing request, the training set including data extracted from a set of manufacturing transactions submitted by a set of entities of a supply chain. A multi-objective optimization model is implemented to (1) receive an input including the set of predictive values and a set of features of a physical object, and (2) generate an output with a set of attributes associated with a manufacture of the physical object in response to receiving the input, the output complying with a multi-objective condition satisfied in the multi-objective optimization model.

Abstract: An animal feeding system having a plurality of network connectable feeding stations, each with a base with a weight sensor for measuring a quantity of animal food placed in a food container, a processor, and network connection circuitry for connecting to a computer network. A server having a processor is coupled to a database to store pet information and use AI to analyze food and water consumption and recommend new foods or issue health alerts based on the consumption data. The server is configured for communication to feeding system bases and network connectable devices, such as smart phones, having executable food management software, wherein animal food intake information is transmitted to the server; and executable artificial intelligence loaded into and running on the server receives and processes data from the feeding stations and analyzes the data to make predictions and recommendations for foods individual animals prefer.

Abstract: A wheel force transducer stator angle correction apparatus. The apparatus includes a stator rod retainer having a through-bore, the stator rod retainer being in mechanical communication with at least one bearing. The apparatus also includes a stator rod having a first portion rigidly attached to an encoder stator attached to a wheel and having a second portion disposed within the through-bore of the stator rod retainer. The apparatus also includes an encoder rigidly attached to a portion of a vehicle associated with the wheel, wherein the encoder is adapted to measure an angle of the stator rod and to adjust at least one value associated with a wheel speed of the wheel based on the measured angle of the stator rod.

Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.

Abstract: A barrier material for a containment system comprising: a first portion of polymeric material having an open structure defined by a plurality of small openings to function as a line screen, the first portion of polymeric material being formed from a plurality of fibrous materials and being configured to form a static structure having a display surface; and a second portion attached to a second surface of the first portion, the second portion having an open structure defined by a plurality openings to function as a reinforcing member for the first portion; wherein the display surface of the first portion is configured to receive and retain a printed image thereon.

Abstract: The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.