Abstract: A surgical system including a patient tracker and a tracking system. The patient tracker is adapted for attachment to a patient, and includes a hybrid marker having a radiological marker contained within an optical marker. The tracking system tracks the hybrid marker. A computing device obtains a three-dimensional image of a patient's anatomy and the attached patient tracker; identifies a three-dimensional portion of the hybrid marker within a scan volume; determines a location of the hybrid marker within the scan volume based on the identified three-dimensional portion; tracks the location of the hybrid marker in three-dimensional space using the tracking system while the patient tracker remains fixed to the patient; and registers the three-dimensional image in three-dimensional space based on a known geometric relationship between the location of the hybrid marker within the scan volume and the location of the hybrid marker in three-dimensional space.

Abstract: A method, apparatus and computer program product are provided for calculating closing metrics regarding a contract between a promotion service and provider. A promotional system may calculate a probability of closing, and an estimated time to close. The promotion service may offer a promotion to consumers for a discounted product or service, to be honored by the provider. A category, lead source, historical data, stage in sales, and/or size of the provider may be used in calculating a probability of close and/or time to close. An example method may comprise supplying a classifying model with a dataset, wherein the dataset comprises an identification of a provider and attributes corresponding to the provider and identifying a class of the provider in accordance with the plurality of corresponding attributes, wherein the identification is determined based on one or more patterns determinative of a return rate by the classifying model.

Abstract: A surgical system including a patient tracker and a tracking system. The patient tracker is adapted for attachment to a patient, and includes a hybrid marker having a radiological marker contained within an optical marker. The tracking system tracks the hybrid marker. A computing device obtains a three-dimensional image of a patient's anatomy and the attached patient tracker; identifies a three-dimensional portion of the hybrid marker within a scan volume; determines a location of the hybrid marker within the scan volume based on the identified three-dimensional portion; tracks the location of the hybrid marker in three-dimensional space using the tracking system while the patient tracker remains fixed to the patient; and registers the three-dimensional image in three-dimensional space based on a known geometric relationship between the location of the hybrid marker within the scan volume and the location of the hybrid marker in three-dimensional space.

Abstract: A method, apparatus and computer program product are provided for calculating closing metrics regarding a contract between a promotion service and provider. A promotional system may calculate a probability of closing, and an estimated time to close. The promotion service may offer a promotion to consumers for a discounted product or service, to be honored by the provider. A category, lead source, historical data, stage in sales, and/or size of the provider may be used in calculating a probability of close and/or time to close. An example method may comprise supplying a classifying model with a dataset, wherein the dataset comprises an identification of a provider and attributes corresponding to the provider and identifying a class of the provider in accordance with the plurality of corresponding attributes, wherein the identification is determined based on one or more patterns determinative of a return rate by the classifying model.

Abstract: A method, apparatus and computer program product are provided for calculating closing metrics regarding a contract between a promotion service and provider. A promotional system may calculate a probability of closing, and an estimated time to close. The promotion service may offer a promotion to consumers for a discounted product or service, to be honored by the provider. A category, lead source, historical data, stage in sales, and/or size of the provider may be used in calculating a probability of close and/or time to close. An example method may comprise supplying a classifying model with a dataset, wherein the dataset comprises an identification of a provider and attributes corresponding to the provider and identifying a class of the provider in accordance with the plurality of corresponding attributes, wherein the identification is determined based on one or more patterns determinative of a return rate by the classifying model.

Abstract: A method, apparatus and computer program product are provided for calculating closing metrics regarding a contract between a promotion service and provider. A promotional system may calculate a probability of closing, and an estimated time to close. The promotion service may offer a promotion to consumers for a discounted product or service, to be honored by the provider. A category, lead source, historical data, stage in sales, and/or size of the provider may be used in calculating a probability of close and/or time to close. An example method may comprise supplying a classifying model with a dataset, wherein the dataset comprises an identification of a provider and attributes corresponding to the provider and identifying a class of the provider in accordance with the plurality of corresponding attributes, wherein the identification is determined based on one or more patterns determinative of a return rate by the classifying model.

Abstract: A surgical system including a patient tracker and a tracking system. The patient tracker is adapted for attachment to a patient, and includes a hybrid marker having a radiological marker contained within an optical marker. The tracking system tracks the hybrid marker. A computing device obtains a three-dimensional image of a patient' s anatomy and the attached patient tracker; identifies a three-dimensional portion of the hybrid marker within a scan volume; determines a location of the hybrid marker within the scan volume based on the identified three-dimensional portion; tracks the location of the hybrid marker in three-dimensional space using the tracking system while the patient tracker remains fixed to the patient; and registers the three-dimensional image in three-dimensional space based on a known geometric relationship between the location of the hybrid marker within the scan volume and the location of the hybrid marker in three-dimensional space.

Abstract: A method, apparatus and computer program product are provided for calculating closing metrics regarding a contract between a promotion service and provider. A promotional system may calculate a probability of closing, and an estimated time to close. The promotion service may offer a promotion to consumers for a discounted product or service, to be honored by the provider. A category, lead source, historical data, stage in sales, and/or size of the provider may be used in calculating a probability of close and/or time to close. An example method may comprise supplying a classifying model with a dataset, wherein the dataset comprises an identification of a provider and attributes corresponding to the provider and identifying a class of the provider in accordance with the plurality of corresponding attributes, wherein the identification is determined based on one or more patterns determinative of a return rate by the classifying model.

Abstract: A method, apparatus and computer program product are provided for calculating closing metrics regarding a contract between a promotion service and provider. A promotional system may calculate a probability of closing, and an estimated time to close. The promotion service may offer a promotion to consumers for a discounted product or service, to be honored by the provider. A category, lead source, historical data, stage in sales, and/or size of the provider may be used in calculating a probability of close and/or time to close. An example method may comprise supplying a classifying model with a dataset, wherein the dataset comprises an identification of a provider and attributes corresponding to the provider and identifying a class of the provider in accordance with the plurality of corresponding attributes, wherein the identification is determined based on one or more patterns determinative of a return rate by the classifying model.

Abstract: Provided herein are systems, methods and computer readable media for classifying a provider of products, services or experiences as a provider that should be engaged based on a predicted return rate for any products, services or experiences that may be offered and purchased by a consumer. An example method may comprise supplying a classifying model with a dataset, wherein the dataset comprises an identification of a provider and a plurality of attributes corresponding to the provider and identifying a class of the provider in accordance with the plurality of corresponding attributes, wherein the identification is determined based on one or more patterns determinative of a return rate by the classifying model.

Abstract: Provided herein are systems, methods and computer readable media for classifying a provider of products, services or experiences as a provider that should be engaged based on a predicted return rate for any products, services or experiences that may be offered and purchased by a consumer. An example method may comprise supplying a classifying model with a dataset, wherein the dataset comprises an identification of a provider and a plurality of attributes corresponding to the provider and identifying a class of the provider in accordance with the plurality of corresponding attributes, wherein the identification is determined based on one or more patterns determinative of a return rate by the classifying model.

Abstract: A method, apparatus and computer program product are provided for calculating closing metrics regarding a contract between a promotion service and provider. A promotional system may calculate a probability of closing, and an estimated time to close. The promotion service may offer a promotion to consumers for a discounted product or service, to be honored by the provider. A category, lead source, historical data, stage in sales, and/or size of the provider may be used in calculating a probability of close and/or time to close. An example method may comprise supplying a classifying model with a dataset, wherein the dataset comprises an identification of a provider and attributes corresponding to the provider and identifying a class of the provider in accordance with the plurality of corresponding attributes, wherein the identification is determined based on one or more patterns determinative of a return rate by the classifying model.

Abstract: Provided herein are systems, methods and computer readable media for classifying a provider of products, services or experiences as a provider that should be engaged based on a predicted return rate for any products, services or experiences that may be offered and purchased by a consumer. An example method may comprise supplying a classifying model with a dataset, wherein the dataset comprises an identification of a provider and a plurality of attributes corresponding to the provider and identifying a class of the provider in accordance with the plurality of corresponding attributes, wherein the identification is determined based on one or more patterns determinative of a return rate by the classifying model.

Abstract: One embodiment relates to a method of real-time three-dimensional electron beam imaging of a substrate surface. A primary electron beam is scanned over the substrate surface causing electrons to be emitted therefrom. The emitted electrons are simultaneously detection using a plurality of at least two off-axis sensors so as to generate a plurality of image data frames, each image data frame being due to electrons emitted from the substrate surface at a different view angle. The plurality of image data frames are automatically processed to generate a three-dimensional representation of the substrate surface. Multiple views of the three-dimensional representation are then displayed. Other embodiments, aspects and features are also disclosed.

Abstract: A prosthetic knee joint mechanism has an hydraulic load-activated knee-stabilizing device for resisting joint flexion. A rotary piston (34) connected to one part of the mechanism is rotatable within a fluid-filled fluid displacement chamber (18) assocciated with another part of the mechanism to drive fluid through a fluid passage which contains a main valve (38) which restricts or allows joint flexion according to the position of a valve member within the valve. The valve member is movable towards an open position in response to fluid pressure in the fluid passage upstream of the valve member caused by application of a flexion torque to the knee joint mechanism, movement of the valve member in the direction of the open position being at least resisted by a valve control arrangement actuated by application of the wearer's weight. The weight-responsive valve control arrangement is preferably a weight-responsive pilot valve (32) for hydraulically resisting movement of the valve member of the main valve.

Abstract: A method of monitoring equipment of an agricultural machine includes taking a process computer and connecting the same to at least one sensor measuring an operational characteristic of the agricultural machine. The process computer evaluates the data received from the sensor and checks whether they indicate a fault of the agricultural machine. In this case, the data may be below and/or above a predetermined threshold. When such as fault or error occurs, the process computer submits a fault message to a remote station using a communications interface. The fault message contains a fault information identifying a type of the fault.

Abstract: A method of monitoring equipment of an agricultural machine includes taking a process computer and connecting the same to at least one sensor measuring an operational characteristic of the agricultural machine. The process computer evaluates the data received from the sensor and checks whether they indicate a fault of the agricultural machine. In this case, the data may be below and/or above a predetermined threshold. When such as fault or error occurs, the process computer submits a fault message to a remote station using a communications interface. The fault message contains a fault information identifying a type of the fault.

Abstract: A method of monitoring equipment of an agricultural machine includes taking a process computer and connecting the same to at least one sensor measuring an operational characteristic of the agricultural machine. The process computer evaluates the data received from the sensor and checks whether they indicate a fault of the agricultural machine. In this case, the data may be below and/or above a predetermined threshold. When such as fault or error occurs, the process computer submits a fault message to a remote station using a communications interface. The fault message contains a fault information identifying a type of the fault.