Abstract: The present disclosure discloses a calibration slide for calibration of an automated microscope. The slide includes at least one calibration zone defined on at least one major surface of the sample slide. The at least one calibration zone is divided by a cross hair to define a plurality of quadrants. Each of the plurality of quadrants is defined with an array of apertures of varying density of arrays. The automated microscope including the calibration slide of the present disclosure enables corrective maintenance. The method of the present disclosure may be employed across various automated microscopes within a lab or at labs at various locations through offline/online mode to achieve similar results when tested on same sample.

Abstract: A platform for data collection, and in particular image collection, and model building therefrom is disclosed. In examples, received media content data, including image data, may be assigned a context category, and one or more context-specific models may be used to automatically annotate the image. Accuracy monitoring of the image annotations may indicate a need to manually annotate images for subsequent training. A priority may be assigned to one or more images, such that images may be queued for additional annotation. Such additional annotations may be used for model retraining. In some instances, a separate classification model may be used to identify a context category for image data from among predetermined contexts.

Abstract: Disclosed herein are systems and methods for determining whether an unknown product matches a scanned barcode during a checkout process. An edge computing device or other computer system can receive, from an overhead camera at a checkout lane, image data of an unknown product that is placed on a flatbed scanning area, identify candidate product identifications for the unknown product based on applying a classification model and/or product identification models to the image data, and determine based on the candidate product identifications, whether the unknown product matches a product associated with a barcode that is scanned at a POS terminal in the checkout lane. The classification model can be used to determine n-dimensional space feature values for the unknown product and determine which product the unknown product likely matches. The product identification models can be used to determine whether the unknown product is one of the products that are modeled.

Abstract: Disclosed herein are systems and methods for determining whether an unknown product matches a scanned barcode during a checkout process. An edge computing device or other computer system can receive, from an overhead camera at a checkout lane, image data of an unknown product that is placed on a flatbed scanning area, identify candidate product identifications for the unknown product based on applying a classification model and/or product identification models to the image data, and determine based on the candidate product identifications, whether the unknown product matches a product associated with a barcode that is scanned at a POS terminal in the checkout lane. The classification model can be used to determine n-dimensional space feature values for the unknown product and determine which product the unknown product likely matches. The product identification models can be used to determine whether the unknown product is one of the products that are modeled.

Abstract: Disclosed herein are systems and methods for determining whether an unknown product matches a scanned barcode during a checkout process. An edge computing device or other computer system can receive, from an overhead camera at a checkout lane, image data of an unknown product that is placed on a flatbed scanning area, identify candidate product identifications for the unknown product based on applying a classification model and/or product identification models to the image data, and determine based on the candidate product identifications, whether the unknown product matches a product associated with a barcode that is scanned at a POS terminal in the checkout lane. The classification model can be used to determine n-dimensional space feature values for the unknown product and determine which product the unknown product likely matches. The product identification models can be used to determine whether the unknown product is one of the products that are modeled.

Abstract: A hoof shoe or hoof shoe insert for a hoofed animal. An object is to relieve the pressure on the foot of a hoofed animal, in particular of a horse, on a hard ground surface. This may be achieved by a foamed plastics cushion which is arranged between the hoof of the animal and the ground surface and which is composed of a closed-cell plastics foam having a thermoplastic or elastomeric matrix with a density of between 100 and 400 all and which, at 50% compression, has a compressive stress of 150-280 kPa.

Abstract: A system for providing real-time optimized product designs may obtain historical data and real-time data related to a product to identify real-time customer preferences and sentiments associated with the product. The system may provide a plurality of real-time potential attribute recommendations comprising attributes likely to be preferred by customers. The system may provide a set of preferred attribute recommendations based on the plurality of real-time potential attribute recommendations ranked highest in an attribute ranking order. The system may provide a cannibalization factor and a similarity index for each of the set of preferred attribute recommendations. The system may provide a real-time demand forecast of the product and may also provide a predicted cannibalization volume and a predicted incremental volume for the product in real-time. The system may determine a set of final attribute recommendations for the product to provide an optimized design for the product in real-time.

Abstract: Systems and methods are provided for evaluating a device design to reduce audio speaker generated vibrational energy transfer between adjoining components of a device. The method performs a system-level modal analysis on the design to extract a natural frequency and a mode shape and thereafter create an analysis monitoring point on the design between two adjacent components defining a relative distance. Simulation inputs are fed into a linear dynamics finite element analysis (FEA) solver to solve system equations for a relative displacement of the two adjacent components at the analysis monitoring point, and if the solved relative displacement causes the relative distance to be equal to or less than a zero-relative distance value, then the device design is modified by at least one value of an element from one of the two adjacent components.