Abstract: A filter screen for cross-flow filtration includes a cross-sectional thickness measured from an outer surface to an inner surface, the outer surface configured to exclude particles; and a plurality of slots that are evenly spaced apart. Each of the slots have a length along a longest axis at the outer surface; a width measured from a perpendicular axis relative to the length at the outer surface that is less than the length; and a depth along the cross-sectional thickness that is tapered.

Abstract: Systems and methods are provided for establishing an AR infrastructure in a defined space. Physical objects in the defined space are identified using proximity technology for inclusion in a geo-location dependency matrix. A plurality of physical identifying characteristics associated with the physical objects is collected. A logical relationship between the physical object and the other physical objects is determined. The physical objects are connected by determined logical relationships. The geographical location and orientation of the physical object within the defined space are processed, and an activity is associated with the physical object.

Abstract: Provided is a filter screen having a plurality of slots, each slot having a longest principal axis A1 that has a length L, and each slot having a second axis A2 that is perpendicular to A1 and that has a length W, wherein the distance between adjacent slots in the direction of the axes A2 is XP; wherein XP is greater than W; wherein the distance between adjacent slots in the direction of the axes A1 is YP; either wherein L is 800 micrometers or less and XP is 350 micrometers or less, or wherein L is 1600 ?m or less and XP is 180 ?m or less. Also provided is a method of filtering feed water using such a filter screen.

Abstract: Methods and systems are provided for processing a signal over a serial link. The methods and systems receive, by an adjustable filter, a serial input signal, the adjustable filter configured to set a corner frequency of a channel response and a gain of the channel response, the adjustable filter adding a zero to the channel response before to a pole of the serial input signal. The methods and systems selectively apply, by a bandwidth booster component, compensation to signal attenuation of the serial input signal in a first mode of operation and of one or more test signals in a second mode of operation of a serial link receiver. The methods and systems generate, by one or more continuous time linear equalizers configured to receive on an output of the bandwidth booster, one or more output signals of the receiver based on an output signal from the bandwidth booster component.

Abstract: Techniques for predicting a manufacturer and/or contents of a received package are described herein. Images of a package may be received from cameras. A visual vector for the package in a vector space of package attributes may be generated using the images. Physical attributes of the package may be received. A subset of candidate packages may be determined by comparing the physical attributes of a plurality of historically received packages to the physical attributes of the package. A ranking of the subset of candidate packages may be determined by identifying a distance in the vector space of the package attributes between a vector for the subset of candidate packages and the visual vector for the package. An identifier associated with a particular package of the ranked subset of candidate packages may be obtained. Data for the particular package may be retrieved from a database using the identifier.

Abstract: Some embodiments of the present application include obtaining first data from a data feed to be provided to a plurality of machine learning models and detecting a changepoint in the first data. In response to the changepoint being detected, a first machine learning model may be executed on the first data to obtain first output datasets. A first performance score for the first machine learning model may be computed based on the first output datasets. A second machine learning model may be caused to execute on the first data based on the first performance score satisfying a first condition.

Abstract: Some embodiments of the present application include obtaining first data from a data feed to be provided to a plurality of machine learning models and detecting a changepoint in the first data. In response to the changepoint being detected, a first machine learning model may be executed on the first data to obtain first output datasets. A first performance score for the first machine learning model may be computed based on the first output datasets. A second machine learning model may be caused to execute on the first data based on the first performance score satisfying a first condition.

Abstract: Some embodiments of the present application include obtaining first data from a data feed to be provided to a plurality of machine learning models and detecting a changepoint in the first data. In response to the changepoint being detected, a first machine learning model may be executed on the first data to obtain first output datasets. A first performance score for the first machine learning model may be computed based on the first output datasets. A second machine learning model may be caused to execute on the first data based on the first performance score satisfying a first condition.

Abstract: A set of first results from a first query are received. Using a natural language processing technique, a set of second results using a second query having at least a portion of the first query and at least a portion of set of first results are generated, wherein the natural language processing technique comprises a machine learning model configured to analyze the set of first results. The set of second results are scored based upon a semantic comparison of the set of first results, the second query, and the set of second results. Using the scored set of the second results, a set of processed results are generated.

Abstract: Provided is a filter screen having a plurality of slots, each slot having a longest principal axis A1 that has a length L, and each slot having a second axis A2 that is perpendicular to A1 and that has a length W, wherein the distance between adjacent slots in the direction of the axes A2 is XP; wherein XP is greater than W; wherein the distance between adjacent slots in the direction of the axes A1 is YP; either wherein L is 800 micrometers or less and XP is 350 micrometers or less, or wherein L is 1600 ?m or less and XP is 180 ?m or less. Also provided is a method of filtering feed water using such a filter screen.

Abstract: A system for online conversion attribution. The system includes a short uniform resource locator (URL) service programmed to, in response to receiving a short URL from a device: provide a cookie that includes a short URL ID to the device, and provide a short URL descriptor including the short URL ID to a user mapping service. The system further includes the user mapping service programmed to receive the short URL descriptor, receive a social media descriptor including a social media ID, map the short URL ID to the social media ID using the short URL descriptor and the social media descriptor, and attribute, using the mapping, a conversion on a website accessed using the device based upon receipt of the short URL ID from the device.

Abstract: A system and a process for building, monitoring, and rebuilding machine learning models includes building a plurality of machine learning models from a design specification, deploy the plurality of machine learning models for operation, and designating a champion and at least one challenger from the plurality of machine learning models built. The system and the process evaluate the plurality of machine learning models and provide results of the evaluation.

Abstract: A method for conversion attribution. The method includes obtaining a first identifier associated with a first device, obtaining a second identifier associated with a second device, bridging the first identifier and the second identifier based on a determination, made by a probabilistic classifier, that the first identifier and the second identifier are associated with a common user, and attributing, using the bridge, a conversion on a website accessed using the second device.

Abstract: A system for online conversion attribution. The system includes a short uniform resource locator (URL) service programmed to, in response to receiving a short URL from a device: provide a cookie that includes a short URL ID to the device, and provide a short URL descriptor including the short URL ID to a user mapping service. The system further includes the user mapping service programmed to receive the short URL descriptor, receive a social media descriptor including a social media ID, map the short URL ID to the social media ID using the short URL descriptor and the social media descriptor, and attribute, using the mapping, a conversion on a website accessed using the device based upon receipt of the short URL ID from the device.

Abstract: A method for conversion attribution. The method includes obtaining a first identifier associated with a first device, obtaining a second identifier associated with a second device, bridging the first identifier and the second identifier based on a determination, made by a probabilistic classifier, that the first identifier and the second identifier are associated with a common user, and attributing, using the bridge, a conversion on a website accessed using the second device.

Abstract: A system for online conversion attribution. The system includes a short uniform resource locator (URL) service programmed to, in response to receiving a short URL from a device: provide a cookie that includes a short URL ID to the device, and provide a short URL descriptor including the short URL ID to a user mapping service. The system further includes the user mapping service programmed to receive the short URL descriptor, receive a social media descriptor including a social media ID, map the short URL ID to the social media ID using the short URL descriptor and the social media descriptor, and attribute, using the mapping, a conversion on a website accessed using the device based upon receipt of the short URL ID from the device.

Abstract: A system, method, and computer-readable storage media, having computer-executable instructions embodied thereon, for organizing and describing product information is provided. The system includes a memory device, an IDML module, and a display module. The memory device is configured to store product data in a plurality of product records. Each product record is associated with an associated one of a plurality of products and has an associated product type. The product records provide may be used to the efficient storage, processing and exchange of product information. The IDML module is configured to receive a product request and receive, from the memory device, results data associated with the product request. The results data includes a plurality of product records. The display module receives the results data and responsively displays the results data associated with the product request.

Abstract: A system for online conversion attribution. The system includes a short uniform resource locator (URL) service programmed to, in response to receiving a short URL from a device: provide a cookie that includes a short URL ID to the device, and provide a short URL descriptor including the short URL ID to a user mapping service. The system further includes the user mapping service programmed to receive the short URL descriptor, receive a social media descriptor including a social media ID, map the short URL ID to the social media ID using the short URL descriptor and the social media descriptor, and attribute, using the mapping, a conversion on a website accessed using the device based upon receipt of the short URL ID from the device.

Abstract: A method for conversion attribution. The method includes obtaining a first identifier associated with a first device, obtaining a second identifier associated with a second device, bridging the first identifier and the second identifier based on a determination, made by a probabilistic classifier, that the first identifier and the second identifier are associated with a common user, and attributing, using the bridge, a conversion on a website accessed using the second device.

Abstract: A set of first results from a first query are received. Using a natural language processing technique, a set of second results using a second query having at least a portion of the first query and at least a portion of set of first results are generated, wherein the natural language processing technique comprises a machine learning model configured to analyze the set of first results. The set of second results are scored based upon a semantic comparison of the set of first results, the second query, and the set of second results. Using the scored set of the second results, a set of processed results are generated.