Procedure and device for the production of pipes from fibrous material mortar.

Procedure for the production of an endless fibrated concrete course

PLASTIC SHEET CORRUGATING APPARATUS

Procédé de moulage de corps creux.

Procédé pour fabriquer des tuyaux en mortier et installation pour la mise en oeuvre de ce procédé.

Installation pour découper dans une bande sans fin et mettre en paquet des feuilles de ciment fibreux encore molles.

Dispositivo per il trasferimento di lastre in fibrocemento dalla macchina di produzione al magazzino di stagionatura.

Procédé et dispositif pour la fabrication directe de plaques planes et ondulées en ciment fibreux.

Procedimento per la fabbricazione di tubi in fibrocemento e macchina per la sua attuazione

Verfahren und Vorrichtung für die Herstellung von armierten Faser-Zementplatten.

Procedimento e macchina per la fabbricazione di oggetti in fibrocemento partendo da una miscela acquosa di fibrocemento.

Vorrichtung zum Auftrennen eines stetig bewegten, plattenförmigen Körpers in Platten bestimmter Länge.

Procedimento e macchina per la produzione di lastre ondulate di fibrocemento.

Giunto per il collegamento a tenuta di elementi tubolari cilindrici coassiali

Machine à calandrer les corps creux cylindriques.

Défibreur pour la préparation de fibres.

Verfahren zum Herstellen von Asbestzementrohren.

Equipaggio di compressione in una macchina per la fabbricazione di tubi in fibrocemento

Procedure and device for the production of plates from fibrous materials, in particular fibrated concrete

PROCESS FOR THE CONTINUOUS MANUFACTURE OF FIBROUS CEMENT SHEETS

SHEET MATERIAL TRIMMING APPARATUS

PULP TUBE MAKING APPARATUS

MANUFACTURE OF TUBES FROM FIBROUS PULP

FIBRO-CEMENT TUBE MANUFACTURE

Device for promoting plates or Stoffbahnen

Procedure and device for the production of plates from fibrous materials, in particular fibrated concrete

Procedure for forming hollow bodies out of plastic masses.

Fitting

Device for the production of fibrated concrete pipes

APPARATUS FOR HANDLING SHEETS

CONTINUOUS MANUFACTURE OF CEMENT FIBROUS SHEETS

APPARATUS FOR MANUFACTURING SHEETS OF FIBROUS MATERIALS

CONTROL APPARATUS FOR TRAVELING WEB CUT-OFF MECHANISM

METHOD AND APPARATUS FOR MANUFACTURING ENDLESS FIBRO-CEMENT SHEETS

METHOD AND APPARATUS FOR MAKING FIBROUS CEMENT SHEETS

METHOD AND APPARATUS FOR PRODUCTION OF REINFORCED FIBROUS CEMENT SHEETS

COMPRESSING EQUIPMENT FOR MACHINES FOR MANUFACTURING FIBRO-CEMENT TUBES

METHOD AND APPARATUS FOR MANUFACTURING ENDLESS FIBRO-CEMENT SHEETS

APPARATUS FOR MAKING REINFORCED FIBROUS CEMENT SHEETS

APPARATUS FOR FEEDING REINFORCING ELEMENTS FOR INCORPORATION INTO CEMENTITIOUS SHEETS

PROCESS AND DEVICE FOR MANUFACTURING FIBRO-CEMENT PIPES

CUTTING, TRIMMING AND DISCHARGING CONTINUOUSLY MANUFACTURED FIBROUS SHEETS

Appareil pour la fabrication de feuilles de matière fibreuse.

Mapping Advertiser Intents to Keywords

In one embodiment, a method includes constructing an intent map for a plurality of products, the intent map comprising intent topics and each intent topic comprising intents, and then deriving a plurality of keywords from the intent map based on keyword templates. 1. A method comprising: by one or more computing devices , the intent map comprises one or more intent topics, and', 'each of the one or more intent topics comprises one or more intents; and, 'constructing an intent map for a plurality of products, whereinderiving a plurality of keywords from the intent map based on one or more keyword templates.2. The method of claim 1 , further comprising constructing the one or more keyword templates.3. The method of claim 2 , wherein at least one of the one or more keyword templates is constructed based on one or more rules.4. The method of claim 3 , wherein the one or more rules are determined based on the one or more intent topics.5. The method of claim 2 , wherein:the one or more intent topics form a hierarchy; andat least one of the one or more keyword templates is constructed based on the hierarchy.6. The method of claim 2 , wherein at least one of the one or more keyword templates is constructed based on a collection of known keywords claim 2 , comprising:analyzing the collection of known keywords;selecting, from the collection of known keywords, one or more known keywords that are applicable to the intent map; andconstructing the at least one of the one or more keyword templates based on the one or more known keywords.7. The method of claim 6 , wherein selecting claim 6 , from the collection of known keywords claim 6 , the one or more known keywords that are applicable to the intent map comprises:selecting, from the collection of known keywords, one or more specific known keywords that are related to the plurality of products;analyzing historical performance information of the one or more specific known keywords that are related to the plurality of products; ...

SYSTEM AND METHOD FOR REAL-TIME COMPRESSION OF DATA FRAMES

The present disclosure relates to system(s) and method(s) for real time compression of a data frame. The system receives the data frame comprising a set of symbols. Further, the system identifies frequency of each symbol, from the set of symbols. The system further sorts the symbols in descending order of frequency, associated with each symbols. Further, the system computes a compression gain associated with each predefined case type, a set of predefined case types. Furthermore, the system selects a target predefined case type, based on the comparison of the compression gain of each predefined case types. The system further assigns a compressed code to Most Frequent Symbols (MFS), in the data frame. The compressed code is assigned based on the target predefined case type. Further, the system generates a compressed frame, associated with the data frame. The compressed frame comprises a header and a sequence of compressed symbols. 1. A method for real-time compression of a data frame , the method comprises:receiving, by a processor, a data frame, wherein the data frame comprises a set of symbols, wherein the length of each symbol is m bits;identifying, by the processor, a frequency associated with each symbol, from the set of symbols, wherein for each symbol, the frequency corresponds to a number of occurrence of the symbol in the data frame;sorting, by the processor, the set of symbols to generate a sorted set of symbols, based on descending order of frequency associated with each symbol from the set of symbols;computing, by the processor, a compression gain associated with each predefined case type, from a set of predefined case types, wherein each predefined case type corresponds to a number of bits (C) used for representing first (2̂C−1) symbols from the sorted set of symbols;selecting, by the processor, a target predefined case type, from the set of predefined case types, based on comparison of the compression gain associated with each predefined case type, ...

SYSTEMS AND METHODS FOR IDENTIFYING ITEMS IN A DIGITAL IMAGE

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of receiving one or more digital images from a repository of digital images; annotating the one or more digital images from the repository of digital images; digitally altering the one or more digital images, as annotated, from the repository of digital images; digitally combining the one or more digital images, as annotated and digitally altered, with at least one or more portions of one or more other digital images of the repository of digital images to create one or more combined digital images; training a machine learning algorithm on the one or more combined digital images; and storing the machine learning algorithm, as trained, in the one or more non-transitory computer readable storage devices. 1. A system comprising:one or more processors; and receiving one or more digital images from a repository of digital images;', 'annotating the one or more digital images from the repository of digital images;', 'digitally altering the one or more digital images, as annotated, from the repository of digital images;', 'digitally combining the one or more digital images, as annotated and digitally altered, with at least one or more portions of one or more other digital images of the repository of digital images to create one or more combined digital images;', 'training a machine learning algorithm on the one or more combined digital images; and', 'storing the machine learning algorithm, as trained, in the one or more non-transitory computer readable storage devices., 'one or more non-transitory computer-readable storage devices storing computing instructions configured to run on the one or more processors and perform acts of2. The system of claim 1 , wherein annotating the one or more digital images from the repository of digital images comprises: an image segmentation algorithm; ...

Systems and methods for identifying items in a digital image

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of receiving a digital image comprising multiple items; determining an embedding for the digital image using a machine learning algorithm trained on one or more combined digital images, the combined digital image comprising one or more annotated digital images; identifying an item of the multiple items in the digital image; and facilitating an alteration of a GUI on an electronic device in response to identifying the item in the digital image.

SYSTEMS, METHOD, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIA FOR MULTI-MODAL PRODUCT CLASSIFICATION

A multi-modal computer classification network system for use in classifying data records is described herein. The system includes a memory device, a first classification computer server, a second classification computer server, and a policy computer server. The memory device includes an item records database and a labeling database. The first classification computer server includes a first classifier program that is configured to select an item record from the item database and generate a first classification record including a first ranked list of class labels. The second classification computer server includes a second classifier program that is configured to generate a second classification record including a second ranked list of class labels. The policy computer server includes a policy network that is programmed to determine a predicted class label based on the first and second ranked lists of class labels. 1. A multi-modal computer classification network system for use in classifying data records , comprising:a memory device including an item records database and a labeling database, the item records database including a plurality of item records, each item record including an item ID, a first classification metadata set, and a second classification metadata set, the labeling database including a plurality of labeling records, each labeling record including a class label and labeling data;a first classification computer server including a first classifier program configured to select an item record from the item database and generate a first classification record including a first ranked list of class labels, the first ranked list of class labels generated using input data including the labeling records and the first classification metadata set included in the selected item record;a second classification computer server including a second classifier program configured to generate a second classification record including a second ranked list of class labels, ...

Systems, method, and non-transitory computer-readable storage media for evaluating, storing, and managing labels for classification model evaluation and training

A system for use in monitoring an operation of a classification model in generating estimated labels for item records is described herein. The system receives a current labeling budget value including a number of trusted labels available for use in a labeling operation, determines a current selection probability for each item record included in an item list as a function of the current labeling budget value, selects a plurality of item records from the item list as a function of each corresponding current selection probability, and generates a sampling list including the selected item records. The system determines a risk measurement value associated with the classification model indicating an accuracy of the estimated labels as compared to trusted labels associated with the item records.

SYSTEMS AND METHODS FOR PROVIDING PLUG-AND-PLAY FRAMEWORKS FOR TRAINING MODELS USING SEMI-SUPERVISED LEARNING TECHNIQUES

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of providing a semi-supervised learning abstraction model that includes an API; receiving, via the API, pre-training parameters at least identifying (a) a first set of unlabeled images and (b) an encoder model selected from the plurality of encoder models; executing a pre-training procedure that trains the encoder model using the first set of unlabeled images; receiving, via the API, supervised training parameters at least identifying (a) a second set of labeled images and (b) the encoder model that is pre-trained using the pre-training procedure; executing a supervised training procedure that further trains the encoder model using the second set of labeled images; and storing a encoder model checkpoint for the encoder model. Other embodiments are disclosed herein. 1. A system comprising:one or more processors; and providing a semi-supervised learning (SSL) abstraction model that includes an application programming interface (API), wherein the API is configured to access an encoder library comprising a plurality of encoder models and to collect user-specified input parameters used to facilitate training of the plurality of encoder models;', 'receiving, via the API, pre-training parameters at least identifying (a) a first set of unlabeled images and (b) an encoder model selected from the plurality of encoder models;', 'executing a pre-training procedure that trains the encoder model using the first set of unlabeled images;', 'receiving, via the API, supervised training parameters at least identifying (a) a second set of labeled images and (b) the encoder model that is pre-trained using the pre-training procedure;', 'executing a supervised training procedure that further trains the encoder model using the second set of labeled images; and', 'storing a encoder model checkpoint ...

SYSTEMS, METHODS, AND TECHNIQUES FOR TRAINING NEURAL NETWORKS AND UTILIZING THE NEURAL NETWORKS TO DETECT NON-COMPLIANT CONTENT

A system can include one or more processors and one or more non-transitory computer-readable storage media storing computing instructions configured to run on the one or more processors and perform: generating a training dataset for training a neural network detection model; identifying, using the neural network detection model, as trained, the non-compliant content in the synthetic training images; receiving, at the neural network detection model, at least one image; and utilizing the neural network detection model to determine whether the at least one image comprises the non-compliant content. Other embodiments are disclosed herein. 1. A system comprising:one or more processors; and [ generating, using a transformation algorithm, synthetic training images by (i) applying one or more random transformations on a first set of images comprising non-compliant content and (ii) appending the non-compliant content to a second set of compliant images; and', 'utilizing the transformation algorithm by (i) applying the one or more random transformations on edge case training images and (ii) appending the edge case training images to one or more compliant images in the second set of compliant images;, 'generating a training dataset for training a neural network detection model comprising, 'identifying, using the neural network detection model, as trained, the non-compliant content in the synthetic training images;', 'receiving, at the neural network detection model, at least one image; and', 'utilizing the neural network detection model to determine whether the at least one image comprises the non-compliant content., 'one or more non-transitory computer-readable storage media storing computing instructions configured to run on the one or more processors and perform2. The system of claim 1 , wherein generating the training dataset for training the neural network detection model further comprises:receiving the first set of images comprising the non-compliant content; ...

MICROPHONE WITH FLEXIBLE PERFORMANCE

Disclosed embodiments provide flexible performance, high dynamic range, microelectromechanical (MEMS) multipath digital microphones, which allow seamless, low latency transitions between audio signal paths without audible artifacts over interruptions in the audio output signal. Disclosed embodiments facilitate performance and power saving mode transitions maintaining high dynamic range capability. 1. An apparatus , comprising:an application specific integrated circuit (ASIC) associated with a microelectromechanical systems (MEMS) acoustic sensor and having a plurality of signal paths associated with the MEMS acoustic sensor, wherein the plurality of signal paths have different gains;a digital signal processing component (DSP) associated with the ASIC configured to receive a plurality of signals from a plurality of adjustable analog-to-digital converters (ADCs) associated with the plurality of signal paths of the MEMS acoustic sensor;a plurality of signal level estimation components associated with the DSP configured to estimate respective signal levels associated with at least respective portions of the plurality of signal paths;a gain adjustment component associated with the DSP configured to adjust respective gains associated with the plurality of adjustable ADCs based at least in part on the respective signal levels;a multipath digital audio combiner component associated with the DSP configured to compensate for gain imbalance among the at least respective portions of the plurality of signal paths to generate an output signal; anda power management component associated with the DSP configured to manage power states associated with components associated with the plurality of signal paths of the MEMS acoustic sensor based at least in part on a selected transition of modes based at least in part on at least one of a performance criteria or a power consumption criteria.2. The apparatus of claim 1 , further comprising:a signal smoothing component configured to smooth ...

Building Product-Based Advertising Campaigns

In one embodiment, a method includes receiving, from an advertiser, an identification of one or more products in a catalog of the advertiser. The method may further include accessing an information graph that contains nodes and edges connecting the nodes. The nodes in the graph represent concepts related to at least one vertical. The method further includes associating a first node in the graph with a second node in the graph based on a relationship between the meaning of the concept represented by the first node and the meaning of the concept represented by the second node. A portion of the graph corresponds to an advertiser's product catalog. The method may further include identifying, based on the portion of the graph corresponding to the products identified by the advertiser, one or more products or product types related to the products identified by the advertiser. The method may further include incorporating into an advertising campaign for the products identified by the advertiser, the products or product types identified from the portion of the graph corresponding to the portion of the products identified by the advertiser. 1by a computing device, receiving, from an advertiser, an identification of one or more products in a catalog of the advertiser;by a computing device, accessing a graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each node connected by at least one edge to at least one other node in the graph, each node representing a concept related to at least one vertical, each edge representing a relationship between two nodes, at least a first node associated with at least one second node based on a relationship between a meaning of the concept represented by the first node and a meaning of the concept represented by the second node, at least a portion of the graph corresponding to the products identified by the advertiser;by a computing device, identifying, based on the portion of the graph corresponding to the ...

Enriched Knowledge Base For Advertising

In one embodiment, a method includes creating an information graph that contains nodes and edges connecting the nodes. The nodes in the graph represent concepts related to at least one vertical. The method further includes associating a first node in the graph with a second node in the graph based on a relationship between the meaning of the concept represented by the first node and the meaning of the concept represented by the second node. 1by a computing device, creating a graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each node connected by at least one edge to at least one other node in the graph, each node representing a concept related to at least one vertical; andby a computing device, associating a first node with a second node based on a relationship between a meaning of the concept represented by the first node and a meaning of the concept represented by the second node.. A method comprising: This application claims the benefit, under 35 U.S.C. §119(e), of U.S. Provisional Patent Application No. 61/800,641, filed 15 Mar. 2013, which is incorporated herein by reference. This application also claims the benefit, under 35 U.S.C. §119(e), of U.S. Provisional Patent Application No. 61/794,925, filed 15 Mar. 2013, which is incorporated herein by reference.This disclosure generally relates to characterizing electronic content and interactions with that content, and to advertising based on those characterizations.Advertising is frequently performed on an electronic medium, such as the internet. An advantage of internet advertising over more traditional advertising (such as advertising on billboards or in newspapers or magazines) is more customized or personal advertising, even down to the level of individual users. More personalized advertising tends to be more effective than less personalized advertising, and personalized advertising tends to be more effective when the advertisements are specifically directed at users who are ...

Automatically Creating Advertising Campaigns

In one embodiment, a method includes accessing an information graph that contains nodes and edges connecting the nodes. The nodes in the graph represent concepts related to at least one vertical. The method further includes associating a first node in the graph with a second node in the graph based on a relationship between the meaning of the concept represented by the first node and the meaning of the concept represented by the second node. A portion of the graph corresponds to an advertiser's product catalog. The method may further include accessing one or more targeting criteria for one or more products in the portion of the product catalog. The method may further include creating at least a portion of an advertising campaign, for at least one product for which targeting criteria has been accessed, based on the targeting criteria and the portion of the graph corresponding to the portion of the product catalog. 1by a computing device, accessing a graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each node connected by at least one edge to at least one other node in the graph, each node representing a concept related to at least one vertical, each edge representing a relationship between two nodes, at least a first node associated with at least one second node based on a relationship between a meaning of the concept represented by the first node and a meaning of the concept represented by the second node, at least a portion of the graph corresponding to a portion of a product catalog of an advertiser;by a computing device, accessing one or more targeting criteria for one or more products in the portion of the product catalog; andby a computing device, creating at least a portion of an advertising campaign for at least one product in the portion of the product catalog based on the targeting criteria and the portion of the graph corresponding to the portion of the product catalog of the advertiser.. A method comprising: This ...

Generating Ad Copy

In one embodiment, a method includes accessing an information graph that contains nodes and edges connecting the nodes. The nodes in the graph represent concepts related to at least one vertical. The method further includes associating a first node in the graph with a second node in the graph based on a relationship between the meaning of the concept represented by the first node and the meaning of the concept represented by the second node. A portion of the graph corresponds to an advertiser's product catalog. The method may further include accessing an ad library that contains elements for an advertisement. The method may further include selecting at least one of the elements based on the portion of the graph corresponding to the portion of the product catalog of the advertiser. The method may further include generating an advertisement for display based on the selected elements. 1by a computing device, accessing a graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each node connected by at least one edge to at least one other node in the graph, each node representing a concept related to at least one vertical, each edge representing a relationship between two nodes, at least a first node associated with at least one second node based on a relationship between a meaning of the concept represented by the first node and a meaning of the concept represented by the second node, at least a portion of the graph corresponding to a portion of a product catalog of an advertiser;by a computing device, accessing an advertisement library comprising one or more elements for an advertisement;by a computing device, selecting, from the advertisement library, one or more of the elements from the advertisement library based on the portion of the graph corresponding to the portion of the product catalog of the advertiser;by a computing device, generating an advertisement for display based on the selected elements.. A method comprising: This ...

Enriching An Advertiser's Product-Related Information

In one embodiment, a method includes accessing information about an advertiser's product catalog. The method may further include accessing an information graph that contains nodes and edges connecting the nodes. The nodes in the graph represent concepts related to at least one vertical. The method further includes associating a first node in the graph with a second node in the graph based on a relationship between the meaning of the concept represented by the first node and the meaning of the concept represented by the second node. A portion of the graph corresponds to the advertiser's product catalog. The method may further include enriching information associated with the portion of the product catalog with information related to the concepts and relationships represented by the portion of the graph corresponding to the portion of the product catalog of the advertiser.

METHODS AND APPARATUS FOR AUTOMATICALLY PROVIDING A RANKING OF ITEMS IN RESPONSE TO A SEARCH REQUEST

This application relates to apparatus and methods for ranking search results. In some examples, a computing device receives item data identifying items for a search query provided by a user. The computing determines, for each item, a first value based on a relevance of the item to the search query. The computing device also determines user engagement data for the user, where the user engagement data identifies engagements by the user on a webpage. The computing device determines, for each item, a second value based on the user engagement data. In some examples, the computing device determines the first values and second values by executing one or more machine learning models. The computing device further determines a ranking of the plurality of items based on the first values and the second values. The computing may transmit the ranking of the plurality of items, such as to a web server. 1. A system comprising: receive item data identifying a plurality of items for a search query provided by a user;', 'determine, for each of the plurality of items, a first value based on a relevance of each of the plurality of items to the search query;', 'determine user engagement data for the user, wherein the user engagement data identifies engagements by the user on a webpage;', 'determine, for each of the plurality of items, a second value based on the user engagement data;', 'determine, based on the first values and the second values, a ranking of the plurality of items; and', 'transmit the ranking of the plurality of items., 'a computing device configured to2. The system of claim 1 , wherein the item data identifies an initial ranking of the plurality of items claim 1 , and wherein the computing device is configured to:determine, for each of the plurality of items, item engagement data identifying engagements by the user for each of the plurality of items; anddetermine, for each of the plurality of items, a third value based on the initial ranking of the plurality of items ...

SYSTEMS AND METHODS FOR RETRAINING OF MACHINE LEARNED SYSTEMS

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform: training a visual similarity model; determining one or more nearest neighbors for an item using the visual similarity model, as trained; ranking the one or more nearest neighbors using results of the visual similarity model, as trained; re-ranking the one or more nearest neighbors using a learning-to-rank algorithm; and facilitating altering a graphical user interface (GUI) displaying the item based upon the one or more nearest neighbors, as re-ranked. Other embodiments are disclosed herein. 1. A system comprising:one or more processors; and training a visual similarity model;', 'determining one or more nearest neighbors for an item using the visual similarity model, as trained;', 'ranking the one or more nearest neighbors using results of the visual similarity model, as trained;', 're-ranking the one or more nearest neighbors using a learning-to-rank algorithm; and', 'facilitating altering a graphical user interface (GUI) displaying the item based upon the one or more nearest neighbors, as re-ranked., 'one or more non-transitory computer-readable storage devices storing computing instructions configured to run on the one or more processors and perform2. The system of claim 1 , wherein:the learning-to-rank algorithm is trained on user engagement data of the item displayed on a website viewed by one or more users.3. The system of claim 2 , wherein features of the user engagement data comprise at least one of:(1) a respective purchase of a respective nearest neighbor of the one or more nearest neighbors after the one or more users have viewed the item;(2) a respective click of the respective nearest neighbor of the one or more nearest neighbors after the one or more users have viewed the item;(3) a respective view of the respective nearest neighbor of the one or more nearest ...

SYSTEMS, METHODS, AND TECHNIQUES FOR TRAINING NEURAL NETWORKS AND UTILIZING THE NEURAL NETWORKS TO DETECT NON-COMPLIANT CONTENT

Systems and methods including one or more processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of: generating a training dataset comprising synthetic training images for training a neural network detection model to identify non-compliant content in images; executing a training procedure that utilizes the synthetic training images to train the neural network detection model to identify the non-compliant content; receiving, at the neural network detection model, at least one image; and utilizing the neural network detection model to determine whether the at least one image includes the non-compliant content. Other embodiments are disclosed herein. 1. A system comprising:one or more processors; and [ receiving a first set of images including the non-compliant content;', 'receiving a second set of compliant images; and', 'executing a transformation algorithm that is configured to generate synthetic training images by applying one or more random transformations on the first set of images including the non-compliant content and appending the non-compliant content to the second set of compliant images;, 'generating a training dataset for training a neural network detection model to identify non-compliant content in images, wherein generating the training dataset comprises, 'executing a training procedure that utilizes the synthetic training images to train the neural network detection model to identify the non-compliant content;', 'receiving, at the neural network detection model, at least one image; and', 'utilizing the neural network detection model to determine whether the at least one image includes the non-compliant content., 'one or more non-transitory computer-readable storage media storing computing instructions configured to run on the one or more processors and perform acts of2. The system of claim 1 , wherein applying the one or more random ...

Systems and methods for detecting offensive content in images using neural network architectures

Systems and methods including one or more processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of: receiving an image at a first-level analysis component comprising a first neural network structure; analyzing, using the first neural network structure of the first-level analysis component, the image to determine an image category associated with the image; selecting at least one second-level analysis component that is associated with the image category to analyze the image; analyzing, using a second neural network structure associated with the at least one second-level analysis component that was selected, the image to determine whether the image includes non-compliant content; and in response to determining that the image includes non-compliant content, executing a corrective measure. Other embodiments are disclosed herein.

Product image evaluation system and method

A product image evaluation system. In embodiments, the system comprises or interacts with a product database comprising a product information record that comprises a product identifier and a product category for a product, and an image database comprising a plurality of candidate images for the product. In embodiments the image database can comprise images received from a plurality of different sources. The system can comprise a parameterized grouping engine configured to separate images into groups of similar images, an image selector configured to select one or more images from each group, and an image sorter configured to determine an order of the selected images. Embodiments can distill the superset of all available images to provide a set of images that are “sufficiently different” from each other and satisfy quality requirements. As a result, no images containing unique information are left behind, and images containing duplicate or irrelevant information are discarded.

Apparatus for manufacturing sheets of fibrous material

Apparatus for making fibrous cement sheets

Method and apparatus for separating asbestos fiber from the rock containing it

Manufacturing process of fiber cement tubes

Systems, methods, and techniques for training neural networks and utilizing the neural networks to detect non-compliant content

Systems and methods including one or more processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of: generating a training dataset comprising synthetic training images for training a neural network detection model to identify non-compliant content in images; executing a training procedure that utilizes the synthetic training images to train the neural network detection model to identify the non-compliant content; receiving, at the neural network detection model, at least one image; and utilizing the neural network detection model to determine whether the at least one image includes the non-compliant content. Other embodiments are disclosed herein.

Process for the direct manufacture of fibrous cement tubes between couples of rotating cylinders

Methods and apparatuses for providing search results using embedding-based retrieval

A system for retrieving products in response to a customer query includes a computing device configured to obtain query information characterizing a query initiated by the customer on an ecommerce marketplace and to determine embedding-based search results comprising a first list of items. The computing device is also configured to obtain legacy search results comprising a second list of items and to blend the embedding-based search results with the legacy search results to obtain blended search results. The computing device is also configured to send the blended search results to the customer.

Systems and methods for extracting patches from digital images

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of receiving one or more digital images; identifying a foreground of the one or more digital images; analyzing the foreground of the one or more digital images to identify a skin region in the foreground of the one or more digital images; when the skin region is identified, clustering a non-skin remainder of the foreground of the one or more digital images into one or more clusters; extracting one or more patches of the one or more digital images from the one or more clusters of the foreground of the one or more digital images; determining one or more scores for the one or more patches of the one or more digital images; and coordinating displaying a patch of the one or more patches on an electronic display based on the one or more scores for the one or more patches. Other embodiments are disclosed herein.

Machine learning glitch prediction

Disclosed embodiments provide glitch prediction based on machine learning algorithms in mixed analog and digital systems, particularly directed to digital microelectromechanical (MEMS) multipath acoustic sensors or microphones, which allow seamless, low latency gain changes without audible artifacts or interruptions in the audio output signal.

Fremgangsmåde ved fremstilling af plader eller bånd af fibercement og apparat til udførelse af fremgangsmåden.

Improved non-gps positioning systems

A method for determining the relative position of each of a plurality of devices, each device having a three-dimensional local coordinate system; the method comprising the steps of: aligning one of the axes of the local coordinate system of each device with a reference direction; and determining the elevation and azimuth angles, and distance, from each device to another such device. Preferably the reference direction is collinear with the direction of gravity. Preferably the method further comprises a step of aligning the local coordinate systems of the devices, particularly preferably by propagating the local coordinate system of a first device to a second device, and so on throughout all the devices. Preferably each device also comprises a wireless sensor, and may thus collect and generate sensing data such as temperature data, pressure data, force data, stress data, strain data, humidity data, vibration data, presence data, pH data, radioactivity data, gas or liquid level data, or gas or liquid flow rate data. As a consequence of the devices' positioning capability, the method may further comprise each device transmitting location data together with the sensing data. The method may be implemented in areas where GPS positioning methods are not applicable or available, such as within underground tunnels, along pipes, inside buildings, or in war zones. Also provided is a system operable to determine the relative position of each of a plurality of devices, and a device for use in such a system.

Verfahren zum Herstellen von Rohren aus Asbestzement

Anordning för avvattning av en fibercementbana, som kontinuerligt bildas på ytan av en vattengenomsläppande, ändlös bandtransportör

Μεθοδος συνεχους κατασκευης λωριδος εξ ινωδους κονιαματος και συσκευη δια την εκτελεσιν της μεθοδουταυτης.

Systems and methods for extracting patches from digital images

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of receiving one or more digital images; identifying a foreground of the one or more digital images; analyzing the foreground of the one or more digital images to identify a skin region in the foreground of the one or more digital images; when the skin region is identified, clustering a non-skin remainder of the foreground of the one or more digital images into one or more clusters; extracting one or more patches of the one or more digital images from the one or more clusters of the foreground of the one or more digital images; determining one or more scores for the one or more patches of the one or more digital images; and coordinating displaying a patch of the one or more patches on an electronic display based on the one or more scores for the one or more patches. Other embodiments are disclosed herein.

Systems and methods for recall estimation

Some embodiments include systems and methods for recall estimation. An exemplary method comprises determining reservoir sampling and size of labeling from each strata; determining recall and variance for each strata; determining sum of sample size for a time period; and determining reservoir sampling for each strata and label the sample items. Other embodiments are described.

Systems and methods for retraining of machine learned systems

A system comprising one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations comprising: training a visual similarity model to output one or more vector representations in a vector space; determining one or more nearest neighbors based on embeddings nearest to a respective embedding in the vector space for the item; ranking the one or more nearest neighbors for the item in an order; re-ranking the order of the one or more nearest neighbors of the item into a re-ranked order; inserting, into a display of the item, the one or more nearest neighbors of the item; and facilitating altering a graphical user interface (GUI) to convey the display of the item. Other embodiments are disclosed herein.

Vorrichtung zum Herstellen von Faserzementrohren

Process and device for manufacturing fibrocement pipes

Process and device for manufacturing fibrocement pipes

Τελειοποιησεις εις η εν σχεσει προς την κατασκευην σωληνων εκ τσιμεντου αμιαντου.

Förfaringssätt för framställning av glättade rör av asbestcement

Verfahren zur Herstellung von Asbestzementrohren.

Calendering machine

Verfahren zum Schneiden duenner und sehr langer, in teigigem Zustande befindlicher Faserzementplatten o. dgl.

Systems and methods for extracting patches from digital images

A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations: analyzing a respective foreground of one or more related digital images to identify a respective skin region in the respective foreground of the one or more related digital images; when the respective skin region is not identified, analyzing the respective foreground of the one or more related digital images to identify a respective head region in the respective foreground; extracting one or more patches from respective non-head region remainders of the respective foreground; and coordinating displaying a patch of the one or more patches on an electronic display based on one or more scores for the one or more patches. Other embodiments are described herein.

Improvements in or relating to machines for manufacturing fibro-cement pipes

Menetelmä ja laite putkien valmistamista varten kuidun sekaisesta laastista

Verfahren und Vorrichtung zur Herstellung von ebenen und gewellten Platten

Förfarande och maskin för framställning av korrugerade fibercementplattor

Improvements in or relating to machines for manufacturing fibro-cement pipes

Druckvorrichtung an einer Maschine zum Wickeln von Asbestzementrohren

Fremgangsmaade og Anordning til Fremstilling af Rør af Trævlestofmortel.

Maskin för framställning av rör av asbestcement eller dylikt material

Förfaringssätt för framställning av plattor eller band av fibercement och apparat för utförande av förfaringssättet

Procedimento per l'applicazione del cavo di uscita in condensatori elettrici e condensatore cosi'ottenuto

Fremgangsmaade ved Fremstilling af Asbestcementrør.

Μεθοδος και συσκευη δια την απομακρυνσιν πλακων εξ ινωδους κονιαματος απο της μηχανης κατασκευης πλακων.

Installation pour la fabrication continue de plaques planes ou ondulées en ciment fibreux

Apparat til fremstilling af korrugerede fibercementplader.

Maskine til Valsning af hule cylindriske Legemer af fibrøs Cement.

Förfaringssätt och apparat för kontinuerlig avskärning och avläggning av fibercementplattor

Microphone with flexible performance

Disclosed embodiments provide flexible performance, high dynamic range, microelectromechanical (MEMS) multipath digital microphones, which allow seamless, low latency transitions between audio signal paths without audible artifacts over interruptions in the audio output signal. Disclosed embodiments facilitate performance and power saving mode transitions maintaining high dynamic range capability.

Machine learning glitch prediction

Disclosed embodiments provide glitch prediction based on machine learning algorithms in mixed analog and digital systems, particularly directed to digital microelectromechanical (MEMS) multipath acoustic sensors or microphones, which allow seamless, low latency gain changes without audible artifacts or interruptions in the audio output signal.

Inertial axis fusion device, system and method

A device includes one or more inertial sensors and fusion circuitry coupled to the one or more inertial sensors. The inertial sensors, in operation, generate inertial sensor data with respect to a plurality of axes of movement. The fusion circuitry, in a polar fusion mode of operation, applies a plurality of polar rotation operations to the generated inertial sensor data to rotate the generated inertial sensor data onto an axis of the plurality of axes of movement. A fused data signal is generated based on a result of the plurality of polar rotation operations. The plurality of inertial sensors may include bone-conduction sensors.

Pressanordning för maskin för framställning av fibercementrör

Inertial axis fusion device, system and method

A device includes one or more inertial sensors and fusion circuitry coupled to the one or more inertial sensors. The inertial sensors, in operation, generate inertial sensor data with respect to a plurality of axes of movement. The fusion circuitry, in a polar fusion mode of operation, applies a plurality of polar rotation operations to the generated inertial sensor data to rotate the generated inertial sensor data onto an axis of the plurality of axes of movement. A fused data signal is generated based on a result of the plurality of polar rotation operations. The plurality of inertial sensors may include bone-conduction sensors.

Defibreringsmaskine til Fremstilling af Asbestfibre og andre, f. Eks. vegetabilske Fibre.

Dispositivo antiscoppio per condensantori elettrici,in particolare del tipo a nastro avvolto

Dispositivo antiscoppio per condensantori elettrici,in particolare del tipo a nastro avvolto