Abstract: A first subject of the present invention has an antiviral formulation with metallic copper particles in an unoxidized form and having a median particle diameter inferior or equal to 200 nm, graphene oxide or reduced graphene oxide, and a bonding matrix material. A second subject of the invention has an antiviral filtering material with a layer of textile and at least one layer of an antiviral coating comprising metallic copper particles in an unoxidized form and having a median particle diameter inferior or equal to 200 nm, graphene oxide or reduced graphene oxide, and a bonding matrix into which both metallic copper particles and graphene oxide or reduced graphene oxide are anchored. The invention also concerns methods of preparation of the antiviral formulation and of the antiviral filtering material. Finally, the invention includes an antiviral face mask with a layer of textile coated with the antiviral formulation.

Abstract: A self-learning system for categorizing log entries may be provided. The system may display a first log entry and receive a categorical identifier for the first log entry. The system may parse the first log entry for predetermined text information and predetermined image information. The predetermined text information may be included in a datafield classifier and the predetermined image information included in a metadata classifier. The system may identify the predetermined text information in the log entry and adjust a first prioritization of respective categorical identifiers included in the datafield classifier. The system may identify the predetermined image information in the first log entry and adjust a second prioritization of the respective categorical identifiers included in the metadata classifier. The system may map a second log entry to the categorical identifier based on adjustment of the first prioritization or adjustment of the second prioritization.

Abstract: A counterfeit detection system provides an artificial intelligence (AI) platform that implements a Generative Adversarial Network (GAN) to classify an image as one of a fake or genuine item and integrates a Classification Activation Module (CAM) to refine counterfeit detection. The GAN may include a generator that generates simulated counterfeit images for a discriminator. The discriminator may be trained to identify faked items by learning from the simulated counterfeit images and/or images of actual faked items. The discriminator may implement a deep neural network of convolutional layers that each analyze a region of an image and produce a weighted output that contributes to the classification based on the analyzed region. The CAM may identify the regions and weights relied upon by the discriminator, provide corresponding heatmaps to subject matter experts, receive annotations from the subject matter experts, and use the annotations as feedback to refine the classifier of the discriminator.

Abstract: An identification and management system for log entries may filter historical data and generate closed log entries as a reference dataset. A dynamic learning engine may perform statistical modelling using the reference dataset to assign predetermined categories to each of a number of open log entries. An automation index may be generated for each of the open log entries. The automation index is indicative of accuracy of the assigned categories. Some of the open log entries may be identified as priority log entries which are representative of a group of the open log entries. The assigned category of the priority log entries may be analyzed for accuracy and the results of the analysis may be used to train the statistical model so that the open log entries may be iteratively assigned and re-assigned a category until the category of each open log entry reaches a desired accuracy.

Abstract: Implementations are directed to providing categorization of transactional data, and include actions of providing a plurality of word embeddings based on domain-relevant text data, clustering word embeddings of the plurality of word embeddings into a plurality of clusters, receiving, in real-time, transactional data representative of a transaction, providing a category that is to be assigned to the transaction based on the transactional data, and the plurality of clusters, processing the category, the transactional data, the text data, and the plurality of clusters using a semantic search to provide reason text data, the reason text data representing a reason for selection of the category assigned to the transaction, and storing the transaction data, the category, and the reason text data in a transaction database.

Abstract: A counterfeit detection system provides an artificial intelligence (AI) platform that implements a Generative Adversarial Network (GAN) to classify an image as one of a fake or genuine item and integrates a Classification Activation Module (CAM) to refine counterfeit detection. The GAN may include a generator that generates simulated counterfeit images for a discriminator. The discriminator may be trained to identify faked items by learning from the simulated counterfeit images and/or images of actual faked items. The discriminator may implement a deep neural network of convolutional layers that each analyze a region of an image and produce a weighted output that contributes to the classification based on the analyzed region. The CAM may identify the regions and weights relied upon by the discriminator, provide corresponding heatmaps to subject matter experts, receive annotations from the subject matter experts, and use the annotations as feedback to refine the classifier of the discriminator.

Abstract: This document describes systems, methods, devices, and other techniques for detecting procurement fraud in one or more procurement processes. In some implementations, a computing device receives input data representing one or more procurement processes, processes the received input data to generate a respective risk score for each procurement process, each risk score representing a likelihood that the respective procurement process is fraudulent, comprising processing the received input data using (i) one or more predetermined rules and scenarios, and (ii) atypical patterns data mined through unsupervised learning mechanisms, and provides, based on the generated risk score, output data indicating procurement processes that are likely to be fraudulent.

Abstract: A manufacturing method of structures formed co-bonding second structural components to a first structural component. The method comprises the following steps: a) preparing for each second structural component an ensemble wherein a preform of the second structural component, surrounded by a band of a suitable material to form a vacuum bag, is disposed between curing tools which are thus in contact with the bag and not with the preform; b) positioning the ensembles on the first structural component and forming the vacuum bag for the complete structure joining the bands and complementary pieces; c) applying to the resulting assembly an autoclave cycle.

Abstract: Implementations are directed to providing categorization of transactional data, and include actions of providing a plurality of word embeddings based on domain-relevant text data, clustering word embeddings of the plurality of word embeddings into a plurality of clusters, receiving, in real-time, transactional data representative of a transaction, providing a category that is to be assigned to the transaction based on the transactional data, and the plurality of clusters, processing the category, the transactional data, the text data, and the plurality of clusters using a semantic search to provide reason text data, the reason text data representing a reason for selection of the category assigned to the transaction, and storing the transaction data, the category, and the reason text data in a transaction database.

Abstract: An identification and management system for log entries may filter historical data and generate closed log entries as a reference dataset. A dynamic learning engine may perform statistical modelling using the reference dataset to assign predetermined categories to each of a number of open log entries. An automation index may be generated for each of the open log entries. The automation index is indicative of accuracy of the assigned categories. Some of the open log entries may be identified as priority log entries which are representative of a group of the open log entries. The assigned category of the priority log entries may be analyzed for accuracy and the results of the analysis may be used to train the statistical model so that the open log entries may be iteratively assigned and re-assigned a category until the category of each open log entry reaches a desired accuracy.

Abstract: Inspection methods and systems for detecting leaks in a vacuum bag assembly used in the manufacture of a composite part based on spraying helium over the vacuum bag and detecting the helium drawn by the vacuum inside the vacuum bag through a leak. The inspection methods comprise creating a local helium atmosphere in a chamber over the vacuum bag assembly by zones, following a programmed zonal sequence, for a first leak detection test of each zone and a subsequent second leak detection test if the first test gives a positive result. The inspection systems comprise a helium spraying system and helium detecting equipment arranged to implement the inspection methods.

Abstract: A self-learning system for categorizing log entries may be provided. The system may display a first log entry and receive a categorical identifier for the first log entry. The system may parse the first log entry for predetermined text information and predetermined image information. The predetermined text information may be included in a datafield classifier and the predetermined image information included in a metadata classifier. The system may identify the predetermined text information in the log entry and adjust a first prioritization of respective categorical identifiers included in the datafield classifier. The system may identify the predetermined image information in the first log entry and adjust a second prioritization of the respective categorical identifiers included in the metadata classifier. The system may map a second log entry to the categorical identifier based on adjustment of the first prioritization or adjustment of the second prioritization.

Abstract: A self-learning system for categorizing log entries may be provided. A text classifier may identify a log description of a log entry in response to text of the log description being associated with indicators of a word model. A datafield classifier may generate a datafield metrics including an accuracy of the categorical identifiers representing the datafield. A metafield classifier may generate a context metrics for the context of the log entry, the context metrics including an accuracy categorical identifiers representing the metafields. A combination classifier may form a weighted classification set and select a categorical identifier as being representative of the datafield based on the weighted classification set. A categorical controller may identify new categories based on an analysis of the context metrics of the log entry.

Abstract: A self-learning system for categorizing log entries may be provided. A text classifier may identify a log description of a log entry in response to text of the log description being associated with indicators of a word model. A datafield classifier may generate a datafield metrics including an accuracy of the categorical identifiers representing the datafield. A metafield classifier may generate a context metrics for the context of the log entry, the context metrics including an accuracy categorical identifiers representing the metafields. A combination classifier may form a weighted classification set and select a categorical identifier as being representative of the datafield based on the weighted classification set. A categorical controller may identify new categories based on an analysis of the context metrics of the log entry.

Abstract: Inspection methods and systems for detecting leaks in a vacuum bag assembly used in the manufacture of a composite part based on spraying helium over the vacuum bag and detecting the helium drawn by the vacuum inside the vacuum bag through a leak. The inspection methods comprise creating a local helium atmosphere in a chamber over the vacuum bag assembly by zones, following a programmed zonal sequence, for a first leak detection test of each zone and a subsequent second leak detection test if the first test gives a positive result. The inspection systems comprise a helium spraying system and helium detecting equipment arranged to implement the inspection methods.

Abstract: A manufacturing method of structures formed co-bonding second structural components to a first structural component. The method comprises the following steps: a) preparing for each second structural component an ensemble wherein a preform of the second structural component, surrounded by a band of a suitable material to form a vacuum bag, is disposed between curing tools which are thus in contact with the bag and not with the preform; b) positioning the ensembles on the first structural component and forming the vacuum bag for the complete structure joining the bands and complementary pieces; c) applying to the resulting assembly an autoclave cycle.

Abstract: The purpose of the present invention is to demonstrate that semiconducting and non-biodegradable implants made with polypyrrole and polyethylenglycol copolymers and iodine-doped and plasma-synthesized pyrrole polymers, have a neuroprotector effect and induce the reconnection of the spinal cord after an injury; this effect was proved in a model involving a complete section of the spinal cord in rats; the results o the functional evaluation demonstrated 5 times greater recovery in animals implanted with the polypyrrole-polyethylenglycol copolymer compared with the control group which only underwent a complete section of the spinal cord; in addition, the functional recovery of the group with iodine-doped polypyrrole was ten times greater compared to the control group; in the histological study various inflammatory and immune cells were identified at the injury site in the three experimental groups with and without implants and the integration of the polymers in the nervous tissue of the spinal cord was also obse

Abstract: The purpose of the present invention is to demonstrate that semiconducting and non-biodegradable implants made with polypyrrole and polyethylenglycol copolymers and iodine-doped and plasma-synthesised pyrrole polymers, have a neuroprotector effect and induce the reconnection of the spinal cord after an injury; this effect was proved in a model involving a complete section of the spinal cord in rats; the results o the functional evaluation demonstrated 5 times greater recovery in animals implanted with the polypyrrole-polyethylenglycol copolymer compared with the control group which only underwent a complete section of the spinal cord; in addition, the functional recovery of the group with iodine-doped polypyrrole was ten times greater compared to the control group; in the histological study various inflammatory and immune cells were identified at the injury site in the three experimental groups with and without implants and the integration of the polymers in the nervous tissue of the spinal cord was also obse