Abstract: Adaptive verifiable training enables the creation of machine learning models robust with respect to multiple robustness criteria. In general, such training exploits inherent inter-class similarities within input data and enforces multiple robustness criteria based on this information. In particular, the approach exploits pairwise class similarity and improves the performance of a robust model by relaxing robustness constraints for similar classes and increasing robustness constraints for dissimilar classes. Between similar classes, looser robustness criteria (i.e., smaller ?) are enforced so as to minimize possible overlap when estimating the robustness region during verification. Between dissimilar classes, stricter robustness regions (i.e., larger ?) are enforced. If pairwise class relationships are not available initially, preferably they are generated by receiving a pre-trained classifier and then applying a clustering algorithm (e.g., agglomerative clustering) to generate them.

Abstract: A froth flotation unit including a flotation tank, a froth collecting launder having a froth overflow lip and a near coarse launder having a second lip. The second lip is arranged closer to the bottom of the flotation tank than the froth overflow lip. A froth flotation method for treating coarse particles suspended in slurry in the froth flotation unit is also provided.

Abstract: Compositions and methods of improving radiation therapy are provided. The composition typically includes an effective amount of 7-DHC or a derivative or analog thereof. The methods typically include administering the composition to a subject in need thereof in combination with one or more doses of radiation therapy, preferably non-ultraviolet radiation therapy. A preferred radiation is ionizing radiation. The compositions and methods can be used to treat tumors, e.g., benign and malignant tumors. Thus, methods of treating cancer are provided. In preferred embodiments, the 7-DHC or a derivative or analog thereof is encapsulated or incorporated into nanoparticles. The particles can be, for example, polymeric nanoparticles, lipoprotein or lipoprotein-like particles, liposomes, inorganic nanoparticles, or a combination thereof. In some embodiments, the 7-DHC or analog thereof is derivatized with a polymer or saccharide, which is some embodiments, can self-assemble into particles.

Abstract: Computer-implemented methods for telemetry data processing and representations for foundation models are provided. Aspects include generating a graph data structure based on processing telemetry data associated with at least one computer system, where the graph data structure is representative of a set of events and a set of entities associated with the at least one computer system. Aspects include generating a textual representation of behavioral information associated with at least one entity of the set of entities and at least one event of the set of events, based on one or more subgraphs included in the graph data structure. Aspects include obtaining an analysis result associated with the at least one computer system based on processing the textual representation by one or more models.

Abstract: A method for determining a trust indicator is provided. The method may include interpreting, via an Internet of Things Universal Identifier (IoT UID) processing circuit, an IoT UID corresponding to a device and identifying, via a record management circuit and based at least in part on the IoT UID, a record in a database corresponding to the device. The method may further include determining, via a trust analysis circuit and based at least in part on the record, a risk indicator of the device and transmitting, via an indicator provisioning circuit, the risk indicator.

Abstract: A method including receiving a first set of one or more street level images of houses into a Machine Learned Model trained with a second set of street level images with one or more exterior features of the houses labeled, identifying the one or more exterior features in the first set of street level images by way of the Machine Learned Model, and quantifying and outputting the counts and/or two-dimensional areas for each of the identified exterior features in the first set of one or more street level images is described. Non-transitory, computer-readable storage media having instructions for executing the method steps by one or more processors as well as computer or computer systems capable of performing the method steps are also described.

Abstract: A method including receiving a first set of one or more street level images of houses into a Machine Learned Model trained with a second set of street level images with one or more exterior features of the houses labeled, identifying the one or more exterior features in the first set of street level images by way of the Machine Learned Model, and quantifying and outputting the counts and/or two-dimensional areas for each of the identified exterior features in the first set of one or more street level images is described. Non-transitory, computer-readable storage media having instructions for executing the method steps by one or more processors as well as computer or computer systems capable of performing the method steps are also described.

Abstract: A method including receiving a first set of one or more street level images of houses into a Machine Learned Model trained with a second set of street level images with one or more exterior features of the houses labeled, identifying the one or more exterior features in the first set of street level images by way of the Machine Learned Model, and quantifying and outputting the counts and/or two-dimensional areas for each of the identified exterior features in the first set of one or more street level images is described. Non-transitory, computer-readable storage media having instructions for executing the method steps by one or more processors as well as computer or computer systems capable of performing the method steps are also described.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating suggested communications during a multi-agent interaction using a language model neural network.

Abstract: A method including receiving a first set of one or more street level images of houses into a Machine Learned Model trained with a second set of street level images with one or more exterior features of the houses labeled, identifying the one or more exterior features in the first set of street level images by way of the Machine Learned Model, and quantifying and outputting the counts and/or two-dimensional areas for each of the identified exterior features in the first set of one or more street level images is described. Non-transitory, computer-readable storage media having instructions for executing the method steps by one or more processors as well as computer or computer systems capable of performing the method steps are also described.

Abstract: A method including receiving a first set of one or more street level images of houses into a Machine Learned Model trained with a second set of street level images with one or more exterior features of the houses labeled, identifying the one or more exterior features in the first set of street level images by way of the Machine Learned Model, and quantifying and outputting the counts and/or two-dimensional areas for each of the identified exterior features in the first set of one or more street level images is described. Non-transitory, computer-readable storage media having instructions for executing the method steps by one or more processors as well as computer or computer systems capable of performing the method steps are also described.

Abstract: A method including receiving a first set of one or more street level images of houses into a Machine Learned Model trained with a second set of street level images with one or more exterior features of the houses labeled, identifying the one or more exterior features in the first set of street level images by way of the Machine Learned Model, and quantifying and outputting the counts and/or two-dimensional areas for each of the identified exterior features in the first set of one or more street level images is described. Non-transitory, computer-readable storage media having instructions for executing the method steps by one or more processors as well as computer or computer systems capable of performing the method steps are also described.

Abstract: A method for registering one or more Greenfield devices via a virtual Internet of Things Universal Identifier (IoT UID) is provided. The method includes identifying one or more Brownfield devices, generating device property data based at least in part on the one or more Brownfield devices, and transmitting, to an IoT device registrar server, a registration request that includes the device property data. The method further includes interpreting one or more IoT UIDs generated in response to the transmitting of the registration request.

Abstract: An apparatus for an Internet of Things device registry display includes a user input processing circuit structured to interpret one or more user input command values, an Internet of Things Universal Identification (IoT UID) identification circuit structured to determine one or more IoT UIDs, based at least in part on the one or more user input command values, a device lookup circuit structured to: generate a query that includes the one or more IoT UIDs, and retrieve device property data corresponding to the one or more IoT UIDs, a query provisioning circuit structured to transmit the query to an IoT device registrar server, a device property processing circuit structured to interpret the device property data generated by the IoT device registrar server in response to the query, and a display circuit structured to display the device property data with the corresponding one or more IoT UIDs.

Abstract: A database system is operable to perform a power supply strategy selection function based on first energy utilization-based operation optimizer input data to generate first energy utilization-based power supply strategy data denoting, for each power supply type of a plurality of power supply types, a corresponding first proportion of power supply resources that be implemented as the each power supply type. A first set of power supply resources is selected to execute a first database operation based on the first energy utilization-based power supply strategy data. The first set of power supply resources are utilized to power a first set of computing devices to enable the first set of computing devices to participate in execution of the first database operation in accordance with the first energy utilization-based power supply strategy data.

Abstract: A database system is operable to determine power usage policy data and generate operation requirement data based on the power usage policy data. A database operation is determined for execution, and an energy utilization-based operation limitation enforcement function is performed upon energy utilization-based operation restriction enforcement input data to generate energy utilization-based operation restriction enforcement data for the database operation based on applying the operation requirement data. The database operation is executed when the energy utilization-based operation restriction enforcement data indicates execution of the operation is allowed based on execution of the database operation adhering to the operation requirement data. Execution of database operation is foregone when the energy utilization-based operation restriction enforcement data indicates execution of the operation is disallowed based on execution of the database operation not adhering to the operation requirement data.

Abstract: A slurry feeding arrangement, flotation cell, line, and a method for treating particles suspended in slurry. The slurry feeding arrangement comprises one or more slurry feed means configured to feed slurry to a froth layer; a feed chamber configured to receive the fed slurry from the one or more slurry feed means; an overflow ramp between the feed chamber and the froth layer configured to lead the slurry from the feed chamber to the froth layer.

Abstract: A guiding arrangement configured to guide a slurry feed in a flotation tank of a flotation cell, a flotation cell and a flotation method. The guiding arrangement comprises at least one guiding plate arranged at the flotation cell. The at least one guiding plate is arranged obliquely in relation to the horizontal.

Abstract: A database system is operable to generate a query operation energy utilization estimation function based on historic energy utilization data and historic query operation execution data. A query is determined for execution and energy utilization estimation input data is determined for the query operation. The query operation energy utilization estimation function is performed upon the energy utilization estimation input data to generate energy utilization estimate data for the query operation. An energy efficiency strategy for the database system is applied based on the energy utilization estimate data generated for the query operation.

Abstract: A method for determining a trust indicator is provided. The method may include interpreting, via an Internet of Things Universal Identifier (IoT UID) processing circuit, an IoT UID corresponding to a device and identifying, via a record management circuit and based at least in part on the IoT UID, a record in a database corresponding to the device. The method may further include determining, via a trust analysis circuit and based at least in part on the record, a risk indicator of the device and transmitting, via an indicator provisioning circuit, the risk indicator.