Abstract: A device may receive tracking data identifying trajectories of objects, and may annotate the tracking data to identify object categories for the tracking data. The device may identify objects based on the object categories, and may determine object trajectories for the objects. The device may transform the object trajectories to overhead planar trajectories, and may generate simplified object trajectories. The device may convert a continuous space associated with the simplified object trajectories into a discrete space, and may convert the discrete space to a lower dimensional space. The device may transform the object trajectories to binary feature vectors, and may process the binary feature vectors, with a clustering model, to determine trajectory clusters. The device may train a classification model with the binary feature vectors and the trajectory clusters, and may cause the trained classification model to be implemented.

Abstract: A device may receive tracking data identifying trajectories of objects, and may annotate the tracking data to identify object categories for the tracking data. The device may identify objects based on the object categories, and may determine object trajectories for the objects. The device may transform the object trajectories to overhead planar trajectories, and may generate simplified object trajectories. The device may convert a continuous space associated with the simplified object trajectories into a discrete space, and may convert the discrete space to a lower dimensional space. The device may transform the object trajectories to binary feature vectors, and may process the binary feature vectors, with a clustering model, to determine trajectory clusters. The device may train a classification model with the binary feature vectors and the trajectory clusters, and may cause the trained classification model to be implemented.

Abstract: The present invention relates to specific binding molecules, such as T cell receptors (TCRs), that bind the HLA-A*02 restricted peptide KVLEYVIKV (SEQ ID NO: 1) derived from the germline cancer antigen MAGEA1. The specific binding molecules may comprise non-natural mutations within the alpha and/or beta variable domains relative to a native MAGEA1 TCR. The specific binding molecules of the invention are particularly suitable for use as novel immunotherapeutic reagents for the treatment of malignant disease.

Abstract: A device may receive tracking data identifying trajectories of objects, and may annotate the tracking data to identify object categories for the tracking data. The device may identify objects based on the object categories, and may determine object trajectories for the objects. The device may transform the object trajectories to overhead planar trajectories, and may generate simplified object trajectories. The device may convert a continuous space associated with the simplified object trajectories into a discrete space, and may convert the discrete space to a lower dimensional space. The device may transform the object trajectories to binary feature vectors, and may process the binary feature vectors, with a clustering model, to determine trajectory clusters. The device may train a classification model with the binary feature vectors and the trajectory clusters, and may cause the trained classification model to be implemented.

Abstract: A device may receive security data identifying assets of an entity, security issues associated with the assets, and objectives associated with the assets and may utilize a data model to generate, based on the security data, asset related data identifying mapped sets of security data. The device may process a first portion of the asset related data, with a first model, to calculate an asset risk likelihood score for an asset of the assets and may process a second portion of the asset related data, with a second model, to calculate an asset criticality score for the asset. The device may process a third portion of the asset related data, with a third model, to calculate an asset control effectiveness score for the asset and may combine the scores to generate a security risk score for the asset. The device may provide the security risk score for display.

Abstract: The present invention relates to specific binding molecules which bind to an HLA-restricted peptide derived from mutant KRAS. Said specific binding molecules may comprise CDR sequences embedded within a framework sequence. The CDRs and framework sequences may correspond to a T cell receptor (TCR) variable domain and may further comprise non-natural mutations relative to a native TCR variable domain. The specific binding molecules of the invention are particularly suitable for use as novel immunotherapeutic reagents for the treatment of cancer.

Abstract: A device may receive security data identifying assets of an entity, security issues associated with the assets, and objectives associated with the assets and may utilize a data model to generate, based on the security data, asset related data identifying mapped sets of security data. The device may process a first portion of the asset related data, with a first model, to calculate an asset risk likelihood score for an asset of the assets and may process a second portion of the asset related data, with a second model, to calculate an asset criticality score for the asset. The device may process a third portion of the asset related data, with a third model, to calculate an asset control effectiveness score for the asset and may combine the scores to generate a security risk score for the asset. The device may provide the security risk score for display.

Abstract: A method for controlling access to one or more of a plurality of target systems includes receiving profile data that defines one or more features associated with a plurality of individuals with one or more entitlements of those individuals. Each entitlement is indicative of target system access. The method further includes generating a model that relates the one or more features and the one or more entitlements of the plurality of individuals. Profile data that defines one or more features associated with a target individual is received from a first user management system. A listing that includes one or more entitlements associated with the target individual, and confidence values associated with the one or more entitlements is generated based on the profile data and the model. Each confidence value is indicative of whether the target individual should be granted a corresponding entitlement.

Abstract: A method for controlling access to one or more of a plurality of target systems includes receiving profile data that defines one or more features associated with a plurality of individuals with one or more entitlements of those individuals. Each entitlement is indicative of target system access. The method further includes generating a model that relates the one or more features and the one or more entitlements of the plurality of individuals. Profile data that defines one or more features associated with a target individual is received from a first user management system. A listing that includes one or more entitlements associated with the target individual, and confidence values associated with the one or more entitlements is generated based on the profile data and the model. Each confidence value is indicative of whether the target individual should be granted a corresponding entitlement.

Abstract: A method for controlling access to one or more of a plurality of target systems includes receiving profile data that defines one or more features associated with a plurality of individuals with one or more entitlements of those individuals. Each entitlement is indicative of target system access. The method further includes generating a model that relates the one or more features and the one or more entitlements of the plurality of individuals. Profile data that defines one or more features associated with a target individual is received from a first user management system. A listing that includes one or more entitlements associated with the target individual, and confidence values associated with the one or more entitlements is generated based on the profile data and the model. Each confidence value is indicative of whether the target individual should be granted a corresponding entitlement.

Abstract: A method for controlling access to one or more of a plurality of target systems includes receiving profile data that defines one or more features associated with a plurality of individuals with one or more entitlements of those individuals. Each entitlement is indicative of target system access. The method further includes generating a model that includes one or more sets of rules where each set of rules is associated with an entitlement of the profile data. Each entitlement is indicative of target system/application access. Each rule within a set relates a combination of one or more features of the profile data with a confidence value. Profile data that defines one or more features associated with a target individual is received from a first user management system. A listing that includes one or more entitlements associated with the target individual, and confidence values associated with the one or more entitlements is generated based on the profile data and the rules.

Abstract: A method for controlling access to one or more of a plurality of target systems includes receiving profile data that defines one or more features associated with a plurality of individuals with one or more entitlements of those individuals. Each entitlement is indicative of target system access. The method further includes generating a model that relates the one or more features and the one or more entitlements of the plurality of individuals. Profile data that defines one or more features associated with a target individual is received from a first user management system. A listing that includes one or more entitlements associated with the target individual, and confidence values associated with the one or more entitlements is generated based on the profile data and the model. Each confidence value is indicative of whether the target individual should be granted a corresponding entitlement.

Abstract: A method for controlling access to one or more of a plurality of target systems includes receiving profile data that defines one or more features associated with a plurality of individuals with one or more entitlements of those individuals. Each entitlement is indicative of target system access. The method further includes generating a model that relates the one or more features and the one or more entitlements of the plurality of individuals. Profile data that defines one or more features associated with a target individual is received from a first user management system. A listing that includes one or more entitlements associated with the target individual, and confidence values associated with the one or more entitlements is generated based on the profile data and the model. Each confidence value is indicative of whether the target individual should be granted a corresponding entitlement.

Abstract: A method for controlling access to one or more of a plurality of target systems includes receiving profile data that defines one or more features associated with a plurality of individuals with one or more entitlements of those individuals. Each entitlement is indicative of target system access. The method further includes generating a model that relates the one or more features and the one or more entitlements of the plurality of individuals. Profile data that defines one or more features associated with a target individual is received from a first user management system. A listing that includes one or more entitlements associated with the target individual, and confidence values associated with the one or more entitlements is generated based on the profile data and the model. Each confidence value is indicative of whether the target individual should be granted a corresponding entitlement.

Abstract: A method for controlling access to one or more of a plurality of target systems includes receiving profile data that defines one or more features associated with a plurality of individuals with one or more entitlements of those individuals. Each entitlement is indicative of target system access. The method further includes generating a model that includes one or more sets of rules where each set of rules is associated with an entitlement of the profile data. Each entitlement is indicative of target system/application access. Each rule within a set relates a combination of one or more features of the profile data with a confidence value. Profile data that defines one or more features associated with a target individual is received from a first user management system. A listing that includes one or more entitlements associated with the target individual, and confidence values associated with the one or more entitlements is generated based on the profile data and the rules.

Abstract: A modular shelving assembly for use in a vehicle, including a cargo space at least partially defined by a floor and a side wall of the vehicle, includes at least two interconnected upright assemblies. Each of the upright assemblies includes a first panel, a second panel, and a coupler member separate from and unitizing the first and second panels. The modular shelving assembly further includes a rail secured to one of the floor and the side wall to which at least one of the interconnected upright assemblies is anchored.

Abstract: A video-on-demand server includes interface modules each providing a communication interface between the video-on-demand server and a switching network; an interface to a management module to monitor and provide to the video-on-demand server information on video-on-demand bandwidth utilization of network resources allocated to particular service groups, each service group including video-on-demand customers sharing a same fixed network bandwidth allocation; each interface module communicatively coupled to service groups simultaneously via service gateways; a total bandwidth of the server is an aggregate bandwidth of all the interface modules, and is less than an aggregate bandwidth of all service groups assigned to be serviced by the server, the switching network configured to make the server available for receiving video on demand service requests from all of the service group customers simultaneously; the server adapted to dynamically assign bandwidth of the server to service groups, by adapting the switchi

Abstract: A method for controlling a process stream comprises detecting interfaces that are present in the process stream under a set of conditions using a phased array ultrasound probe, reconstructing an image of the interfaces, and providing the image, or information derived therefrom, to a control system. The control system either modifies or maintains the set of conditions in process stream. The method may be used for controlling an industrial process stream, such as a process stream in a chemical or petrochemical processing plant.

Abstract: A modular shelving assembly for use in a vehicle, including a cargo space at least partially defined by a floor and a side wall of the vehicle, includes at least two interconnected upright assemblies. Each of the upright assemblies includes a first panel, a second panel, and a coupler member separate from and unitizing the first and second panels. The modular shelving assembly further includes a rail secured to one of the floor and the side wall to which at least one of the interconnected upright assemblies is anchored.