Abstract: Making the best customer-agent matching decision to engage in a communication to resolve a work item is a primary objective of any contact center. In addition to or as an alternative to standard routing decisions, a real-time agent-matching module is selected from a pool of agent-matching modules, each real-time agent-matching module being unique in its ability to match a resource (e.g., agent) to a customer. The real-time agent-matching modules may differ from one another in terms of information gathered and/or utilizing logic unique to that particular agent-matching module. An orchestration layer is provided to select a single agent-matching module or a series or parallel number of agent-matching modules to select a resource and connect to the customer.

Abstract: Methods, apparatus and computer readable media are provided for identifying functional features from a computed tomography (CT) image. The CT image may be a contrast-enhanced CT image or a non-contrast CT image. According to some examples, methods, apparatus and computer readable media are also provided for using machine learning to identify functional features from CT images. According to some examples, simulated functional image datasets such as simulated PET images or simulated SUV images are generated from a received CT image.

Abstract: The ability to comprehend the context of a given programming artifact and extracting the underlying functionality is a complex task extending beyond just syntactic and semantic analysis of code. All existing automation capabilities, hence heavily depend on manual involvement of domain experts. Even recent approaches leveraging Machine Learning Capabilities are supervised techniques, whereby the dependency on domain experts still remains—in preparing suitable training sets. A method and system for automated classification of variables using unsupervised distribution agnostic clustering has been provided. The present disclosure focuses to tap the flexibility of the code and presents a domain agnostic approach using unsupervised machine learning which automatically extracts the context from source code, by classifying the underlying elements of the code. The method and system do not require any manual intervention and opens a wide range of opportunities in reverse engineering and variable level analysis space.

Abstract: Disclosed herein are system, method, and computer program product embodiments for synchronizing data in a source system to an application without relying on middleware. An embodiment operates by performing an initial load of records for an object for an application from a source system, thereby retrieving a first set of records. The embodiment first maps the first set of records to the object using a transform template. The embodiment creates the object in the application using the first set of records based on the first mapping. The embodiment performs a delta load of records for the object from the source system, thereby retrieving a second set of records. The embodiment second maps the second set of records to the object using the transform template. The embodiment then updates the object using the second set of records based on the second mapping.

Abstract: The three-dimensional printer head for printing metal articles, the printer comprises a nozzle that is cylindrical and manufactured from a heat-resistant material with low electric conductivity, an embedded channel within the nozzle and running along a longitudinal length of the nozzle; a receiving space at a first end of the embedded channel in which a solid metal material is received; an extrusion space at a second end of the embedded channel from which a continuous bead of liquid or semisolid metal material is extruded, a feeder mechanism that continuously drives the solid metal material into the embedded channel through the receiving space, an induction coil surrounding an outer surface of the nozzle and extending over a substantial portion of the longitudinal length of the nozzle.

Abstract: A computer-based system and process are disclosed for reconstructing the internal electrical behavior of a patient's heart based partly or wholly on the patient's electrocardiogram (ECG). The output of the process may include, for example, a cardiac activation map, and/or a representation of transmembrane potentials over time. The process advantageously does not require any medical imaging of the patient, and does not require any special medical equipment. For example, the patient's activation map and transmembrane potentials may be reconstructed based solely on a preexisting or newly-obtained 12-lead cardiac ECG of the patient. The process makes use of a machine learning model, such as a neural network based model, trained with actual and/or simulated ECGs and intracardiac electrical data (typically transmembrane potentials) of many thousands of patients.

Abstract: A system and a method for managing workload of an application in a cloud infrastructure is disclosed. The cloud infrastructure may include an existing cloud infrastructure (ECI) and an Elastic Machine Pool Infrastructure (EMPI). The method may include connecting the EMPI to the ECI by configuring cloud control manager of the ECI. Further, the method may include receiving the workload from the application running on the cloud infrastructure. The workload may be allocated to an Elastic Virtual Machine (EVM) hosted by the EMPI or a VM hosted by the ECI based on at least one of an EMP profile of the application, status of the EVM, and workload characteristics of the EVM. Further, the one or more bare metal servers and the one or more EVMs may be managed based on at least one of the workload characteristics and the status of the EVM.

Abstract: Systems and methods that support the creation and timely electronic scheduling and delivery of course materials for training of individuals in an organization, in which course recommendations, scheduling, and rollout are based upon a number of factors including, for example, specific individual and/or business day-to-day operational performance measures, sales performance, and seasonal weather conditions by geographical region.

Abstract: A system for controlling a heating device by monitoring the status of any dish being cooked. The system is provided with connectivity to cloud server comprising the relevant reference data, one or more sensors configured to monitor the status of dish being cooked, and processing circuitry that prevents the dish from being overcooked, burned, or spilled over by using the combination of reference data that is stored on the cloud server as well as the sensory data from one or more of its sensors, and generating a warning signal to the user. Additionally, the system and its one or more sensors will monitor the surroundings for hazardous conditions such as cooking gas leakages, active heating device left unattended for a long time.

Abstract: Performance optimization of power plants is one of the major challenges. Several machine learning based techniques are available which are used for optimization of the power plants. Coal selection and blending is critical to ensuring optimum operation of thermal power plants. The present disclosure provides a system and method for optimum coal selection for the power plant and power plant optimization. The system mainly comprises two components. First, a coal usage advisory module providing coal usage and blending ratio advice to the operators based on the available coal. The optimization is with respect to the entire power plant operation including its components. And second, a performance optimization advisory module provides operation instruction for boiler, SCR, APH and other power plant equipment based on the implemented coal blend in real-time.

Abstract: Sidechain functionalized organosiloxane compounds are provided having a first end and a second end; a polysiloxane backbone; and a first plurality of sidechains covalently attached to the polysiloxane backbone and a second plurality of sidechains covalently attached to the polysiloxane backbone; wherein the first plurality of sidechains comprise polyalkylene glycol sidechains; wherein the first plurality of sidechains and the second plurality of sidechains comprise a tethered end covalently attached to the polysiloxane backbone and a free end opposite to the tethered end; and wherein the free end in one or both of the first plurality of sidechains and the second plurality of sidechains comprises a reactive end group. Compositions comprising the sidechain functionalized organosiloxane compounds are also provided, as well as coated articles. Sidechain functionalized lubricants are also provided that can be used with compositions and coated articles herein.

Abstract: An optical apparatus is disclosed, the apparatus comprising an optical element having a reflective surface for reflecting incident radiation in a beam path, and at least one sensor configured to sense radiation corresponding to a temperature of a respective portion of a backside surface of the optical element. Also disclosed is a method of controlling a temperature of a reflective surface of an optical element in a lithographic apparatus.

Abstract: Methods, devices, and systems for compressing and decompressing a stream of indices associated with graphics primitives. A group of delta values is determined based on a group of indices of the stream of indices. The group of delta values is compared to delta values in a lookup table. The group of indices is compressed based on an entry in the lookup table if the group of delta values matches all delta values in the entry, otherwise, the group of indices is compressed based on variable-length encoding.

Abstract: A multi-layer cybersecurity system and method for protecting digital wallets holding blockchain-based tokens traded on a financial platform. Specifically, the invention employs random temporal windowing in relation to: (1) reshuffling designated machines running a multi-party computation protocol; and (2) rekeying of private keys held in both hot and cold environments. Furthermore, environmental based signature weighting is applied to the keys. As a result, cold signers can do anything hot signers can but hot signers cannot do what cold signers can such as taking control, recovering control, or reconstitute the holdings of the wallet in real time, if necessary.

Abstract: Methods, systems, and apparatuses are provided to determine object depth within captured images. For example, an imaging device, such as a VR or AR device, captures an image. The imaging device applies a first encoding process to the image to generate a first set of features. The imaging device also generates a sparse depth map based on the image, and applies a second encoding process to the sparse depth map to generate a second set of features. Further, the imaging device applies a decoding process to the first set of features and the second set of features to generate predicted depth values. In some examples, the decoding process receives skip connections from layers of the second encoding process as inputs to corresponding layers of the decoding process. The imaging device generates an output image, such as a 3D image, based on the predicted depth values.

Abstract: Systems, computer program products, and methods are described herein for secure channel selection for multi-factor authentication using non-fungible electronic resources.

Abstract: Various embodiments for customizing a dynamic navigation system are described herein. An embodiment operates by receiving a request from a support user device for debug access to an application. A predetermined time period for which to provision a set of computing resources is identified and the set of computing resources are provisioned for a pod on a server. Both a first container including access to a new instance of the application and a second container providing access to a debugger program are generated for the pod. Upon determining that the predetermined time period has expired, access to the provisioned set of computing resources of the pod is revoked, and the provisioned set of computing resources to be made available for other processes of the server.

Abstract: Embodiments provide systems and methods to load balance using tenant affinities. A method includes configuring a load balancer with a set of tenant affinities, the set of tenant affinities including a tenant affinity for each of a plurality of tenants with respect to each of a plurality of computing nodes that provide services to users in a multitenant environment. Load balancing may include receiving a user request, associated with a tenant, for a service provided by the computing nodes, determining a highest tenant affinity computing node for the tenant using the set of tenant affinities and directing the user request to the highest tenant affinity computing node for the tenant.

Abstract: Physics informed machine learning faces challenges in real industrial environment and in digital twins where the systems are far more complex. Physics of the process is multi-dimensional, multi-material and multi-phenomena. Therefore, building physics informed machine learning models is challenging as it needs to be developed from scratch for each new system or for each significant change in the process/equipment. Once built, the models are not suitable for real-time dynamic changes in operating conditions. Therefore, embodiments herein provide a method and system that can enable quick development of Physics Informed Digital Twin (PIDT) models that are generalized, do not need re-training for dynamic conditions in the industrial plants, can learn from multiple data sources, equipment, and materials. On top of this, the method and system can enable Physics Informed Digital Twin (PIDT) models to learn and update themselves with minimal human intervention in digital twin environments.

Abstract: A method includes providing a Fibonacci confidence interval level on user program viewership data to distinguish user interest level in different linear entertainment programs. The method also includes creating a behavior shift feature space for acquiring information about user behavior over time based on a behavior sequence, a first derivative on the behavior sequence, and a second derivative on the behavior sequence. The method further includes utilizing, based on a trained machine learning model, a transformer structure and attention to map user data from the behavior shift feature space into a prediction of the Fibonacci confidence interval level.