Abstract: Methods, systems, and computer program products for service-to-service scheduling in container orchestrators are provided herein. A computer-implemented method includes reserving, by a network orchestrator, network resources requested between a plurality of services, wherein each of the services is implemented as one or more replicas running on a set of nodes of a cluster, managed by the network orchestrator, that use the network resources to serve incoming requests to the plurality services; monitoring utilization of the network resources; and scheduling, by the network orchestrator based on the monitoring, one or more new replicas of the plurality of services and the incoming requests to the plurality of services in a collaborative manner to increase at least one network performance characteristic.

Abstract: A method, computer system, and a computer program product for detecting face mask usage based on a crowd sound is provided. The present invention may include capturing an audio stream including a crowd voice data. The present invention may also include analyzing the crowd voice data using a machine learning model to determine an amount of people wearing masks. The present invention may further include in response to determining that the amount of people wearing masks does not meet a compliance threshold, displaying a content to promote face mask usage.

Abstract: A computer-implemented method, according to one implementation, includes: monitoring requests received for an AI interface prompt in real-time, and determining whether one or more of the requests violate compliance metrics. Risk scores are calculated for requests determined as violating the compliance metrics. The requests determined as violating the compliance metrics are updated by implementing protective measures correlated with the calculated risk scores. Moreover, the updated requests are sent to the AI interface prompt.

Abstract: A system, platform, computer program product, and/or method for managing UAV resources is disclosed that includes: receiving UAV specifications to provision one or more UAVs; converting the UAV specifications to UAV specification metadata; transforming the UAV specification metadata to UAV configuration metadata to configure UAV software for the one or more UAVs; and configuring, using the UAV configuration metadata, the UAV software for the one or more UAVs. The system, platform, program product, and method can further include assembling, using the UAV configuration metadata, the UAV hardware of the one or more UAVs; deploying the one or more UAVs from a base location to a new location; transferring control over operation of the one or more UAVs to a third-party operator; creating and configuring a network connection to the one or more UAVs; and/or remotely logging into an operating system of the one or more UAVs.

Abstract: A computer-implemented method to generate a hotspot confidence score for a hotspot in a network graph includes, receiving input data, wherein the input data includes a plurality of messages, each message containing a set of message data. The method further includes generating, based on the plurality of messages, a network graph. The method also includes identifying, in the network graph, a first hotspot. The method includes compiling a set of hotspot characteristics for the first hotspot. The method further includes receiving, in response to identifying the first hotspot, a first user feedback. The method also includes, generating, by a learning model, a hotspot confidence score for the first hotspot; and outputting the hotspot confidence score.

Abstract: One or more systems, devices, or methods of use provided herein relate to a process of long-range coupling qubits in a quantum computing device with energy loss protection. A system can comprise a first transmon coupler capable of selectively coupling a first tunable coupler qubit to a first fluxonium qubit; a second transmon coupler capable of selectively coupling a second tunable coupler qubit to a second fluxonium qubit. Additionally, in one or more embodiments, the system can include a long-range coupler capable of selectively coupling the first fluxonium qubit to the second fluxonium qubit. The first transmon coupler can be coupled to a first B mode of the first tunable coupler qubit, and the second transmon coupler can be coupled to a second B mode of the second tunable coupler qubit.

Abstract: A method for storing metadata and a configuration schema for each of a plurality of capabilities, and storing a plurality of catalogs, each catalog identifying the metadata and configuration schema associated with at least one of the plurality of capabilities. The method also includes receiving a request for implementation of one of the plurality of capabilities on a pluggable system, and associating, by a lifecycle manager and based on a catalog of the plurality of catalogs related to the request, the metadata and configuration schema related to the requested one of the plurality of capabilities with a domain specific capabilities controller compatible with the pluggable system.

Abstract: By analyzing first configuration data of a set of sensors, a first configuration of the set of sensors is measured. A set of permutations of the first configuration is generated. For each permutation in the set of permutations, a corresponding set of virtual sensor data is generated. Using an analysis on each set of virtual sensor data and a set of real sensor data obtained using the first configuration, a corresponding analysis result is caused to be determined. Using the quality measure, a configuration producing a highest quality analysis result is determined. A contextual situation and the configuration are stored as a sensor configuration rule. By analyzing second configuration data of the set of sensors, a second configuration of the set of sensors is measured. The second configuration is adjusted according to the configuration specified in the sensor configuration rule.

Abstract: Using a first dataset of labeled data, a model is trained by adjusting a feature extractor parameter, a classifier parameter, and a discriminator parameter of the model. Using the discriminator parameter and a parametric function of the feature extractor parameter, a plurality of samples of a dataset of unlabeled data is scored. A subset of the scored plurality of samples is selected for labeling. Responsive to receiving a label of each of the selected subset of the scored plurality of samples, the first dataset of labeled data is augmented with the selected subset of the scored plurality of samples and the label of each of the selected subset of the scored plurality of samples. Using the augmented dataset of labeled data, the model is retrained. The retraining comprises further adjusting the feature extractor parameter, the classifier parameter, and the discriminator parameter of the model.

Abstract: Semiconductor devices and methods of forming the same include forming a stack of alternating first and second sacrificial layers. The first sacrificial layers are recessed relative to the second sacrificial layers. Replacement channel layers are grown from sidewalls of the first sacrificial layers. A first source/drain region is grown from the replacement channel layer. The recessed first sacrificial layers are etched away. A second source/drain region is grown from the replacement channel layer. The second sacrificial layers are etched away. A gate stack is formed between and around the replacement channel layers.

Abstract: An information handling system and method for translating virtual addresses to real addresses including a processor for processing data; memory devices for storing the data; and a memory controller configured to control accesses to the memory devices, where the processor is configured, in response to a request to translate a first virtual address to a second physical address, to send from the processor to the memory controller a page directory base and a plurality of memory offsets. The memory controller is configured to: read from the memory devices a first level page directory table using the page directory base and a first level memory offset; combine the first level page directory table with a second level memory offset; and read from the memory devices a second level page directory table using the first level page directory table and the second level memory offset.

Abstract: Aspects include receiving a document and classifying at least a subset of the document as having a first type of data. Features are extracted from the document. The extracting includes initiating processing of the at least a subset of the document by a first processing engine that was previously trained to extract features from the first type of data. The extracting also includes initiating processing of a remaining portion of the document not included in the at least a subset of the document by a second processing engine that was previously trained to extract features from a second type of data. The first type of data is different than the second type of data. Features are received from one or both of the first processing engine and the second processing engine. The received features are stored as features of the document.

Abstract: A method for minimizing data transfer and storage utilization on cloud object storage systems is disclosed. In one embodiment, such a method replicates a file from a production system to a cloud object storage system. The method determines whether a number of hard links associated with the file is greater than one. In the event the number is greater than one, the method creates, on the cloud object storage system, a special object for the file and associates the file with the special object. Upon creating a hard link on the production system in association with the file, the method replicates the hard link from the production system to the cloud object storage system without replicating data associated with the file. A metadata reference to the special object is added to the hard link on the cloud object storage system. A corresponding system and computer program product are also disclosed.

Abstract: The present disclosure relates to methods and apparatuses related to the deposition of a protective layer selective to an interlayer dielectric layer so that the protective layer is formed onto a top portion associated with the interlayer dielectric layer. In some embodiments, a method comprises: forming an interlayer dielectric layer on a substrate; covering a trench region with a metal liner, wherein the trench region is situated above the substrate and formed within the interlayer dielectric layer; and depositing a protective layer selective to the interlayer dielectric layer so that the protective layer is formed onto a top portion associated with the interlayer dielectric layer. In various embodiments, the depositing the protective layer comprises: repeatedly depositing the protective layer via a multi-deposition sequence; or depositing a self-assembled monolayer onto the top portion.

Abstract: A system, method, and computer program product for implementing digital script modification is provided. The method includes generating image sequences associated with textual content of a digital story. Multiple contextual dimensions are identified within the textual content and a group of dimensions are selected. The image sequences in combination with the group of dimensions are expanding or contracted and image sequences are altered based on detected interactions with the group of dimensions. Dimensions are extracted from the group of dimensions during presentation of the digital story and a scriptwriter is enabled to modify the dimensions. The image sequences are modified and a hardware interface device is enabled to interact with various image sequences and alter the multiple contextual dimensions. The textual content of the digital story is dynamically altered.

Abstract: A mechanism is provided in a data processing system for displaying cyber threat data in a narrative format. The mechanism receives a cyber threat information file that comprises cyber threat data in a serialized format. The mechanism generates a tree data structure representing relationships between objects in the cyber threat data and generates a user interface presenting the cyber threat data in a narrative format based on the tree data structure. The mechanism presents the user interface to an analyst.

Abstract: Techniques regarding tiling a CR gate configuration to one or more lattices characterizing quantum circuit topologies are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a tiling component that can generate a cross-resonance gate configuration that delineates a control qubit assignment and a target qubit assignment in conjunction with a frequency allocation onto a lattice characterizing a quantum circuit topology.

Abstract: Embodiments of the present invention provide methods, computer program products, and systems. Embodiments of the present invention can dynamically generate audio for one or more images associated with a location based on contextual information that satisfies a request. Embodiments of the present invention can embed the generated audio into the one or more images. Embodiments of the present invention can then display the one or more images with the embedded audio on a user device.

Abstract: A technique for generating a performance prediction of a machine learning model with uncertainty intervals includes obtaining a first model configured to perform a task and a production dataset. At least one metric predicting a performance of the first model at performing the task on the production dataset is generated using a second model. The second model is a meta-model associated with the first model. At least one value predicting an uncertainty of the at least one metric predicting the performance of the first model at performing the task on the production dataset is generated using a third model. The third model is a meta-meta-model associated with the second model. An indication of the at least one metric and the at least one value is provided.

Abstract: Embodiments include in response to monitoring a processor during operation, detecting a first number of throttling amounts in the processor, determining that the first number of throttling amounts fulfills a first condition regarding a throttling amounts threshold, and modifying a voltage level of the processor by a first amount. Embodiments include in response to modifying the voltage level of the processor by the first amount, detecting a second number of throttling amounts in the processor, determining that the second number of throttling amounts fulfills a second condition regarding the throttling amounts threshold, and modifying the voltage level of the processor by a second amount.