Abstract: An embodiment includes detecting by a Speech Detection Component of a system a speech metric of a speaker in response to a reference speech. The embodiment includes responsive to the detected speech metric, computing by a Speech Analysis Component of the system a deviation metric between the speech metric and the reference speech. The embodiment includes training a machine learning model by a Speech Prediction Component of the system based on the deviation metric to generate a predicted speech pattern of the speaker. The embodiment also includes transforming by a Controller Component of the system the reference speech based on the predicted speech pattern.

Abstract: Secure container use is provided. The method generates respective user group permission identifications associated with image layer staging operations permissions assigned to different user groups as well as a list of the user group permission identifications. Responsive to a request from a user to perform an image layer staging operation, the method verifies whether the user has a user group permission identification in the list of the user group permission identifications. Responsive to verification that the user has a user group permission identification in the list of the user group permission identifications, the requested operation is executed. Responsive to determination that the user does not have a user group permission identification in the list of the user group permission identifications, the requested operation is denied.

Abstract: An example system includes a processor to mask a ciphertext using four random elements to generate masked ciphertexts. The processor can send the masked ciphertexts to a server device. The processor can receive masked plaintexts from the server device. The processor can unmask the masked plaintexts using the four random elements to generate unmasked plaintexts.

Abstract: Described are techniques including a computer-implemented method comprising appending a HyperText Transfer Protocol (HTTP) header to a HTTP request, wherein the HTTP header includes a source Internet Protocol (IP) address of a client generating the HTTP request, a universally unique identifier (UUID) of the HTTP request, a timestamp, a lifetime, a Universal Resource Locator (URL) of the HTTP request, and a signature. The method further comprises transmitting the HTTP request with the HTTP header to a web server.

Abstract: Embodiments of the present invention provide computer-implemented methods, computer program product, and computer systems. One or more processors, collect information associated with a target edge platform. The one or more processors, generate a set of rules for a target edge platform for different situations that can occur on the target edge platform. The one or more processors in response to receiving additional information, dynamically adjust the generated set of rules for the target platform.

Abstract: The present inventive concept provides for a method of unmanned machine synchronization using robotic sensing. The method includes generating at least one physical signal in the vicinity of at least one unmanned machine. The at least one generated physical signal is received by the at least one unmanned machine. At least one task is performed by the at least one unmanned machine based on the at least one received generated physical signal.

Abstract: A processor may receive a request for a new computing task to be scheduled. The processor may identify that the new computing task requires processing in a cloud computing environment. The processor may identify resource needs of the new computing task. The processor may predict, utilizing an AI model, a future computing task based on the new computing task, where the future computing task requires processing at a future time in the cloud computing environment. The processor may identify resource needs of the future computing task. The processor may select one or more computing node hosts for processing the new computing task based on the future computing task.

Abstract: Described are techniques for A/B testing including a computer-implemented method of identifying, in an A/B testing database, a set of feature values with a statistically significant difference in A/B testing outcomes above a threshold. The method further includes partitioning records in the A/B testing database into a plurality of population strata according to the set of feature values. The method further includes performing A/B testing, and identifying heterogeneous outcomes of the A/B testing for respective strata of the plurality of population strata.

Abstract: An apparatus for enriching a target gas from a gas mixture. The apparatus includes a cascading series of parallel arrangements of a plurality of gas separator cells. The gas separator cells of a second stage receive the output of gas separator cells of a prior stage as input. A gas separator cell includes an input portion, and a depleted gas outlet that is fed to an input of another gas separator cell or fed back to upstream stages. The outlet of a current stage connects to an input inlet of a subsequent stage. The input and output portions of the gas separator cell connect to form a chamber formed by connection of the input portion and the output portion and which includes a gas permeable membrane, selective to a target gas. The gas separator cell includes a gas permeable material supporting the gas permeable membrane.

Abstract: The method comprises a first device recording audio data responsive to a wireless proximity contact event with a second device and performing a first Fourier transform on the recorded audio data. The first device sends the first Fourier transform to the second device and receives a second Fourier transform of audio data recorded concurrently by the second device in response to the wireless proximity contact event. The first device, computes a cross correlation of the Fourier transforms and finding a maximum of the cross correlation that constitutes an exposure score. The first device compares the exposure score to a specified threshold that determines whether or not users of the first and second devices have had unacceptable exposure to each other and outputs the exposure score and a binary threshold result.

Abstract: Embodiments of the present invention provide an approach for compressing data, and more particularly, to large-scale text data encoding and compression using absolute overfitting on pre-trained language models. Large-scale data is parsed into sentences. A unique token is generated for each sentence to form a token list. A generative (or compression) model is trained from the tokens in the token list to produce the corresponding sentence of each token through absolute overfitting of a pre-trained language model. The compressed text data is stored as the token list and generative model, resulting in a storage space savings.

Abstract: An approach for optimizing storage on a local storage device. The approach receives a cloud resource budget limit and a cloud budget time interval. The approach estimates future cloud resource requests expected to arrive before the end of the cloud budget time interval. The approach calculates definitive and estimated costs of cloud resource usage types. The approach calculates a total estimated resource budget consumption. The approach determines if the total estimated resource budget consumption exceeds the cloud resource budget limit. If the approach determines the cloud resource budget limit is not exceeded, then the approach outputs a set of existing unfulfilled cloud resource requests for fulfillment. If the approach determines the cloud resource budget limit is exceeded, then the approach outputs a subset of set of existing unfulfilled cloud resource requests that do not exceed the cloud resource budget limit for fulfillment.

Abstract: A computer-implemented method for generating a custom thumbnail is disclosed. The computer-implemented method includes segmenting an audio file into one or more audio segments based, at least in part, on a respective context associated with each of the one or more audio segments. The computer-implemented method further includes selecting an initial thumbnail image based, at least in part, on one or more contexts associated with the one or more audio segments. The computer-implemented method further includes generating a customized thumbnail image based, at least in part, on performing a neural style transfer of the initial thumbnail image and a style reference image.

Abstract: Mechanisms are provided for automatically predicting vehicle weight of a moving vehicle. Vehicle operation data is obtained from one or more on-board sensors/systems of the vehicle and features are extracted. The features are filtered based on a required working condition of the vehicle to identify intervals of features having valid feature data to thereby generate a filtered valid data. The filtered valid data is processed by a first artificial intelligence (AI) computer model based on time slices of the filtered valid data to generate a first prediction of vehicle weight, and by a second AI computer model based on buckets of key variables to generate a second prediction of vehicle weight. The first prediction is fused with the second prediction to generate a final prediction of vehicle weight which is output to downstream computing logic.

Abstract: An example system includes a processor to receive a ciphertext including an encrypted packed plaintext. The processor can, in response to detecting that a reshape is to be executed for a data structure including the packed ciphertext, identify a target shape for the data structure and execute the reshape based on the identified target shape. The reshape is executed using multiplication by an identity element. The processor can then execute a homomorphic computation using the reshaped data structure.

Abstract: A computer-implemented method, a computer system and a computer program product enhance an intent classifier through training data augmentation. The method includes selecting a target sample from a plurality of samples. The method also includes determining an ambiguity level for the target sample based on confidence scores of at least two intent labels associated with the target sample. The method further includes selecting a nearest neighboring sample from a group of neighboring samples when the ambiguity level is below a threshold. The nearest neighboring sample includes a confidence score associated with an intent label. The method also includes, for every intent label, merging the confidence scores of the two samples into an overall confidence score for the intent label and modifying the ambiguity level using the overall confidence score. Lastly, the method includes labeling the target sample with the intent label when the modified ambiguity level is above the threshold.

Abstract: According to a computer-implemented method, an available amount of each of multiple computing resources is determined by machine logic over a period of time at a computing device. The machine logic also determines an expected usage of each computing resource to execute each workflow in a queue. The machine logic also determines a time of execution of each workflow in the queue based on the available amount of each of the multiple computing resources over time and the expected usage of each computing resource to execute each workflow in the queue.

Abstract: A method includes identifying a cluster of users with a plurality of devices, where each user from the cluster of users is associated with at least one device from the plurality of devices. The method also includes identifying an authorized user from the cluster of users to delegate role assignments to a remaining portion of the cluster of users and receiving, from the authorized user, a first role assignment for a first user from the remaining portion of the cluster of users. In response to receiving, from the first user, an audio command, the method also includes determining whether the first user is authorized to provide the audio command to the intelligent virtual assistant based on the first role assignment. In response to determining the first user is authorized to provide the audio command, the method also includes performing the audio command from the first user.

Abstract: A device, a method, and an article of manufacture are disclosed. The device includes a first optical fiber, a second optical fiber, an electrochromic component positioned between tips of the optical fibers, and a voltage source connected to the electrochromic component. The method includes providing an electrochromic component, providing optical fibers and a voltage source, and assembling an optical switch that includes the electrochromic component, the optical fibers, and the voltage source. The voltage source is connected to the electrochromic component. The article of manufacture includes an optical switch with a voltage source connected to an electrochromic component positioned between optical fiber tips.

Abstract: A computer-implemented method, a computer system, and a computer program product are provided. A first computer receives first data from a first sensor associated with a first user. The first computer uses artificial intelligence to generate a first recommendation for a replacement object for the first user. The generating is based on the first data. The first recommendation indicates ability of the replacement object to replace a first object associated with the first user. The first computer transmits the first recommendation for presentation to the first user.