Abstract: The invention relates generally to systems and methods estimating a target outcome using a combination of quantum computing and a Monte Carlo simulation. A quantum processor loads variables and distributions into a quantum system, begins a quantum walk, performs arithmetic operations with the variables and distributions to initiate the steps in the quantum walk, and ultimately performs a quantum estimation of the quantum state to estimate a target variable.

Abstract: Techniques are described with respect to a system, method, and computer product for voice-based augmented reality locomotion. An associated method includes receiving a first linguistic input; and determining a label and a duration associated with the linguistic input based on an analysis of the first linguistic input. The method further including converting the label into a heading and the duration into a magnitude in a virtual environment; and merging the heading and magnitude in a vector in the virtual environment.

Abstract: Video analysis by receiving video data associated with a multi-participant meeting, identifying a first participant viewpoint, a related argument and an authority level of a viewpoint-argument, from the video data using a machine learning model, identifying a first topic within the video data, correlating the first participant viewpoint to the first topic, determining a distance between the first participant viewpoint and a second participant viewpoint, the second participant viewpoint correlated to the first topic, and providing a depiction of a relationship between the first participant viewpoint and the second participant viewpoint according to the distance.

Abstract: According to one embodiment, a method, computer system, and computer program product for mixed reality is provided. The present invention may include receiving 3D hand keypoints (keypoints) of a user's visible hand joints from the user's capturable hand, and visible hand joints, if any, from the user's uncapturable hand; using random noise sampled with a unit normal distribution as initial keypoints for the uncapturable hand joints from the user's uncapturable hand; inputting the received and the initial keypoints, in a preset order, into a trained 3D hand joint generative model; performing an iterative refinement of the uncapturable hand joints from the user's uncapturable hand using the trained 3D hand joint generative model; identifying whether generated keypoints of the user's uncapturable hand are synchronized with the keypoints of the user's capturable hand; and rendering the generated 3D keypoints for the user's uncapturable hand joints using a 3D virtual hand modeler.

Abstract: An approach for assisting software developers to fill the data gap and reproducing client application issue using reported reproducing steps is disclosed. The approach involves constructing service request/response sequence (from the developer's side based on the limited data) from customer's reproducing steps and developer's running inspection result and perform UI-service mapping, redirecting service call to data simulator which replay the service request and response, and adjusting service response with multiple data sources and policies. Lastly, the approach can transform the issue to an automatic test script with the service response in a mockup function (e.g., can be used to extend test data and enhance test cases).

Abstract: Aspects of the invention include techniques for intimacy-based masking of three dimensional (3D) face landmarks within a metaverse. A non-limiting example method includes determining a degree of intimacy R between a first user and a second user responsive to a first avatar of the first user being observed by a second avatar of the second user in a virtual environment. An initial set of M landmarks of a feature of the first avatar is determined and N landmarks are randomly selected from M for masking. The N landmarks are replaced with random noise sampled with a unit normal distribution to define a set of noised landmarks X that are then iteratively denoised to define a set of denoised landmarks D. A masked version of the first avatar is presented to the second user by modifying the feature of the first avatar with the set of denoised landmarks D.

Abstract: Embodiments relate to decoding communications with token sky maps. At least one electronic communication including emoticons having a non-original meaning is received. A candidate meaning is determined for the emoticons having the non-original meaning in the at least one electronic communication based at least in part on token neighborhood distribution structures. The candidate meaning for the emoticons having the non-original meaning is caused to be displayed on at least one device.

Abstract: A method, computer system, and a computer program product for syllable-based pronunciation help are provided. An input text in a first language may be received. A selection of a target language that is different from the first language may be received. From the target language, syllables with a pronunciation most closely matching a pronunciation of the input text in the first language are obtained. The obtaining is based on a comparison of one or more spectrograms for the input text with one or more spectrograms for text of the target language. The obtained syllables in the target language are presented.

Abstract: An approach for assisting software developers to fill the data gap and reproducing client application issue using reported reproducing steps is disclosed. The approach involves constructing service request/response sequence (from the developer's side based on the limited data) from customer's reproducing steps and developer's running inspection result and perform UI-service mapping, redirecting service call to data simulator which replay the service request and response, and adjusting service response with multiple data sources and policies. Lastly, the approach can transform the issue to an automatic test script with the service response in a mockup function (e.g., can be used to extend test data and enhance test cases).

Abstract: A computer-implemented method includes: extracting, by one or more processors, media data from an information technology ticket; extracting, by one or more processors, a plurality of data elements from the media data; and generating, by one or more processors, a ticket knowledge graph based on the plurality of data elements, wherein a node of the ticket knowledge graph represents a data element, and an edge between a first node and a second node in the ticket knowledge graph represents a correlation between a first data element represented by the first node and a second data element represented by the second node.

Abstract: A pilot protection method includes: obtaining time-domain signals data of target element at a preset sampling frequency; fusing time-domain signals data of multiple first sampling periods to obtain first time-domain signals combination data; based on a machine learning model, determining whether a fault occurs in target element according to the first time-domain signals combination data; when it is determined that a fault occurs in target element according to the first time-domain signals combination data, based on the machine learning model, determining whether a fault occurs in target element in the second sampling period according to the second time-domain signals combination data. The second sampling period is the sampling period after determining a fault occurs; when it is determined that the same type of fault occurs in target element in multiple consecutive second sampling periods, the pilot protection system is controlled to perform the protection action on the target element.

Abstract: Aspects of the present disclosure relate to support content generation. An issue description is received from a user. A software feature associated with the issue description is identified using a trained classification model. A base image associated with the software feature is obtained. The base image is modified to add information indicated in the issue description, wherein the modified base image is generated support content. The generated support content is transmitted.

Abstract: A computer-implemented method, system and computer program product for providing high quality speech recognition. A first speech-to-text model is selected to perform speech recognition of a customer's spoken words and a second speech-to-text model is selected to perform speech recognition of the agent's spoken words during a call. The combined results of the speech-to-text models used to process the customer's and agent's spoken words are then analyzed to generate a reference speech-to-text result. The customer speech data that was processed by the first speech-to-text model is reprocessed by multiple other speech-to-text models. A similarity analysis is performed on the results of these speech-to-text models with respect to the reference speech-to-text result resulting in similarity scores being assigned to these speech-to-text models.

Abstract: Aspects of the present disclosure relate to support content generation. An issue description is received from a user. A software feature associated with the issue description is identified using a trained classification model. A base image associated with the software feature is obtained. The base image is modified to add information indicated in the issue description, wherein the modified base image is generated support content. The generated support content is transmitted.

Abstract: A pilot protection method includes: obtaining time-domain signals data of target element at a preset sampling frequency; fusing time-domain signals data of multiple first sampling periods to obtain first time-domain signals combination data; based on a machine learning model, determining whether a fault occurs in target element according to the first time-domain signals combination data; when it is determined that a fault occurs in target element according to the first time-domain signals combination data, based on the machine learning model, determining whether a fault occurs in target element in the second sampling period according to the second time-domain signals combination data. The second sampling period is the sampling period after determining a fault occurs; when it is determined that the same type of fault occurs in target element in multiple consecutive second sampling periods, the pilot protection system is controlled to perform the protection action on the target element.

Abstract: Aspects of the present disclosure relate to automatically generating a user manual using a technique that includes training a first model with a first set of training data. The technique further includes generating, by the first model, a set of operations and a set of windows, where the set of operations and the set of windows are functions of the program. The technique further includes, generating a plurality of tasks, where a first task comprises a first operation being performed on a first window. The technique further includes determining an order of the plurality of tasks and calculating a level score for the first operation of the first window. The technique further includes assembling the user manual having the plurality of tasks in the determined order.

Abstract: Embodiments relate to decoding communications with token sky maps. At least one electronic communication including emoticons having a non-original meaning is received. A candidate meaning is determined for the emoticons having the non-original meaning in the at least one electronic communication based at least in part on token neighborhood distribution structures. The candidate meaning for the emoticons having the non-original meaning is caused to be displayed on at least one device.

Abstract: Disclosed is a diagnostic apparatus for a chronic obstructive pulmonary disease (COPD) based on prior knowledge CT subregion radiomics, belonging to the field of medical imaging. The diagnostic apparatus comprises: a subregion partitioning module based on prior knowledge configured for partitioning a CT lung image of a patient into three subregions based on the CT values of the interior of the lung, wherein the CT value of the interior of the lung of a subregion 1 is in the range of (?1024, ?950), the CT value of the interior of the lung of a subregion 2 is in the range of (?190, 110), and the CT value of the interior of the lung of a subregion 3 is in the range of (?950, ?190); a feature extraction module configured for extracting the radiomics features of the three subregions, respectively, and obtaining the LAA-950I features.

Abstract: Video analysis by receiving video data associated with a multi-participant meeting, identifying a first participant viewpoint, a related argument and an authority level of a viewpoint-argument, from the video data using a machine learning model, identifying a first topic within the video data, correlating the first participant viewpoint to the first topic, determining a distance between the first participant viewpoint and a second participant viewpoint, the second participant viewpoint correlated to the first topic, and providing a depiction of a relationship between the first participant viewpoint and the second participant viewpoint according to the distance.

Abstract: A computer-implemented method, system and computer program product for providing high quality speech recognition. A first speech-to-text model is selected to perform speech recognition of a customer's spoken words and a second speech-to-text model is selected to perform speech recognition of the agent's spoken words during a call. The combined results of the speech-to-text models used to process the customer's and agent's spoken words are then analyzed to generate a reference speech-to-text result. The customer speech data that was processed by the first speech-to-text model is reprocessed by multiple other speech-to-text models. A similarity analysis is performed on the results of these speech-to-text models with respect to the reference speech-to-text result resulting in similarity scores being assigned to these speech-to-text models.