Abstract: Embodiments of the invention are directed to a computer-implemented method that includes accessing, using a processor system, a three-dimensional (3D) model of a device-under-design (DUD). The processor system is used to receive a first design operation associated with the 3D model of the DUD. A collaboration dependency model is used to make a prediction of a dependency relationship between the first design operation and a second design operation.

Abstract: An embodiment includes classifying an incoming communication message as having an instruction classification based on a natural language processing (NLP) analysis of the incoming communication message. The embodiment extracts, responsive to classifying the incoming communication message as having the instruction classification, user operations as a workflow dataset. The embodiment clusters the workflow dataset into a task cluster with other similar workflow datasets representative of previously-extracted user operations. The embodiment designates the instruction classification as a trigger event based at least in part on the NLP analysis of the incoming communication message. The embodiment generates a robotic process automation (RPA) bot script that comprises program instructions executable by a processor to cause the processor to perform operations that automate the user operations in response to the trigger event.

Abstract: An embodiment senses an interaction among a software agent and a plurality of humans, responsive to the sensed interaction, computes a mood pattern in a Mood Pattern Observation Component based on the sensed interaction. The embodiment computes a prevalent mood pattern in a Mood Pattern Grouping Component based on the mood pattern. The embodiment decides by an Orchestration of Agent Interactions Component based on the prevalent mood pattern to adapt a response of the software agent to influence at least one of the plurality of humans towards the prevalent mood pattern, the deciding further comprises training a Text Generation Component to generate a text sequence based on the response wherein the software agent emits the text sequence and the sensed interaction among the software agent and the plurality of humans is updated with the text sequence.

Abstract: Described is a method for generating graphics in a user interface corresponding to options provided by an interactive voice response component by determining an interactive voice response (IVR) component is active on a call initiated by a user. The method identifying a various options provided by the IVR component with respect to a keypad in a user interface on a touchscreen of a device and displaying a graphic for each option from the various options provided by the IVR component. In response to receiving a graphic selection for the plurality options from a user, sending an option selection corresponding to the graphic selection to the IVR component.

Abstract: According to one embodiment, a method, computer system, and computer program product for identifying induced deformation of a 3D object is provided. The embodiment may include receiving an unaltered three-dimensional (3D) rendering of an object and attribute information of the object. The embodiment may include identifying one or more influencing factors of forecasted local deformation of one or more portions of the 3D rendering based on the attribute information. The embodiment may include creating, via a generative adversarial network (GAN), a 3D rendering of the object showing the forecasted local deformation. The embodiment may include identifying induced deformation of one or more other portions of the 3D rendering caused by the forecasted local deformation. The embodiment may include creating, via the GAN, a 3D rendering of the object showing the identified induced deformation.

Abstract: A computer-implemented method, a computer system and a computer program product adapt a vehicle communication network range based on an awareness of vehicle speed. The method includes identifying a plurality of devices within a recommended range of a vehicle. The method also includes obtaining a current driving environment from the plurality of devices. In addition, the method includes calculating a required range for a communications network based on the current driving environment and determining required devices within the required range. Lastly, the method includes dynamically creating the communications network when the required range is greater than the recommended range, where the communications network includes the vehicle, the plurality of devices within the recommended range and the required devices.

Abstract: A computer-implemented method, a computer program product, and a computer system for training a context-aware chatbot. A computer receives a prompt form a user, where the prompt has a level of ambiguity. A computer identifies context of the prompt, by analyzing collected data from various sources. A computer identifies an intent of the prompt, by using natural language processing to disambiguate the prompt. A computer provides a modified prompt, according to the context and the intent. A computer selects datasets relevant to the context. A computer generates a response to the prompt, based on the modified prompt and the datasets, where the context-aware chatbot responds to the prompt with the response.

Abstract: Methods, systems, and a computer program product are disclosed. The first method includes obtaining virtual session data in real time, identifying a positional utterance in the virtual session data, and generating a positional insight for the positional utterance. The first method also includes generating a best-practices recommendation based on the positional insight. The second method includes obtaining virtual session data, identifying positional utterances in the virtual session data, and generating positional insights for each of the positional utterances. The second method also includes selecting each of the positional insights having confidence scores above a threshold score and generating best-practices recommendations based on the selected positional insights.

Abstract: An embodiment for altering a machine based on a predicted problem in a multi-machine environment is provided. The embodiment may include receiving data relating to an activity and functionalities of a primary machine in a multi-machine environment. The embodiment may also include executing a digital twin simulation of a digital twin model of the primary machine performing the activity in accordance with the functionalities. The embodiment may further include identifying a problem condition with at least one component of the primary machine in executing one or more steps of the activity. The embodiment may also include in response to determining the primary machine is not capable of performing an alternative activity with the problem condition, deploying one or more secondary machines having at least one substitute component for the at least one component of the primary machine to collaborate with the primary machine.

Abstract: A method, computer system, and computer program product for utilizing crowdsourcing of images captured by individuals to determine the status of a subject is provided. The embodiment may receive, by a processor associated with a broad beacon, an impulse. The embodiment may also transmit a request to each client device within a preconfigured distance through the broad beacon based on the received impulse. The embodiment may further, in response to an acceptance of the transmitted request by a user associated with a client device, initializing a pairing sequence between the client device and an aimable beacon. The embodiment may also transmit information to identify a subject of photographic capture from the aimable beacon to the client device. The embodiment may further receive an image captured by the user based on the received information.

Abstract: Rendering an emotional state of a virtual reality headset user is provided. An emotion feature vector predicting a current emotional state of a user of a virtual reality headset is mapped to a matching set of existing avatar vectors a mapping function. A best matching avatar vector is selected from the matching set of existing avatar vectors based on determining that values of the best matching avatar vector most closely match values of the emotion feature vector predicting the current emotional state of the user of the virtual reality headset. An avatar associated with the user is rendered in a metaverse consistent with the current emotional state of the user of the virtual reality headset based on the best matching avatar vector to the emotion feature vector predicting the current emotional state of the user.

Abstract: The present inventive concept provides for a method of unique hiking interaction via IoT data assimilation. The method includes obtaining health data for a user and location data for a location that includes at least one activity trail. Health features are extracted from the health data and terrain features are extracted from the location data. The extracted health features and the extracted terrain features are analysed and mapped. The extracted health features include biometric measurements from at least one IoT device and the extracted terrain features include characteristics of the at least one activity trail. A unique activity experience is calculated for the user to perform a preselected activity on the at least one activity trail based at least in part on the analysed and mapped extracted health features and the extracted terrain features.

Abstract: The illustrative embodiments provide for improved transcription accuracy using a corpus of reference information. An embodiment includes retrieving, using web-scraping, written content for a topic from a source. The embodiment also includes generating a corpus of reference material for a user using the written content. Generating the corpus of reference may include using a natural language processor. The embodiment also includes analyzing, an audio of a video for spoken content for a reference in the corpus of reference material; Where analyzing may include using a content analyzer. The embodiment also includes transcribing, using a transcription service, spoken content within an audio of the video. The embodiment also includes identifying, using the content analyzer, references in the transcription using a content analyzer. Where the content analyzer compares the spoken content to written content within the corpus.

Abstract: A computer-implemented method, a computer system and a computer program product recommend an optimal break for a user. The method includes capturing activity data for the user from an environment using a device. The method also includes obtaining prior activity data related to the user and identifying a preferred break type for the user, wherein the preferred break type for the user is associated with a prior activity of the user. In addition, the method includes determining that the user needs a break from a current activity based on the activity data. The method further includes generating a break recommendation for the user, wherein the break recommendation associates the preferred break type for the user with the current activity in the activity data. Lastly, the method includes displaying the break recommendation to the user.

Abstract: According to one embodiment, a method, computer system, and computer program product for mitigating computer fan noise. The embodiment may include retrieving a previously generated baseline profile for a user participating in a real-time e-conference call via a computing device. The embodiment may include identifying real-time hardware and software metrics of the computing device. The embodiment may include calculating a current fan indicative noise (FIN) score for the call based on the baseline profile and the identified metrics. The embodiment may include determining whether the current FIN score is above a threshold value. In response to determining that the FIN score is above a threshold value, the embodiment may include determining whether the computing device is at risk of damage. In response to determining that the computing device is not at risk of damage, the embodiment may include limiting operation of one or more fans of the computing device.

Abstract: A method for countering adversarial attacks on deep neural networks is disclosed. In one embodiment, such a method includes observing, by a first system, actual traffic behavior within a transportation network. The method classifies, by a deep neural network of a second system, a traffic sign for regulating traffic within the transportation network. The method determines whether a conflict exists between the actual traffic behavior and expected traffic behavior based on the traffic sign. If a conflict is deemed to exist, the method adjusts training data of the deep neural network with respect to classifying the traffic sign. In certain embodiments, the first system includes one or more forerunner vehicles and the second system is an autonomous vehicle. The one or more forerunner vehicles may be configured to travel ahead of the autonomous vehicle when navigating the transportation network. A corresponding system and computer program product are also disclosed.

Abstract: Provided is a computer-implemented method, system, and computer program product for predictively preventing robotic devices from privacy overreach through object detection amelioration. A processor may train a machine learning model, using training image data and risk-based profiling data, to identify personal privacy boundaries within one or more environments. The processor may deploy the machine learning model to a robotic device, where the robotic device includes sensors to generate image data for a first environment of the robotic device. The processor may input the image data for the first environment to the machine learning model. The processor may analyze, using the machine learning model, the image data to identify an object and/or area associated with a personal privacy boundary. The processor may classify, using the machine learning model and based on the analyzing, the object and/or area as being associated with the personal privacy boundary.

Abstract: A computer-implemented method, a computer system and a computer program product project incident information within an augmented reality environment based on vehicle movements. The method includes determining a predicted path of a vehicle based on telemetry data associated with the vehicle. The method also includes obtaining driving conditions associated with a surrounding environment using a sensor. In addition, the method includes identifying an object in the predicted path of the vehicle. The method further includes determining a collision zone on the object and a corresponding collision zone on the vehicle based on physical attributes of the object and the predicted path of the vehicle. Lastly, the method includes generating a display of the driving conditions using an augmented reality device, where the display indicates the collision zone on the object and includes a virtual model of the vehicle that indicates the corresponding collision zone on the vehicle.

Abstract: In an approach to determining the optimal size and shape of additive manufactured packaging, a delivery location corpus, a storage location corpus, and a transportation mechanism corpus are received. A notification to design a package for an item is received. The optimal design attributes are determined for the delivery location. The optimal design attributes are determined for the storage location. The optimal design attributes are determined for the transportation mechanism. The additive manufactured packaging for the item is designed based on the optimal design attributes for the delivery location, the storage location, and the transportation mechanism.

Abstract: A bite guard configured to conform to teeth of a patient, and an array of sensor assemblies encapsulated in the bite guard, where the array of sensor assemblies is distributed throughout the bite guard, and where each sensor assembly includes a piezo pressure sensor.