Abstract: The illustrative embodiments provide for adaptation of reference architecture documents across clouds. An embodiment includes loading a reference architecture document. The embodiment also includes populating a knowledge repository corpus where the knowledge repository corpus includes data from information technology (IT) products, cloud services, and integrations stored with associated metadata about functionalities. The IT products, the cloud services, and the integrations are stored with metadata. The embodiment also includes classifying, using an incident analysis module, the service incidents based on the reference architecture document. The embodiment also includes detecting flaws in the reference architecture document based on the classified service incidents. The embodiment also includes creating a weighted graph of the cloud services. The embodiment also includes traversing the weighted graph and creating an adapted reference architecture based on the traversed weighted graph.

Abstract: A method for detecting content generated by artificial intelligence is disclosed. In one embodiment, such a method includes monitoring interaction between a user and a generative AI model. The method intercepts a response returned from the generative AI model to the user and embeds, within the response prior to its return to the user, codes that are invisible to the user when viewing the response. In certain embodiments, these codes are embedded within the response in a particular invisible code insertion pattern to indicate that the response was generated by the generative AI model. The method returns the response to the user for viewing. A third party may utilize the embedded codes to determine whether the response was generated by the generative AI model. A corresponding system and computer program product are also disclosed herein.

Abstract: An embodiment includes loading a plurality of data sources where each data source is comprised of content of interest. The embodiment also includes scanning the plurality of data sources for the content of interest. The embodiment also includes detecting the content of interest from scanning the plurality of data sources where detecting is based on a key word search. The embodiment also includes organizing the content of interest as data elements, based on a topic modeling technique. The embodiment also includes distributing the data elements into a plurality of topics based on a Latent Dirichlet Allocation technique. The embodiment also includes merging the data elements within each of the topics. The embodiment also includes generating a document with the topics into one or more filtered lists, based on the key word search.

Abstract: An embodiment collects a first set of patient data and a first set of treatment data associated with a patient population treated with neuromodulation. The embodiment clusters the patient population into a plurality of cohorts. The embodiment generates a plurality of states using a second set of patient data associated with a cohort in the plurality of cohorts. The embodiment generates a plurality of actions using a second set of treatment data associated with the cohort. The embodiment determines, based on the plurality of actions, a plurality of probabilities associated with a transition from a first state to a second state in the plurality of states. The embodiment generates, based on the plurality of probabilities, a neuromodulator action policy for a patient in the cohort.

Abstract: An embodiment collects a first set of patient data and a first set of treatment data associated with a patient population treated with spinal cord stimulation. The embodiment clusters the patient population into a plurality of cohorts. The embodiment generates a plurality of states using a second set of patient data associated with a cohort in the plurality of cohorts. The embodiment generates a plurality of actions using a second set of treatment data associated with the cohort. The embodiment determines, based on the plurality of actions, a plurality of probabilities associated with a transition from a first state to a second state in the plurality of states. The embodiment generates, based on the plurality of probabilities, a stimulator action policy for a patient in the cohort.

Abstract: A feature request and a price corresponding to the feature request are received. The feature request is validated, the validating determining an implementation cost of the feature request. Using a return on investment of the feature request, the feature request is selected for implementation, the return on investment computed using the implementation cost and the price. Implementation of the selected feature request is caused.

Abstract: An embodiment intercepts a notification including a portion of natural language text and a Uniform Resource Locator (URL). An embodiment identifies, using a natural language understanding model, a topic of the notification. An embodiment tags, using a content summarization model, a content located at the URL, the tagging comprising assigning a set of content tags to the content, the set of content tags comprising a predefined tag representing the content. An embodiment calculates a relevancy score scoring a comparison between the set of content tags and a set of user tags, the set of user tags comprising a predefined tag representing a profile of an intended recipient of the notification. An embodiment generates, responsive to the relevancy score being above a threshold, using the topic and the set of content tags, a customized notification, the customized notification replacing the notification.

Abstract: An embodiment includes sending a first drone, including a carbon dioxide sensor, into an area. The embodiment includes detecting a level of carbon dioxide in the area and generating a map including a position and level of carbon dioxide. The embodiment includes calculating a carbon dioxide hotspot above a threshold. The embodiment includes creating a plan to diffuse the carbon dioxide hotspot in a time limit by calculating an amount of a drones to send to the area based on a needed amount of humidity and light to diffuse the carbon dioxide hotspot in the time limit. The amount of humidity and light are calculated using an optimizer module. The embodiment includes sending the calculated amount of drones to the area of the carbon dioxide hotspot. The embodiment includes diffusing the carbon dioxide hotspot, sampling the area, and updating the map with new levels of carbon dioxide.

Abstract: A computer-implemented method includes: receiving, by a computer device and from a user device, a draft social media message; determining, by the computer device and based on the receiving, data of an Internet of Things (IoT) device that is related to the draft social media message; generating, by the computer device and based on the determining, a suggested social media message that includes the data of the IoT device; and transmitting, by the computer device, the suggested social media message to the user device.

Abstract: Classifier accuracy is increased in machine learning applications by training a machine learning (ML) model including a classifier across classes by determining weighted input points for a contributing set to store the values for true positive and true negative predications. In a following step, input data is provided to the classifier of the machine learning model at runtime, and a classification output is determined from the classifier. For the classification output, values for input during runtime are compared with a sample of inputs stored for training the machine learning model to determine the distance in spread for the classification output. A class is determined from the classification output having a smallest distance and spread. The method can further determine if the class with the smallest distance and spread is a true positive or true negative by comparing the class with the smallest distance and spread with the classification output.

Abstract: Techniques regarding post polymerization modifications to polycarbonate polymers via a flow reactor are provided. For example, one or more embodiments described herein can comprise a cyclic carbonate monomer that can be employed to facilitate polymerization of one or more polycarbonate platforms susceptible to post polymerization modification. For instance, one or more embodiments can regard a cyclic carbonate molecular backbone covalently bonded to an aryl halide functional group via in accordance with a chemical structure selected from the group consisting of: In the chemical structures, “R1” can be selected from the group consisting of a hydrogen atom and a functional group comprising a first alkyl group; “L” can represent a linkage group, comprising: a second alkyl group and an end group having at least one member selected from the group consisting of an oxygen atom and a nitrogen atom; and “A” can represent the aryl halide functional group.

Abstract: A recommender system and method to facilitate non-biasing search queries, social media feeds, and other platforms in which a user searches, scrolls, and engages with information and ideas so that a user can explore ideas outside of, or even contrary to, the ones with which they are aligned. Through a computer-implemented “curiosity halo” recommendation engine and method, users are made aware of the existence of other notions centered around or connected to a topic. The users could also engage to be directed to adjacent notions and “lines of flight” around the topic, thereby broadening their perspective and strengthening their ability to think “outside the box”—or bubble. By adjusting a threshold based on curiosity level and tolerance for divergent thinking, the boundaries of the curiosity halo are continually redrawn in real time so that users can dynamically uncover topics and ideas outside of their day-to-day experience.

Abstract: A computer-implemented method, including receiving, by a processor set, a query including a query string for a system catalog; identifying, by the processor set, a default index structure of the system catalog; executing, by the processor set, the query based on the default index structure of each index in the system catalog; ranking, by the processor set, a performance of each execution of the query by each index; mapping, by the processor set, a query pattern to a corresponding index of the system catalog; selecting, by the processor set, the index to perform the query using a machine learning (ML) model trained with a knowledge base that includes the ranking and the mapping; executing, by the processor set, the query on the selected index; and in response to executing the query on the selected index, returning, by the processor set, a result of the query.

Abstract: Aspects of the invention include generating a plurality of predictions that each define a plurality of future inputs for a model. A deviation curve is generated by determining a distance between each prediction of the plurality of predictions and a respective known data point of a plurality of known data points. One or more points in the deviation curve are sampled and the sampled points are compared to a low threshold and a high threshold. A judgement is determined for each prediction to determine whether the respective prediction will be accepted or denied as an input to the model. The future inputs for the model are modified based on the judgments.

Abstract: A method for managing a plurality of computing machines includes accessing a catalogue memory structure storing a plurality of component signatures, discovering one or more of the software components being instantiated in a software image of each computing machine according to corresponding ones of the component signatures, detecting one or more connections each being established between at least two instantiated software components of different computing machines, receiving a restore command for restoring a target recovery point selected among a plurality of recovery points, and restoring the target recovery point in response to the restore command by restoring the snapshots associated with the target recovery point on corresponding computing machines.

Abstract: The present inventive concept provides for a method of harnessing artesian aquifer power. The method includes obtaining weather data and artesian aquifer data for a geolocation. Weather features and artesian aquifer features are extracted from the obtained weather data and artesian aquifer data, respectively. Compression and decompression events are predicted for water in an artesian well at the geolocation by mapping the weather features and the artesian aquifer features. A plurality of piezoelectric springs connected to the artesian well are modulated to maximize artesian aquifer energy harnessed based on the predicted compression and decompression events.

Abstract: A processor may receive transportation data associated with one or more vehicles and one or more routes having one or more roads. The processor may analyze the transportation data for one or more vehicle capabilities associated with the one or more vehicles and one or more road capabilities associated with the one or more roads of the one or more routes. The processor may generate one or more simulations associated with the one or more roads and the one or more vehicles. The processor may identify an optimal vehicle from the one or more vehicles and an optimal route from the one or more routes. Identifying the optimal vehicle and the optimal route may be based, at least in part, on the one or more simulations. The processor may assign the optimal vehicle to the optimal route.

Abstract: A computer-implemented method for counterfactual conversation simulation is disclosed. The computer-implemented method includes generating a system output based, at least in part, on a user input. The computer-implemented method further includes determining that a system output/user input pair is not satisfactory based, at least in part, on a system output/user input score being below a predetermined threshold. The computer-implemented method further includes generating, in response to determining the system output/user input pair is not satisfactory, a counterfactual simulation of the user input based, at least in part, on a target intent of the user input.

Abstract: Embodiments of the invention include a computer-implemented method for allocating computing resources. The computer-implemented method includes generating, using a processor, tracing data that results from data traffic processed through multiple data paths by the processor. The processor is used to analyze the tracing data to identify a predicted bottleneck path among the multiple data paths, wherein the predicted bottleneck path include a data path on which a data bottleneck is predicted to occur. The computer resources are allocated to the predicted bottleneck path before the predicted data bottleneck occurs.

Abstract: A method, computer system, and a computer program product for automatically generated question suggestions is provided. The present invention may include generating an intent-entity sequence representative of a current chat conversation with a user. The present invention may also include predicting, using a trained intent-entity prediction model, a next intent-entity sequence based on the generated intent-entity sequence representative of the current chat conversation. The present invention may further include converting the predicted next intent-entity sequence into at least one likely question suggestion to return back to the user.