Abstract: An apparatus for correcting a defect in an object using three-dimensional (3D) printing. The apparatus includes a flexible wrapper-shaped printing module including an array of port openings adapted to allow a 3D printable material to move therethrough. The flexible wrapper-shaped printing module is configured to wrap around an object to allow the 3D printable material to move through a first set of selected port openings of the array of port openings and be injected into the defect in order to correct the defect.

Abstract: Hardware and software on a computing device is analyzed based on a regulatory profile for the computing device and regulatory compliance for an entity associated with the computing device. A determination is made whether at least one of the hardware and software on the computing device includes at least one regulatory non-compliance issue. In response to determining that at least one of the hardware and software on the computing device includes at least one regulatory non-compliance issue, one or more scripts are executed on the hardware and software on the computing device to cause the hardware and software to resolve the at least one regulatory non-compliance issue based on the regulatory profile for the computing device.

Abstract: Aspects of the present disclosure relate to personal protective equipment (PPE) management. A set of personal protective equipment (PPE) data describing use time limits of respective PPE articles of a set of PPE articles can be received. Use of a PPE article of the set of PPE articles can be monitored using one or more sensors. A determination can be made whether a PPE usage rule of the PPE article is satisfied based on the monitoring, where the PPE usage rule is based on at least a use time limit of the PPE article. A PPE recommendation action can be issued in response to determining that the PPE usage rule of the PPE article is satisfied.

Abstract: A stop assembly for damper masses of a damper system has a stop device and a stop device carrier which holds the stop device. The stop device has at least one shoulder, which is intended to engage in at least one associated receiving portion of the stop device carrier. In at least one support region, the shoulder is oversized relative to the associated receiving portion to facilitate captive engagement in the receiving portion, and, at a distance from the at least one support region, the shoulder is undersized relative to the associated receiving portion to facilitate assembly-simplifying engagement in the receiving portion.

Abstract: Techniques are disclosed for systems and methods associated with a micromobility transit vehicle battery connection and lock. In accordance with one or more embodiments, a micromobility transit vehicle is provided. The micromobility transit vehicle may include a frame, a battery configured to be received at least partially within the frame, and a battery lock within the frame. The frame may include a downtube having a recess disposed therein. The battery may be configured to be received within the downtube and the recess to establish a continuous surface comprising one or more outer surfaces of the downtube and one or more outer surfaces of the battery. The battery lock may be positioned within the recess and configured to engage the battery to lock the battery in place.

Abstract: Disambiguation of search keywords to expert systems is performed through the application of a semantic ranking function to determine a classification category with confidence for a given query. The semantic ranking function is executed through an application of a semantic distance distribution profile score through analysis of user problem statement (UPS) with nodes in the taxonomy in the same vector space to create a search that combines a user problem statement and a taxonomical node in the search engine index. The distribution profile score calculation is provenance influenced to derive geographic, cultural, and demographic provenance for a user problem statement.

Abstract: Systems, methods, and computer program products for selectively customizing, modifying and changing performance parameters, capabilities and behaviors of AI devices within AI device networks by sharing user-selected portions of a knowledge corpus with other AI device networks. Selectively sharing parameters, learned behaviors, capabilities, and features of the knowledge corpus allows for AI devices within a second AI device network to mimic, clone or recreate the performance or behaviors of AI devices operating within the environment of a first AI device network. Users can create portable nodes that travel with the user and upon connecting with the second device network, identify AI devices that can be modified using the portions of the knowledge corpus to recreate selected portions of the first AI device network within the environment of the second AI device network either permanently or for a user-selected amount of time.

Abstract: An example method includes capturing, via an x-ray machine, a plurality of x-ray images of a patient covering a number of different anatomy of the patient in any order, using a machine learning algorithm to process the plurality of x-ray images for identification of an anatomy in respective x-ray images of the plurality of x-ray images, associating a label with each of the plurality of x-ray images based on the identification of the anatomy, positioning each of the plurality of x-ray images upright based on a preset coordinate scheme for the anatomy, arranging the plurality of x-ray images into a predetermined order based on the species of the patient, and generating and outputting a data file including the plurality of x-ray images in the predetermined order, positioned upright, and labeled.

Abstract: Systems, methods, devices, and non-transitory media of the various embodiments may provide for managing data quality anomalies in an enterprise system. Various embodiments may enable one or more network computing device to identify control points for monitoring data sets in the enterprise system, track data quality metrics using at least one threshold for each of the identified control points, determine whether a data quality anomaly is detected, and classify a review priority in response to determining that a data quality anomaly is detected.

Abstract: A computing device may be configured to continuously, repeatedly, or recursively generate, train, improve, focus, or refine the machine learning classifier models that are used data anomalies. The computing device may create a corpus of data based on architecture or standards documents, generate classifier models based on the corpus of data, collect information from one or more data sources, generate feature vectors based on the collected information, apply the feature vectors to the classifier models to generate an analysis result, and identify a data anomaly based on the generated analysis result.

Abstract: A method, computer system, and a computer program product for securing transportation of Items. In one embodiment, packaging particulars may be determined including packaging configuration and materials. At least a sensor may be embedded when packaging the Item. The sensor type and location may be selected by a processor. The Sensor(s) may be selected to monitor changes to the condition of the Item during the transportation. Sensor data may be monitored and any risk to the Item during the transportation may be mitigated. In one embodiment, when a risk has been determined, an alert may be provided such as to a person or an IoT enabled device to mitigate the risk.

Abstract: A method, system and computer program product includes identifying a presence of a problem with one or more items in transport using cognitive analytics and information received from at least one sensing device. In response to the identifying, storing an identification of the presence of the problem in a block chain ledger by a secure and validated feed having an indexed encryption identifying the sensing device, and recommending a remediation action to fix the problem with the one or more items.

Abstract: A shock absorber that includes a pressure tube that defines a working chamber having a hydraulic fluid located therein; a piston assembly positioned in the working chamber, and dividing the working chamber into an upper working chamber and a lower working chamber; and a piston rod engaged with the piston assembly that moves the piston assembly in the working chamber, wherein the hydraulic fluid includes a primary oil, a secondary oil, and an additive package, the secondary oil includes at least a gas-to-liquid oil in an amount that ranges between 4.0 wt % to 10.0 wt % relative to a total amount of the hydraulic fluid, and the hydraulic fluid includes a flash point of at least 174 degrees C.

Abstract: A system and method for bandwidth management are provided. In embodiments, a method includes: training, by a computing device, a predictive machine learning (ML) model based on historic network usage data of software applications in a cloud environment and historic business context data; assigning, by the computing device, priority rankings to software application activities of the cloud environment using the predictive ML model based on predicted resource requirements for the software application activities of the cloud environment and predicted contextual scenarios that impact the predicted resource requirements using an input of real-time network usage data of the cloud environment and real-time business context data; and initiating, by the computing device, scheduling of the software application activities based on the priority rankings.

Abstract: A system and method for bandwidth management are provided. In embodiments, a method includes: training, by a computing device, a predictive machine learning (ML) model based on historic network usage data of software applications in a cloud environment and historic business context data; assigning, by the computing device, priority rankings to software application activities of the cloud environment using the predictive ML model based on predicted resource requirements for the software application activities of the cloud environment and predicted contextual scenarios that impact the predicted resource requirements using an input of real-time network usage data of the cloud environment and real-time business context data; and initiating, by the computing device, scheduling of the software application activities based on the priority rankings.

Abstract: A method, computer program product, and a system where a processor(s) obtains data from one or more sources, wherein a portion of the one or more sources comprise training data for a first artificial intelligence decision-making system. The processor(s) ingest data from each source into a corpus and ingest metadata corresponding to the data, into a volume accessible to a second artificial intelligence decision-making system. The processor(s) search public sources and obtain information describing quality and non-objective influence of the data from each source. The processor(s) provide as inputs to the second artificial intelligence decision-making system, the information and the metadata, to classify the quality and the non-objective influence of each source. The processor(s) obtains outputs comprising, for each source, a first rating classifying the quality of the source of the one or more sources.

Abstract: In an approach for enabling multiple users to make e-commerce purchases from interactive advertisements using wearable device gestures, a processor identifies a wearable device attempting to pair with a smart display. A processor verifies a user wearing the wearable device is an authenticated user. A processor detects a gesture made by the user based on a sensor of the wearable device. A processor identifies an action the gesture is mapped to. A processor determines whether the user is authorized to complete the action mapped to the gesture detected. Responsive to determining that the user is authorized to complete the action mapped to the gesture, a processor completes the action the gesture is mapped to.

Abstract: A computer-implemented method includes: monitoring, by a computing device, network communications to a server; determining, by the computing device, a threat to the server based on the monitoring; determining, by the computing device, a risk level of the threat; selecting, by the computing device, a response to the threat based on the determined risk level, wherein the response is selected from a predefined set of responses; initiating, by the computing device, the selected response.

Abstract: System and methods for type ahead search amelioration based on image processing are provided. In embodiments, a method includes: capturing, by a computing device, image data based on images viewed by a user during a computing session; converting, by the computing device, the image data to text using image processing; and storing, by the computing device, the text in a temporary buffer of a type ahead search function, wherein the text constitutes image context data for use by the type ahead search function.

Abstract: Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: iteratively obtaining utilization parameter values from first to Nth edge computing environments, training one or more predictive model by machine learning using parameter values of the utilization parameter values obtained by the iteratively obtaining, wherein the training includes training a first computing environment predictive model with use of parameter values of the utilization parameters obtained from the first computing environment by the iteratively obtaining.