Abstract: A technique relates to a manufacturing process. A computer system receives a material identification of a resource being manufactured, and receives images captured of units of the resource, the resource having been cut into the units. Features are determined for each of the units from the images. Feature vectors are created on a one-to-one basis for each of the units. A blockchain is formed using the feature vectors associated with each of the units, the blockchain having the material identification of the resource and a certificate identifying the units. A feasibility of the certificate for the units of the resource is validated via the blockchain.

Abstract: A hybrid knowledge representation is searched for a machine learning component corresponding to a search query. The hybrid knowledge representation may be structured as nodes representing machine learning workflow components and edges (e.g., links) connecting the nodes based on relationships between the nodes. Responsive to finding the machine learning component in the hybrid knowledge representation, the machine learning component is returned. Responsive to not finding the machine learning component in the hybrid knowledge representation, the hybrid knowledge representation is searched for machine learning model fragments associated with building the machine learning component, generating a new machine learning component by combining the machine learning model fragments and returning the new machine learning component.

Abstract: Aggregating and transforming data, and performing analytics thereupon, for application-specific optimization based on multiple data sources. The data is preferably ingressed automatically, and may originate from various public and/or private data sources. Data transformation preferably aligns the data aggregated from the various sources, to thereby allow meaningful referencing. Complex and non-aligned data can therefore be consolidated, such that it is readily digestible by simulation (or other) software. In an embodiment, risk of flooding for a supply chain is computed from the aggregated and transformed data, using data analytics based on physical computation for flood risk assessment, allowing the supply chain to be optimized with regard to threat of flooding and/or actual flooding. In another embodiment, risk of wild fire may be assessed. Other types of risk may also be assessed.

Abstract: A technique relates to a manufacturing process. A computer system receives a material identification of a resource being manufactured, and receives images captured of units of the resource, the resource having been cut into the units. Features are determined for each of the units from the images. Feature vectors are created on a one-to-one basis for each of the units. A blockchain is formed using the feature vectors associated with each of the units, the blockchain having the material identification of the resource and a certificate identifying the units. A feasibility of the certificate for the units of the resource is validated via the blockchain.

Abstract: A technique relates to tracking a foodstuff. A device images human consumable code formed on the foodstuff, the human consumable code being part of the foodstuff, the foodstuff being unpackaged. A coding associated with the human consumable code is determined. Product information of the foodstuff is retrieved from a computer system by using the coding. The product information of the foodstuff is provided on the device.

Abstract: Aggregating and transforming data, and performing analytics thereupon, for application-specific optimization based on multiple data sources. The data is preferably ingressed automatically, and may originate from various public and/or private data sources. Data transformation preferably aligns the data aggregated from the various sources, to thereby allow meaningful referencing. Complex and non-aligned data can therefore be consolidated, such that it is readily digestible by simulation (or other) software. In an embodiment, risk of flooding for a supply chain is computed from the aggregated and transformed data, using data analytics based on physical computation for flood risk assessment, allowing the supply chain to be optimized with regard to threat of flooding and/or actual flooding. In another embodiment, risk of wild fire may be assessed. Other types of risk may also be assessed.

Abstract: A computer-implemented method, a computer program product, and a computer system for infrastructure resource provisioning using trace-based workload temporal analysis. An infrastructure provider receives, from an on-premises infrastructure, scheduler traces of the on-premises infrastructure, one or more scenarios, one or more goals, and one or more constraints of resource deployment on the on-premises infrastructure. The infrastructure provider performs trace-based workload temporal analysis, based on the scheduler traces, the one or more scenarios, the one or more goals, and the one or more constraints. The infrastructure provider generates one or more options of provisioning infrastructure resources, based on the trace-based workload temporal analysis.

Abstract: A method, computer system, and a computer program product for dynamic role assignment is provided. The present invention may include identifying a crisis event based on data collected by one or more internet-connected sensors. The present invention may then include selecting an incident plan based on the identified crisis event. The present invention may then include communicating an incident role to a registered device of a crowd member.

Abstract: An illustrative embodiment includes a method for improving performance of a computer. The method includes: automatically identifying an algorithm supplied by a user for execution on the computer; searching a database of algorithms for at least one algorithm similar to the user-supplied algorithm; determining whether the at least one similar algorithm will improve performance of the computer relative to the user-supplied algorithm; and if the at least one similar algorithm will improve performance of the computer relative to the user-supplied algorithm, modifying the user-supplied algorithm to incorporate at least in part the at least one similar algorithm.

Abstract: A system for automatically generating an athletic training schedule includes a wearable device having one or more sensors for determining a quantity of athletic training performed by a user wearing the wearable device and an athletic performance of the user. A processor is configured to receive the quantity of athletic training performed and the athletic performance data from the wearable device, and to estimate a relationship between the quantity of athletic training performed and the athletic performance. A selection of a competitive target is received. A performance level of the selected competitive target is estimated. A minimum level of training needed to meet or exceed the estimated performance level is determined based on the estimated relationship between the quantity of athletic training performed and the athletic performance. The athletic training schedule is automatically generated based on the determined minimum level of training.

Abstract: An ore content prediction system is provided. The system receives structured geological data that is derived based on spatial geological information that is associated with an input region. The received structured geological data includes a plurality of multidimensional tensors that are derived from spatial geological information of a plurality of sub-regions of the input region. The spatial geological information includes one or more types of data. The system trains a prediction model to produce a prediction output based on an average grade of an ore of a target mineral type at a target region by using the received structured geological data.

Abstract: A method for transporting data from a source location to a destination location includes receiving the data from at least one sender at the source location, the sender specifying at least one recipient at the destination location; splitting the data into a plurality of portions; and finding one or more couriers who will travel from the source location to the destination location. The method also includes: while at least a given courier is at the source location, sending at least one of the plurality of portions to a mobile device of at least the given courier; once the given courier travels to the destination location, receiving the at least one of the portions from the mobile device of the given courier; and once the plurality of portions of the data have been received at the destination location, sending the data set to the at least one recipient.

Abstract: A plurality of datasets may be received. Multiple instances of a machine learning algorithm may be run to create corresponding multiple machine learning models trained for a specific task in a given domain. Each of the multiple instances may use a different subset of the plurality of datasets in training the corresponding machine learning model. The multiple machine learning models may be run with input data. The multiple machine learning models produce corresponding multiple outcomes. A candidate machine learning model may be determined based on comparing each of the multiple outcomes with ground-truth output. A value associated with the different subset of the plurality of datasets may be determined based on comparing of each of the multiple outcomes with ground-truth output. A smart contract may be created which may include the value and the different subset of the plurality of datasets. The smart contract may be recorded in a blockchain.

Abstract: A method for coordinating activities includes monitoring physiologic stress signals and movement signals from a plurality of individuals, and learning at least one baseline for each of the plurality of individuals from the physiologic stress signals and the movement signals. The method further includes estimating a psychological stress level for each individual by comparing the individual's physiologic stress signals to their baseline, determining a current activity for each individual, and learning correlations between current activities and sequences of activities and estimated psychological stress levels.

Abstract: A pollution source detection system, includes an automated vehicle including a position sensor that detects a geographic position of the automated vehicle and at least one pollution detection sensor that measures a concentration of pollution at the automated vehicle. The pollution source detection system includes a back-end system. The back-end system includes a network interface that receives the geographic position and the concentration of the pollution from the automated vehicle. The back-end system includes a database that stores the geographic position and the concentration of the pollution received via the network interface. The back-end system includes a processor that measures a gradient of the concentration of the pollution and controls a movement of the automated vehicle based on the gradient to guide the automated vehicle toward a source of the pollution.

Abstract: A populace centric weather forecast system, method of forecasting weather and a computer program product therefor. A forecasting computer applies a grid to a forecast area and provides a weather forecast for each grid cell. Area activity data sources indicate human activity in the forecast area. A dynamic selection module iteratively identifies grid cells for refinement in response to the weather forecast and to indicated/expected human activity. The dynamic selection module provides the forecasting computer with a refined grid for each identified grid cell in each iteration. The forecasting computer provides a refined weather forecast in each iteration.

Abstract: Aggregating and transforming data, and performing analytics thereupon, for application-specific optimization based on multiple data sources. The data is preferably ingressed automatically, and may originate from various public and/or private data sources. Data transformation preferably aligns the data aggregated from the various sources, to thereby allow meaningful referencing. Complex and non-aligned data can therefore be consolidated, such that it is readily digestible by simulation (or other) software. In an embodiment, risk of flooding for a supply chain is computed from the aggregated and transformed data, using data analytics based on physical computation for flood risk assessment, allowing the supply chain to be optimized with regard to threat of flooding and/or actual flooding. In another embodiment, risk of wild fire may be assessed. Other types of risk may also be assessed.

Abstract: Aggregating and transforming data, and performing analytics thereupon, for application-specific optimization based on multiple data sources. The data is preferably ingressed automatically, and may originate from various public and/or private data sources. Data transformation preferably aligns the data aggregated from the various sources, to thereby allow meaningful referencing. Complex and non-aligned data can therefore be consolidated, such that it is readily digestible by simulation (or other) software. In an embodiment, risk of flooding for a supply chain is computed from the aggregated and transformed data, using data analytics based on physical computation for flood risk assessment, allowing the supply chain to be optimized with regard to threat of flooding and/or actual flooding. In another embodiment, risk of wild fire may be assessed. Other types of risk may also be assessed.

Abstract: A computer storage management system includes a memory storing a process; a processor executing the process; and an operating system (OS). The OS includes a filesystem configured to receive a plurality of requests from the process to access data stored on the memory; and a filesystem event handler configured to receive the requests in a sequence determined by an order in which instructions associated with the requests occur within the process, store the sequence of requests without accessing the memory, and execute the sequence of requests.

Abstract: A method of performing a notification event at a headphone device includes receiving, at the headphone device, a wireless notification signal. The wireless notification signal is received from a transmitting device including a camera sensor, a display and a touchscreen interface. The headphone device is selected to receive the wireless notification signal in response to a touchscreen event occurring at the transmitting device. An image including a representation of the headphone device is composed by the camera sensor and is presented on the display. The touchscreen event includes receiving a touch input via the touchscreen interface. The method further includes determining the notification event to be performed at the headphone device by decoding the wireless notification signal. The method further includes performing the notification event indicated by the wireless notification signal at the headphone device in response to receiving the wireless notification signal.