Abstract: Techniques for real-time modeling temperature distributions based on streaming sensor data are provided. In one aspect, a method for creating a three-dimensional temperature distribution model for a room having a floor and a ceiling is provided. The method includes the following steps. A ceiling temperature distribution in the room is determined. A floor temperature distribution in the room is determined. An interpolation between the ceiling temperature distribution and the floor temperature distribution is used to obtain the three-dimensional temperature distribution model for the room.

Abstract: A method is provided for personalized behavioral-driven event management. The method includes determining, by a processor, derivative behaviors from user behavioral data for one or more users. The derivative behaviors include intent driven behavioral data and habitual behavioral data. The method further includes deriving, by the processor, one or more behavioral triggers that differentiate the intent driven behavioral data from the habitual behavioral data. The method also includes generating, by the processor, a risk prediction based on a predictive risk assessment model that uses the intent driven behavioral data differentiated from the habitual behavioral data by the one or more behavioral triggers to enhance a predictive power of the user behavioral data. The method additionally includes enabling, by the processor, risk intervention for at least one of the one or more users by directly targeting the behavioral triggers, responsive to the risk prediction.

Abstract: Causal performance analysis for store merchandising may be provided. A clustering technique may be performed based on target store location data and existing store data. Based on the clustering technique, a peer selection group is determined comprising a group of stores determined to have similar attributes to the target store location. Sales distortions for a plurality of divisions associated with the group of stores in the peer selection group may be determined. A distortion matrix may be generated comprising a ranked list of the plurality of divisions. A merchandise mix recommendation for the target store location may be presented via a user interface device.

Abstract: A method and system are provided. The method includes receiving by a computer having a processor and a memory, sequence data that includes labeled data and unlabeled data. The method further includes generating, by the computer having the processor and the memory, a recurrent neural network model of the sequence data, the recurrent neural network model having a recurrent layer and an aggregate layer. The recurrent neural network model feeds sequences generated from the recurrent layer into the aggregate layer for aggregation, stores temporal dependencies in the sequence data, and generates labels for at least some of the unlabeled data.

Abstract: A method and system are provided. The method includes converting, by a computer having a processor and a memory, categorical sequence data for a customer journey into a numerical similarity matrix. The method further includes learning, by the computer, features of the customer journey by applying a distance metric learning based matrix factorization approach to the numerical similarity matrix.

Abstract: Methods and a system are provided that is performed by a computer server for inferring location context categories for a set of mobile users having at least two members. A method includes, for each mobile user in the set, obtaining at least one location context category therefor from publically available information responsive to uncertain mobile device location data. The method further includes applying multi-user collaborative machine learning to the at least one location context category for each mobile user in the set to infer a single refined location context category for each mobile user in the set.

Abstract: Geo-defect repair modeling is provided. A method includes logically dividing a railroad network according to spatial and temporal dimensions with respect to historical data collected. The spatial dimensions include line segments of a specified length and the temporal dimensions include inspection run data for inspections performed for each of the line segments over a period of time. The method also includes creating a track deterioration model from the historical data, identifying geo-defects occurring at each inspection run from the track deterioration model, calculating a track deterioration condition from the track deterioration model by analyzing quantified changes in the geo-defects measured at each inspection run, and calculating a derailment risk based on track conditions determined from the inspection run data and the track deterioration condition.

Abstract: Methods, systems and apparatus for determining a proposed cost for use of sensor resources and selecting a method of processing of sensed data are presented. Such a method includes the steps of: predicting a state of an environment, obtaining at least one criterion related to the use of the sensor resources comprising one or more data sensors, determining the proposed cost for use of the sensor resources, acquiring the sensed data from the one or more data sensors, determining a characteristic of the sensed data, and selecting the method of processing the sensed data according to the determined characteristic and the predicted state. The at least one criterion is based upon the predicted state. The determining of the proposed cost is based on the at least one criterion. One or more of steps are implemented on the processor device.

Abstract: Geo-defect repair modeling is provided. A method includes logically dividing a railroad network according to spatial and temporal dimensions with respect to historical data collected. The spatial dimensions include line segments of a specified length and the temporal dimensions include inspection run data for inspections performed for each of the line segments over a period of time. The method also includes creating a track deterioration model from the historical data, identifying geo-defects occurring at each inspection run from the track deterioration model, calculating a track deterioration condition from the track deterioration model by analyzing quantified changes in the geo-defects measured at each inspection run, and calculating a derailment risk based on track conditions determined from the inspection run data and the track deterioration condition.

Abstract: Methods and a system are provided that is performed by a computer server for inferring location context categories for a set of mobile users having at least two members. A method includes, for each mobile user in the set, obtaining at least one location context category therefor from publically available information responsive to uncertain mobile device location data. The method further includes applying multi-user collaborative machine learning to the at least one location context category for each mobile user in the set to infer a single refined location context category for each mobile user in the set.

Abstract: Provided is a mechanism to evaluate and predict credit ratings of corporations from a transaction perspective (i.e., on a transaction-by-transaction basis) by integrating real-time event and external information such as, for example, social media and news reports. In various embodiments, such a mechanism may be implemented via systems, methods and/or computer program products.

Abstract: The invention provides a nitrogen-doped graphene coated nano sulfur positive electrode composite material, a preparation method, and an application thereof. The composite material includes: an effective three-dimensional conductive network formed by overlapping of nitrogen-doped graphenes, and nano sulfur particles coated by nitrogen doped graphene layers evenly. The preparation method includes: dispersing nitrogen-doped graphenes in a liquid-phase reaction system including at least sulfur source and acid, and depositing nano sulfur particles by an in-situ chemical reaction of the sulfur source and the acid, thereby preparing the positive electrode composite material. The positive electrode composite material of the invention has a high conductivity, a high sulfur utilization rate, and a high rate, thereby restraining the dissolution and shuttle effect in the lithium sulfur batteries, and enhancing the cyclic performance of the batteries.

Abstract: A hierarchical multi-stage model of asset failure risk for complex heterogeneously distributed physical assets is built. The hierarchical multi-stage model considers heterogeneity of failure patterns for the assets. At least one data stream is analyzed to determine whether the hierarchical multi-stage model needs to be updated due to a change in the failure patterns. If the analysis indicates that the hierarchical multi-stage model needs to be updated, the hierarchical multi-stage model is dynamically updated to obtain an updated hierarchical multi-stage model.

Abstract: Predicting operational changes in a multi-detector environment includes generating, via a computer processing device, a factor matrix for each univariate time series data in a set of sparse time series data collected from data sources, identifying a subset of the time series data as a feature selection based on application of a loss function, and generating a predictive model from the subset of the time series data.

Abstract: A polymer electrolyte membrane fuel cell that includes a positive electrode, a negative electrode, a polyelectrolyte membrane and a solution of reduced graphene oxide and/or graphene oxide functionalized with metallized nanoparticles. The electrodes are coated with a polymer and the polyelectrolyte membrane has a hydrophobic exterior surface that is subjected to ultraviolet/ozone (UV/O3) exposure, which changes the hydrophobic, exterior surface to a hydrophilic exterior surface. The polyelectrolyte membrane is disposed between the positive electrode and the negative electrode and can include a sulfonated tetrafluoroethylene based fluoropolymer-copolymer. The solution forms a coating on the hydrophilic exterior surface of the polymer electrolyte membrane and the positive and negative electrodes. The positive and negative electrodes can be coated with a polymer, preferably polytetrafluoroethylene (PTFE) that can be subjected to ultraviolet/ozone (UV/O3) exposure.

Abstract: Predicting operational changes in a multi-detector environment includes generating, via a computer processing device, a factor matrix for each univariate time series data in a set of sparse time series data collected from data sources, identifying a subset of the time series data as a feature selection based on application of a loss function, and generating a predictive model from the subset of the time series data.

Abstract: Generating an electronic data model of a logical supply chain and regenerating the model based on changes to modelling parameters, to guide decision making. The data model is generated using known information about the supply chain. One or more decision scenarios are modelled based on a simulated loan request, and the data model is regenerated to consider the consequences. A recommendation is made based on pre-defined or user-defined criteria.

Abstract: A method of providing video feeds from a plurality of cameras to a plurality of screens including determining a plurality of constraints on a centralized processor processing the video feeds, determining a camera semantic classification for each of the plurality of cameras, determining historical events captured by each of the plurality of cameras, and providing at least one video feed to at least one of the screens according to the plurality of constraints on the centralized processor, the camera semantic classifications and the historical events.

Abstract: A hierarchical multi-stage model of asset failure risk for complex heterogeneously distributed physical assets is built. The hierarchical multi-stage model considers heterogeneity of failure patterns for the assets. At least one data stream is analyzed to determine whether the hierarchical multi-stage model needs to be updated due to a change in the failure patterns. If the analysis indicates that the hierarchical multi-stage model needs to be updated, the hierarchical multi-stage model is dynamically updated to obtain an updated hierarchical multi-stage model.

Abstract: Electronic health records of a plurality of patients are received. A risk prediction model for a disease based on the electronic health records of the plurality of patients is created. An electronic health record of an original patient is received. A neighboring group of patients of the plurality of patients is identified, wherein the neighboring group of patients is two or more patients similar to the original patient. An ordering of the two or more patients of the neighboring group of patients is received, wherein the ordering of the two or more patients of the neighboring group of patients is based upon how similar each patient of the two or more patients is to the original patient. The risk prediction model is updated based on the ordering of the two or more patients of the neighboring group of patients.