Abstract: Embodiments of the invention are directed to a computer-implemented method. A non-limiting example of the computer-implemented method includes accessing, using a processor system, a process-step sequence that includes a plurality process-steps and a plurality of queue-times. A process-step sequence mining operation is applied to the process-step sequence, wherein the process-step sequence mining operation is operable to make a prediction of an impact of a portion of the process-step sequence on a characteristic of a product generated by the process-step sequence.

Abstract: Tabular data is accessed that contains multiple entries of alphanumeric data. Multiple tokens are generated of the multiple entries of alphanumeric data using a tokenization process. The tokenization process maintains jargon-specific features of the alphanumeric data. Multiple embeddings of the multiple entries of alphanumeric data are generated using the tokens. The embeddings capture similarity of the multiple entries considering all of global features, column features, and row features in the tokens of the tabular data. A neural network is used to predict probabilities for pre-defined classes for the tabular data using the generated embeddings.

Abstract: Users of an endpoint remediation system can be assigned to different roles, from which they can request exceptions, approve exceptions, and/or enable remediation on endpoint devices. The compliance scanning and enforcing process can be automated, while allowing entities to request and/or approve certain exceptions. Therefore, security compliance for customers can be actively managed to provide visibility to the endpoint device compliance state at any time.

Abstract: Temporal and spatially integrated forecast modeling includes generating a plurality of forecast models for a plurality of short-term to long-term time periods for a plurality of locations. Temporally integrating the plurality of forecast models sequentially over the plurality of time periods for the plurality of locations and spatially integrating the temporally integrated plurality of forecast models for each location hierarchically over the geographic areas. The forecast models are autoregressive distributed lag models with different explanatory variables for the short-term and long-term forecast models. The temporally integrating includes recursively integrating the plurality of forecast models over the time periods from the short-term to the long-term time periods and the spatially integrating includes recursively integrating the temporally integrated plurality of forecast models hierarchically from larger size geographic areas to smaller size geographic areas.

Abstract: A concept associated with a feature used in machine learning model can be determined, the feature extracted from a first data source. A second data source containing the concept can be identified. An additional feature can be generated by performing a natural language processing on the second data source. The feature and the additional feature can be merged. A second machine learning model can be generated, which use the merged feature. A prediction result of the first machine learning model can be compared with a prediction result of the second machine learning model relative to ground truth data, to evaluate effective of the merged feature. Based on the evaluated effectiveness, the feature can be augmented with the merged feature in machine learning.

Abstract: Users of an endpoint remediation system can be assigned to different roles, from which they can request exceptions, approve exceptions, and/or enable remediation on endpoint devices. The compliance scanning and enforcing process can be automated, while allowing entities to request and/or approve certain exceptions. Therefore, security compliance for customers can be actively managed to provide visibility to the endpoint device compliance state at any time.

Abstract: Users of an endpoint remediation system can be assigned to different roles, from which they can request exceptions, approve exceptions, and/or enable remediation on endpoint devices. The compliance scanning and enforcing process can be automated, while allowing entities to request and/or approve certain exceptions. Therefore, security compliance for customers can be actively managed to provide visibility to the endpoint device compliance state at any time.

Abstract: A method is provided for creating a semantic model for submitting search queries thereto. The method includes an act of receiving data from one or more input sources in an entity and relationship capture service of a situational awareness engine. The method further includes an act of extracting entities and relationships between the entities in two or more extraction services, where the two or more extraction services include at least two of a table-to-graph service, an event-to-graph service, a sensor-to-graph service, a text-to-graph service, and an image-to-graph service. The method includes an act of generating a semantic model based on fusion and labeling the extracted data provided by the at least two extraction services, where the semantic model can receive a search query and respond to the search query based on the generated semantic model.

Abstract: Content is selectively provided to users of mobile devices within a venue including an on-site wireless network. User authorization requests and/or user account registration data are transmitted to the on-site wireless network from mobile devices within the venue. Attributes such as user interests and professions, which comprise inferred user profiles, are obtained using the network traffic data. Identities of mobile devices are established based on a combination including two or more of network identifiers, mobile device signatures, and browser signatures. The inferred user profiles are correlated with the mobile device identities. The inferred user profiles are aggregated into user profile groups and then matched with a content provider's intended target profiles. Content is transmitted to the mobile devices corresponding to the intended target profiles and based on correlation of the inferred user profiles with identities of the devices.

Abstract: Providing real-time awareness of an audience to a presenter during the presentation. In response to presenting a presentation to an audience, information is automatically collected about the audience from sensors positioned amongst the audience. The collected information about the audience is analyzed and, during the presentation, recommendations are made to the presenter for improving the presentation based on the collected information.

Abstract: Providing real-time awareness of an audience to a presenter during the presentation. In response to presenting a presentation to an audience, information is automatically collected about the audience from sensors positioned amongst the audience. The collected information about the audience is analyzed and, during the presentation, recommendations are made to the presenter for improving the presentation based on the collected information.

Abstract: Users of an endpoint remediation system can be assigned to different roles, from which they can request exceptions, approve exceptions, and/or enable remediation on endpoint devices. The compliance scanning and enforcing process can be automated, while allowing entities to request and/or approve certain exceptions. Therefore, security compliance for customers can be actively managed to provide visibility to the endpoint device compliance state at any time.

Abstract: Content is selectively provided to users of mobile devices within a venue including an on-site wireless network. User authorization requests and/or user account registration data are transmitted to the on-site wireless network from mobile devices within the venue. Attributes such as user interests and professions, which comprise inferred user profiles, are obtained using the network traffic data. Identities of mobile devices are established based on a combination including two or more of network identifiers, mobile device signatures, and browser signatures. The inferred user profiles are correlated with the mobile device identities. The inferred user profiles are aggregated into user profile groups and then matched with a content provider's intended target profiles. Content is transmitted to the mobile devices corresponding to the intended target profiles and based on correlation of the inferred user profiles with identities of the devices.

Abstract: Content is selectively provided to users of mobile devices within a venue including an on-site wireless network. User authorization requests and/or user account registration data are transmitted to the on-site wireless network from mobile devices within the venue. Attributes such as user interests and professions, which comprise inferred user profiles, are obtained using the network traffic data. Identities of mobile devices are established based on a combination including two or more of network identifiers, mobile device signatures, and browser signatures. The inferred user profiles are correlated with the mobile device identities. The inferred user profiles are aggregated into user profile groups and then matched with a content provider's intended target profiles. Content is transmitted to the mobile devices corresponding to the intended target profiles and based on correlation of the inferred user profiles with identities of the devices.

Abstract: A method and system of characterizing a job market is provided. The available job postings of a job market are determined. For each job posting, one or more technical skills, a job role level, and one or more professional capabilities related to the job posting are determined. The professional capabilities are aggregated by job dimensions. The determined technical skills and the professional capabilities of each job posting and the aggregated professional capabilities are stored in a database as reference data. A job capability profile for one or more job dimensions is provided based on the stored reference data in the database.

Abstract: For each of a plurality of endpoints of an information technology system having a plurality of security policies, a probability of being safe of each of said endpoints is determined according to each of said security policies. Said determining takes into account probability of security compromise for a single violation of each given one of said security policies. A risk-aware compliance metric is determined for said information technology system based on each of said probabilities of being safe for each of said endpoints and each of said policies. At least one of an operation and a remediation is carried out on said information technology system based on said risk-aware compliance metric. Techniques for optimizing risk-aware compliance are also provided.

Abstract: For each of a plurality of endpoints of an information technology system having a plurality of security policies, a probability of being safe of each of said endpoints is determined according to each of said security policies. Said determining takes into account probability of security compromise for a single violation of each given one of said security policies. A risk-aware compliance metric is determined for said information technology system based on each of said probabilities of being safe for each of said endpoints and each of said policies. At least one of an operation and a remediation is carried out on said information technology system based on said risk-aware compliance metric. Techniques for optimizing risk-aware compliance are also provided.

Abstract: In one embodiment, the invention is a method and apparatus for variation enabling statistical testing using deterministic multi-corner timing analysis. One embodiment of a method for obtaining statistical timing data for an integrated circuit chip includes obtaining deterministic multi-corner timing data for the integrated circuit chip and constructing the statistical timing data from the deterministic multi-corner timing data.

Abstract: In one embodiment, the invention is a method and apparatus for variation enabling statistical testing using deterministic multi-corner timing analysis. One embodiment of a method for obtaining statistical timing data for an integrated circuit chip includes obtaining deterministic multi-corner timing data for the integrated circuit chip and constructing the statistical timing data from the deterministic multi-corner timing data.

Abstract: A method for constructing delay rules which include the effects of MIS simulations for static timing analysis with reduced cost. The present method includes constructing skew windows for applying MIS penalties purely from SIS data, and scales the MIS penalties during rule use based upon how closely the skews in the use case approach the edge of the skew window. The method applies both to timing rule construction for a library of circuits and to timing rule construction for macros where only part of the circuits in the macro may be sensitive to skew between macro inputs.