Abstract: Techniques are disclosed for a multi-layer micro model analytics framework for analyzing or otherwise processing data. For example, a method comprises building two or more micro models respectively for two or more stages of a given process, wherein each micro model of the two or more micro models comprises a user interaction layer and a predictive learning layer that coordinate to train the micro model based on input to the user interaction layer and data accessible by the predictive learning layer for the corresponding stage of the two or more stages of the given process. The method then assembles the two or more micro models to perform analysis for the given process. In one non-limiting example, the given process is a new product introduction process and each micro model is built and trained to perform analytics for a specific lifecycle stage of the process.

Abstract: The present disclosure provides various approaches for smart area monitoring suitable for parking garages or other areas. These approaches may include ROI-based occupancy detection to determine whether particular parking spots are occupied by leveraging image data from image sensors, such as cameras. These approaches may also include multi-sensor object tracking using multiple sensors that are distributed across an area that leverage both image data and spatial information regarding the area, to provide precise object tracking across the sensors. Further approaches relate to various architectures and configurations for smart area monitoring systems, as well as visualization and processing techniques. For example, as opposed to presenting video of an area captured by cameras, 3D renderings may be generated and played from metadata extracted from sensors around the area.

Abstract: A system is provided for automatically generating electronic artifacts using extended functionality. In particular, the system may use a template-based process to automatically generate artifacts based on a defined set of parameters and/or variables. The system may further use one or more plugins which may provide extended functionality with respect to the artifact generation process. Accordingly, the artifact generation process may include initializing a parameter list based on application parameters and/or plugin parameters, processing the parameters, generating variables based on the parameters, and replacing variables in scheme template files with appropriate values (e.g., user supplied or plugin generated values) to output an artifact file to a predetermined location. In this way, the system provides a robust and efficient way to automatically generate artifacts.

Abstract: Disclosed are apparatuses, systems, and techniques that improve efficiency and quality of data streaming in time-sensitive network communications. The techniques include but are not limited to proactive replacement of packets in network communications that use forward error correction techniques. Proactive replacement of packets that have been lost or can potentially become lost reduces network latency and increases the number of timely communicated data messages.

Abstract: Techniques are disclosed for domain-driven intent-based feedback data analysis. For example, a method comprises obtaining a feedback data set, and classifying the feedback data set into at least one domain of a plurality of domains. The feedback data set is mapped to a domain data set corresponding to the at least one domain, and a root cause is computed for the feedback data set to enable one or more actions to be taken in response to the feedback data set based on the root cause. By way of further example, computing the root cause for the feedback data set may further comprise utilizing at least one computed intent attribute, at least one computed sentiment attribute, and the domain data set to compute a decision on the root cause for the feedback data set.

Abstract: A system is provided for automatically generating electronic artifacts using extended functionality. In particular, the system may use a template-based process to automatically generate artifacts based on a defined set of parameters and/or variables. The system may further use one or more plugins which may provide extended functionality with respect to the artifact generation process. Accordingly, the artifact generation process may include initializing a parameter list based on application parameters and/or plugin parameters, processing the parameters, generating variables based on the parameters, and replacing variables in scheme template files with appropriate values (e.g., user supplied or plugin generated values) to output an artifact file to a predetermined location. In this way, the system provides a robust and efficient way to automatically generate artifacts.

Abstract: The instant disclosure relates to microbial decontamination of solid surfaces. The disclosure provides method for reducing or eliminating microbes from a solid surface by employing a combination of quaternary ammonium compound coating onto the solid surface and electric field application. Particularly, the method comprises subjecting a solid surface to an electric field comprising a voltage of 2 kV/cm to 6 kV/cm and a capacitance of 0.002 ?F to 0.06 ?F, to reduce or eliminate the microbes from the solid surface, wherein said solid surface comprises a coating of quaternary ammonium compound. Corresponding products including kit and solid material/device are also provided. The present method has several advantages including but not limiting to high efficiency (>4 log10 or >99.99%) in reducing/eliminating microbial load on solid surfaces; requirement of very low concentrations of quaternary ammonium compound [about 0.01% (w/v) to 1% (w/v)] to achieve said high efficiency; and shorter time-periods.

Abstract: Techniques are disclosed for hyper-segmented personalization using machine learning-based models in an information processing system. For example, a method obtains one or more product experience recommendation data sets respectively from one or more product entities, and one or more purchase experience recommendation data sets respectively from one or more commerce entities. The method applies a federated ensemble-based machine learning algorithm to at least one of the one or more purchase experience recommendation data sets and at least one of the one or more product experience recommendation data sets to generate a personalized model, and causes adaptation of a purchasing interface of at least one of the one or more commerce entities with respect to a given user based on the personalized model.

Abstract: In one aspect, an example methodology implementing the disclosed techniques includes, by a product subscription service, receiving information regarding a hardware asset being returned at an end of a subscription and predicting, using a first machine learning (ML) model, whether the hardware asset has reached EOL. The method also includes, responsive to predicting that the hardware asset has reached EOL, creating, by the product subscription service, a work order to dispatch an eco-partner. The method may further include, by the product subscription service, responsive to predicting that the hardware asset has not reached EOL, predicting, using a second ML model, one or more new subscription orders matching the hardware asset and recommending the one or more matching new subscription orders as possible fits for the hardware asset.

Abstract: A method comprises analyzing a plurality of natural language inputs associated with at least one user, and determining a plurality of contexts for the plurality of natural language inputs based, at least in part, on the analysis. In the method, a plurality of relationships linked to the at least one user are identified based, at least in part, on the analysis, and the at least one user is classified in one or more categories based, at least in part, on the plurality of contexts and the plurality of relationships. At least one of the analyzing, determining, identifying and classifying is performed using one or more machine learning models.

Abstract: A method comprising: generating first sentiment identifier of a user, the first sentiment identifier of the user being a text sentiment identifier; generating a second sentiment identifier of the user, the second sentiment identifier including one of a voice sentiment identifier of the user and an image sentiment identifier of the user, the image sentiment identifier being an indication of an emotional state of the user that is manifested in a facial expression of the user during the telephone call; generating a composite signature of the user based on the first sentiment identifier and the second sentiment identifier; and classifying the composite signature of the user into one of a plurality of categories.

Abstract: Methods, apparatus, and processor-readable storage media for automatically prioritizing supply chain-related demand using artificial intelligence techniques are provided herein.

Abstract: Path computation systems and methods are provided herein. According to one embodiment, a method includes obtaining topological information representing a topology of at least a portion of a network. The topological information includes one or more nodes and one or more links, each link configured to connect a node with a neighboring node. Each node includes a plurality of internal components and a plurality of connections configured to interconnect the internal components. The method further includes running path computation through the topological information to determine a plurality of paths from a first internal component to a second internal component. Also, the method includes applying elimination rules during the path computation to filter out one or more paths detected as being invalid. The elimination rules are based on one or more predetermined path sequences that include at least two hops involving an unviable sequence of specific types of internal components.

Abstract: A method in a networking environment to generate personalized data-streaming for a multimedia playback device is provided. The method includes deploying an ABR based data-streaming logic as a base-model at a multimedia playback device, obtaining parameters for a time duration based on a multimedia-playback at the multimedia playback device, obtaining a statistical mean for the parameters based on a first statistical analysis, identifying a parameter from the parameters by comparing the obtained mean against a threshold weight associated with the parameters in accordance with the base model, scaling the identified parameter in a predefined format as training, applying a second statistical analysis to the identified parameter of the playback device and another playback device for determining a covariance between both devices and determining a category of the playback device based on the covariance and deploying a version of the trained base model upon the playback device based on the category.

Abstract: A text reconstruction system for reconstructing a primary text data is provided. A voice input signal of a user is converted into an input text data by a speech recognition module. A text classifier module generates one or more tokens and adds the tokens into a word bag corresponding to the user. A text identifier module generates a text corpus based on the input text data. A user profile builder module creates a user profile based on the word bag, the input text data, and the text corpus. A decision module determines, based on the word bag, whether the primary data is to be reconstructed and reconstructs the primary text data to generate a personalized text data based on the user profile.

Abstract: The present invention relates to a process according to Scheme 1 for the preparation of microbiocidal 5-trifluoromethyl-1,2,4-oxadiazole derivatives of formula (I) suitable for use, e.g., as active ingredients, which have microbiocidal activity, in particular, fungicidal activity.

Abstract: An imaging apparatus includes at least one processor to implement: a re-sizer configured to re-size an image to a predetermined size, an encoder configured to encode the re-sized image, and a frame rate controller configured to calculate an actual bit rate of the encoded image for a preset period of time, compare a user-set target bit rate with the calculated actual bit rate, adjust a frame rate of the encoded image according to a result of the comparison, and output an encoded image signal at a user-set target bit rate irrespective of a complexity of the encoded image.

Abstract: A method in a networking environment to generate personalized data-streaming for a multimedia playback device is provided. The method includes deploying an ABR based data-streaming logic as a base-model at a multimedia playback device, obtaining parameters for a time duration based on a multimedia-playback at the multimedia playback device, obtaining a statistical mean for the parameters based on a first statistical analysis, identifying a parameter from the parameters by comparing the obtained mean against a threshold weight associated with the parameters in accordance with the base model, scaling the identified parameter in a predefined format as training, applying a second statistical analysis to the identified parameter of the playback device and another playback device for determining a covariance between both devices and determining a category of the playback device based on the covariance and deploying a version of the trained base model upon the playback device based on the category.

Abstract: A system is provided for automatically generating electronic artifacts using extended functionality. In particular, the system may use a template-based process to automatically generate artifacts based on a defined set of parameters and/or variables. The system may further use one or more plugins which may provide extended functionality with respect to the artifact generation process. Accordingly, the artifact generation process may include initializing a parameter list based on application parameters and/or plugin parameters, processing the parameters, generating variables based on the parameters, and replacing variables in scheme template files with appropriate values (e.g., user supplied or plugin generated values) to output an artifact file to a predetermined location. In this way, the system provides a robust and efficient way to automatically generate artifacts.

Abstract: Path computation systems and methods are provided herein. According to one embodiment, a method includes obtaining topological information representing a topology of at least a portion of a network. The topological information includes one or more nodes and one or more links, each link configured to connect a node with a neighboring node. Each node includes a plurality of internal components and a plurality of connections configured to interconnect the internal components. The method further includes running path computation through the topological information to determine a plurality of paths from a first internal component to a second internal component. Also, the method includes applying elimination rules during the path computation to filter out one or more paths detected as being invalid. The elimination rules are based on one or more predetermined path sequences that include at least two hops involving an unviable sequence of specific types of internal components.