Abstract: Embodiments relate to a system, program product, and method for employing deep learning techniques to fused data across modalities. A multi-modal data set is received, including a first data set having a first modality and a second data set having a second modality, with the second modality being different from the first modality. The first and second data sets are processed, including encoding the first data set into one or more first vectors, and encoding the second data set into one or more second vectors. The processed multi-modal data set is analyzed, and the encoded features from the first and second modalities are iteratively and asynchronously fused. The fused modalities include combined vectors from the first and second data sets representing correlated temporal behavior. The fused vectors are then returned as output data.

Abstract: Methods and systems for tag-based identification include receiving a set of parameters at a user device from a remote server. A counterfeit-proof identification tag is read using a sensor in the user device using the set of parameters. Features of the counterfeit-proof identification tag are extracted in accordance with a feature extraction function, using a processor, to generate a tag bit sequence. A challenge function is applied to the extracted features to generate a result. The result is transmitted to the remote server to authenticate the counterfeit-proof identification tag. The counterfeit-proof identification tag is authenticated with a tag database at the remote server.

Abstract: An assistive shopping cart system for guiding a user and monitoring the user's physical and cognitive conditions in a shopping environment is described. The assistive shopping cart system provides assistance and guidance to a user based on a user profile. The assistive shopping cart system routes the user through the shopping environment using a shopping route generated based on the user profile. The assistive shopping cart system also detects and tracks user physical and cognitive conditions and user actions in the shopping environment. The user actions are used to aid in the completion of a purchase/transaction and generate shopping notifications for the user and others to understand the process of the shopping experience.

Abstract: A computer-implemented method includes: receiving, using a processor, multiple data session records (DSRs); storing the multiple DSRs in a memory communicatively coupled to the processor; analyzing, using the processor, the stored multiple DSRs for temporal and spatial data; and determining, using the processor, quality degradation by using the temporal and spatial data for the stored multiple DSRs.

Abstract: Methods and systems for tag-based identification include receiving a set of parameters at a user device from a remote server. A counterfeit-proof identification tag is read using a sensor in the user device using the set of parameters. Features of the counterfeit-proof identification tag are extracted in accordance with a feature extraction function, using a processor, to generate a tag bit sequence. A challenge function is applied to the extracted features to generate a result. The result is transmitted to the remote server to authenticate the counterfeit-proof identification tag. The counterfeit-proof identification tag is authenticated with a tag database at the remote server.

Abstract: Techniques for determining temporal dependencies and inter-time series dependencies in multi-variate time series data are provided. For example, embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor that can execute the computer executable components stored in the memory. The computer executable components can include: a computing component that encodes recurrent neural networks (RNNs) with time series data and determines decoded RNNs based on temporal context vectors, to determine temporal dependencies in time series data; a combining component that combines the decoded RNNs and determines an inter-time series dependence context vector and an RNN dependence decoder; and an analysis component that determines inter-time series dependencies in the time series data and forecast values for the time series data based on the inter-time series dependence context vector and the RNN dependence decoder.

Abstract: Methods and systems for tag-based identification include reading a counterfeit-proof identification tag using a sensor in a user device. Features of the identification tag are extracted in accordance with a feature extraction function, using a processor, to generate a tag bit sequence. A challenge function is applied to the extracted features to generate a result. The result is transmitted to a remote server to authenticate the identification tag.

Abstract: Methods are provided for enabling secure big data analytics in the cloud. A method includes reading a secure file, by a Secure Distributed File System in a public cloud service provider. The reading step includes computing a hash of a name of the secure file to obtain a hashed file name, finding metadata for the secure file using the hashed file name, retrieving a sharing policy identifier from the metadata, and obtaining authorization from an external entity to decrypt the secure file. The reading step further includes extracting a security key and encrypted data file names from the metadata using the sharing policy identifier, requesting one or more encrypted data files that form the secure file from a node of the public cloud service provider, and at least one of decrypting and reconstructing plaintext data for the secure file from the one or more encrypted data files.

Abstract: A method, system and computer program product are disclosed for providing content to a communications device. In an embodiment of the invention, a communications network receives a first content portion from a content provider and sends the first content portion to the communications device. The communications network also sends a second content portion to the communications device, and this second content portion is customized for the user of the communications device based on selected information about the user that the communications network has. In one embodiment, the communications network uses the selected information about the user to customize the second content portion for the user, and sends the customized second content portion to the communications device. In an embodiment, the communications network sends the selected information to the content provider, and the content provider uses the selected information to customize the second content portion.

Abstract: A system and computer program product to externalize mobile device state migration (i.e., checkpointing) without being dependent upon any particular Edge Application (EdgeApp) proxy server or cellular network base station. In this manner, the Edge Application (EdgeApp) proxy server does not have to be aware of a migration process, yet will enable state information to be provided to other EdgeApp proxy/server nodes at the edge of the network (cell tower).

Abstract: A processor receives time series data and a function describing a type of dependency that is desired to be determined from the time series data. A probe matrix is determined based upon the function. A weight matrix including a plurality of weights is determined, and a weighted probe matrix is determined based upon the probe matrix and the weighted matrix. The time series data and the weighted probe matrix is input into a neural network, and the neural network is trained using the time series data and the weighted probe matrix to converge the plurality of weights in the weight matrix. The converged weight matrix is extracted from an output of the neural network, and dependencies in the time series data are determined based upon the converged weight matrix.

Abstract: An embodiment of the invention provides a method for including receiving a natural language query from a user with an interface, and generating multiple dependency parses of the natural language query with a parser device connected to the interface. The generating of the multiple dependency parses includes dividing the natural language query into multiple components, and creating a single dependency parse by connecting each component of the components with at least one other component of the components. A processor connected to the parser device applies rules to all of the multiple dependency parses to identify entities and relations in the natural language query.

Abstract: Methods are provided for enabling secure big data analytics in the cloud. A method includes reading a secure file, by a Secure Distributed File System in a public cloud service provider. The reading step includes computing a hash of a name of the secure file to obtain a hashed file name, finding metadata for the secure file using the hashed file name, retrieving a sharing policy identifier from the metadata, and obtaining authorization from an external entity to decrypt the secure file. The reading step further includes extracting a security key and encrypted data file names from the metadata using the sharing policy identifier, requesting one or more encrypted data files that form the secure file from a node of the public cloud service provider, and at least one of decrypting and reconstructing plaintext data for the secure file from the one or more encrypted data files.

Abstract: An embodiment of the invention provides a method wherein a natural language query is received from a user with an interface. An ontological representation of data in a database is received with an input port, including names of concepts and names of concept properties. Template rules are received with the input port, the templates rules being language dependent and ontology independent, the template rules including widely used constructs of a language. Rules are automatically generated with a rule generation engine with the ontological representation of the data in the database and the template rules to identify entities and relations in the natural language query. Entities and relations are identified with a processor, the entities and relations being identified in the natural language query with the rules. The structured data language query is generated with a query generation engine from the entities and relations.

Abstract: Methods are provided for enabling secure big data analytics in the cloud. A method includes reading a secure file, by a Secure Distributed File System in a public cloud service provider. The reading step includes computing a hash of a name of the secure file to obtain a hashed file name, finding metadata for the secure file using the hashed file name, retrieving a sharing policy identifier from the metadata, and obtaining authorization from an external entity to decrypt the secure file. The reading step further includes extracting a security key and encrypted data file names from the metadata using the sharing policy identifier, requesting one or more encrypted data files that form the secure file from a node of the public cloud service provider, and at least one of decrypting and reconstructing plaintext data for the secure file from the one or more encrypted data files.

Abstract: Mechanisms are provided for generating a composite service. A request to generate the composite service is received that identifies a geospatial region of interest for the composite service. One or more types of components needed to generate the composite service are determined and, for each component of a plurality of components of the one or more types of components, a corresponding spatial coverage characteristic is determined. A subset of components, from the plurality of components, is selected based on the spatial coverage characteristics of the plurality of components and the geospatial region of interest. The composite service is then generated based on the selected subset of components from the plurality of components.

Abstract: Mechanisms are provided for generating a composite service. A request to generate the composite service is received that identifies a geospatial region of interest for the composite service. One or more types of components needed to generate the composite service are determined and, for each component of a plurality of components of the one or more types of components, a corresponding spatial coverage characteristic is determined. A subset of components, from the plurality of components, is selected based on the spatial coverage characteristics of the plurality of components and the geospatial region of interest. The composite service is then generated based on the selected subset of components from the plurality of components.

Abstract: Methods and systems for tag-based identification include reading a counterfeit-proof identification tag using a sensor in a user device. Features of the identification tag are extracted in accordance with a feature extraction function, using a processor, to generate a tag bit sequence. A challenge function is applied to the extracted features to generate a result. The result is transmitted to a remote server to authenticate the identification tag.

Abstract: A method and system for providing on-line services to a user from a services provider over a wireless cellular network. The cellular network is located between the user and the services provider, and a distributed computer system such as the Internet is located between the services provider and the cellular network for transmitting data between the services provide and the cellular network. In one embodiment, the services provider transmits software and operating characteristics over the distributed computer system to the cellular network, and the cellular network installs this software on one or more nodes of the network. When a user connects to the cellular network for services from the service provider, the network operates the software on the one or more nodes in accordance with the operating characteristics, to provide one or more services from this one or more nodes to the user from the service provider.

Abstract: Mechanisms are provided for generating a composite service. A request to generate the composite service is received that identifies a geospatial region of interest for the composite service. One or more types of components needed to generate the composite service are determined and, for each component of a plurality of components of the one or more types of components, a corresponding spatial coverage characteristic is determined. A subset of components, from the plurality of components, is selected based on the spatial coverage characteristics of the plurality of components and the geospatial region of interest. The composite service is then generated based on the selected subset of components from the plurality of components.