Abstract: Techniques are provided for caching of machine learning model training parameters. One method comprises training a machine learning model using a given training dataset; and caching a parameter of the machine learning model from the training with the given training dataset. The cached parameter of the machine learning model is used for a subsequent training of the machine learning model. The caching may be performed after each of multiple iterations of the training of the machine learning model. A given cached iteration of the training of the machine learning model may be identified using a key based on: (i) a hash of the given training dataset, (ii) a hash of the machine learning model parameter, and/or (iii) hyperparameters of the machine learning model. The caching of a given iteration of the machine learning model may occur when the given cached iteration is not found in a cache memory.

Abstract: In some examples, a computing device may determine, based on sensor data, that the computing device is in a public environment. In response, the computing device may display an entry wheel to enable a user to enter a password. The entry wheel may include multiple input symbols arranged equidistant around a circle. In some cases, one or more geometric patterns linking a portion of the input symbols may be displayed. After receiving an individual character of the password, the computing device may display the entry wheel rotated a number of positions in either a clockwise or counter-clockwise direction and display zero or more of the geometric patterns. After all the characters of the password have been received, the computing device may determine if the password matches a previously stored password. If the password matches, the computing device may transition from a low power state to an active state.

Abstract: Techniques are provided for caching of machine learning model training parameters. One method comprises training a machine learning model using a given training dataset; and caching a parameter of the machine learning model from the training with the given training dataset. The cached parameter of the machine learning model is used for a subsequent training of the machine learning model. The caching may be performed after each of a plurality of iterations of the training of the machine learning model. A given cached iteration of the training of the machine learning model may be identified, for example, using a key based at least in part on: (i) a hash of the given training dataset, (ii) a hash of the machine learning model parameter, and/or (iii) hyperparameters of the machine learning model. The caching of a given iteration of the machine learning model may occur when the given cached iteration is not found in a cache memory.

Abstract: An apparatus in one embodiment comprises at least one processing platform comprising a plurality of processing devices. The processing platform is configured to abstract a plurality of partner platforms and a plurality of enterprise applications to extract a plurality of connectivity parameters associated with respective ones of the partner platforms and the enterprise applications, to manage connections between the partner platforms and the enterprise applications by implementing connectivity parameters, wherein the implementing provides the partner platforms with centralized access to the enterprise applications via a broker layer, to select one or more of the connectivity parameters to be used in connection with routing of data between a given partner platform and a given enterprise application, and to route the data between the given partner platform and the given enterprise application via the broker layer using the selected one or more connectivity parameters.

Abstract: Techniques are provided for analytically generating micro-service Consumer- Driven Contracts and automated tests. One method comprises obtaining a plurality of usage data records for consumers of a service from a run-time environment; extracting data features from the usage data records; applying a clustering algorithm to the usage data records to assign the usage data records to a given usage pattern cluster of a plurality of usage pattern clusters based on the extracted data features, wherein each of the plurality of usage pattern clusters comprises usage data records; and performing the following steps when the clustering algorithm creates a new usage pattern cluster: creating a new Consumer-Driven Contract that defines consumer expectations of the service, with respect to the new usage pattern associated with the new usage pattern cluster; and generating automated Consumer-Driven Contract tests to test the new Consumer-Driven Contract.

Abstract: Techniques are provided for machine learning based query optimization for federated databases. An exemplary method comprises obtaining a query to be processed in a federated database; generating at least one predictive data movement instruction to move data to a target data source when the target data source satisfies one or more of a predefined efficiency criteria with respect to a query type of the query and a predefined capacity criteria at an expected execution time of the query; and generating a query execution plan for the query by calculating a cost of execution for a plurality of potential target data sources and selecting a target data source for the query based on the calculated cost of execution. The federated database optionally employs a dynamic federated query schema.

Abstract: In some examples, a computing device may determine, based on sensor data, that the computing device is in a public environment. In response, the computing device may display an entry wheel to enable a user to enter a password. The entry wheel may include multiple input symbols arranged equidistant around a circle. In some cases, one or more geometric patterns linking a portion of the input symbols may be displayed. After receiving an individual character of the password, the computing device may display the entry wheel rotated a number of positions in either a clockwise or counter-clockwise direction and display zero or more of the geometric patterns. After all the characters of the password have been received, the computing device may determine if the password matches a previously stored password. If the password matches, the computing device may transition from a low power state to an active state.

Abstract: An apparatus in one embodiment comprises at least one processing platform comprising a plurality of processing devices. The processing platform is configured to abstract a plurality of partner platforms and a plurality of enterprise applications to extract a plurality of connectivity parameters associated with respective ones of the partner platforms and the enterprise applications, to manage connections between the partner platforms and the enterprise applications by implementing connectivity parameters, wherein the implementing provides the partner platforms with centralized access to the enterprise applications via a broker layer, to select one or more of the connectivity parameters to be used in connection with routing of data between a given partner platform and a given enterprise application, and to route the data between the given partner platform and the given enterprise application via the broker layer using the selected one or more connectivity parameters.

Abstract: Techniques are provided for generating specifications for a microservice implementation of an existing application. An exemplary method comprises: analyzing request data and corresponding response data for an application implemented as a monolithic application and/or a Service Oriented Architecture application to generate data features; parsing an audit log and/or a transaction log of the application to identify interactions with a data store; clustering the data store interactions using an unsupervised learning technique to identify patterns of usage of the data store; selecting one or more service types to generate using a trained supervised machine learning model for the requests, the corresponding response data and the data store interactions; and generating an application programming interface specification, a data model specification and/or a message specification for the selected service types for a microservice implementation of the application.

Abstract: Techniques are provided for generating specifications for a microservice implementation of an existing application. An exemplary method comprises: analyzing request data and corresponding response data for an application implemented as a monolithic application and/or a Service Oriented Architecture application to generate data features; parsing an audit log and/or a transaction log of the application to identify interactions with a data store; clustering the data store interactions using an unsupervised learning technique to identify patterns of usage of the data store; selecting one or more service types to generate using a trained supervised machine learning model for the requests, the corresponding response data and the data store interactions; and generating an application programming interface specification, a data model specification and/or a message specification for the selected service types for a microservice implementation of the application.

Abstract: Dried foods infused with inulin are provided, especially whole vegetable pieces. Such products are characterized as food pieces having a water activity ranging from about 0.15 to 0.5. The foods can comprise about 1% to 30% inulin. The inulin has a D.P ranging from about 2-9. The products are shelf stable and provide high levels of fiber. Methods of preparing dried inulin infused vegetable products are described comprising the steps of providing a quantity of un-comminuted food pieces having a moisture content ranging from about 40% to about 95%; infusing the food pieces with an inulin wherein the inulin has a degree of polymerization ranging from about 2-9 to form an at least partially inulin infused food piece; and drying the inulin infused food piece to a finish water activity ranging from about 0.4 to 0.55.

Abstract: Cooked cereal dough products are provided that are fortified with at least a 0.65% calcium (dry weight basis) at least a major portion of which is supplied by calcium phosphate salts having an median particle size of 2 to 15 ?m. Dried cereal finished products such as Ready-To-Eat breakfast cereals are fabricated from cooked cereal doughs that can comprise even lightly colored cereal materials such as rice and/or corn (maize) and minor levels of other conventional cereal ingredients and calcium phosphate. Methods for preparing such calcium fortified cooked cereal compositions and dried cereal finished food products essentially comprise: A. providing a calcium fortified cooked cereal dough or mass containing at least 0.65% calcium (dry weight basis) at least a portion of which is supplied by calcium phosphate; B. forming the lightly colored calcium fortified cereal dough into pieces; and, C. drying the pieces to form the present rice based finished food products fortified with high levels of calcium.

Abstract: Dried foods infused with inulin are provided, especially whole fruit pieces. Such products are characterized as food pieces having a water activity ranging from about 0.15 to 0.5. The foods can comprise about 1% to 30% inulin. The inulin has a D.P ranging from about 2-9. The products are shelf stable and provide high levels of fiber. The inulin bearing dried products can be added to other foods such as Ready-to-eat cereals base to provide high fiber blended products without need to altering the characteristics of the cereal base or its method of manufacture.

Abstract: Cold start performances in an engine of a wax-containing fuel may be assessed by drawing said fuel from a container under standardized conditions through a filter and measuring the rate of flow of fuel past said filter and comparing said flow rate with a flow rate obtained under the same conditions with a fuel of known cold start performance. This provides a relatively quick and simple indication of whether an engine running on such a fuel at the test temperature might be expected to have its filter blocked by the wax, preventing it from starting.