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This project is meant to simplyfy the usage of the excelent Configuration Admin and MetaType services for Felix OSGi. The bundle will create a service that allows other bundles to register an annotated interface. The ManagedProperties service will then create all the Metatype information, as well as ensuring that objects are cast to their right types. ManagedProperties also has a feature called Filters. A Filter is used to create an object, say a File, directly from a primitive Configuration Admin type. It can also contain logic, to allow the configuration to fail if, for example, a File doesn't exist.

This is a plugin to Madura Objects. It provides a rules/constraint engine to assist with validation, deriving new values from user inputs (eg total of invoices entered on this customer) an manipulating metadata (eg because the amount is above X we make some field readonly). Note that the Java that is using the monitored objects is quite unaware of the rules layer implemented here. That means you can change rules without having to go back to your Java code, and it also means you don't have to wonder if everything implemented the same rules. Anything using that Java object has the rules (unless you turn them all off).

FunctionExecutors 1. GeoWithinFunctionExecutor Input : (longitude double, latitude double, geoJSONGeometryFence string) OR (geoJSONGeometry string, geoJSONGeometryFence string) Output : true if (longitude, latitude) or geoJSONGeometry is within the geoJSONGeometryFence 2. GeoIntersectsFunctionExecutor Input : (longitude double, latitude double, geoJSONGeometryFence string) OR (geoJSONGeometry string, geoJSONGeometryFence string) Output : true if (longitude, latitude) or geoJSONGeometry intersects the geoJSONGeometryFence 3. GeoWithinDistanceFunctionExecutor Input : (longitude double, latitude double, geoJSONGeometryFence string, distance double) OR (geoJSONGeometry string, geoJSONGeometryFence string, distance double) Output : true if (longitude, latitude) or geoJSONGeometry is within distance of the geoJSONGeometryFence StreamProcessors 1. GeoCrossesStreamProcessor Input : (id string, longitude double, latitude double, geoJSONGeometryFence string) OR (id string, geoJSONGeometry string, geoJSONGeometryFence string) Output : an event with `crosses` additional attribute set to true when the object ((longitude, latitude) or geoJSONGeometry) crosses into geoJSONGeometryFence and an event with `crosses` additional attribute set to false when the object crosses out of the geoJSONGeometryFence 2. GeoStationaryStreamProcessor Input : (id string, longitude double, latitude double, geoJSONGeometryFence string, radius double) OR (id string, geoJSONGeometry string, geoJSONGeometryFence string, radius double) Output : when the object ((longitude, latitude) or geoJSONGeometry) starts being stationary within the radius an event with `stationary` additional attribute set to true. When the object starts to move out of the radius an event with `stationary` additional attribute set to false. 3. GeoProximityStreamProcessor Input : (id string, longitude double, latitude double, geoJSONGeometryFence string, radius double) OR (id string, geoJSONGeometry string, geoJSONGeometryFence string, radius double) Output : when two objects ((longitude, latitude) or geoJSONGeometry) starts being in close proximity within the radius an event with `inCloseProximity` additional attribute set to true. When the object starts to move out of the radius an event with `inCloseProximity` additional. attribute set to false. On each event, additional attributes `proximityWith` gives the id of the object that this object is in close proximity and `proximityId` is an id unique to the pair of objects

We propose two efficient algorithms for exploring topic diversity in large document corpora such as user generated content on the social web, bibliographic data, or other web repositories. Analyzing diversity is useful for obtaining insights into knowledge evolution, trends, periodicities, and topic heterogeneity of such collections. Calculating diversity statistics requires averaging over the similarity of all object pairs, which, for large corpora, is prohibitive from a computational point of view. Our proposed algorithms overcome the quadratic complexity of the average pair-wise similarity computation, and allow for constant time (depending on dataset properties) or linear time approximation with probabilistic guarantees.

This is an open source library that allows generating performance indicators easily for java based application. This library is configurable through an xml file (similar to log4j) in order to define the performance object types, dimensions, counters, the output format and statistics generation periodicity. Those statistics can be saved as a file (xml/json) or injected directly in a database. Then they can be correlated and analyzed through any Business Intelligence solution in order to check the application performance and quality: number of transactions, ratio of successful and failure ...

POJava DateTime is a simple, light-weight Java-based API for parsing and manipulating dates. It parses dates from most languages and formats out of the box without having to specify which format is expected. Defaults such as time zones, and whether to interpret an internationally ambiguous date like "03/06/2014" as DMY order or MDY order are inferred by system time zone and locale and stored in a default config object that can be replaced or overridden. Multiple languages for month names are supported without any additional configuration needed.

eFaps is a framework used to map objects with or without attached files to a relational database and optional file systems (only for attaches files). Configurable access control can be provided down to object and attribute level depending on implementation and use case. Depending on requirements, events (like triggers) allow to implement business logic and to separate business logic from user interface. The framework includes integrations (e.g. webdav, full text search) and a web application as 'simple' configurable user interface. Some best practises, example web application modules (e.g. team work module) support administrators and implementers using this framework.

JavaCL is an Object-Oriented API that makes the C OpenCL API available to Java in a very natural way. It hides away the complexity of cross-platform C bindings, has a clean OO design (with generics, Java enums, NIO buffers, fully typed exceptions...), provides high-level features (OpenGL-interop, array reductions) and comes with samples and demos. For more info, please visit http://code.google.com/p/nativelibs4java/wiki/OpenCL.

JavaCL is an Object-Oriented API that makes the C OpenCL API available to Java in a very natural way. It hides away the complexity of cross-platform C bindings, has a clean OO design (with generics, Java enums, NIO buffers, fully typed exceptions...), provides high-level features (OpenGL-interop, array reductions) and comes with samples and demos. For more info, please visit http://code.google.com/p/nativelibs4java/wiki/OpenCL.