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Feature selection method based on correlation measureand relevance and redundancy analysis. Use in conjunction with an attribute set evaluator (SymmetricalUncertAttributeEval). For more information see: Lei Yu, Huan Liu: Feature Selection for High-Dimensional Data: A Fast Correlation-Based Filter Solution. In: Proceedings of the Twentieth International Conference on Machine Learning, 856-863, 2003.

Extracting command line options directly into data members: each field marked with an @External annotation automatically becomes a command line option. Extracting the options values from the command line arguments, i.e., the "String[] args" parameter to main, into the field(s), requires a single method invocation: Introspector.extract(args, o1, o2, ...) where o1,o2, ... are the objects in which the fields annotated with @External.

Sometimes we sacrifice encapsulation just to let us access a method or field of an object from its unit tests. This framework uses reflection and dynamic proxies to access private portion of your objects, allowing you to keep them strongly encapsulated and still be able to test their internals using the provided accessors.

Avalon Excalibur's DataSource package allows you to manage pooled connections in one of two ways. You can have the package handle it for you, or you can use a J2EE server's DataSource management. It provides the same kind of access regardless of which method you choose, since they are obtained through Avalon's Component Manager infrastructure. The DataSource package requires that you load the necessary driver classes at init time, but it will take care of all necessary issues from there.

Avalon Excalibur's DataSource package allows you to manage pooled connections in one of two ways. You can have the package handle it for you, or you can use a J2EE server's DataSource management. It provides the same kind of access regardless of which method you choose--since they are obtained through Avalon's Component Manager infrastructure. The DataSource package requires that you load the necessary driver classes at init time, but it will take care of all necessary issues from there.

The standardization of KHQR code specifications will help promote wider use of mobile retail payments in Cambodia and provide consistent user experience for merchants and consumers. It can enable interoperability in the payment industry. A common QR code would facilitate payments among different schemes, e-wallets and banks and would encourage small merchants to adopt KHQR code as payment method. KHQR is created for retail or remittance in Cambodia and Cross-Border. It only requires a single QR for receiving transactions from any payment provider through Bakong including Bakong App.

Geordi Test Framework is a Kotlin-based testing framework integrating with JUnit 5's TestTemplate for dynamic and parameterized testing. It supports file-based and parameter-based scenarios, suitable for various testing contexts. Key features include dynamic test case generation, SimulationGroup for scenario organization, and integration with JUnit 5's advanced features. It also includes a utility class, UnitSim, for method-level testing and mocking with Mockk. Geordi is inspired by the Spock framework, aiming to provide comparable functionality in a Kotlin-optimized package.

The app library component of SDL is meant to run on the end user’s smart-device from within SDL enabled apps, as an embedded app, or connected to the cloud. App libraries allow the apps to connect to SDL enabled head-units and hardware through bluetooth, USB, and TCP for Android, and cloud and embedded apps can connect through web sockets, Java Beans, and other custom transports. Once the library establishes a connection between the smart device and head-unit through the preferred method of transport, the two components are able to communicate using the SDL defined protocol. The app integrating this library project is then able to expose its functionality to the head-unit through text, media, and other interactive elements.

The app library component of SDL is meant to run on the end user’s smart-device from within SDL enabled apps, as an embedded app, or connected to the cloud. App libraries allow the apps to connect to SDL enabled head-units and hardware through bluetooth, USB, and TCP for Android, and cloud and embedded apps can connect through web sockets, Java Beans, and other custom transports. Once the library establishes a connection between the smart device and head-unit through the preferred method of transport, the two components are able to communicate using the SDL defined protocol. The app integrating this library project is then able to expose its functionality to the head-unit through text, media, and other interactive elements.

The app library component of SDL is meant to run on the end user’s smart-device from within SDL enabled apps, as an embedded app, or connected to the cloud. App libraries allow the apps to connect to SDL enabled head-units and hardware through bluetooth, USB, and TCP for Android, and cloud and embedded apps can connect through web sockets, Java Beans, and other custom transports. Once the library establishes a connection between the smart device and head-unit through the preferred method of transport, the two components are able to communicate using the SDL defined protocol. The app integrating this library project is then able to expose its functionality to the head-unit through text, media, and other interactive elements.