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The SAP Java Connector (SAP JCo) is a toolkit that allows a Java application to communicate with any SAP system. It combines an easy to use API with unprecedented flexibility and performance. The package supports both, Java to SAP System as well as SAP System to Java calls. - All SAP Connectors are licensed without additional license fees as part of the respective solution or component license. However, please note that each connector may be used only for connecting external (non-SAP) applications to SAP Systems / SAP Solutions. Scenarios, in which two external (non-SAP) applications are integrated via an SAP Connector, are not allowed. - The redistribution of any connector is not allowed. - All SAP users accessing application functionality through the relevant connector are required to be licensed under a respective solution or component license. To use the SAP JCo with the Hibersap project, you need to either install the SAP JCo jar downloaded from SAP to your local Maven repository (variant a) or deploy it to e.g. an enterprise Maven repository like Nexus or Artifactory (variant b): (a) mvn install:install-file -DgroupId=org.hibersap -DartifactId=sapjco3 -Dversion=3.0.12 -Dpackaging=jar -Dfile=path/to/sapjco3.jar (b) mvn deploy:deploy-file -DrepositoryId=[your.repo.id] -DgroupId=org.hibersap -DartifactId=sapjco3 -Dversion=3.0.12 -Dpackaging=jar -Dfile=sapjco3.jar

The SAP Java Connector (SAP JCo) is a toolkit that allows a Java application to communicate with any SAP system. It combines an easy to use API with unprecedented flexibility and performance. The package supports both, Java to SAP System as well as SAP System to Java calls. - All SAP Connectors are licensed without additional license fees as part of the respective solution or component license. However, please note that each connector may be used only for connecting external (non-SAP) applications to SAP Systems / SAP Solutions. Scenarios, in which two external (non-SAP) applications are integrated via an SAP Connector, are not allowed. - The redistribution of any connector is not allowed. - All SAP users accessing application functionality through the relevant connector are required to be licensed under a respective solution or component license. To use the SAP JCo with the Hibersap project, you need to either install the SAP JCo jar downloaded from SAP to your local Maven repository (variant a) or deploy it to e.g. an enterprise Maven repository like Nexus or Artifactory (variant b): (a) mvn install:install-file -DgroupId=org.hibersap -DartifactId=sapjco3 -Dversion=3.0 -Dpackaging=jar -Dfile=path/to/sapjco3.jar (b) mvn deploy:deploy-file -DrepositoryId=[your.repo.id] -DgroupId=org.hibersap -DartifactId=sapjco3 -Dversion=3.0 -Dpackaging=jar -Dfile=sapjco3.jar

The IntelligentGraph SAIL offers an extended capability for embedded calculation support within any RDF graph. When enabled as an RDF4J SAIL, it offers calculation functionality as part of the RDF4J engine, on top of any RDF4J repository, using a variety of script engines including JavaScript, Jython, and Groovy. It preserves the SPARQL capability of RDF4J, but with additional capabilities for calculation debugging and tracing. IntelligentGraph includes the PathQL query language. Just as a spreadsheet cell calculation needs to access other cells, an IntelligentGraph calculation needs to access other nodes within the graph. Although full access to the underlying graph is available to any of the scripts, PathQL provides a succinct, and efficient method to access directly or indirectly related nodes. PathQL can either return just the contents of the referenced nodes, or the contents and the path to the referenced nodes. PathQL can also be used standalone to query the IntelligentGraph-enabled RDF database. This supplements, rather than replaces, SPARQL and GraphQL, as it provides graph-path querying rather than graph-pattern querying capabilities to any IntelligentGraph-enabled RDF database. The principles of IntelligentGraph are described here: https://inova8.com/bg_inova8.com/intelligent-graph-knowledge-graph-embedded-analysis/ The full PathQL syntax is described here: https://inova8.com/bg_inova8.com/pathpatternql-intelligently-finding-knowledge-as-a-path-through-a-maze-of-facts/ Using Jupyter as an IDE to IntelligentGraph and RDF4J, shown here: https://inova8.com/bg_inova8.com/intelligentgraph-getting-started/ IntelligentGraph source is here in GitHub: https://github.com/peterjohnlawrence/com.inova8.intelligentgraph IntelligentGraph Docker containers are available here: https://hub.docker.com/repository/docker/inova8/intelligentgraph

This is an implementation of the Neural Gas algorithm on distance data (Relational Neural Gas) for unsupervised clustering. We recommend that you use the functions provided by the RelationalNeuralGas class for your purposes. All other classes and functions are utilities which are used by this central class. In particular, you can use RelationalNeuralGas.train() to obtain a RNGModel (i.e. a clustering of your data), and subsequently you can use RelationalNeuralGas.getAssignments() to obtain the resulting cluster assignments, and RelationalNeuralGas.classify() to cluster new points which are not part of the training data set. The underlying scientific work is summarized nicely in the dissertation "Topographic Mapping of Dissimilarity Datasets" by Alexander Hasenfuss (2009). The basic properties of an Relational Neural Gas algorithm are the following: 1.) It is relational: The data is represented only in terms of a pairwise distance matrix. 2.) It is a clustering method: The algorithm provides a clustering model, that is: After calculation, each data point should be assigned to a cluster (for this package here we only consider hard clustering, that is: each data point is assigned to exactly one cluster). 3.) It is a vector quantization method: Each cluster corresponds to a prototype, which is in the center of the cluster and data points are assigned to the cluster if and only if they are closest to this particular prototype. 4.) It is rank-based: The updates of the prototypes depend only on the distance ranking, not on the absolute value of the distances.

IronPDF Java library offers an extensive compatibility range, making it a go-to solution for a wide array of developers. It fully supports JVM languages like Java, Scala, and Kotlin, making it incredibly versatile. This Java PDF library is also compatible with Java 8 and above, providing optimum performance across multiple platforms. It's been designed with a wide range of users in mind Here's a look at what it supports: JVM Languages: Java, Scala, Kotlin.Platforms: Java 8 and above.Operating Systems: Microsoft Windows, Linux, Docker, Azure, AWS.IDEs: Jetbrains IntelliJ IDEA, Eclipse. You can deploy IronPDF Java across various platforms, including Microsoft Windows, Linux, Docker, Azure, and AWS. It is also fully compatible with popular IDEs like Jetbrains IntelliJ IDEA and Eclipse, facilitating smooth project development and management. Your pom.xml file is essentially the backbone of your project when you're using Maven. It's here where you introduce new dependencies that you wish to include. To make IronPDF Java package a part of your Maven project, you simply need to add the following snippets to your pom.xml: Remember to replace '20xx.xx.xxxx' with the latest version of IronPDF. IronPDF Java simplifies the process of creating PDF files. Convert HTML files, HTML strings, or URLs directly to new PDF documents in a few lines of code. The variety of file formats it handles is vast, as it can even transform images into PDF documents and vice versa. Need to use base 64 encoding, base URLs, or custom file paths? No problem! IronPDF Java has got you coveredFor more detail about installing and using IronPDF Java. When you run your project for the first time post-integration, IronPDF's engine binaries will automatically be downloaded. The engine starts its journey when you call any IronPDF function for the first time and takes a breather when your application is either closed or enters an idle state. It is not an open source java PDF library but here's the best part - IronPDF Java is offering a 30-day free trial. So, why wait? Give it a go and boost your PDF operations today.

Jsgen is a Java Source Generation Framework: That means, it should be a valuable tool, if you intend to write a custom generator for Java sources. As such, it is the successor of a previous framework, called JaxMeJS (http://jaxme.sourceforge.net/JaxMeJS/docs/index.html). The predecessor came into being as a standalone project. It was incorporated into the bigger JaxMe project, when the latter was adopted by the Apache Webservices project. And it was buried as part of the bigger project, when the latter was moved to the Apache Attic (http://svn.apache.org/repos/asf/webservices/archive/jaxme/). That was fine for quite some time, because the latest released version (JaxMeJS 0.5.2) did its job quite well. Over the years, however, the Java language has evolved, and the lack of support for features like Generics, or Annotations, became a burden. Hence the Successor: Jsgen picks up, where JaxMeJS ended. It is, however, a complete rewrite with several additional features, that the author considers to be important for modern Java applications: 1. It supports Generics. 2. It supports Annotations. 3. The builder pattern has been adopted. Almost all important classes are implemented as builders. This should make writing the actual source generators much more concise, and maintainable, than it used to be before. 4. The code style is configurable. Code styles allow you to concentrate on the actual work. The resulting Jave source will look nicely formatted, anyways. As of this writing, you can select between two builtin code styles: - The default code style is basically the authors personal free style, roughly comparable to the default code style of the Eclipse Java IDE. - As an alternative, there is also a Maven code style, which is widely used in the Open Source communities. Compared to the default style, it is less concise, if not even a bit verbose. On the other hand, it is widely adopted by projects in the vicinity of {{{https://maven.apache.org}Apache Maven}}. 5. Import lists are created, and sorted, automatically.

This is the main aggregator for all gwt submodules. All gwt-specific code resides here. Submodules should avoid inheriting from each other unless necessary. This goes for maven structure and gwt.xml structure. The super module is where our jre emulation layer and super-source live; all modules should inherit super, and a minimum of other modules. Some modules, like injection, are fulfilling an api in the core module, and should be accessed only through core service interfaces. Other modules, like reflection, are capable of being standalone inherits, but can benefit from core utilities like injection, so, two (or more) .gwt.xml modules may be provided. As XApi nears 1.0, all submodules will be routinely stitched together into an uber-jar, in order to have a single jar with a single gwt module that can provide all of the services at once. Internal projects will never use the uber jar, to help maintain modularity, but external projects that want to use more than one service will certainly prefer inheriting one artifact, instead of twelve. When distributed in uber-jar format, it will likely be necessary for either the uber jar, or just xapi-gwt-api.jar to appear before gwt-dev on your compile-time classpath. If using gwt-maven-plugin, the gwtFirstOnClasspath option may become problematic. If so, we will provide a forked gwt-plugin to make sure our compiler enhancements are included in the build process. There is also work going on to make a super-source-everything plugin, which will use maven to find source files, and generate synthetic .gwt.xml for you, as part of an effort to create a wholly unified programming environment. In addition to java-to-javascript, we intend to compile java-to-java and possibly other languages, like go; imagine implementing gwt deferred binding to eliminate cross-platform differences between server environments, or operating systems, or versions of a platform, or anywhere else a core api needs to bind to multiple implementations, depending on the runtime environment.