Download JAR files tagged by functions with all dependencies

Xypron Statistics is a Java library which was developped with supply chain simulation in mind. The normal, the exponential and the gamma distribution have been included. Methods to calculate fill rate and order rate service levels as well as safety factors are provided. The Mersenne Twister algorithm is used to provide high quality random number generation. Some functions for the gamma distribution where adopted from http://www.ssfnet.org/download/ssfnet_raceway-2.0.tar.gz. For these the following applies: Copyright 1999 CERN - European Organization for Nuclear Research. Permission to use, copy, modify, distribute and sell this software and its documentation for any purpose is hereby granted without fee, provided that the above copyright notice appear in all copies and that both that copyright notice and this permission notice appear in supporting documentation. CERN makes no representations about the suitability of this software for any purpose. It is provided "as is" without expressed or implied warranty.

Sirix is a versioned, treebased storage system. It provides an ID-less diff-algorithm to import differences between two versions. Furthermore an ID-based diff-algorithm facilitates the comparison of versions stored within Sirix. A GUI with several visualizations for comparing these versions visually is available to aid an analyst. Versions are stored using well known versioning strategies (full, incremental, differential). The architecture is especially well suited for flash-disks because of a COW-principle. In the future we aim to provide throughout security as well as a replaced page-structure to speedup our architecture. A brackit(.org) binding will enable XQuery and the XQuery Update Facility. Temporal XPath axis and possibly diff-functions will help analysts to gain quick knowledge from the stored data.

Sirix is a versioned, treebased storage system. It provides an ID-less diff-algorithm to import differences between two versions (currently XML-documents). Furthermore an ID-based diff-algorithm facilitates the comparison of versions stored within Sirix. A GUI with several visualizations for comparing these versions visually is available to aid an analyst. Versions are stored using well known versioning strategies (full, incremental, differential). The architecture is especially well suited for flash-disks because of a COW-principle. In the future we aim to provide throughout security as well as a replaced page-structure to speedup our architecture. A brackit(.org) binding will enable XQuery and the XQuery Update Facility. Temporal XPath axis and possibly diff-functions will help analysts to gain quick knowledge from the stored data.

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.

This package currently contains classes for training multilayer perceptrons with one hidden layer, where the number of hidden units is user specified. MLPClassifier can be used for classification problems and MLPRegressor is the corresponding class for numeric prediction tasks. The former has as many output units as there are classes, the latter only one output unit. Both minimise a penalised squared error with a quadratic penalty on the (non-bias) weights, i.e., they implement "weight decay", where this penalised error is averaged over all training instances. The size of the penalty can be determined by the user by modifying the "ridge" parameter to control overfitting. The sum of squared weights is multiplied by this parameter before added to the squared error. Both classes use BFGS optimisation by default to find parameters that correspond to a local minimum of the error function. but optionally conjugated gradient descent is available, which can be faster for problems with many parameters. Logistic functions are used as the activation functions for all units apart from the output unit in MLPRegressor, which employs the identity function. Input attributes are standardised to zero mean and unit variance. MLPRegressor also rescales the target attribute (i.e., "class") using standardisation. All network parameters are initialised with small normally distributed random values.

The Video SDKs are app development kits provided to enrich apps with video collaboration features to connect customers and communities. Use these SDKs to build apps with highly customized user interfaces along with access to raw video and audio data. Video SDKs are designed to be: * Easy to use: Import libraries, call required functions, and all video conferencing will be handled for you. * Lightweight: Video SDKs are streamlined toolkits with an enormous reduction in size compared to Meeting SDKs with all the power of Zoom's video and audio solutions. * Highly customizable: Raw video and audio data is available to you, allowing your chosen renderer to customize the video experience. Video sessions created by the Video SDKs are launched instantly, bringing a delightful video communication experience to your users with high-quality video and audio. Direct access to raw video and audio data allows improved interaction between users and the app video stream. Imagine a gaming video streaming app with direct interaction between the player and viewers based on in-game events or prompts from the community. Or, imagine an AR streaming platform with direct viewer access to the on-screen video. As with our Meeting SDKs, Video SDKs allow screen-sharing from devices, in-session chat messages, and high-quality video and audio streams similar to Zoom's core capabilities. The Video SDKs enable the following functionality in your app: * Launch a video communication session instantly * Share screen directly from your device * Send instant chat messages during the session * Capture and review raw data locally * Test different rendering schema and enjoy high-quality video and audio streams * Broadcast the video session to third-party live streaming providers To know more, see: https://developers.zoom.us/docs/video-sdk/

The Video SDKs are app development kits provided to enrich apps with video collaboration features to connect customers and communities. Use these SDKs to build apps with highly customized user interfaces along with access to raw video and audio data. Video SDKs are designed to be: * Easy to use: Import libraries, call required functions, and all video conferencing will be handled for you. * Lightweight: Video SDKs are streamlined toolkits with an enormous reduction in size compared to Meeting SDKs with all the power of Zoom's video and audio solutions. * Highly customizable: Raw video and audio data is available to you, allowing your chosen renderer to customize the video experience. Video sessions created by the Video SDKs are launched instantly, bringing a delightful video communication experience to your users with high-quality video and audio. Direct access to raw video and audio data allows improved interaction between users and the app video stream. Imagine a gaming video streaming app with direct interaction between the player and viewers based on in-game events or prompts from the community. Or, imagine an AR streaming platform with direct viewer access to the on-screen video. As with our Meeting SDKs, Video SDKs allow screen-sharing from devices, in-session chat messages, and high-quality video and audio streams similar to Zoom's core capabilities. The Video SDKs enable the following functionality in your app: * Launch a video communication session instantly * Share screen directly from your device * Send instant chat messages during the session * Capture and review raw data locally * Test different rendering schema and enjoy high-quality video and audio streams * Broadcast the video session to third-party live streaming providers To know more, see: https://developers.zoom.us/docs/video-sdk/

The Video SDKs are app development kits provided to enrich apps with video collaboration features to connect customers and communities. Use these SDKs to build apps with highly customized user interfaces along with access to raw video and audio data. Video SDKs are designed to be: * Easy to use: Import libraries, call required functions, and all video conferencing will be handled for you. * Lightweight: Video SDKs are streamlined toolkits with an enormous reduction in size compared to Meeting SDKs with all the power of Zoom's video and audio solutions. * Highly customizable: Raw video and audio data is available to you, allowing your chosen renderer to customize the video experience. Video sessions created by the Video SDKs are launched instantly, bringing a delightful video communication experience to your users with high-quality video and audio. Direct access to raw video and audio data allows improved interaction between users and the app video stream. Imagine a gaming video streaming app with direct interaction between the player and viewers based on in-game events or prompts from the community. Or, imagine an AR streaming platform with direct viewer access to the on-screen video. As with our Meeting SDKs, Video SDKs allow screen-sharing from devices, in-session chat messages, and high-quality video and audio streams similar to Zoom's core capabilities. The Video SDKs enable the following functionality in your app: * Launch a video communication session instantly * Share screen directly from your device * Send instant chat messages during the session * Capture and review raw data locally * Test different rendering schema and enjoy high-quality video and audio streams * Broadcast the video session to third-party live streaming providers To know more, see: https://developers.zoom.us/docs/video-sdk/

We have deprecated ZoomVideoSDK maven repository. Since Video SDK features have been modularized, we are deprecating this repository and publishing new releases into the following repositories. See the feature libraries documentation for details. ZoomVideoSDK Core — core Video SDK features: https://mvnrepository.com/artifact/us.zoom.videosdk/zoomvideosdk-core ZoomVideoSDK Annotation — Screen share annotation feature: https://mvnrepository.com/artifact/us.zoom.videosdk/zoomvideosdk-annotation ZoomVideoSDK Videoeffects — Virtual background feature: https://mvnrepository.com/artifact/us.zoom.videosdk/zoomvideosdk-videoeffects The Video SDKs are app development kits provided to enrich apps with video collaboration features to connect customers and communities. Use these SDKs to build apps with highly customized user interfaces along with access to raw video and audio data. Video SDKs are designed to be: * Easy to use: Import libraries, call required functions, and all video conferencing will be handled for you. * Lightweight: Video SDKs are streamlined toolkits with an enormous reduction in size compared to Meeting SDKs with all the power of Zoom's video and audio solutions. * Highly customizable: Raw video and audio data is available to you, allowing your chosen renderer to customize the video experience. Video sessions created by the Video SDKs are launched instantly, bringing a delightful video communication experience to your users with high-quality video and audio. Direct access to raw video and audio data allows improved interaction between users and the app video stream. Imagine a gaming video streaming app with direct interaction between the player and viewers based on in-game events or prompts from the community. Or, imagine an AR streaming platform with direct viewer access to the on-screen video. As with our Meeting SDKs, Video SDKs allow screen-sharing from devices, in-session chat messages, and high-quality video and audio streams similar to Zoom's core capabilities. The Video SDKs enable the following functionality in your app: * Launch a video communication session instantly * Share screen directly from your device * Send instant chat messages during the session * Capture and review raw data locally * Test different rendering schema and enjoy high-quality video and audio streams * Broadcast the video session to third-party live streaming providers To know more, see: https://developers.zoom.us/docs/video-sdk/

Apache Commons Crypto is a cryptographic library optimized with AES-NI (Advanced Encryption Standard New Instructions). It provides Java API for both cipher level and Java stream level. Developers can use it to implement high performance AES encryption/decryption with the minimum code and effort. Please note that Crypto doesn't implement the cryptographic algorithm such as AES directly. It wraps to Openssl or JCE which implement the algorithms. Features -------- 1. Cipher API for low level cryptographic operations. 2. Java stream API (CryptoInputStream/CryptoOutputStream) for high level stream encyrption/decryption. 3. Both optimized with high performance AES encryption/decryption. (1400 MB/s - 1700 MB/s throughput in modern Xeon processors). 4. JNI-based implementation to achieve comparable performance to the native C++ version based on OpenSsl. 5. Portable across various operating systems (currently only Linux/MacOSX/Windows); Apache Commons Crypto loads the library according to your machine environment (it checks system properties, `os.name` and `os.arch`). 6. Simple usage. Add the commons-crypto-(version).jar file to your classpath. Export restrictions ------------------- This distribution includes cryptographic software. The country in which you currently reside may have restrictions on the import, possession, use, and/or re-export to another country, of encryption software. BEFORE using any encryption software, please check your country's laws, regulations and policies concerning the import, possession, or use, and re-export of encryption software, to see if this is permitted. See <http://www.wassenaar.org/> for more information. The U.S. Government Department of Commerce, Bureau of Industry and Security (BIS), has classified this software as Export Commodity Control Number (ECCN) 5D002.C.1, which includes information security software using or performing cryptographic functions with asymmetric algorithms. The form and manner of this Apache Software Foundation distribution makes it eligible for export under the License Exception ENC Technology Software Unrestricted (TSU) exception (see the BIS Export Administration Regulations, Section 740.13) for both object code and source code. The following provides more details on the included cryptographic software: * Commons Crypto use [Java Cryptography Extension](http://docs.oracle.com/javase/8/docs/technotes/guides/security/crypto/CryptoSpec.html) provided by Java * Commons Crypto link to and use [OpenSSL](https://www.openssl.org/) ciphers