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libjpeg-turbo is a JPEG image codec that uses SIMD instructions (MMX, SSE2, AVX2, Neon, AltiVec) to accelerate baseline JPEG compression and decompression on x86, x86-64, Arm, and PowerPC systems, as well as progressive JPEG compression on x86, x86-64, and Arm systems. On such systems, libjpeg-turbo is generally 2-6x as fast as libjpeg, all else being equal. On other types of systems, libjpeg-turbo can still outperform libjpeg by a significant amount, by virtue of its highly-optimized Huffman coding routines. In many cases, the performance of libjpeg-turbo rivals that of proprietary high-speed JPEG codecs.

libjpeg-turbo is a JPEG image codec that uses SIMD instructions (MMX, SSE2, AVX2, Neon, AltiVec) to accelerate baseline JPEG compression and decompression on x86, x86-64, Arm, and PowerPC systems, as well as progressive JPEG compression on x86, x86-64, and Arm systems. On such systems, libjpeg-turbo is generally 2-6x as fast as libjpeg, all else being equal. On other types of systems, libjpeg-turbo can still outperform libjpeg by a significant amount, by virtue of its highly-optimized Huffman coding routines. In many cases, the performance of libjpeg-turbo rivals that of proprietary high-speed JPEG codecs.

libjpeg-turbo is a JPEG image codec that uses SIMD instructions (MMX, SSE2, AVX2, Neon, AltiVec) to accelerate baseline JPEG compression and decompression on x86, x86-64, Arm, and PowerPC systems, as well as progressive JPEG compression on x86, x86-64, and Arm systems. On such systems, libjpeg-turbo is generally 2-6x as fast as libjpeg, all else being equal. On other types of systems, libjpeg-turbo can still outperform libjpeg by a significant amount, by virtue of its highly-optimized Huffman coding routines. In many cases, the performance of libjpeg-turbo rivals that of proprietary high-speed JPEG codecs.

Nuun Kernel is a software kernel for framework creation. It brings a powerful plugin design plus a JSR 330 compliant injection mechanism backed by Guice. Plugin benefits from kernel capabilities by sending requests to it : - kernel params request : - Classpath scans request :on class by name, annotation, meta annotation or more generally Predicate - Binding Request : Nuun Kernel provides an SPI in order to bring IOC from other vendors. Nuun Kernel come with 2 plugins: - Configuration Plugin : a plugin that inject the good property based on @Property annotation. - Log plugin : a Log handler that inject the good Log implementation

The crypto4j library provides a simple and pluggable crypto abstraction library for Java, including both cryptographic primitives and the artifacts defined in the JOSE standard. This library separates the cryptographic primitives from the JOSE artifacts. The library uses the algorithms available through JCA (JCE). The implementations of the cryptographic primitives provided in this library rely on the standard JCA implementation, and can be configured and extended through the JCA mechanisms. The JOSE portion of the library allows custom extensions by either replacing the provided JOSE artifact implementations with custom implementations, or by adding new JOSE artifacts, for instance in form of additional algorithms, which is particularly useful in case that the JOSE standard is updated or in case custom extensions to the JOSE standard should be implemented. The implementations available in this library generally come in two variants: a standard implementation of the primitives and advanced algorithms, and a high-performance implementation that takes advantage of implementation patterns that do not compromise cryprographic security, but speed up the overall processing time.

Nuun Kernel is a software kernel for framework creation. It brings a powerful plugin design plus a JSR 330 compliant injection mechanism backed by Guice. Plugin benefits from kernel capabilities by sendings request to it : - kernel params request : - Classpath scans request :on class by name, annotation, meta annotation or more generally Predicate - Binding Request : Nuun Kernel provides an SPI in order to bring IOC from other vendors. Nuun Kernel come with 2 plugins: - Configuration Plugin : a plugin that inject the good property based on @Property annotation. - Log plugin : a Log handler that inject the good Log implementation

Nuun Kernel is a software kernel for framework creation. It brings a powerful plugin design plus a JSR 330 compliant injection mechanism backed by Guice. Plugin benefits from kernel capabilities by sendings request to it : - kernel params request : - Classpath scans request :on class by name, annotation, meta annotation or more generally Predicate - Binding Request : Nuun Kernel provides an SPI in order to bring IOC from other vendors. Nuun Kernel come with 2 plugins: - Configuration Plugin : a plugin that inject the good property based on @Property annotation. - Log plugin : a Log handler that inject the good Log implementation

This package contains a classifier that can be used to train a two-class kernel logistic regression model with the kernel functions that are available in WEKA. It optimises the negative log-likelihood with a quadratic penalty. Both, BFGS and conjugate gradient descent, are available as optimisation methods, but the former is normally faster. It is possible to use multiple threads, but the speed-up is generally very marginal when used with BFGS optimisation. With conjugate gradient descent optimisation, greater speed-ups can be achieved when using multiple threads. With the default kernel, the dot product kernel, this method produces results that are close to identical to those obtained using standard logistic regression in WEKA, provided a sufficiently large value for the parameter determining the size of the quadratic penalty is used in both cases.

JSONXML project is library used to parse/format tree-like object structures in most popular text formats: XML and JSON. For parsing it accepts "java.io.Reader" and return java object. For formatting it accepts java object and "java.io.Writer". Object is generally structure that contains Map and/or List elements. Map is ordered set of named items. List is set of unnamed items. Reflection may be used to convert objects into set of maps/lists and vice versa. JSON parser is implemented explicitly. XML parser is based on SAX parser and applies only certain rules for result. Library is designed to allow various entry points for variable decisions depending on end use needs. 1. Formats - formats are used to enable locale-specific parsing/formatting of numbers and dates. 2. ReflectiveBuilder - enables reflection. Default implementation uses getters/setters only. 3. ObjectsRegistry - used to keep track of parsed or formatted objects and allow resolvable references in formatted (text) form.

Chips-n-Salsa is a Java library of customizable, hybridizable, iterative, parallel, stochastic, and self-adaptive local search algorithms. The library includes implementations of several stochastic local search algorithms, including simulated annealing, hill climbers, as well as constructive search algorithms such as stochastic sampling. Chips-n-Salsa now also includes genetic algorithms as well as evolutionary algorithms more generally. The library very extensively supports simulated annealing. It includes several classes for representing solutions to a variety of optimization problems. For example, the library includes a BitVector class that implements vectors of bits, as well as classes for representing solutions to problems where we are searching for an optimal vector of integers or reals. For each of the built-in representations, the library provides the most common mutation operators for generating random neighbors of candidate solutions, as well as common crossover operators for use with evolutionary algorithms. Additionally, the library provides extensive support for permutation optimization problems, including implementations of many different mutation operators for permutations, and utilizing the efficiently implemented Permutation class of the JavaPermutationTools (JPT) library. Chips-n-Salsa is customizable, making extensive use of Java's generic types, enabling using the library to optimize other types of representations beyond what is provided in the library. It is hybridizable, providing support for integrating multiple forms of local search (e.g., using a hill climber on a solution generated by simulated annealing), creating hybrid mutation operators (e.g., local search using multiple mutation operators), as well as support for running more than one type of search for the same problem concurrently using multiple threads as a form of algorithm portfolio. Chips-n-Salsa is iterative, with support for multistart metaheuristics, including implementations of several restart schedules for varying the run lengths across the restarts. It also supports parallel execution of multiple instances of the same, or different, stochastic local search algorithms for an instance of a problem to accelerate the search process. The library supports self-adaptive search in a variety of ways, such as including implementations of adaptive annealing schedules for simulated annealing, such as the Modified Lam schedule, implementations of the simpler annealing schedules but which self-tune the initial temperature and other parameters, and restart schedules that adapt to run length.