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The Java Advanced Imaging API extends the Java 2 platform by allowing sophisticated, high-performance image processing to be incorporated into Java applets and applications. It is a set of classes providing imaging functionality beyond that of Java 2D and the Java Foundation classes, though it is designed for compatibility with those APIs. This API implements a set of core image processing capabilities including image tiling, regions of interest, deferred execution and a set of core image processing operators, including many common point, area, and frequency domain operators.

The ONNX Runtime Mobile package is a size optimized inference library for executing ONNX (Open Neural Network Exchange) models on Android. This package is built from the open source inference engine but with reduced disk footprint targeting mobile platforms. To minimize binary size this library supports a reduced set of operators and types aligned to typical mobile applications. The ONNX model must be converted to ORT format in order to use it with this package. See https://onnxruntime.ai/docs/reference/ort-format-models.html for more details.

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.