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Lossless data compression algorithms can use statistical redundancy to represent data using a fewer number of bits in comparison to the original uncompressed data. Run-Length Encoding is one of the simplest lossless compression algorithms in terms of understanding its principles and software implementation, as well as in terms of temporal and spatial complexity. If this principle is applied to individual bits of original uncompressed data without respecting the byte boundaries, this approach is referred to as bit-level Run-Length Encoding. Algorithm for lossless data compression, proposed in this paper, optimizes bit-level Run-Length Encoding data compression, uses special encoding of repeating data blocks, and, if necessary, combines it with delta data transformation or representation of data in its original form intending to increase compression efficiency compared to a conventional bit-level Run-Length Encoding approach. The advantage of the algorithm proposed in this paper is in the increase of the compression ratio in comparison to the bit-level Run-Length Encoding, with the higher time and space consumption as the trade-off. Test results, that were obtained by compression of the segmentation metadata of different volume datasets take place in the last part of the paper. [ABSTRACT FROM AUTHOR]

The syntactic primitives and the description language can be used for assignment and analysis of vehicles movement. The paper introduces a method that allows spotting vehicles' manoeuvres on and between traffic lanes, observing images, registered by a video camera. The analysis algorithms of the vehicles' movement trajectories were considered in this paper as well. [ABSTRACT FROM AUTHOR]

Fuzzy logic controller is one of the most prominent research fields to improve efficiency for process industries, which usually stick to the conventional proportional-integral-derivative (PID) control. The paper proposes an improved version of the threeterm PID-like fuzzy logic controller by removing the necessity of having user-defined parameters in place for the algorithm to work. The resulting non-parametric three-term dissimilarity-based clustering fuzzy logic controller algorithm was shown to be very efficient and fast. The performance study was conducted by simulation on armaturecontrolled and field-controller DC motors, for linguistic type and Takagi-Sugeno-Kang (TSK) models. Comparison of the created algorithm with fuzzy c-means algorithm resulted in improved accuracy, increased speed and enhanced robustness, with an especially high increase for the TSK type model. [ABSTRACT FROM AUTHOR]