This paper addresses the problem of speeding up string matching by text compression, and presents a compressed pattern matching (CPM) algorithm which finds a pattern within a text given as a collage system 〈D,S〉 such that variable sequence S is encoded by byte-oriented Huffman coding. The compression ratio is high compared with existing CPM algorithms addressing the problem, and the search time...

This paper presents new fixed-rate texture compression systems for RGB and RGBA images, which use variable precision differential encoding for the color codewords, resulting in reduced compression artifacts, in particular for smooth color variations. Experiments using hundreds of textures show that they achieve higher quality than the commonly used S3TC at the same compression ratio or (for RGB...

We investigate the motion of a colloidal particle driven out of equilibrium by a time-varying stiffness of the optical trap that produces persistent nonequilibrium work. Measurements of work production for repeated cycles composed of the compression and expansion processes for the optical potential show huge fluctuations due to thermal motion. Using a precise technique to modulate the stiffness...

In all System-on-a-Chip (SoC) designs, there is a necessity to reduce the large test data volume and this is achieved by test data compression. One of the methods is the variable-to-variable length compression method. A selective run-length based compression which comes under variable-to-variable method is presented in this paper. The proposed work is based on threshold calculation on don’t car...

Abnormal combustion occurrences in compression ignition engines are one of the main causes of engine failures, which severely affect the continuity of transportation operations. The detection of these occurrences may help to take measures to minimize the engine failures and increase engine life. In this work, we implement a machine learning system for abnormal combustion detection system in a s...

The main objective of the research is to compare the accurateness of Artificial Neural Networks (ANN) and Multiple Linear Regressions (MLR) model for Specific Fuel Consumption for pyrolysis oil blended with diesel used in a single cylinder diesel engine. In this study, parameters i. e. Injection Timing, Injection Pressure, Compression Ratio, and Load are taken. Artificial Neural Networks (ANN) ...