We describe a solution for fast indexing and searching within large heterogeneous data sets whose main purpose is to support investigators that need to analyze forensic disk images originated by seizures or created from bodies of evidence. Our approach is based on a combination of techniques aimed at improving efficiency and reliability of the indexing process.We do not rely on existing frameworks like Hadoop but borrow concepts from different contexts including High Performance Computing and Database management.

Deterioration of stones is a complex problem and one of the main concern for people working in the field of conservation and restoration of cultural heritage. One important point in cultural heritage is to obtain information about the damage in a non-invasive way. By this paper, we propose a new non-invasive tool that permits evaluation of the thickness of (Formula presented.) (gypsum) grown (sulfation) on marble stones, using a mathematical model on data detected by pulsed infrared thermography.

. A guideline for an effective and efficient use of a deterministic variant of the Particle Swarm Optimization (PSO) algorithm is presented and discussed, assuming limited computational resources. PSO was introduced in Kennedy and Eberhart (1995) and successfully applied in many fields of engineering optimization for its ease of use. Its performance depends on three main characteristics: the number of swarm particles used, their initialization in terms of initial location and speed, and the set of coefficients defining the behavior of the swarm.