Green criminology and dirty collar crime

As a contribution to literature drawing together green criminology and studies of organised and corporate crime, this paper provides a case study of crimes and public health harms linked to the Naples garbage disposal crisis. The context is the inability of modern consumer society to cope with the problem of mass production of waste. In turn this leads to opportunities for both legal and criminal entrepreneurs to offer services that promise but fail to ‘dispose’ of the problem. The analysis draws upon environmental law and classic studies of organised crime.

Correlation-based damage detection for complicated truss bridges using multi-layer genetic algorithms

The study presents a multi-layer genetic algorithm (GA) approach using correlation-based methods to facilitate damage determination for through-truss bridge structures. To begin, the structure’s damage-suspicious elements are divided into several groups. In the first GA layer, the damage is initially optimised for all groups using correlation objective function. In the second layer, the groups are combined to larger groups and the optimisation starts over at the normalised point of the first layer result. Then the identification process repeats until reaching the final layer where one group includes all structural elements and only minor optimisations are required to fine tune the final result. Several damage scenarios on a complicated through-truss bridge example are nominated to address the proposed approach’s effectiveness. Structural modal strain energy has been employed as the variable vector in the correlation function for damage determination. Simulations and comparison with the traditional single-layer optimisation shows that the proposed approach is efficient and feasible for complicated truss bridge structures when the measurement noise is taken into account.