This research deals with the development of an optimization system to minimize employee noise exposure in the work environment. It is known from the literature that continuous exposure to high noise levels can cause heart overload, stress, fatigue, and increase accident numbers at a production line. Thus, it is necessary to develop acoustic solutions at an industrial level that could minimize failures and accident occurrences. The rules that regulate occupational noise exposures allow an assessment of the degrees of exposure and subsequent corrections of working conditions. It is observed that the exposure is necessary for further evaluation and correction. Therefore, this research proposes to simulate occupational noise exposure conditions through mathematical models implemented in C++, using the GUROBI linear optimization package and to act previously to minimize ONIHL (Occupational Noise-Induced Hearing Loss). One of this work results is based on Doses Values, TWA (Time Weighted Average) and Distances Covered, using these three factors simultaneously through the optimization, it obtains a route that minimizes exposure and avoids ONIHL. Although there is a need for balanced doses between employees, to this end, the Designation Problem was implemented. Thus, with the routes obtained by optimization, an efficient allocation task was made for the maintenance crew, resulting in minimized and balanced doses. This model was applied to a real industrial plant that will not be identified, only methodology and results obtained will be presented.

An innovative system designed for the continuous monitoring of acoustic climate of urban areas was presented in the paper. The assessment of environmental threats is performed using online data, acquired through a grid of engineered monitoring stations collecting comprehensive information about the acoustic climate of urban areas. The grid of proposed devices provides valuable data for the purpose of long and short time acoustic climate analysis. Dynamic estimation of noise source parameters and real measurement results of emission data are utilized to create dynamic noise maps accessible to the general public. This operation is performed through the noise source prediction employing a propagation model being optimized for computer cluster implementation requirements. It enables the system to generate noise maps in a reasonable time and to publish regularly map updates in the Internet. Moreover, the functionality of the system was extended with new techniques for assessing noise-induced harmful effects on the human hearing system. The principle of operation of the dosimeter is based on a modified psychoacoustic model of hearing and on the results of research performed with participation of volunteers concerning the impact of noise on hearing. The primary function of the dosimeter is to estimate, in real time, auditory effects which are caused by exposure to noise. The results of measurements and simulations performed by the system prototype are depicted and analyzed. Several cases of long-term and short-term measurements of noise originating from various sources were considered in detail. The presented outcomes of predicted degree of the hearing threshold shift induced during the noise exposure can increase the awareness of harmfulness of excessive sound levels.

The article presents an overview and a classification of X-ray detection methods. The main motivation for its preparation was the need to select a suitable and useful method for detecting signals from a currently developed miniature micro-electro-mechanical system (MEMS) X-ray source. The described methods were divided into passive and active ones, among which can be distinguished: chemical, luminescent, thermo-luminescent, gas ionization, semiconductor, and calorimetric methods. The advantages and drawbacks of each method were underlined, as well as their usefulness for the characterisation of the miniature MEMS X-ray source.