The article outlines various approaches to developing a fuzzy decision algorithm designed for monitoring and issuing warnings about driver drowsiness. This algorithm is based on analyzing EOG (electrooculography) signals and eye state images with the aim of preventing accidents. The drowsiness warning system comprises key components that learn about, analyze and make decisions regarding the driver’s alertness status. The outcomes of this analysis can then trigger warnings if the driver is identified as being in a drowsy state. Driver drowsiness is characterized by a gradual decline in attention to the road and traffic, diminishing driving skills and an increase in reaction time, all contributing to a higher risk of accidents. In cases where the driver does not respond to the warnings, the ADAS (advanced driver assistance systems) system should intervene, assuming control of the vehicle’s commands.

Vibratory machines are widely used for the separation of granular materials of various densities and characteristics. Vibrations are used in this case to increase the technological speed of separation of these materials. Vibratory machines are limited in functioning to fixed oscillation patterns. Control of the oscillation can offer the possibility of changing the oscillation pattern, adapting it to the type of granular material. This paper proposes a vibratory machine with controllable elastic characteristics and pneumatic actuation. From the perspective of functional generalization of these machines, a parallel mechanism with 3 degrees of mobility, starting from the study of the Stewart platform, was designed. The proposed system has been studied both in terms of structure and kinematics, using instruments of simulation tools available in MATLAB and Simulink 2021. The developed model was validated and optimized using multi-body dynamic software ADAMS 2014, obtaining optimal parameters for one type of granular material.

This paper exposes the initial part of a larger research on the impact of the automotive on human health and the quality of life and environment. After a brief introduction on the need for responsible and sustainable approaches and few questions on the subject, some considerations and statistical data are presented, based on a study of the literature on the impact of road traffic and vehicles noise and vibration on people's comfort and health and their quality of life. The research results show, based on official statistics, the significant harmful impact of noise and vibration from motor vehicles and road transport on people's health and quality of life, especially in urban areas during the day. Also, the significant increase in the number of electric and hybrid vehicles from one year to another, a reality and a necessity nowadays, and the awareness that electric vehicles are not perfectly quiet and comfortable, open new research opportunities and require the development of new standards, materials, tools, equipment and test methods in the field of NVH, in a sustained synergistic approach from all stakeholders, to meet the needs and demands of today's consumers, and to comply with existing regulations and standards on environmental protection and sustainable development.

The aim of this study was to evaluate, in a laboratory study, the accumulation of arsenic (As), cadmium (Cd), nickel (Ni) and lead (Pb) in the root, stem, leaves and flowers of some aromatic and medicinal plants grown on polluted soils. To carry out these experiments, the seeds of different plant species (Mentha piperita, Sinapis alba, Satureja hortensis and Thymus serpyllum) were planted in a mini-greenhouse, in universal soil (unpolluted). The seedlings thus obtained were transferred to pots containing soils polluted with metals (As, Cd, Ni and Pb) in different concentrations and combinations. The experiments were carried out over a period of three months. The concentration of metals in different plant organs (root, stem, leaves, flowers) was determined by inductively coupled plasma optical emission spectrometry. (ICP-OES). The accumulation of metals in plants was evaluated by calculating the translocation factor (TF) and the bioaccumulation factor (BCF).