Machine Learning algorithm on seat comfort level measurement, mapping pressure values with body regions

The comfort level of the seat has a major effect on the usage of a vehicle; thus, car manufacturers have been working on elevating car seat comfort as much as possible. However, still, the testing and evaluation of comfort are done using exhaustive trial and error testing and evaluation of data. In this thesis, we resort to machine learning and Artificial Neural Networks (ANN) to develop a fully automated approach. Even though this approach has its advantages in minimizing time and using a large set of data, it takes away the degree of freedom of the engineer on making decisions. The focus of this study is on filling the gap in a two-step comfort level evaluation which used pressure mapping with body regions to evaluate the average pressure supported by specific body parts and the Self-Assessment Exam (SAE) questions on evaluation of the person’s interest. This study has created a machine learning algorithm that works on giving a degree of freedom to the engineer in making a decision when mapping pressure values with body regions using ANN. The mapping is done with 92% accuracy and with the help of a Graphical User Interface (GUI) that facilitates the process during the testing time of comfort level evaluation of the car seat, which decreases the duration of the test analysis from days to hours.

Assessing the effectiveness of ISO 3382 for evaluating the acoustical quality of italian historical theatres: the case study of the Bonci Theatre

The present study concerns the acoustical characterisation of Italian historical theatres. It moved from the ISO 3382 which provides the guidelines for the measurement of a well established set of room acoustic parameters inside performance spaces. Nevertheless, the peculiarity of Italian historical theatres needs a more specific approach. The Charter of Ferrara goes in this direction, aiming at qualifying the sound field in this kind of halls and the present work pursues the way forward. Trying to understand how the acoustical qualification should be done, the Bonci Theatre in Cesena has been taken as a case study. In September 2012 acoustical measurements were carried out in the theatre, recording monaural e binaural impulse responses at each seat in the hall. The values of the time criteria, energy criteria and psycho-acoustical and spatial criteria have been extracted according to ISO 3382. Statistics were performed and a 3D model of the theatre was realised and tuned. Statistical investigations were carried out on the whole set of measurement positions and on carefully chosen reduced subsets; it turned out that these subsets are representative only of the “average” acoustics of the hall. Normality tests were carried out to verify whether EDT, T30 and C80 could be described with some degree of reliability with a theoretical distribution. Different results, according to the varying assumptions underlying each test, were found. Finally, an attempt was made to correlate the numerical results emerged from the statistical analysis to the perceptual sphere. Looking for “acoustical equivalent areas”, relative difference limens were considered as threshold values. No rule of thumb emerged. Finally, the significance of the usual representation through mean values and standard deviation, which may be meaningful for normal distributed data, was investigated.