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The main topic of the paper is the definition of the optimal design of an aeronautical seat, in terms of maximization of occupants’ safety level and of prediction capability of a FE/MB coupled numerical procedure, based on TNO Madymo® MB software and LSTC LS-Dyna® FE software. The proposed numerical procedure can support the physical prototype development and the experimental phase of the current design approach by using design of experiments methods. In particular, the paper deals with the simulation of an experimental seat sled test against the aircraft front fuselage bulkhead (Figure 1). The FE model has been analysed by using LSTC-LsDyna® code; the multibody model has been analysed by considering TNO-Madymo code.Parameters evaluated during the tests are the acceleration of the head, with the relative calculation of HIC, and the loads transmitted to the lower limbs of the dummy. To approach the development phase, it may result very effective to take into account previous experiences, before entering the cumbersome development of the detailed finite element model. The implementation of simplified multibody (MB) structural models, together with design of experiment (DOE) may simplify the definition of the crashworthy scenario for a new seat. Though the adoption of an integrated MB and DOE approach will not eliminate the need for a detailed FE impact model and its experimental validation, it will surely help in identifying the most sensitive parameters to be complying with the applicable regulation (from the numerical simulation point of view) and in reducing the number of tests needed to reach the certification requirements. The paper presents the initial attempt in applying such development strategy, highlighting the importance of previous experience and how to take advantage from it through dedicated self- developed computer tools.

In several context ranging from medical to social sciences, rater reliability is assessed in terms of intra (-inter) rater agreement. The extent of rater agreement is commonly characterized by comparing the value of the adopted agreement coefficient against a benchmark scale. This deterministic approach has been widely criticized since it neglects the influence of experimental conditions on the estimated agreement coefficient. In order to overcome this criticism, in this paper a statistical procedure for benchmarking is presented. The proposed procedure is based on non parametric bootstrap confidence intervals. The statistical properties of the proposed procedure have been studied via a Monte Carlo simulation.

This paper presents a critical review of some kappa-type indices proposed in the literature to measure the degree of rater agreement. Single measures of agreement provide only limited information and do not account for statistical uncertainty thus, following recommended guidelines for reporting agreement studies, we will present agreement indices including their confidence intervals. The magnitude of each estimated agreement coefficient will be related to the notion of extent of agreement by comparing the lower limit of its confidence interval against a benchmark scale. Specifically, we will explore the case of agreement among series of ratings referring to n items classified into k ordered categories by different raters (i.e., inter-rater agreement) or, equivalently, by the same rater in different occasions (i.e., intra-rater agreement). The reviewed indices are Gwet’s AC2 and the linear weighted variants of Scott’s Pi coefficient, Cohen’s Kappa and Brennan-Prediger statistic. In order to evaluate the statistical behavior of the reviewed indices and of a non-parametric benchmarking procedure, a Monte Carlo simulation study has been conducted for several scenarios differing from each other in sample size, rating scale dimension and agreement level. The estimate precision is evaluated in terms of relative bias, variance and coverage rate of the percentile bootstrap confidence interval, whereas the effectiveness of the benchmarking procedure is assessed in terms of statistical power. Simulation results suggest that the analyzed indices have satisfactory estimate precision that improves as n, k and agreement level increase and a coverage rate close to its nominal level, only for n ≥ 30; the benchmarking procedure is generally adequately powered in testing null and non-null cases of rater agreement and thus it can be suitably applied for the characterization of agreement over a small or moderate number of subjective ratings provided by one or more raters.

Over the years, air traffic has been constantly increasing: in 2013, over 3 billion passengers were carried by the world’s airlines; according to a recent Airbus’ global market forecast, air traffic will double in the next 15 years, showing 4.7% annual growth between 2013 and 2034 (Airbus, 2016). Despite the growing demand, airlines are still one of the lowest-scoring industries in the American Customer Satisfaction Index (ACSI) and seat comfort is the most unsatisfying aspect of flying (ACSI, 2016). As a matter of fact, improving seat comfort can provide an opportunity to gain competitive edge in aircraft industry. This paper focuses on the assessment of aircraft seating (dis)comfort via a statistical-experimental approach. Seating (dis)comfort data (both objective and subjective) were collected during an experiment involving 18 volunteers (9 males and 9 females) who tested two aircraft seats in upright and upright/reclined configuration, respectively. Data were collected under controlled experimental conditions. In order to minimize experimental uncertainty due to well-known noise factors (i.e. patterns of discomfort during the work week and during the workday, evalua-tion sequence, inter-individual variability), experimental trials were performed according to a crossover de-sign. The whole experiment consisted of 54 experimental sessions; the duration of each session was approxi-mately 40 minutes. In each test run, the participant performed a fixed task so as to minimize differences in postures and control the effect of body posture upon pressure distribution at seat-interface. Statistical data analysis aimed at: 1) investigating gender–based differences in seating (dis)comfort; 2) identifying critical discomfort body areas; 3) analyzing time-variation in seating (dis)comfort. The experimental results are in line with the acknowledged hypotheses that males and females are exposed to different loading patterns and experience different discomfort pathways, due to fundamental biomechanical differences in their sitting pos-ture and anthropometric peculiarities. Moreover, results pinpoint that perceived discomfort increases signifi-cantly over time in several body areas.

Student Evaluations of Teaching (SETs) are the most common way to measure teaching quality in Higher Education (HE): they are assuming a strategic role in monitoring teaching quality, becoming helpful in taking major formative academic decisions aimed at improving and shaping teaching quality for future courses starting from the evidence shown by quality evaluations. In the context of HE, the choice of using the student as primary rater of teaching quality has dominated worldwide for the past 40 years. Nevertheless, a review of specialized literature evidences that researchers widely discuss whether SETs can be considered reliable measures for quality evaluation. Although some researchers believe that SET is the best option to provide quantifiable and comparable measures, others point out that student ratings could be influenced by significant impacting factors (such as own classroom experience and class size) losing reliability. The majority of studies concerning SETs reliability focus on the instruments and the procedures adopted to collect students' evaluations or on the inter-rater reliability rather than the intra-rater reliability. In this paper the main results of a reliability study on SETs provided for a university course are fully illustrated. The data sets have been collected during three supervised experiments carried out on successive classes. The class sizes were more than 20 students, homogeneous in curriculum and instruction. SETs collected in each experiment have been analysed by measuring the reliability of each student (i.e. single rater), the reliability of the whole class (i.e. multiple raters) and the agreement among students. Particularly, the reliability has been measured as the coherence of the evaluations provided in two occasions using the same rating instrument (i.e. same items and same rating scale) or using partially different rating instruments (i.e. same items but different rating scales); whereas the agreement has been measured for students’ ratings collected exactly in the same conditions (i.e. same occasion, same items and same rating scales).

Literature on seat comfort recognizes that seat interface pressures are the objective comfort measures that most clearly relate to users’ comfort perceptions about sitting experience. In this paper, the above relationship is quantitatively investigated by performing simple but effective explorative analyses on seat comfort data collected during experimental sessions involving 22 volunteers who tested 4 office chairs (differing in terms of cushion softness). Statistical data analyses show that subjective sitting comfort/discomfort ratings are significantly related to several combinations of pressure variables. The joint analysis of synthetic indexes based on seat interface pressures reveals to be a useful tool for comparative seat comfort assessment. Besides valuable suggestions for the definition of an effective strategy for seat comfort assessment, the results of data analyses provide useful information to support the product design phase. In fact, the sitting experience results to be significantly improved by: (1) a balancing of pressures between the bilateral buttocks; and (2) a balancing of contact areas between buttocks and thighs.