Injury Characteristics of Motorcyclists Involved in Motorcycle Crashes in Klang Valley, Malaysia

The objectives of this study were to establish the relationship between injury outcomes and i) riders' characteristics, ii) their exposure and iii) the motorcycle factors resulting from serious and fatal motorcycle crashes. Data on motorcycle crashes and injuries from January to December 1998 were obtained from two sources, namely the police reports and hospital records. These linked data were then used to examine the injury patterns sustained by the motorcyclists involved in motorcycle crashes in Malaysia. In order to assess the independent variables in influencing the injury outcome, the logistic regression method was used to determine the odds ratios and the multivariate models for the injured motorcyclists. In the statistical analysis, a total of five independent variables were found to significantly (p<O.05) influence the fatality risk. Those variables were (i) age of motorcyclists, (ii) engine capacity of the motorcycles, (iii) objects struck, (iv) type of collisions and (v) location sites. Results showed that fatality risks were likely to associate with older motorcyclists, larger engine motorcycles, collision with a heavy commercial vehicle, head-on collision, and non-junction sites. The study also revealed that the most frequent injuries to fatally injured motorcyclists were head injuries (56.5%) and chest injuries (27.4%). Injuries to the lower limbs, however, accounted for the highest proportion (54.4%) for the serious injury cases investigated. This is followed by the upper limb injuries (19.9%). Most motorcyclists were detained for one or two nights for observation and recovery. The mean stay for all patients were about 5 days. However, those motorcyclists who suffered from lower limb injuries often required longer stay in hospital. In addition, the study indicated that side collisions presented a difficult problem in crash protection towards the lower limbs. Despite the fact that most motorcycles in Malaysia had very little crushable and protective structure around the rider's lower limb region. Whereas, this kind of protection was found to reduce the risk of lower limb injures i n many studies. As such, further investigation on the design of effective leg protector for motorcyclists should be carried out

Pandemic-induced course and assessment changes for undergraduate engineering education: The Development of Graduate Attributes

Educators constantly need to make adjustments to their pedagogy and learning activities to reflect the fast changes in society, the economy and industry. This has been clearly demonstrated throughout the world in the response to the COVID-19 pandemic required fully remote delivery of tertiary education. The aim of this study was comparing the experiences and perceptions of tertiary students in a fully online and a blended delivery mode, particularly in response to their laboratory skills and development of graduate attributes. Pedagogical aspects were kept consistent across delivery modes to minimise the differences in learning activities across cohorts. A comparison was made between the 2020 fully online cohort and the 2021 blended delivery cohort. The students were asked about their perceptions of how well they thought the course developed their graduate attributes; how authentic they thought the course was; and how easy the content was to navigate and understand. A mixed methods approach was used, where both quantitative and qualitative data was gathered. The blended delivery mode students appeared to benefit from having a specific reflective task, which allowed them to see their learning in a broader context. The paper discusses the blending and online learning from the students’ perspectives of developing graduate attributes and experiential learning. Specifically, where hands on skills are required, students need further guidance in “learning how to learn” or metacognition. A key challenge for future blended learning is getting the balance right between achieving efficiency in online learning and lack of social and dynamic interactions aspect of the online community

Does an assessment rubric provide a better learning experience for undergraduates in developing transferable skills?

There is ongoing interest in developing rigorous and accurate assessment methods in higher education, particularly in the use of assessment rubrics and in providing more useful feedback to students rather than a simple grade. However, there has been little used of reliable assessment rubrics that provide feedback to individual students on their teamwork participation and skills, and which assist academic staff in assessing teamwork among students. This paper reports on the second phase of a study that aimed to evaluate a rubric to assess skills and processes in teamwork, and whether a rubric facilitated a better learning experience than a simple marking scheme. The second phase focused on the implementation of a revised assessment rubric designed to assist students and staff in understanding what was expected in the assessment process, and in particular the creation of efficient tools and metrics to measure both teamwork and individual performance during collaborative team design projects. Findings from two surveys of students provided the dataset for this second phase of the study. The findings demonstrate that assessment rubrics provide an important adjunct in improving students’ teamwork performance and their understanding of their learning activities. This study will also contribute to ongoing discussions on higher education assessment methods

Ultra-Low Temperature Coefficient of Capacitance (Tcc) of the SrSnO

The perovskite-structured SrSnO3 possessing steady capacitance over the temperature range between 27°C and 300°C in a frequency domain spanning nearly four decades has been evaluated. The samples investigated in this study were synthesized by using solid-state reaction (SSR) and self-heat-sustained (SHS) techniques. These samples were sintered at a temperature (T ) ranging between 1200°C and 1600°C with a soak-time (t) ranging between 2 h and 60 h. The ac immittance (impedance or admittance) measurements were conducted on these sintered bodies in the frequency range 5Hz to 13 MHz. These ac electrical data were found to exhibit relaxation in more than one complex plane formalisms in a simultaneous manner. The magnitude of the terminal capacitance was found to be in a narrow window of 3 pF to 6 pF possessing very weak temperature dependence. Further analysis also revealed that this material system possessed low dielectric constant and ultra-low temperature coefficient of capacitance (TCC) or dielectric constant (TCK). The electrical behavior of these sintered bodies has been systematically correlated with the evolved microstructures. Plausible equivalent circuit elements were extracted using the lumped parameter/complex plane analysis (LP/CPA) and evaluated at various situations

A novel hierarchical clustering algorithm for the analysis of 3D anthropometric data of the human head

In recent years, the use of 3D anthropometry for product design has become more appealing because of advances in mesh parameterisation, multivariate analyses and clustering algorithms. The purpose of this study was to introduce a new method for the clustering of 3D head scans. A novel hierarchical algorithm was developed, in which a squared Euclidean metric was used to assess the head shape similarity of participants. A linkage criterion based on the centroid distance was implemented, while clusters were created one after another in an enhanced manner. As a result, 95.0% of the studied sample was classified inside one of the four computed clusters. Compared to conventional hierarchical techniques, our method could classify a higher ratio of individuals into a smaller number of clusters, while still satisfying the same variation requirements within each cluster. The proposed method can provide meaningful information about the head shape variation within a population, and should encourage ergonomists to use 3D anthropometric data during the design process of head and facial gear

Improving fit of bicycle helmet liners using 3D anthropometric data

3D anthropometry has provided much-needed information about the size and shape of the head, which can be used to improve the fit of protective helmets. In this study, a new 3D head scan sizing method was implemented in a reverse engineering approach for bicycle helmet liner dimensioning. The inside liner of a commercially available helmet was modified to improve the fit for a selected size group of 30 participants. The fit of the standard and new liner were assessed and compared, using the Helmet Fit Index (HFI). The HFI scores showed a significant improvement of overall fit (Difference: 11.32 ± 7.82 (μ ± SD), p < 0.0005) and for each of five defined regions of the liner inside surface. The presented methodology for dimensioning helmet liners based on 3D anthropometry proved effective, resulting in improved fit for the end users

3D digital headform models of Australian cyclists

Traditional 1D anthropometric data have been the primary source of information used by ergonomists for the dimensioning of head and facial gear. Although these data are simple to use and understand, they only provide univariate measures of key dimensions. 3D anthropometric data, however, describe the complete shape characteristics of the head surface, but are complicated to interpret due to the abundance of information they contain. Consequently, current headform standards based on 1D measurements may not adequately represent the actual head shape variations of the intended user groups. The purpose of this study was to introduce a set of new digital headform models representative of the adult cyclists' community in Australia. Four models were generated based on an Australian 3D anthropometric database of head shapes and a modified hierarchical clustering algorithm. Considerable shape differences were identified between our models and the current headforms from the Australian standard. We conclude that the design of head and facial gear based on current standards might not be favorable for optimal fitting results

Finite Element Bicycle Helmet Models Development

AbstractImpact attenuation performance of three different range of commercial bicycle helmet were investigated in lateral drop impact test in accordance to AS/NZS 2063:2008, Australian/New Zealand Standard for bicycle helmet using numerical simulation and and experimental impact test. The aim of this research is to develop a simulation model of drop impact test, which to be used in further investigations of user-centred design approach of bicycle helmet. Three commercial bicycle helmet models were used in this study. All helmets and J headform were scanned using Flexscan 3D scanning equipment. Post-scan processing jobs of scanned geometry models such as helmet liner, shell and headform were conducted in Geomagic Studio 12. The experimental impact test is carried out using 2-wire drop test facility in accordance to the AS/NZS 2063:2008, Australian Standard for bicycle helmet. A few samples were cut from the liner of each helmet to determine the density of Expanded Polystyrene (EPS). Headform peak linear acceleration, impact duration and impact speed of each helmet were measured and recorded from the drop test. The scanned geometry models were imported into Abaqus. A drop impact simulation was developed based on the density and impact speed data obtained from the physical test. Inner liner of bicycle helmet, made from Expanded Polystyrene (EPS), was modeled using crushable foam properties, while headform and anvil were modeled as rigid bodies. Peak linear accelerations and impact duration of the headform on each helmet at three different impact locations of helmet were recorded. A robust correlation study using peak linear acceleration score, impact duration score and Pearson correlation coefficient between the data from physical test and numerical model was conducted. Good correlation scores (>80%) were achieved between the numerical model and experimental impact test in terms of headform peak linear acceleration and impact duration score, suggesting that the simulation model is in good correlation with those from physical test

The helmet fit index - an intelligent tool for fit assessment and design customization

Helmet safety benefits are reduced if the headgear is poorly fitted on the wearer's head. At present, there are no industry standards available to assess objectively how a specific protective helmet fits a particular person. A proper fit is typically defined as a small and uniform distance between the helmet liner and the wearer's head shape, with a broad coverage of the head area. This paper presents a novel method to investigate and compare fitting accuracy of helmets based on 3D anthropometry, reverse engineering techniques and computational analysis. The Helmet Fit Index (HFI) that provides a fit score on a scale from 0 (excessively poor fit) to 100 (perfect fit) was compared with subjective fit assessments of surveyed cyclists. Results in this study showed that quantitative (HFI) and qualitative (participants' feelings) data were related when comparing three commercially available bicycle helmets. Findings also demonstrated that females and Asian people have lower fit scores than males and Caucasians, respectively. The HFI could provide detailed understanding of helmet efficiency regarding fit and could be used during helmet design and development phases

A design framework for the mass customisation of custom-fit bicycle helmet models

Mass customisation (MC) can provide significant benefits to the customers. For example, custom-fit design approaches can improve the users’ perceived comfort of products where the fit is an important feature. MC can also bring major value to the producers, where for instance, premium prices can be implemented to the products. Research show that MC can bring competitive advantages especially when the system is new. It is therefore surprising that MC of helmets has not been studied more extensively, especially given the advances in 3D scanning, computational analyses, parametric design, and additive manufacturing techniques. The purpose of this study was to present a novel MC framework for the design of custom-fit bicycle helmet models. In the proposed design framework, we first categorized a subset of the Australian population into four groups of individuals based on their similar head shapes. New customers were then classified inside one of these groups. The customisation took place inside these groups to ensure that only small variations of the helmet liner were implemented. During the design process, the inside surfaces of a generic helmet model was modified to match the customer's head shape. We demonstrated that all the customized models created complied with the relevant drop impact test standard if their liner thickness was between the worst and best case helmets of each group. Fit accuracy was verified using an objective evaluation method. Future work should include detailed description of the manufacturing methods engaged in our MC framework