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The objective of this paper is to develop a fast modelling technique for predicting magneto-rheological fluid damper behaviour under impact loading applications.

The adaptive neuro-fuzzy inference system (ANFIS) technique was adopted to predict the behaviour of a magneto-rheological fluid (MRF) damper through experimental characterisation data. In this study, an MRF damper manufactured by Lord Corporation was used for characterisation using an impact pendulum test rig. The experimental characterisation was carried out with various impact energies and constant input currents applied to the MRF damper.

This research provided a fast modelling technique with relatively less error in predicting MRF damper behaviour for the development of control strategies. Accordingly, the ANFIS model was able to predict MRF damper behaviour under impact loading and showed better performance than the modified Bouc–Wen model.

This study only focused on modelling technique for a single type of MRF damper used for impact loading applications. It is possible for other applications, such as cyclic loading, random loadings and system identification, to be studied in future experiments.

Future researchers could apply the ANFIS model as an actuator model for the development of control strategies and analyse the control performance. The model also can be replicated in other industries with minor modifications to suit different needs.

Aging adults from low-income residential areas were found to have poor nutritional status and mental health based on National Health and Morbidity Survey Malaysia (2015). Good nutrient intake contributes positively in averting these problems. Traditional Asian vegetables (ulam) are rich in polyphenols, antioxidants and fibres which could enhance nutritional status and mood state. This study intended to determine the relationship between habitual ulam intake and nutritional status, mood state and cognition among 252 aging Malaysian adults aged 45–80 years from the low-income residential areas in Klang Valley, Malaysia.

It was a cross-sectional study that used convenient sampling. Advertisement and invitation letters were sent to three selected community centres in Klang Valley prior to data collection. Informed consent was obtained prior to the collection of socio-demographic data. Anthropometric measurement was performed as per standard protocols. Validated surveys were conducted to obtain information on ulam consumption, mood state and cognitive status using validated food frequency questionnaires, Profile of Mood State and Mini-Mental State Examination questionnaires, respectively.

The average of ulam intake was 20.5 ± 2.5 g/day (½ serving daily). Habitual ulam intake was associated with lower waist circumference (R² = 0.166, β = −0.216, p < 0.01), better MMSE scores (R² = 0.337, β = 0.128, p < 0.05), less anger (R² = 0.081, β = −0.116, p < 0.05), less tension (R² = 0.139, β = −0.204, p < 0.01) and positive total mood disturbance (R² = 0.095, β = 0.164, p < 0.05) after adjustment for gender, age, energy intake, total fruits and vegetables (non-ulam) consumption. The ulam intake at 100th percentile (=30g/day) associated to a better nutritional status, mood state and cognitive status in comparison to 25th percentile (<7.9 g/day) (p < 0.05).

Findings from this research would recommend people to consume not less than 1 serving of ulam everyday in order to have improved nutritional status, mood and cognition; nonetheless, future studies are required to clarify the causal mechanism concerning this relationship.