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BUKU ABSTRAK - Universiti Putra Malaysia

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Science, Technology & Engineering<br />

Design and Prototype of an Ergonomic Back-leaning Posture Support for<br />

Motorbike Riders<br />

Prof. Ir. Dr. Mohd. Sapuan Salit<br />

Karmegam Kurupiah, Md. Yusof Ismail and Napsiah Ismail<br />

Faculty of Engineering, University <strong>Putra</strong> <strong>Malaysia</strong>,<br />

43400 UPM Serdang, Selangor, <strong>Malaysia</strong>.<br />

+603-8946 6336; sapuan@eng.upm.edu.my<br />

This study presents a prototype of an ergonomic back-leaning posture support for motorbike in <strong>Malaysia</strong>.<br />

Motorbike riders are more exposed to musculoskeletal disorders such as lower back pain. Prototype consists<br />

of two basic components, frame and backrest cushion. Prototype back-leaning posture support is evaluated by<br />

comparing it with anthropometry data in terms of flexible range accommodations and by test runs on road with<br />

riders. Prototype has shown better comfort seating, adjustability, stability, solidity, durability and safety for riders.<br />

Keywords: Back posture support, ergonomic, lower back pain, motorbike<br />

Robust Estimators in Simple Mediation Analysis<br />

Assoc. Prof. Dr. Habshah Midi<br />

Anwar Fitrianto<br />

Institute of Mathematical Research, University <strong>Putra</strong> <strong>Malaysia</strong>,<br />

43400 UPM Serdang, Selangor, <strong>Malaysia</strong>.<br />

+603-8946 6876; habshahmidi@gmail.com<br />

Simple mediation model involves a series of regression equations. The Ordinary Least Squares (OLS)<br />

method is often used to estimate the parameters of the mediation model. However, many researchers are not<br />

aware of the fact that the OLS estimators suffer a huge set back in the presence of outliers. In order to rectify this<br />

problem, robust methods which are not easily affected by outliers, have been created. We have proposed a robust<br />

M and MM procedure for estimation of mediation parameters in the presence of single outlier. The performance<br />

of the MM, M, and OLS estimates are compared by numerical example. The empirical evidence shows that the<br />

MM, M, and OLS estimators are equally good in a well behaved data. Nevertheless, when contamination occurs<br />

in the data, the performance of the MM is the best followed by the M and the OLS estimators.<br />

Keywords: Simulation, mediation analysis, unusual observation, outliers, indirect effect, M-estimator, MM-estimator<br />

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