Using Monte Carlo Simulation for Vehicle Emission Estimation-A Case Study in Hong Kong

Background and Objectives: Air pollution caused by vehicular emission has been a public concern and is more seriously in Hong Kong which is a highly urbanized and congested city. Therefore, a study was conducted to observe the vehicular pollutant emission and concentration. This study intends to update the driving behavior in terms of vehicle speed and vehicle acceleration for heavy diesel vehicles in Hong Kong residential area. Materials and Methods: A total of over 900 min of data were collected by the car chasing technique for 93 heavy diesel vehicles in Shatin, one of the most crowd residential area in Hong Kong during the period November and December, 2019. A three dimensions speed-acceleration matrix and plot were developed by the sampled result. Project team further applied the Hong Kong based speed-acceleration probability distribution to the tunnel mass balance emission model for CO and NO vehicle emission estimation. Results: A Hong Kong based three-dimension speed-acceleration-frequency matrix was successfully developed. Monte Carlo simulation were further carried out for 1000 times within obtained driving cycle and then further calculating the CO and NO emission factor. It was observed that in average one heavy diesel vehicles has emitted 6.5 g CO and 7.1 g NO for one trip in residential area (around 10 km). Conclusion: This research project focuses on the interaction effect between vehicle speed and acceleration and showed there was interaction effect. This method is simple and extremely good under limited budgets. Statistical Monte Carlo simulation further improved the accuracy of the driving cycle modeling

Design and implementation of mlearning for calculus in tertiary education

Using IT in education has become prevalent worldwide. It is believed that IT not only motivates students to learn in class, but also encourages students to take the initiative to explore and inquire subject matters outside classroom by themselves (i.e. independent learning). The Hong Kong Education Bureau offered a series of professional development programmes to principals, vice principals, middle managers as well as teachers who have joined the "Support Scheme for e-Learning in Schools" since April 2014 to 2016/17 school year to further equip schools to implement e-learning. In primary and secondary education, for example, the HKSAR Government (2004) has been giving support to schools for using e-textbooks and e-learning resources during lessons. At tertiary level, other e-learning platforms such as MOODLE and BLACKBOARD have been widely used in different institutions. In recent years, the rapid development of mobile apps has been provided learners with ample opportunities to learn independently. There are various learning apps such as Math Tricks, Complete Mathematics, Mathematics Dictionary, IXL Maths Practice, etc on the market for primary and secondary education; nonetheless, the use of mobile apps in students’ learning of disciplinary subject seems to be new in tertiary level, and its effectiveness in students’ learning is worth investigation. Through this study, the project team hopes to a) explore whether a disciplinary-specific mobile app can help learners to acquire and apply disciplinary knowledge in and beyond classroom, b) identify elements to be included in a mobile app to helps students to learn outside classroom

Hilbert-Schmidtness of weighted composition operators and their differences on Hardy spaces

Let u and φ be two analytic functions on the unit disk D such that φ (D) ⊂ D. A weighted composition operator uCφ induced by u and φ is defined on H2, the Hardy space of D, by [formula] for every ∫ in H2. We obtain sufficient conditions for Hilbert-Schmidtness of v,Cv on H2 in terms of function-theoretic properties of u and φ. Moreover, we characterize Hilbert-Schmidt difference of two weighted composition operators on H2

Closed range weighted composition operators between lp-spaces

We characterize the closedness of ranges of weighted composition operators between Lp-spaces, where 1 <≤ p ≤ ∞. When the Lp-spaces are weighted sequence spaces, several corollaries about this class of operators are also deduced