The purpose of this study is to examine the relationship between board leadership structure and earning quality banking sectors in Malaysia. This purposely focuses on four which size, independent non-executive director, gender diversity Chief Executive Officer (CEO) tenure. Data that used 10 Malaysia are publicly listed Bursa As for period, data cover from year 2016 2019. In order find value qu...

Teaching plays a very important role in our society, by spreading human knowledge and educating our next generations. A good teacher will select appropriate teaching materials, impact suitable methodologies, and set up targeted examinations, according to the learning behaviors of the students. In the field of artificial intelligence, however, one has not fully explored the role of teaching, and...

Inference models, which replace an optimization-based inference procedure with a learned model, have been fundamental in advancing Bayesian deep learning, the most notable example being variational auto-encoders (VAEs). In this paper, we propose iterative inference models, which learn how to optimize a variational lower bound through repeatedly encoding gradients. Our approach generalizes VAEs ...

While earning processes are commonly unobservable income flows which evolve in continuous time, observable income data are usually discrete, having been aggregated over time. We consider continuous-time earning processes, specifically (non-linearly) transformed Ornstein-Uhlenbeck processes, and the associated integrated, i.e. time aggregated process. Both processes are characterised, and we sho...

OBJECTIVE: To examine the loss of earning capacity and permanent impairment of a cohort of male patients who had experienced finger amputation due to occupational injury. DESIGN: Prospective cohort study. SETTING: University teaching hospital, Hong Kong. PATIENTS: Twenty-eight male patients aged 26 to 55 years who presented with work-related finger amputations in their dominant right hand from ...

We propose a novel neural network architecture to learn the task of clustering end-to-end: salient features for any similarity criterion specified through weakly labeled training data are extracted with an embedding network; during evaluation, the network groups similar data of any modality together, by assigning a probabalistic cluster index, and further gives a probabilistic estimate of the n...