Hong Kong Polytechnic University

About: Hong Kong Polytechnic University is a education organization based out in Hong Kong, China. It is known for research contribution in the topics: Computer science & Tourism. The organization has 29633 authors who have published 72136 publications receiving 1956312 citations. The organization is also known as: HKPU & PolyU.

Reducing building waste at construction sites in Hong Kong

Abstract: The building industry is using a considerable amount of resources, but if the life cycle of the material on site is closely examined, it is generally known that there is a relatively large portion of the materials being wasted because of poor material control on building sites. The problem of material wastage is not an isolated issue on construction sites. It is also an environmental concern. Hong Kong is running out of both reclamation sites and landfill space for the disposal of construction & demolition (C&D) waste. Many resources can be conserved and the amount of C&D waste required to be disposed of should be greatly reduced if better management of materials is practiced on building sites. This paper reports on a recent study conducted in Hong Kong relating to material control on construction sites with high‐rise multi‐storey buildings. In the paper, the causes of building waste are identified and the wastage levels of various trades for public housing and private residential projects in Hong Kong ar...

Investor Sentiment and Stock Market Response to Earnings News

Abstract: We examine whether market-wide investor sentiment influences the stock price sensitivity to firm-specific earnings news. Using the recently developed measure of investor sentiment by Baker and Wurgler (2006), we find that the stock price sensitivity to good earnings news is higher during high sentiment periods than during periods of low sentiment, whereas the stock price sensitivity to bad earnings news is higher during periods of low sentiment than during periods of high sentiment. This influence of sentiment is especially pronounced for the earnings news of small stocks, young stocks, high volatility stocks, non-dividend-paying stocks, and stocks with extremely high and low market-to-book ratios. Further analysis suggests that the sentiment-driven mispricing of earnings contributes to the general mispricing of stocks due to investor sentiment. JEL Classifications: D14; D21; G24.

Domain Adaptation Extreme Learning Machines for Drift Compensation in E-Nose Systems

Abstract: This paper addresses an important issue known as sensor drift, which exhibits a nonlinear dynamic property in electronic nose (E-nose), from the viewpoint of machine learning. Traditional methods for drift compensation are laborious and costly owing to the frequent acquisition and labeling process for gas samples’ recalibration. Extreme learning machines (ELMs) have been confirmed to be efficient and effective learning techniques for pattern recognition and regression. However, ELMs primarily focus on the supervised, semisupervised, and unsupervised learning problems in single domain (i.e., source domain). To our best knowledge, ELM with cross-domain learning capability has never been studied. This paper proposes a unified framework called domain adaptation extreme learning machine (DAELM), which learns a robust classifier by leveraging a limited number of labeled data from target domain for drift compensation as well as gas recognition in E-nose systems, without losing the computational efficiency and learning ability of traditional ELM. In the unified framework, two algorithms called source DAELM (DAELM-S) and target DAELM (DAELM-T) are proposed in this paper. In order to perceive the differences among ELM, DAELM-S, and DAELM-T, two remarks are provided. Experiments on the popular sensor drift data with multiple batches collected using E-nose system clearly demonstrate that the proposed DAELM significantly outperforms existing drift-compensation methods without cumbersome measures, and also bring new perspectives for ELM.

An Imperative Need for Research on the Role of Environmental Factors in Transmission of Novel Coronavirus (COVID-19).

Abstract: I the last two decades, the emergence of viral epidemics poses great threats to human health and society. These infectious viruses have been identified as hemorrhagic fever viruses (Lassa, Ebola), novel coronaviruses including severe acute respiratory syndrome CoV (SARS-CoV), Middle East respiratory syndrome MERS-CoV), and highly pathogenic influenza. Coronaviruses (CoVs), as a class of enveloped, positive-sense single-stranded RNA virus, cause various diseases in humans. CoVs are subdivided into four groups: Alphacoronavirus, Betacoronavirus (βCoV), Gammacoronavirus, and Deltacoronavirus. Two novel βCoVs, severe acute respiratory syndrome CoV (SARSCoV) and Middle East respiratory syndrome CoV (MERS-CoV), have recently emerged and can induce a high mortality. The current outbreak of novel coronavirus COVID-19 (HCoV-19 or SARS-CoV-2), has resulted in the World Health Organization (WHO) declaring this outbreak a global pandemic. By March 15, 2020, infected cases had reached 81 048 in China and a total of 72 600 cases outside China have been reported to the WHO from 146 countries and territories (https://experience. a r c g i s . c o m / e x p e r i e n c e / 685d0ace521648f8a5beeeee1b9125cd). Similar to the SARS-CoV, symptoms of COVID-19 infection at onset of the illness include fever, myalgia, fatigue, and cough, and more than half of patients developed dyspnoea. Some patients had radiographic ground-glass lung alterations, and lower than average circulating lymphocyte and platelet populations. To date, the global deaths reached 5746, and the fatality rate was estimated as 3.7% for COVID-19 virus ( h t t p s : / / e x p e r i e n c e . a r c g i s . c o m / e x p e r i e n c e / 685d0ace521648f8a5beeeee1b9125cd), which is lower than that of SARS-CoV (10%) or MERS-CoV (37%). The major challenge of the coronavirus family and similar infectious agents is that no effective drugs or vaccine are available, and it may take many months for research and development. Human-to-human transmission of COVID-19 occurs when individuals are in the incubation stage or showing symptoms, while some individuals remain contagious while remaining asymptomatic (superspreaders). Transmission is thought to occur via touching infected surfaces (skin-to-skin, touching infected inanimate objects) then mediating the COVID-19 infection through the mouth, nose, or eyes. Transmission can also be through inhalation of exhaled virus in respiratory droplets. It has been reported that infectious viruses, including coronavirus, can survive for long periods outside of its host organism. COVID-19 virus is thought to survive for several hours on surfaces such as aluminum, sterile sponges, or latex surgical gloves, increasing the opportunity for transmission via touch. Transmission via the inhalation of small, exhaled respiratory droplets may occur as the aerosol droplets remain airborne for prolonged periods, mediating long-range humanto-human transmission via air movement. The relative contributions of large respiratory droplets, smaller airborne aerosol, or direct surface contacts to the transmissibility of COVID-19 still need to be evaluated to enable a fully effective control of transmission and infection. Faecal transmission routes should also be considered, as the COVID-19 virus has been positively detected in stool samples of infected patients. Studies have shown that SARS-CoV can