Alice Yeung - Academia.edu (original) (raw)

Papers by Alice Yeung

The conceptions of learning have undergone fundamental changes in recent years. The learning proc... more The conceptions of learning have undergone fundamental changes in recent years. The learning processes have shifted their focus to learners‟ understanding and application of knowledge (Riedler & Eryaman, 2010) to become critical thinkers and lifelong learners (Candy, 2002; Wong, 2010). These changes have made information literacy become an important educational mission, which aims to equip students for effective academic investigation and career development in the future (Owusu-Ansah, 2004). Information literacy, being one of the essential abilities necessary to students in the 21 st century, is a set of abilities requiring individuals to “recognize when information is needed and have the ability to locate, evaluate, and use effectively the needed information” (American Library Association, 1989, p.1). Although many studies examined students‟ information literacy (Emmett & Emde, 2007; Green & Bowser, 2006; Maughan, 2001; Samson & Millet, 2003; Sharma, 2007), little focused on resear...

BackgroundNon-pharmaceutical interventions (NPIs) and voluntary behavioral changes during the COV... more BackgroundNon-pharmaceutical interventions (NPIs) and voluntary behavioral changes during the COVID-19 pandemic have influenced the circulation of non-SARS-CoV-2 respiratory infections. We aimed to examine interactions among common non-SARS-CoV-2 respiratory virus and further estimate the impact of the COVID-19 pandemic on these viruses.MethodsWe analyzed incidence data for seven groups of respiratory viruses in New York City (NYC) during Oct 2015 - May 2021 (i.e., before and during the COVID-19 pandemic). We first used elastic net regression to identify potential virus interactions and further examined the robustness of the found interactions by comparing the performance of Auto Regressive Integrated Moving Average (ARIMA) models with and without the interactions. We then used the models to compute counterfactual estimates of cumulative incidence and estimate the reduction during the COVID-19 pandemic period from March 2020 to May 2021, for each virus.ResultsWe identified potential...

The Lancet Infectious Diseases, 2020

Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on ... more Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre-including this research content-immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

BackgroundAs the COVID-19 pandemic continues to unfold, the infection fatality risk (IFR, i.e. ri... more BackgroundAs the COVID-19 pandemic continues to unfold, the infection fatality risk (IFR, i.e. risk of death among all infections including asymptomatic and mild infections) is crucial for gauging the burden of death due to COVID-19 in the coming months or years. Here we estimate the IFR of COVID-19 in New York City (NYC), the first epidemic center in the United States where the IFR remains unclear.MethodsWe developed a meta-population network model-inference system to estimate underlying SARS-CoV-2 infection rates in NYC during the 2020 spring pandemic wave using case, mortality, and mobility data. Based on these estimates, we further estimated the IFR for all ages overall and for 5 age groups (i.e. <25, 25-44, 45-64, 65-74, and 75+ years) separately, during March 1 – June 6, 2020 (i.e., before NYC began its phased reopening).FindingsDuring March 1 – June 6, 2020, 205,639 laboratory-confirmed COVID-19 cases were diagnosed and 21,447 confirmed and probable COVID-19 deaths occurre...

Birth Defects Research, 2019

Background: Pregnant women with influenza are more likely to have complications, but information ... more Background: Pregnant women with influenza are more likely to have complications, but information on infant outcomes is limited. Methods: Five state/local health departments collected data on outcomes of infants born to pregnant women with 2009 H1N1 influenza reported to the Centers for Disease Control and Prevention from April to December 2009. Collaborating sites linked information on pregnant women with confirmed 2009 H1N1 influenza, many who were severely ill, to their infants' birth certificates. Collaborators also collected birth certificate data from two comparison groups that were matched with H1N1-affected pregnancies on month of conception, sex, and county of residence.

Journal of Librarianship and Information Science, 2016

Inquiry project-based learning is a contemporary focus area in curriculum development around the ... more Inquiry project-based learning is a contemporary focus area in curriculum development around the world. This new learning approach requires students to locate appropriate information from various sources in order to satisfy their information needs under strict anti-plagiarism requirements. However, technological advancement inadvertently allows convenient plagiarism opportunities. Students must learn how to enhance their academic integrity and not to copy information directly from readily available sources like the Internet. This study investigated junior secondary students’ standard of academic integrity. Data was collected through information literacy tests, plagiarism checks on student group projects and structured interviews. Poor information literacy and language abilities were found to be potential factors behind poor academic practice, and academic integrity teaching proved to be largely effective. Therefore, related teaching should be further included in the school curriculu...

2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009

Over the past decade, multiple-instance learning (MIL) has been successfully utilized to model th... more Over the past decade, multiple-instance learning (MIL) has been successfully utilized to model the localized content-based image retrieval (CBIR) problem, in which a bag corresponds to an image and an instance corresponds to a region in the image. However, existing feature representation schemes are not effective enough to describe the bags in MIL, which hinders the adaptation of sophisticated single-instance learning (SIL) methods for MIL problems. In this paper, we first propose an evidence region (or evidence instance) identification method to identify the evidence regions supporting the labels of the images (i.e., bags). Then, based on the identified evidence regions, a very effective feature representation scheme, which is also very computationally efficient and robust to labeling noise, is proposed to describe the bags. As a result, the MIL problem is converted into a standard SIL problem and a support vector machine (SVM) can be easily adapted for localized CBIR. Experimental results on two challenging data sets show that our method, called EC-SVM, can outperform the state-of-the-art methods in terms of accuracy, robustness and efficiency.

American Journal of Infection Control, 2015

Timely outbreak detection is necessary to successfully control influenza in long-term care facili... more Timely outbreak detection is necessary to successfully control influenza in long-term care facilities (LTCFs) and other institutions. To supplement nosocomial outbreak reports, calls from infection control staff, and active laboratory surveillance, the New York City (NYC) Department of Health and Mental Hygiene implemented an automated building-level analysis to proactively identify LTCFs with laboratory-confirmed influenza activity. Geocoded addresses of LTCFs in NYC were compared with geocoded residential addresses for all case-patients with laboratory-confirmed influenza reported through passive surveillance. An automated daily analysis used the geocoded building identification number, approximate text matching, and key-word searches to identify influenza in residents of LTCFs for review and follow-up by surveillance coordinators. Our aim was to determine whether the building analysis improved prospective outbreak detection during the 2013-2014 influenza season. Of 119 outbreaks identified in LTCFs, 109 (92%) were ever detected by the building analysis, and 55 (46%) were first detected by the building analysis. Of the 5,953 LTCF staff and residents who received antiviral prophylaxis during the 2013-2014 season, 929 (16%) were at LTCFs where outbreaks were initially detected by the building analysis. A novel building-level analysis improved influenza outbreak identification in LTCFs in NYC, prompting timely infection control measures.