Shabir Hussain¹, Muhammad Ayoub², Yang Yu¹, Junaid Abdul Wahid¹, Akmal Khan³, Dietmar P. F. Moller⁴, Hou Weiyan^1,*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5355-5377, 2023, DOI:10.32604/cmc.2023.036779 - 29 April 2023

Abstract As the COVID-19 pandemic swept the globe, social media platforms became an essential source of information and communication for many. International students, particularly, turned to Twitter to express their struggles and hardships during this difficult time. To better understand the sentiments and experiences of these international students, we developed the Situational Aspect-Based Annotation and Classification (SABAC) text mining framework. This framework uses a three-layer approach, combining baseline Deep Learning (DL) models with Machine Learning (ML) models as meta-classifiers to accurately predict the sentiments and aspects expressed in tweets from our collected Student-COVID-19 dataset. Using the… More >

Abdelwahed Motwakel^1,*, Hala J. Alshahrani², Abdulkhaleq Q. A. Hassan³, Khaled Tarmissi⁴, Amal S. Mehanna⁵, Ishfaq Yaseen¹, Amgad Atta Abdelmageed¹, Mohammad Mahzari⁶

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4767-4783, 2023, DOI:10.32604/cmc.2023.034840 - 29 April 2023

Abstract Applied linguistics is an interdisciplinary domain which identifies, investigates, and offers solutions to language-related real-life problems. The new coronavirus disease, otherwise known as Coronavirus disease (COVID-19), has severely affected the everyday life of people all over the world. Specifically, since there is insufficient access to vaccines and no straight or reliable treatment for coronavirus infection, the country has initiated the appropriate preventive measures (like lockdown, physical separation, and masking) for combating this extremely transmittable disease. So, individuals spent more time on online social media platforms (i.e., Twitter, Facebook, Instagram, LinkedIn, and Reddit) and expressed their… More >

Regina Lai-Tong Lee^1,2,*, Anson Chiu-Yan Tang³, Ho-Yu Cheng¹, Connie Yuen-Yu Chong¹, Wilson Wai-San Tam⁴, Wai-Tong Chien¹, Sally Wai-Chi Chan⁵

International Journal of Mental Health Promotion, Vol.25, No.3, pp. 327-342, 2023, DOI:10.32604/ijmhp.2022.026388 - 21 February 2023

Abstract The present study aimed to examine work environment related factors and frontline primary healthcare professionals’ mental-emotional wellbeing during the COVID-19 pandemic in school communities of Hong Kong. A total of 61 (20%) school health nurses (frontline primary healthcare professionals) participated in a cross-sectional online survey from March to June 2020. Outcomes of mental-emotional health were measured using the Mental Health Continuum-Short Form (14-item scale with three subscales related to emotional, social and psychological wellbeing); the Perceived Stress Scale (10-item scale with two subscales related to perceived helplessness and lack of self-efficacy; and the Coping Orientation… More >

Abdullah S. AL-Malaise AL-Ghamdi^1,2,3, Sultanah M. Alshammari^3,4, Mahmoud Ragab^3,5,6,*

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1863-1877, 2023, DOI:10.32604/csse.2023.035869 - 09 February 2023

Abstract Notwithstanding the religious intention of billions of devotees, the religious mass gathering increased major public health concerns since it likely became a huge super spreading event for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Most attendees ignored preventive measures, namely maintaining physical distance, practising hand hygiene, and wearing facemasks. Wearing a face mask in public areas protects people from spreading COVID-19. Artificial intelligence (AI) based on deep learning (DL) and machine learning (ML) could assist in fighting covid-19 in several ways. This study introduces a new deep learning-based Face Mask Detection in Religious Mass… More >

Jingjing Wang¹, Xiangli Guan^1,*, Yue Zhang², Yang Li¹, Md Zahir Ahmed³, Mary C. Jobe⁴, Oli Ahmed⁵

International Journal of Mental Health Promotion, Vol.25, No.2, pp. 223-235, 2023, DOI:10.32604/ijmhp.2022.025570 - 02 February 2023

Abstract Individuals’ perceptions, attitudes, and patterns of getting along with family members are important factors influencing Chinese people’s self-evaluation. The aim of this study was to investigate the effect of family cohesion on depression and the role of perceived social support and intentional self-regulation in this association. A hypothesized model of the association of family cohesion, perceived social support, intentional self-regulation, and depression was examined. A convenience sampling method was used to survey 1,180 college students in Yunnan Province using self-report. Data were collected using the Family Cohesion Scale, the Perceived Social Support Scale, the Intentional More >

Eun-Joo Choi¹, Yun-Jung Choi^2,*

International Journal of Mental Health Promotion, Vol.25, No.1, pp. 21-29, 2023, DOI:10.32604/ijmhp.2022.022641 - 29 November 2022

Abstract This study aimed to explore citizens’ emotional responses and issues of interest in the context of the coronavirus disease 2019 (COVID-19) pandemic. The dataset comprised 65,313 tweets with the location marked as New York State. The data collection period was four days of tweets when New York City imposed a lockdown order due to an increase in confirmed cases. Data analysis was performed using R Studio. The emotional responses in tweets were analyzed using the Bing and NRC (National Research Council Canada) dictionaries. The tweets’ central issue was identified by Text Network Analysis. When tweets… More > Graphic Abstract

Choon-Hong Tan¹, Ah-Choo Koo^1,*, Hawa Rahmat², Wei-Fern Siew³, Alexius Weng-Onn Cheang³, Elyna Amir Sharji¹

International Journal of Mental Health Promotion, Vol.25, No.1, pp. 99-126, 2023, DOI:10.32604/ijmhp.2022.025004 - 29 November 2022

Abstract The prevalence of mental health problems in both Malaysian and global workplaces has significantly increased due to the presence of the coronavirus disease (COVID-19) pandemic, globalization, technology advancement in Industry 4.0, and other contributing factors. The pervasiveness of the issue poses a huge challenge to improving the occupational safety and health (OSH) of workers in various industries, especially in the digital industry. The emergence of the innovative industry is evident mainly due to the rapid development of Industry 4.0 and the relevant demands of multiple businesses in the digital transformation. Nonetheless, limited studies and academic… More > Graphic Abstract

Sunisa Junnumtuam, Sa-Aat Niwitpong^*, Suparat Niwitpong

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1229-1254, 2023, DOI:10.32604/cmes.2022.022098 - 27 October 2022

Abstract A new three-parameter discrete distribution called the zero-inflated cosine geometric (ZICG) distribution is proposed for the first time herein. It can be used to analyze over-dispersed count data with excess zeros. The basic statistical properties of the new distribution, such as the moment generating function, mean, and variance are presented. Furthermore, confidence intervals are constructed by using the Wald, Bayesian, and highest posterior density (HPD) methods to estimate the true confidence intervals for the parameters of the ZICG distribution. Their efficacies were investigated by using both simulation and real-world data comprising the number of daily More > Graphic Abstract

Marco Frisenda^1,2,*, Stefano Signore¹, Giampaolo Delicato¹, Andrea Giovanni Martinelli¹, Andrea Cantiani¹, Marco Colafelice³, Antonio Tufano², Francesco Del Giudice², Michael L. Eisenberg⁴, Alessandro Sciarra², Vittorio Canale^1,2,*

Canadian Journal of Urology, Vol.29, No.2, pp. 11095-11100, 2022

Abstract This article has no abstract. More >

Rofingatul Mubasyiroh^1,*, Indri Yunita Suryaputri¹, Sri Idaiani², Lely Indrawati¹, Tri Wurisastuti¹, Siti Isfandari¹, Nikson Sitorus¹, Enung Nurhotimah³, Felly Philipus Senewe¹

International Journal of Mental Health Promotion, Vol.24, No.5, pp. 725-737, 2022, DOI:10.32604/ijmhp.2022.021452 - 27 July 2022

Abstract The extraordinary situation related to COVID-19 makes people worry about their health, family health, work, finances, and other daily activities. This condition can lead to social unrest, which has consequences for mental health problems. This study aims to determine the mental health consequences at the beginning of the COVID-19 pandemic in Indonesia. This is a cross-sectional study involving a target population aged 18 years and over who had access to electronic communication devices. An online questionnaire was randomly distributed and snowballed throughout 34 provinces in Indonesia. The study was conducted from 2 to 4 May… More >