Covid-19 Pandemic: Help-seeking for Smoking Cessation among Adult Smokers in Malaysia during the Full Movement Control Order (FMCO)

INTRODUCTION: In Malaysia, death due to tobacco smoking habits recorded as more than 23 thousand yearly. Hence smoking cessation should be emphasized to reduce the annual mortality and morbidity. The purpose of this study is to identify the help-seeking behavior in smoking cessation among adult smokers and to determine its predictive factors during the Full Movement Control Order (FMCO) in Malaysia. MATERIALS AND METHOD: Data were collected from cross-sectional surveys of Malaysian adult smokers. The questionnaire was distributed online through the official social media account of the Ministry of Health Malaysia (MOHM) which commenced from 31st May 2021 in conjunction with the World No Tobacco Day. A multivariate binomial logistic regression was employed to analyze the relationship model between the predictors with the help-seeking for smoking cessation. RESULT: Out of 2,545 Malaysian adult smokers who have responded, 2,303 were males (90.5% of respondents) with mean age(sd) of 34.82(8.11) years (18 to 77 years). Slightly half (n=1353, 53%) have reported seeking help for smoking cessation and (n=1468, 57.7%) reported being unaware of the quitline services. Factors, such as quit smoking attempt (OR;1.844, 95% CI = 1.384-2.458), Covid-19 pandemic situation (OR;1.841, 95% CI=1.553-2.183), being married (OR: 1.279, 95% CI = 1.04-1.57), unaware about quitline services (OR;0.660, 95% CI = 0.557-0.781), non-alcohol drinkers (OR;0.658, 95% CI=0.473-0.916) significantly predicted the behaviour of help-seeking for smoking cessation. CONCLUSION: The results of this study would potentially support public health efforts in Malaysia in further enhancing health promotion and education programs as well as further strengthen the policy towards quit smoking issues © 2023, IIUM Medical Journal Malaysia.All Rights Reserved.

Adaptive Learning Systems based on ILOs of Courses

Nowadays, the use of e-learning techniques and methods is a very important challenge due to the importance of digital transformation to all countries. Firstly, the spread of the COVID-19 virus all over the world. Secondly, all students need to study their courses remotely from home to reduce the communication with others to save their life. All teachers need to engage their students effectively to study an online course, get more knowledge and high results at the end of these courses. Data mining is the best tool used to find a hidden pattern. We used an educational data mining tool to help teachers find the pros and cons of using an e-learning course with their students. We need to classify students on these online courses according to their ability to understand materials and quizzes, or assessment methods of the course, by making adaptive e-learning courses. In this paper, we will show the importance of using adaptive e-learning courses and the challenges faced by authors to build these systems, and we will list the different methods used with adaptive learning like gamification, brain-hex models, facial emotions, and we will also list a survey about other authors' techniques and methods used to find the student's learner style. We build a new proposed model of ILOs(Intended Learning Outcomes) adaptive learning with the emotion-based system to let the system find the student's learning style and build the material according to their skills and knowledge outcomes from the course and engage the use of facial emotion while taking the quiz to predict the student's results and the topics he/she needs to study more via our system to achieve high grades and knowledge. Our system finds that the visual students have the highest grades with 75%, followed by kinesthetic with 70% and the lowest grades in auditory with 50%. © 2023, World Scientific and Engineering Academy and Society. All rights reserved.

Covid-19 Pandemic: Help-seeking for Smoking Cessation among Adult Smokers in Malaysia during the Full Movement Control Order (FMCO)

INTRODUCTION: In Malaysia, death due to tobacco smoking habits recorded as more than 23 thousand yearly. Hence smoking cessation should be emphasized to reduce the annual mortality and morbidity. The purpose of this study is to identify the help-seeking behavior in smoking cessation among adult smokers and to determine its predictive factors during the Full Movement Control Order (FMCO) in Malaysia. MATERIALS AND METHOD: Data were collected from cross-sectional surveys of Malaysian adult smokers. The questionnaire was distributed online through the official social media account of the Ministry of Health Malaysia (MOHM) which commenced from 31st May 2021 in conjunction with the World No Tobacco Day. A multivariate binomial logistic regression was employed to analyze the relationship model between the predictors with the helpseeking for smoking cessation. RESULT: Out of 2,545 Malaysian adult smokers who have responded, 2,303 were males (90.5% of respondents) with mean age(sd) of 34.82(8.11) years (18 to 77 years). Slightly half (n=1353, 53%) have reported seeking help for smoking cessation and (n=1468, 57.7%) reported being unaware of the quitline services. Factors, such as quit smoking attempt (OR;1.844, 95% CI = 1.384-2.458), Covid-19 pandemic situation (OR;1.841, 95% CI=1.553-2.183), being married (OR: 1.279, 95% CI = 1.04- 1.57), unaware about quitline services (OR;0.660, 95% CI = 0.557-0.781), non-alcohol drinkers (OR;0.658, 95% CI=0.473-0.916) significantly predicted the behaviour of helpseeking for smoking cessation. CONCLUSION: The results of this study would potentially support public health efforts in Malaysia in further enhancing health promotion and education programs as well as further strengthen the policy towards quit smoking issues. [ FROM AUTHOR]

Adaptive Learning Systems based on ILOs of Courses

Nowadays, the use of e-learning techniques and methods is a very important challenge due to the importance of digital transformation to all countries. Firstly, the spread of the COVID-19 virus all over the world. Secondly, all students need to study their courses remotely from home to reduce the communication with others to save their life. All teachers need to engage their students effectively to study an online course, get more knowledge and high results at the end of these courses. Data mining is the best tool used to find a hidden pattern. We used an educational data mining tool to help teachers find the pros and cons of using an e-learning course with their students. We need to classify students on these online courses according to their ability to understand materials and quizzes, or assessment methods of the course, by making adaptive e-learning courses. In this paper, we will show the importance of using adaptive e-learning courses and the challenges faced by authors to build these systems, and we will list the different methods used with adaptive learning like gamification, brain-hex models, facial emotions, and we will also list a survey about other authors' techniques and methods used to find the student's learner style. We build a new proposed model of ILOs(Intended Learning Outcomes) adaptive learning with the emotion-based system to let the system find the student's learning style and build the material according to their skills and knowledge outcomes from the course and engage the use of facial emotion while taking the quiz to predict the student's results and the topics he/she needs to study more via our system to achieve high grades and knowledge. Our system finds that the visual students have the highest grades with 75%, followed by kinesthetic with 70% and the lowest grades in auditory with 50%. © 2023, World Scientific and Engineering Academy and Society. All rights reserved.

Moderating Effects of Personality Traits On Online Learning Transition and Acceptance Among Culinary Arts Students

Many Higher Education Institutions (HEI) students had to make an immediate change to online learning from the conventional face-to-face mode due to the COVID-19 pandemic and Movement Control Order (MCO) imposed by the government. Learning practical courses such as Culinary Arts via online without application or practical work generated bigger challenges for HEIs. It was emphasised that Culinary Arts education depends predominantly on hands-on application and training. The purpose of this study is to investigate Culinary Arts program students' acceptance with online learning methods (hands-on learning at home) and how the Big Five Personality Traits (BFPT) could have an impact on the relationship. A total of 234 responses from Culinary Arts based program students of six (6) HEIs in Malaysia were obtained and analysed using SPSS statistical software. Findings showed that students were able to accept the transition in learning from face-to-face to online learning. However, it was found that BFPT did not have a significant moderating impact on the relationship between Learning Transition and Online Learning Acceptance. The results could help HEIs in adapting to the new Learning Transition without compromising the quality of the graduates and the curriculum set by the institutions. In addition, the results of this study could enhance further investigations on Online Learning Acceptance to a wider scope and type of study programs. © Universiti Tun Hussein Onn Malaysia Publisher's Office.

Covid-19 Detection Based on Cascade-Correlation Growing Deep Learning Neural Network Algorithm

COVID-19, is a dangerous disease, that is widely spread among humans by inhalation of the virus, and it harms and may damage the lung. The aim of this paper is to detect COVID-19 using our new algorithm called “Cascade-Correlation Growing Deep Learning Neural Network Algorithm (CCGDLNN)” from Computed tomography (CT) scan images of a patient’s chest. We apply the algorithm over 48,260 computed tomography scan images from 377 persons divided into 282 normal persons and 95 patients were infected by COVID-19. Our system is divided into two stages: Firstly, the system removes unclear computed tomography-scan lung images by analyzing them. Secondly, we run our algorithm based on the exception model that begins with a small network without any hidden layers but has input and output layers only. The algorithm after that, adds new neurons and connects them to the last layer or add a new layer with one neuron. Finally, after performing these two stages, the system can be able to detect COVID-19 patients from their lung computed tomography-scan images. We train the data using two different models and compared the results with our model. In the image classification process, our model achieved 98.8% accuracy on more than 7996 test images. © ISCA.

The influence of Covid-19 on E-commerce towards online shopping

The COVID-19 emergency is resuscitating a growth of online business towards new firms, clients and sorts of things, likely including a drawn out move of web business exchanges from luxuriousness item and endeavors to standard necessities. It in addition incorporates how strategy producers can use the limit of front line change in retail and related regions to help business assortment and to update social secluding, while at the same time guaranteeing that nobody is abandoned. Retail and food association’s deals among February and April 2020 were down 7.7% stood apart from a near period in 2019. In any case, deals stretched out for business areas and non-store retailers (all things considered online business providers) by 16% and 14.8% freely. Subsequent to running the model the exhibition demonstrate that the precision of the CHAID model is 89.09% and Classification Error is 10.91% this is the best Operator for anticipating Types of Goods that purchasers will purchases as contrasted and Decision Tree and Random Tree as showing in Table 8 and showed in Figure 11. The results of this contextual analysis plainly demonstrate that CHAID is appropriate porter for identifying Types of Goods that customer demeanor for taking choice for buying or Not. One preliminary for predicting buyer lead for E-exchange online through 1000000 models and 8 apparent credits. The expert parceled the data to rule regions at first is getting ready data equal 90% and second is attempting data equal 10% In the wake of running the CHAID pattern, the CHAID made as appeared in Figure 4 by Rapid miner Tool for Invoice Types for items is the most Attributes in all Attributes. Execution vector CHAID Operator for Types of Goods quality showed in Figure 6. Precision CHAID Model showed in Figure 4 Classification mistake CHAID Model showed in Figure 5. Disarray Matrix CHAID Model showed in Figure 6. X Plot CHAID Model showed in Table 4. Accuracy Decision Tree Model showed in Table 5. Characterization mistake Decision Tree Model showed in Figure 9. Disarray Matrix Decision Tree Model showed in Figure 8. X Plot Decision Tree Model showed in Figure 8. Accuracy Ranom Tree Model showed in Table 7. Order blunder Ranom Tree Model showed in Figure 9. Disarray Matrix Ranom Tree Model showed in Figure 9. X Plot Ranom Tree Model showed in Figure 10. © 2021 Little Lion Scientific.

Pharmacy education during and beyond COVID-19 in six Asia-Pacific countries: Changes, challenges, and experiences

The COVID-19 pandemic shifted pharmacy education to remote teaching and learning (T&L) strategies. To share changes, challenges, and experiences in pharmacy education among member countries, the Federation of Asian Pharmaceutical Associations hosted a 1.5-hour webinar on 15th May 2020. Questions collected during registration and the live webinar were coded using thematic analysis. A total of 794 participants from 18 countries/territories registered, while 346 attended the webinar. Of 445 questions, 392 were from the registration form and 53 from the webinar. All questions were coded to four major themes: new normal pharmacy education, ethics and safety, material accessibility, and teaching and evaluation methods. Questions during registration were mostly on new normal adaptation (n=79), T&L formats (n=65), and access/resources/ sustainability (n=59). Webinar questions were mainly on assessment format (n=13), laboratory skills (n=9), and access/resources/sustainability (n=9). The webinar provided an opportunity to quickly identify issues regarding pharmacy education during the COVID-19 pandemic for prompt actions and further research.