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For more than a year and a half, educators and students have been navigating the stormy seas of remote teaching-learning. After months of the coronavirus epidemic and countless research on its impacts on university teaching and learning, the repercussions of this unparalleled state of affairs are only partially known. This paper adds to the current research on how university teachers have dealt with it in an effort to understand the impacts on teaching the course of "design studio" that has never been taught online before. However, many are returning to in-person classes or planning to use a blended teaching approach. As a result, the second purpose of this study is to learn more about how teachers plan to teach in the future, which is an innovative topic that has piqued our attention. Six professors agreed to let us observe their design studio classes for the total period of 8 months spread over three semesters from 2020 and 2021. The majority of students had favorable experiences with online teaching and examinations, and most would welcome this format in the future, according to an analysis of these programs. The same cannot be said for teachers, who see this method of instruction as time-consuming and demanding. Simultaneously, this paper aims to highlight the advantages of remote teaching-learning models in teaching design studios, suiting students' educational needs, and aiding in their professional growth as architects. The research stems from the hypothesis that the pandemic will have a long-term impact on lesson planning, and opens a fresh discussion about multi-mode educational implications that learners, teachers, and other education actors should consider in the next phase of post-COVID-19 era before deciding on going back to the pre-COVID-19 pandemic classroom teaching-learning. [ABSTRACT FROM AUTHOR]

Promotional activities are among the most significant aspects in ensuring continual visits and engagements from visitors to heritage sites and institutions, including museums. An ineffective marketing technique will make it challenging to attract visitors and communities. This leads to the decrease number of visitors, undermining the fundamental mission of museums as an informal educational establishment for the public. However, few studies have been done on a promotional strategy for museum management in Malaysia. This paper seeks to bridge the gap by exploring the current museum's marketing technique, using the Kelantan State Museum as a case study. It aims to look further into the museum's promotional strategy, the involvement of responsible bodies, and the challenges in promoting the museum, specifically during the covid-19 pandemic. The research employed a qualitative design with purposeful approaches and snowballing techniques by interviewing the personnel at the Kelantan State Museum. The collected data were then analysed by applying Braun and Clarke's six-step thematic analysis methodology. The results identified three main themes: marketing strategies and activities, collaboration between stakeholders and challenges going forward. The overarching findings highlighted major stakeholders and their degree of participation in museum promotion. This paper also discussed the challenges posed by the museum management in promoting their establishment to the public. This include issues such as visitor expectations, funding cuts and digital adaptation; and the cessation of many museum hubs for physical visitations due to the Covid-19, leading to new rules being presented to adapt to the recent changes in ensuring visitors' safety. It is believed that the new norm has impacted the museum management's efforts to promote their institution, necessitating the development of new strategies to increase public participation. [ABSTRACT FROM AUTHOR]

The Coronavirus Disease 2021 or COVID-19 has affected almost all individuals around the globe. Consequently, Malaysia is one of the nations that has been facing tremendous changes in various sectors due to COVID-19. As the number of positive cases is on the rise, the Malaysian government has executed its National COVID-19 Immunization Program to reduce the spread of COVID-19 and the severity of disease in case a vaccinated person is infected. However, there are also individuals who have contributed to vaccine refusal due to many factors including misinformation about vaccines, religious beliefs, lack of knowledge, and awareness. Therefore, this paper presents a combination of instructional design and cognitive load theory named CoLoMo model, to increase the awareness of COVID-19 among parents. The CoLoMo model is a theory for mobile application development involving three elements in mobile instruction design which include platform, design, accessibility, and design page. These elements have been chosen prior to the target users which are parents or adults. The three cognitive load theory types in this model are intrinsic, extraneous, and germane cognitive load. The combination of the mobile interaction design and cognitive load theory types will affect the user's cognitive performance which are concentration, learning capabilities and attributes. This paper also discusses the previous research on the implementation of cognitive load theory through mobile applications. Several strategies that emphasize different relevant cognitive processes which are useful to consider when developing mobile applications are also discussed. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has forced many higher education institutions (HEIs) to implement online learning. Various courses including entrepreneurship were conducted by using online methods, such as synchronous and asynchronous. However, the achievement of course outcomes through these two methods has yet to be examined. As such, this paper presented the level of entrepreneurial intention exhibited by university students after they have completed an entrepreneurship course through online learning method. It further compared the entrepreneurial intention level between students who attended the course through synchronous and asynchronous online learning modes. The data were collected through questionnaire survey method, in which only quantitative data pertaining to students' background and entrepreneurial intention were gathered. A total of 315 students were randomly selected from a population of full-time students who have completed an entrepreneurship course in a local university. They were required to respond to an online self-administered questionnaire. Informed consent was obtained prior to the process of data collection and responses were treated anonymously. As for data analysis, descriptive and inferential statistical analyses were performed. Specifically, mean and standard deviation were used to determine the level of entrepreneurial intention. Internal consistency was used to confirm the reliability of data. While independent sample t-test was carried out to compare the entrepreneurial intention level between students from synchronous and asynchronous learning modes. The data demonstrated that differences were found in entrepreneurial intention between the two groups of students. Therefore, it could be concluded that synchronous and asynchronous modes yielded different level of entrepreneurial intention among students. This paper provided new insight on online learning for entrepreneurship course, especially in the COVID-19 pandemic period in which most courses were conducted online. It was also useful for HEIs to assess the effectiveness of online learning in delivering entrepreneurship course. [ABSTRACT FROM AUTHOR]

Since the Covid-19 pandemic, videotelephony has become a popular communication method. Some communication, like business meetings, school classroom activities, market transactions, etc, should be replaced with online ways because of the social distancing policy. But not all people can easily use the online meeting platform. Some still struggle with bandwidth consumption of online meeting (video conference) activities. They need more low bandwidth consumption in doing video conferences because high bandwidth consumption means high costs. This paper discusses lowering video conferences based on turning on or off cameras. Because of this case, some platforms create their video conference applications. One of the popular video conference applications is Zoom Meeting. The data used in this paper are collected by using 30 computers in a laboratory. Firstly, the total time every user turns on his camera and his bandwidth consumption is investigated, every computer is set to turn on its camera for 1, 2, 3..., 30 minutes. The result shows there is no relation between them. Secondly, the number of people who turn on their cameras and the bandwidth consumption of every user is collected. All computer cameras are turned on in the first observation, and then a computer turns off its camera every three minutes. The result shows a relation with decreasing trend between both variables, but there is heteroscedasticity between them. The data is reduced until only fifteen computers turn on its camera until one computer. The result is a strong connection between both variables. It is caused by the gallery view method is using in the observation. Lastly, we recommended only speaker view in doing Zoom Meetings. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak impacted drastically to education and most of educational institutions started preferring online education for students. However, after the settlement of the pandemic there is uncertainty among people about whether they should prefer online education for furthermore or start in offline mode to make it more interactive, so this paper is about an analysis of people's sentiments and emotions through Tweets about COVID-19 Education. This paper aims to study the reaction of people around the world toward online education during COVID-19. This study is conducted on the basis of the responses of students, teachers, parents, college professors, etc. We started with labeling the data into three sentiments namely positive, neutral, and negative and for validation then we used Machine learning (ML) classifiers namely, Logistic regression, Decision tree, Random Forest, Multilayer Perceptron (MLP), Naïve Bayes, Support vector machine (SVM), K-nearest neighbors (KNN), and XG-Boost. Then we performed emotion detection by considering 5 emotions namely happy, surprise, sad, fear, and angry and for validation we used ML classifiers. After applying all these ML approaches, the XG Boost ML classifier achieved the highest accuracy of 94% in classifying the tweets as positive, neutral, or negative, and 96% accuracy in classifying the tweets as happy, surprised, sad, fearful, or angry. [ABSTRACT FROM AUTHOR]

COVID 19 disease has spread worldwide, disrupting the economy, society, education, and health. It became crucial to understand the transmission curve and identify the best action in combating this highly transmissible epidemic. Epidemiological parameters of the deterministic Susceptible-Infected-Removed (SIR) model are widely used in explaining the characteristics and behavior of the disease spreading. Disease like COVID-19 is highly influenced by the uncontrolled factors of randomness, hence in this paper, the deterministic susceptible-infected-recovered-death (SIRD) model is extended to the stochastic SIRD (SSIRD) model. SSIRD model takes into consideration the noisy behavior of the process which explains the uncontrolled effects of the COVID-19 outbreak. The epidemiological parameter of the model changes throughout the epidemic due to external factors such as enforcement and public obedience to the control measures as well as the changes in healthcare facilities. These parameters need to be estimated. This paper estimates the epidemiological parameters of the SSIRD model using the Markov Chain Monte Carlo (MCMC) method of the Metropolis Hasting algorithm. The COVID-19 data from Malaysia and Indonesia are used and the dynamical behavior of the COVID-19 outbreak in both countries is simulated. The results show the parameter changing due to the uncontrolled factors influencing the trend of the pandemic curve. [ABSTRACT FROM AUTHOR]

The implementation of Community Activities Restrictions Enforcement (PPKM) during the Covid-19 pandemic reduced activities in the transportation sector. This paper presents the measurement of Carbon Monoxide (CO) concentrations during the PPKM in Makassar City, Indonesia. The samples were collected weekly from August to September 2021 from two traffic-heavy roads using Tedlar bags and a vacuum pump and then analyzed using the Non-Dispersive Infrared method (NDIR). Results showed that the average concentrations of CO on the first street in the morning, midday, and afternoon were 826.63±83.34 µg/m3, 685.65±57.43 µg/m3, 861.6±59.79 µg/m3, respectively; and on the second street were 875.46±77.80 µg/m3, 741.80±62.95 µg/m3, 833.04±44.80 µg/m3, respectively. These CO concentrations measured during the PPKM are lower than those measured before the PPKM on the same sites, reported in another paper. The concentrations are also much lower than those of the Air Quality Standard in Makassar, 30,000 µg/m3. This finding implies that similar policies to reduce traffic and pollution, such as car-free-day, should be enacted to improve air quality. [ABSTRACT FROM AUTHOR]

Today, the world is exposed to many widespread health crises. One of these crises is the emergence and spread of the covid-19 virus, where any person becomes infected with this disease through the rapid transmission of infection between people, either by palpation or by inhaling droplets of carriers of this virus. Hence, there is a need to build a tracking system to respond quickly to problems. This paper proposes using one of the unsupervised machine learning algorithms, the K-Means Clustering Data, to determine the areas with the most significant percentage of infections by dividing them into infected and uninfected human groups. Where the infected persons are divided into three high groups (C1), medium (C2), and low (C3), and follow the path of the infected persons using Google Maps. The contribution to this paper is to support appropriate decision-making by public health authorities by predicting endemic areas and how to address problems that occur as they can use this system to reduce other infectious diseases. [ABSTRACT FROM AUTHOR]

In this proposed system we have achieved the benefit of online voting as we all know that internet and gadgets are very good. In this pandemic situation we can prefer Online Voting System instead of offline voting system. By using the Online Voting System, we can avoid the crowd, gathering and to overcome the Covid cases. For Example, nowadays people are not maintaining social distance that can causes more Covid cases. In order to save the time and life's of the citizens of nation we can prefer Online Voting System project. This paper presents an effort to leverage benefits to achieve an effective scheme for online voting. The election can be conducted in two ways: By Paper Polling form and Mechanized Voting Form. Web-based voting refers to the decisions made by robotized polling forms. The internet casting a ballot framework is profoundly evolved and the web-based surveying framework can be supplanted by precisely and legitimately casting a ballot on the web and prompt outcomes to provide the security implementation. User-based voting will benefit from this system. Both the implementation and its implementation are made up of two parts: There are two sections: one for voters and one for administrators. In these protocols, the voter segment can be found at home or work, or through a device that allows the voter to access the information and grant data authentication. It is up to the administrator section to perform or allow the functions of a voter based on validation of voter ID, candidate registration, verification and the database result. A One Time Password module is the mainly used for the security implementation. In this research, each time a user logs in to the system, a unique password is generated. Every time a user logs on to complete an operation, an OTP is sent to their registered mobile number. This OTP is made up of a series of random digital numbers, and it changes over time. [ABSTRACT FROM AUTHOR]