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Moodle-based Learning Management Systems have been widely used in learning during the Covid-19 pandemic, especially in Indonesia. In this regard, this study aims to identify and describe the implementation of the Whole Language Approach in improving the ability to write simple scientific papers for students at PGRI Yogyakarta University through the Moodle-based Learning Management System. The method in this research is descriptive qualitative with data in the form of descriptions of the results of research implementation supported by observations, interviews, theoretical studies, and relevant research. The results of this study indicate an increase in the ability to write student scientific papers in the experimental class after using the Whole Language Approach through Moodle-based LMS in learning to write. Several aspects that were assessed were structure, systematics, language use, content coherence, and references used. This increase is indicated by the test numbers before and after the use of the Whole Language Approach through the Moodle-based LMS with mean values of 6.5 to 8.8 in the experimental class, and 6.7 to 7.1 in.the control class. This shows that the use of the Whole Language Approach through Moodle-based LMS is proven to improve students' ability to write simple scientific papers. [ABSTRACT FROM AUTHOR]

The Covid-19 epidemic has negatively impacted many industries around the world; the fashion industry is no exception. However, the business activities of the high-end fashion field have found virtual solutions to maintain operations by new technology platforms, which help improve the customer's access to the fashion brand. This paper identifies digital fashion as the most optimal solution not only in the present time but also further in the future of the fashion industry, by collecting the methods, software and tools that many fashion brands have used since 2020 and predicting that the technology industry will explode in the following years. Through analyzing and synthesizing the effectiveness of the software applications that fashion designers have used, the study presents design trends that use technology as a platform to reality clothes on computer screens, clothes that look real without the use of sewing machines and fabrics. These results provide an overview of how top brands communicate, operate and control the fashion industry in the context of the Covid-19 epidemic. On the other side, it helps expand design knowledge and thinking for countries with a growing fashion industry. In general, digital fashion is a fast, convenient, useful and effective transformation and connection between many fashion departments, design and business in the era of industry 4.0. [ABSTRACT FROM AUTHOR]

Advantages of using temporary structures in emergencies were most emphasized during the Covid-19 pandemic, where the need for fast construction and low-cost buildings became the primary requirement. In addition to emergency use, temporary facilities can significantly contribute to the positive transformations of city districts and improve the cultural and social life of residents. However, the government in Sarajevo never proposed solutions involving temporary structures in emergencies, although there was a considerable need for their application in the last two years. With its linear organization of the city, precious historical heritage, unregulated illegal construction, and poor concept of urbanization, Sarajevo is an extraordinarily complex area for any new interventions and transformations. Therefore, applying temporary structures in such a complex urban matrix could be easily interpreted as positive or negative transformations. Unfortunately, the current use of temporary structures has been reduced to the organization of various temporary sales pavilions that most often degrade the city's image and represent negative examples of the transformation of urban zones. For this reason, one of the aims of this paper is to investigate unified, standardized temporary structures that could be used in both previously mentioned situations. These aspirations led us to the following research question: "Which kind of standardized temporary structure could positively contribute to the activation of urban zones and improve the living standards of Sarajevo citizens, but also be used in case of emergency?" The following types of temporary structures were analyzed in this paper: tent constructions, prefabricated modular containers, transport containers, prefabricated wooden buildings, and deployable bar structures. The analyses were conducted according to criteria divided into two groups. Temporary structures were compared according to the first group of criteria, and these analyses resulted in the selection of prefabricated modular containers and deployable bar structures for further analysis. This paper expands criteria established by authors who have previously researched these structures with new parameters, such as system adaptability, local stability of elements, aesthetics, impact on the urban image, system mobility, etcetera. Analyses results point to deployable bar structures as most suitable for the application as a standardized structure. Further analysis was conducted to create guidelines for location selection in Sarajevo and set up the framework for analyzing both advantages and disadvantages of temporary structure applications at these locations. An analysis led us to conclude that applying temporary structures could significantly improve temporary urbanism in Sarajevo and living standards in inactive urban areas further from the town center. Furthermore, we have concluded that temporary camps should be located closer to the town center in emergency cases due to specific infrastructure needs, and this paper assesses some of the potential locations that are not investigated before. Conducted analysis in this paper has proven advantages in using deployable temporary structures, but these structures are in different development stages, and it is essential to update analysis results with structure developments. [ABSTRACT FROM AUTHOR]

This paper is a study about COVID-19 cases in India to analyze and visualize the spread of COVID-19 cases in INDIA. For the analysis, the concept Exploratory Data Analysis (EDA) and some well know prediction models like Prophet Model, ARIMA Light GBM, Random Forest Regressor, XGBoost Regressor have been used to get the correct analyzed result. Furthermore, it has been observed that these prediction models and tools are helpful to analyze and visualize the COVID-19 situation in India and reason to spread it in optimal ways. Here, Matplotlib library has also been used to show the proper output in the form of graphs and charts. Analysis has been done on different Age/Gender Group. The Spike of Cases in India, State-wise Insights, the reason for the spread of COVID 19 cases. So, the main objective of this paper is to do analysis to know the reasonforCOVID-19 cases in India, State-wise Insight and State-Wise Testing, Prediction. To understand the optimal result of growth factors, the concept of Prophet Model ARIMA, LightGBM, Random Forest Regressor, XGBoost Regressor have been used on the data set. In addition, the data set includes the parameters of Age Group, Spike of Cases and Testing in India. From the literature survey, it has been observed that authors have used two and three techniques to analyze the result, but they have not used the methods we stated earlier for optimal result. This paper will provide the State-wise Insight and State-Wise Testing going in India with reason for spreading of COVID-19 cases. [ABSTRACT FROM AUTHOR]

Steel has been widely used & accepted all over India in various sectors. The primary goal of this study is to learn more about steel production and industry growth in India, which has a significant impact on the Indian economy, accounting for around 2% of GDP. The paper briefly discusses steel demands, steel consumption & production rate, etc. The paper explores the background and history of the steel industry, as well as its development over time, such as the establishment of TISCO industries, SAIL, and other factors that contributed to India becoming the world's second-largest steel manufacturer with 111 crude steel MT production. The paper also considers the government initiative scheme & policies (National rail plan, Bharatmala scheme, Jal Jeevan, etc.) with their objective to improve the production & demands of steel. The paper provides a detailed review & vision of the National steel policy of 2017. This paper includes NSP 2017 goals & objective, which gives governments the expectation of reaching 300 MT of finished steel production in 2030-31. The paper also discusses the impact of steel on the infrastructure & construction industry, which consumes a larger portion of steel around 45-62% of total steel. This paper also provides a glimpse of the position of the Indian steel industry after the covid-19 pandemic (shows exports of steel have been grown by 22%) & sector-wise demand for steel. The problems that come along with the development of steel industries like CO2 emission (6.2% of total), waste generation & energy consumption (25% of total) have been also addressed in this paper. In this paper, an attempt has been made by the author to concisely review & explain steel industry growth over the years, the current scenario of the steel industry & its future aspiration through the various researcher reports & outcomes. In this paper, the outcome of the results has been briefly evaluated. [ABSTRACT FROM AUTHOR]

Foreign direct investment (FDI) is a powerful economic growth tool, particularly in today's global environment. The host nations try their best to create an appealing and advantageous investment climate for international investors in order to attract FDI inflows. Both developing countries i.e. India, Bangladesh and even developed economy like USA have dependency on FDI. All these three Bangladesh, USA and India have made significant efforts in recent years to attract FDI, offering a variety of lucrative incentives and benefits. Due to this covid pandemic there was some reduction in the trends of FDI inflows but eventually it again resumed momentum due to policies of the government. In this research paper we have tried to do the comparison between FDI inflows between these three countries and even tried to do the prediction for next 2 years. Statistical tools like Mean, Standard Deviation and CAGR have been used for this research paper. This paper also included the data of FDI inflows into these three countries for 6 years, top 10 countries' share in FDI inflows of these countries and some general comparison is also being done. This paper revealed that Mauritius is the top investor in India whereas in Bangladesh its China and in USA, its Japan. [ABSTRACT FROM AUTHOR]

Distance estimation between two or more objects is a crucial task in the computer vision research area. Moreover, in the era of COVID-19, it becomes an urgent issue as it can enable social distance preserved. Distance estimation could be done using stereo vision (stereoscopic photogammetry) but requires more complexity. In this paper, researchers show distance estimation is possible using only monocular vision. We propose a deep-learning based method, Mobilenet Single Shot Detector (MSSD), combined with Camera Calibration to detect objects and estimate the distance between them in the setting of monocular vision. To verify the robustness of the proposed method, we created a dataset video using a monocular camera. The experimental results showed the performance of the proposed method could estimate the distance properly using the recorded dataset. [ABSTRACT FROM AUTHOR]

COVID-19 has shown that risk is not one-dimensional. The influence of Covid-19 on risks arising due to breaches by Third-party and nth party ecosystem on organizations has been quick with wide range of consequences like reputational and financial losses. Although automation has been around and being implemented for quite some time now, there is a pressing need to incorporate intelligent decision-making systems in the outdated automated processes and practices that used rule-based manual risk assessments. The improvements in the field of Artificial Intelligence, Robotic Process Automation and related technologies have given rise to intelligent process automation, which can take advantage of these underlying technologies to effectively provision end to end actions on the risks arising due to third-parties. In academic research domain this area has remained under-focused. Hence this study tries to address this gap by introducing how intelligent process automation can aid third party risk management processes and proposes a conceptual model for understanding system can be put to use. Key challenges and opportunities are also provided in this qualitative research paper based on narrative literature approach. The study provides implications to developers for designing and developing Intelligent process automation tools for assessing risks associated with third-parties, it helps academicians to explore latest developments and technologies in the automation domain and to the employees of the existing organizations as it will help gain perspective of the underlying technologies involved in IPA and TPRM. [ABSTRACT FROM AUTHOR]

The world economy is transformed by a number of factors, such as globalization, privatization, government reforms, international political upheaval, hyper competition, trade and commerce activities, and market dynamics. In addition, the COVID-19 pandemic outbreak influences the marketplaces, causing volatility, uncertainties, complexities, and ambiguities to a great extent. On the other hand, most of the firms were struggling for existence. On the other hand, notable corporations like Amazon make huge profits. It was digital marketing that empowered them to continue business activities. It is imperative for firms to make effective use of technology for strategic management, competitiveness, and cost-effectiveness. The current paper investigates how digital marketing can be integrated with business innovation strategies to maximize resource utilization for the long-term development of people, the planet, and profits. Digital interactive platforms and "service innovations" enabled by artificial intelligence, chatbots, and robotics have gained momentum. Along with the competitive advantages of digital marketing, its implications are also considered in the present study. Innovation is the key to success. The world is simply "a click away." The paper examines best practices to foster a culture of innovation in the workplace by offering customized and affordable products and services to customers. [ABSTRACT FROM AUTHOR]

Teaching is an axiomatic activity for a lecturer. The teaching strategies are prepared before the teaching start. It might be a semester before, or even a year before the teaching activity. This will be challenging for EFL lecturer who teach in a vocational higher education that prepares the students with full skills to work in the field (having a real-world skill). Today, a challenge disrupting well-planned teaching strategies is the sudden Corona Virus or Covid-19 pandemic. This virus forces the world activities online to keep distance and stop the spread of the virus, including Indonesia. Luckily, the application of strategies is quite flexible, the lecturer could change it and adjust to the current changing situation [1]. Also, the lecturer usually has a backup plan or plan B to prepare for the unexpected challenges that emerge suddenly in the process of teaching and learning. Thus, this paper attempted to find interesting strategies that lecturers choose to achieve the goals of the vocational higher education, in some classes with field-skill practice goals in a vocational higher education. Specifically, this paper attempted in the English Department, Politeknik Negeri Padang, during the Covid-19 pandemic. [ABSTRACT FROM AUTHOR]

The social media and internet has sparked an unparalleled spread of incorrect information. The world relies on information. It becomes even more apparent during times of emergency or crisis, like the pandemic of COVID-19. COVID-19 outbreak is a continuing disaster that is predicted to now have a long-term impact on almost all countries throughout the world, including mixed results, thus it seems to dominate many other incidents. Many models and innovative techniques have been introduced for the purpose to deal with the detection of fake news. This paper firstly presents a clear picture of different categories of fake news including rumours (which can be either fake or real) in a tabular form and classifies them on the basis of parameters like its genuineness and intentions. Further the paper discusses several false news detection techniques proposed to track COVID-19 related fake news and compares them on the basis of parameters like learning technique, modal approach, dataset used etc. Hence the work presented in the paper provides adequate knowledge of the need, categories; different state-of-the-art technique used and recommends some effective countermeasures to deal with misleading information. [ABSTRACT FROM AUTHOR]

"Social media is the fastest way of reducing the social barriers and helps to connect people," but this statement turned out to be true and very effective when the world witnessed the first wave of the devastating epidemic called covid-19. Information technology has always been an essential part of organizations and strongly affects human resource practices, policies, and processes. Today, Organizations are also moving towards building smart, incorporating green HRM, and adopting sustainable activities, but the scenario that has changed with the emergence of covid-19 was never. The pandemic has forced organizations to incorporate many changes for which they were unprepared as they suddenly had to take their ventures into "unknowns and unknows." Therefore, the only way that seems to be out of all this was the use of artificial intelligence. During the pandemic, government restrictions on social distancing and lockdown have limited people staying at home and working remotely. The work from the home policy has helped the organizations continue their workings and enhanced their technology- based green human resource practices by minimizing their carbon footprints by reducing power and energy consumption, transportation and fuel, paperwork, documentation, and reducing organizational waste. Therefore, our papers aim to present a need to develop an artificial intelligence-powered work-from-home culture, which will help avoid the unnecessary presence of employees in the organization and help the organizations increase their profits and corporate image by reducing their carbon footprints. Method: The study is quantitative, and the data is analyzed using linear regression in SPSS. The data of 215 employees was collected, and the results have analyzed that AI-enabled work-from-home culture has a positive effect on strengthening green HRM. Implication: The study will help create an awareness in the organizations of the need to incorporate work from the home culture in organizations to reduce their carbon footprints and lead themselves towards sustainability and growth with the help of AI. Originality: There have been various kinds of research on green HRM, but the sudden outbreak of covid-19 has resulted in work-from-home culture and increased use of AI strengthening the green HRM aspects and helping the companies in sustainable development. Therefore, our paper discusses the effect of AI-enabled work from the home culture in strengthening green HRM. [ABSTRACT FROM AUTHOR]

Nowadays, there are numerous and wide variety of online learning platforms (OLP) available for students and educators. In order to make the online learning process run smoothly, educators need to be smart in choosing a good medium to use. Many factors should be considered concurrently during decision-making processes. As a result, Multi Criteria Decision-Making (MCDM) method, which seeks to pick the best option from a set of choices, can help decision makers in making suitable and unambiguous judgments in difficult situations. To evaluate such difficulties, this paper combines neutrosophic set with the Best-Worst Method (BWM) approach. The neutrosophic set is important in solving indeterminacy problems and it is more suitable to solve real-world decision-making problems. Besides, in the MCDM problem, similarity measures may be used to describe how different alternatives vary and are similar to one another. However, it appears that the existing similarity measures seem to have a few major weaknesses and inherent problems, such as producing unreasonable results in some cases. Therefore, to cater such problems, this paper introduced a novel single-valued neutrosophic best-worst method, SVN-BWM approach with improved similarity measures of the single-valued neutrosophic set (SVNS) model into a case study of selecting the best online learning platforms based on educators' preferences. The data are collected from six decision makers (DM) among Mathematics lecturers of Universiti Teknologi MARA (UiTM) Shah Alam. From the findings, it is found that Google Meet is the most preferred online learning platform. [ABSTRACT FROM AUTHOR]

With the strike of the covid-19 outbreak end of 2019, the styles of teaching and learning at the higher institutions all over the world were forced to online platforms. This paper discusses the difference level of understandings in solving the hypothesis testing problems for four different groups of non-statistical students at the Universiti Teknologi MARA (UiTM), Shah Alam, Malaysia. Methodology: This observational study involved 102 students comprises of four groups (A, B, C and D) from the Faculty of Hotel and Tourism Management, UiTM Shah Alam who enrolled for Statistics for Business and Social Sciences during academic semester March – August 2022. The scores of test which consist of six problems related to hypothesis testing for one population mean, the difference of two-population means, dependent (paired) samples, Analysis of Variance (ANOVA), test of association and Regression were analyzed using the Welch's ANOVA test. Result: The findings clearly show that whilst the students from different groups received the same method of lectures and guidance from the same lecturer, the scores for test were significantly different between two groups; between A and C and between C and D. The scores for Question 1 – Regression analysis and Question 3 – Analysis of Variance (ANOVA) questions were significantly different between group C and D and the scores for Question 1 only between group B and C. In addition, this paper innovatively identifies prevalent statistical errors committed by students, contributing to enhanced understanding and improved learning in statistics. [ABSTRACT FROM AUTHOR]

The prolonged COVID-19 pandemic has severely hampered microentrepreneurs' economic activities and pushed them towards poverty and vulnerability. In this situation, digitalising business is considered an effective means to resume business activities and, thus, scale-up micro-business owners' financial status. By relying on the literature review method, this paper offers a conceptual model for micro-business digitalisation focusing on its sustainability governance through data acquisition. Various points such as electronic financial transaction systems (e-wallet), e-marketplace, integrated social networks, crowdfunding sources, and the other stakeholders' involvement have been taken as the potential gateways for data acquisition. This model is deemed a convenient e-platform to the Malaysian underprivileged micro-entrepreneurs while being effectively and sustainably governed by the authority. The outcomes of this paper will help policymakers to create an alternative platform to rescue impoverished micro-business holders. It will further create opportunities for future research. [ABSTRACT FROM AUTHOR]

COVID-19 pandemic causes devastating impacts globally, including Surabaya. One of the significant impacts is that the increasing number of death cases, forcing every activity to comply with the health protocol for people safety. DISPENDUKCAPIL Surabaya (City Council for Civil Registration) faces the condition of increasing demand for the death certificate while the health protocol is obliged. To overcome this condition, DISPENDUKCAPIL transforms their service system from KLAMPID to KLAMPID COVID and the latest one into KLAMPID ONLINE. These transformations intend to reduce the crowd and direct human contact by shifting the activity into online activity. These transformations are proven in reducing transportation and human contact, however, increasing electricity and internet consumption. This study tries to assess the environmental impact change from each transformation. The SimaPro software calculation results for KLAMPID, KLAMPID COVID-offline submission, KLAMPID COVID-online submission, KLAMPID ONLINE-offline submission, and KLAMPID ONLINE-online submission generate 77.67 mPt, 169.31 mPt, 153.69 mPt, 61.74 mPt, and 54.53 mPt of environmental impact. It shows that there's an environmental impact jump during the KLAMPID COVID system because of the COVID-19 pandemic even though there is a reduction in transportation and paper use. [ABSTRACT FROM AUTHOR]

Coronavirus Disease-2019 (COVID-19) pandemic discovered in 2019 was caused through Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2). It is spreading rapidly as a communicable disease which has been declared as a pandemic by WHO. This virus was firstly reported in people of China who were associated with the Huanan seafood wholesale market of Wuhan. COVID-19 pandemic has challenged the lives of millions of people in India butdiabetic patients are at high risk of hospitalization and mortality during the COVID-19 pandemic. So, they need to deal effectively with the difficulty of its treatment as diabetes acts as a risk factor for the severity of this disease. This paper presents a statistical analysis of the information given by 125 diabetic patients in India. The effect of this information was determined through analysis of variance (ANOVA) using SPSS. Further, a bibliometric analysis of 51 Indian publications indexed in Scopus related to diabetic patients having COVID-19 was also conducted. The aim of this paper is to briefly study the effect of coronavirus on diabetic people as well as to study the recent research trends of present researches togive a better knowledge of COVID-19 in diabetic patients. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic has fueled the shift towards a more digital world and incremental online shopping behavior changes. It also highlights how decision-makers can leverage the potential of digital transformation in retail and related areas to support business adaption and enhance their competitive ability. This paper measures the top eight e-commerce sites' technological innovation efficiency in the US market from 2016 to 2019 using the data envelopment analysis (DEA) Malmquist model. The proposed model considers total assets, total equity, portfolio investment, and total liabilities as input factors, while total revenue and net income as output factors. This paper aims to provide comprehensive managerial implications to the e-commerce industry for assessing technological evolution effects with other competitors. The results show that the best performing e-commerce site is DMU2-eBay, followed by DMU4-Target and DMU1-Amazon. In contrast, DMU5-Groupon and DMU7-Costco showed the worst performance during the research periods. The current study assists e-commerce practitioners and investors in determining key performance indicators, aiming for effective strategies, and expediting the industry toward sustainability development. [ABSTRACT FROM AUTHOR]

Online examinations and E-learning systems have gained more attention in the educational institutions nowadays due to the spread of the COVID-19 epidemic. Unlike traditional exams, web-based or online examination systems are very useful to prepare an exam, save time and money and provide accurate results. In this paper, new e_Exam system is developed to give us efficient exam in terms of saving time and cost and effort and cheating probability The proposed system, named Web-Bases Examination System (WBES), is implemented by using PHP, MySQL and a little of JavaScript. WBES provides four examinations with a time limit for each one and an ability for the admin to add, edit or delete questions from the exams. WBES has a feature that each client or user will be tested by a different set of questions or different order and that decreases the cases of cheating between users or students. WBES can be accessed from any client in the same local network that the server is connected to. [ABSTRACT FROM AUTHOR]

In a pandemic outbreak such as COVID-19, that spreads widely around the world requires in depth research to predict the pattern of its spread and strategies to reduce the number of spreads. Predictive control is a mathematical approach to control systems where a model is used to make predictions about the future behavior of a system, and these predictions are then used to determine the control actions that should be taken. Based on these predictions, control measures such as lockdowns and social distancing could be optimized to reduce the spread of the virus and minimize its impact. A dynamic model is needed for quick and precise handling decisions. Mathematical models Epidemiology can be used in various fields, the implementation of which is COVID-19. The presentation of a dynamical system can use the basic compartment model, in which critical 퐶 and death 풟 states are considered, addressing more possibilities of mutual transitions between compartment states. 풮ℰℐℛ풞풟 estimates and forecasts the COVID-19 spread under uncertainties and constraints. This paper focuses on This paper focuses on fit and predict the 풮ℰℐℛ풞풟 model with time dependent basic reproduction numbers and health resource-dependent death rates to real COVID-19 data in Indonesia. Data have been collected for a specific period of time, the best-fitting parameters have been obtained, and the changes in the basic reproduction number over time have been estimated. The presented model has included the transition probability of the infected state to the critical state and the transition probability of the critical state to the death state, based on different age groups, so that the number of hospital beds has also been cooperative in computing the compartment states. Using the best-fitting parameters of the 풮ℰℐℛ풞풟 model, the development of the compartment states in the near future was estimated. The simulation result shows that the obtained parameters of the 풮ℰℐℛ풞풟 model were reasonably satisfying where the simulated states from the model could fit the real data with a small degree of error so that it can be used to predict the path of further deployment. [ABSTRACT FROM AUTHOR]

In this paper, we describe the dynamics of the spread of the COVID-19 disease. In this paper, a mathematical model of the problem is rewritten. Mathematical models can be used to find strategies to prevent the Coronavirus disease spread. A Susceptible-Exposed-Infected-Recovered (SEIR) mathematical model in the spread of COVID-19 disease is solved using fourth and fifth-order Runge-Kutta methods. The simulation results of the two methods show the same pattern of solution behavior as the results of the reference solution obtained using the ODE45 algorithm in the MATLAB software. Theoretically, the accuracy of the fourth-order Runge-Kutta method is not better than that of the fifth-order Runge-Kutta method. We show the correctness of this theory through simulations in this paper by solving the SEIR mathematical model for the COVID-19 disease. [ABSTRACT FROM AUTHOR]

This concept paper explores the challenges faced by employees from various industries as the world faces the COVID-19 pandemic at this point. The current situation finds that employees cannot go out to work face to face or are not allowed to come to the office physically as usual as a result of this COVID-19 pandemic outbreak. Furthermore, all citizens from almost all countries are involved in the implementation of the movement control order (MCO). However, jobs that involve day-to-day operations in the organisation still need to carry out their activities as usual for the sake of the survival of their respective organisations. Thus, there are various online platforms that are used to enable activities in the organisation to continue in the interest of stakeholders. To continue daily work activities there are several online platforms that are often used as communication media in organisations such as 'Google Meet', 'Google Classroom', 'Zoom', 'Webex', 'Microsoft Team' and 'Skype'. When the COVID-19 pandemic situation was announced to have subsided, there were organisations that adopted hybrid methods where online and face-to-face communication media were practiced for the purpose of discussions and meetings. This concept paper aims to identify the challenges faced by employees throughout working from home (WFH) when faced with this COVID-19 pandemic. Researchers have proposed three (3) recommendations in facing employee challenges throughout WFH with reference to Sociotechnical Systems Theory (STS) and Motivation-Hygiene Theory based on reference highlights of papers reviewed from 15 journals in previous studies. The results of this study can contribute to knowledge and in addition to the highlights of the work for this topic, especially to employers and employees who practice the concept of WFH. [ABSTRACT FROM AUTHOR]

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 pandemic has been going on for more than a year. COVID-19 causes asymptomatic infection, severe infection, until death. Diagnosis of COVID-19 infection is made by blood tests, antigen swabs, PCR, as well as radiology and CT-scan examinations. Severe COVID-19 infection shows similar symptoms to acute radiation injury. The paper aims to describe the similarity of severe infection COVID-19 and syndrome of acute radiation injury. This paper is a literature review. Literature was searched in the Science Direct and PubMed databases. The keywords were severe COVID-19 infection, acute radiation syndrome, similarity. The similarities between the pathophysiology of severe COVID-19 infection and acute radiation injury are cytokine storms. Symptoms of severe COVID-19 infection are acute respiratory distress syndrome (ARDS), hypoxia, and damage to the cardiovascular system. Researchers are trying to look for symptoms similar to this severe COVID-19 infection so they can find better prevention and therapeutic measures. Study of biological radiation has shown complex organ failure after exposure to high doses of radiation. This condition is called the acute radiation syndrome (ARS). Severe inflammation accompanied by cytokine storms causes severe symptoms of COVID-19 or ARS infection. ARS is diagnosed with a variety of biomarkers of radiation exposure. The similarity of symptoms and pathophysiology may be used to plan better treatment for patients with severe COVID-19 infection in the future. The treatment would be the same. [ABSTRACT FROM AUTHOR]

The ongoing COVID-19 pandemic affected everyone's life in every aspect. World Health Organization declared it as global emergency in March 2020 which leads to halt all the human activity around the world. While this pandemic was hazardous for human beings the nature was nourishing itself and seems to be on reset as the Pollution decreased due to this pandemic. In countries like China, Italy, USA and many more which initiated the lockdown in their countries to avoid the spread of this deadly virus has shown the reduction of air pollution. The emission of air pollutants were reduced due the lockdowns in many countries. In the paper different types of environmental pollution, their reasons and effects on nature are discussed and also the impact of COVID-19 pandemic on environment is discussed. [ABSTRACT FROM AUTHOR]

The importance of medicinal plants has widely increased throughout the world, especially during the COVID-19 pandemic. It is essential for a layman to identify a medicinal plant and know about its medicinal values. In this view, this paper proposes an approach that helps a person to identify the medicinal values of different plants. The paper focuses on designing a mobile application that can identify the leaf and list its medicinal values with a mere snapshot of it by performing instance segmentation, feature extraction and classification in the backend. The models were trained and tested on a custom dataset generated by collecting around 1500 images spreading over 5 medicinal plant species. The paper uses a deep learning-based segmentation approach for real-time segmentation of the leaf from the complex natural background. The segmented leaf will undergo a feature extraction process and will be given as an input to the traditional Machine Learning algorithms. Manual Feature Extraction and Deep Learning based Feature extraction processes were implemented. Various features including shape, colour and texture were extracted in the manual feature extraction process and a MobileNet pre-trained model was used for deep learning-based feature extraction. The Mask Region-based Convolutional Neural Network (Mask R-CNN) yielded the best performance for real-time segmentation with a Dice score of 0.92 and for the classification MobileNet + Logistic Regression gave the best accuracy of 0.97 and AUC score of 0.99. [ABSTRACT FROM AUTHOR]

This article raises the question whether there is in fact a specific field within civil engineering that may be connected to the impact of Covid-19, namely radon exposure in interior spaces in certain parts of the world. Radon exposure is particularly high in regions that have seen high mortality rates related to SARS-CoV-2. Examples of these include the Bergamo region in Italy and the Erz Mountains, the Fichtel Mountains or the Bavarian Forest in south-eastern Germany. But is there actually a correlation, or is this merely a coincidence? Is there in fact a causality? If so, constructional measures to protect against the decay products of radon in interior spaces would gain a new significance that goes beyond the realms of current knowledge. This article cannot provide a definitive answer to these questions due to the current patchiness of data in Germany. Nevertheless, this paper will use the data available to demonstrate that there is evidence of a possible correlation or causality between the two, and that this merits further research. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, the world has witnessed rampant use of digital technology in almost every facet of huma lives. However, these digital techniques like use of mobile apps have certain drawbacks and constrains. These could be addressed with the use of emerging technologies like Internet of Things (IoT). In healthcare, that is Internet of Medical Things (IoMT). A number of ongoing studies show that integrating security measures with technology will lead to the adoption of stable IoMT applications. Emerging IoMT technologies used in conjunction with Blockchain, Artificial Intelligence, and Big Data, provide feasible solutions. The paper focuses on IoMT models, innovations, and security progress made to tackle COVID-19 issues. This paper contains the bibliometric research highlighting the use of disruptive technology for the diagnosis of COVID-19. It reviews the adoption of contactless services in the post-COVID-19 period along with potential opportunities as well as challenging obstacles for healthcare agencies, policymakers, and customers. [ABSTRACT FROM AUTHOR]

The goal of this research paper is to use the Open-source intelligence approach and content analysis to analyze the fundamental aspects of nationally issued COVID-19 contact tracing apps and derive a theme from them. We conduct a qualitative examination of contemporary discourse on OSINT and SIGINT, as well as their impact on global health. A theme can be built around it, depending on how serious the situation is or assumed to be, by gathering input from everyday people working in various sectors, students, and patients who have tested positive for COVID, and creating a quantitative and qualitative study of current health data collection capabilities. This paper analyses how individuals can find and decipher various consumer activities on social media, opinions through discussion forums, knowledge consumption, and sharing through blogging, The challenges of efficiently deploying contact tracing systems are the same across countries. This needs a thorough assessment of the various approaches for supporting governments in identifying the most promising apps. Although several studies have looked into the factors that influence COVID-19 monitoring app acceptance, little study has been done on cross-country comparisons. Hence, by generating a hypothesis and testing it against nature, a similar investigation of the COVID-19 epidemic should be achievable, and it should study how such devices may be used in the location, announcement, and control of signs and symptoms associated with a 'risk' by the worldwide local area. [ABSTRACT FROM AUTHOR]

The world has been living with the Coronavirus Disease 2019 (COVID-19) pandemic for more than two years and it has altered humanity in numerous ways, by the implementation of lockdowns, border closures, other movements, and social restrictions. The pandemic has also led to the deferral or termination of all events including sports, religion gathering, political elections, and social events. Industries, in particular oil and gas, entail to react within a short span of time to productively manage the stakeholders. As workforces began to work from home, business meetings, discussions, and engagements were swapped by video calls, and businesses around the globe began their contingency planning. The stakeholder management becomes critical when there is no standard procedure available under the circumstances, thus this paper aims to propose procedures on improving the stakeholder management in petrochemical projects during the COVID-19 pandemic. The paper assesses the impacts of the pandemic on stakeholder engagement in petrochemicals projects, examines current coping strategies in different projects, and recommends several practical actions to promote and maintain meaningful exchange with stakeholders in times of social distancing and lockdowns. The outcome of the paper enlists various improvement levers for a petrochemical company to adapt to ensure project stakeholders are satisfied and well-informed. [ABSTRACT FROM AUTHOR]

The weighty increase in the daily COVID-19 infected cases around us is frightening, and many researchers are currently working on various mathematics-based estimation models to predict the subsequent trend of this pandemic. In this paper, some trajectories of COVID-19 in. India are predicted using data available in public domain. We employed a time series model called Auto-Regressive Integrated Moving Average Model to make forecast the daily number of infected cases of COVID-19 in.near future. Our analysis predicted very alarming outcomes. A set of intense preventive measures are proposed to avoid such a deadly situation. Based on our estimations, Indian health officials should adapt warmongering interference to grasp the stepped-up growth, and cursory infection control actions at hospital levels are immediately needed to downsize the COVID-19 pandemic. If stringent precautionary measures are not implemented by Indian government to control the spread of COVID-19, then the effects may be worsened. [ABSTRACT FROM AUTHOR]

The security of image during its communication over public channel got extreme concern with the sharp rise of sharing of information nowadays, especially in this COVID-19 pandemic period. Visual cryptography scheme (VCS), which is already familiar image encryption scheme due to its simplicity, finds its applicability in real-life field. A secure image transmission system based on XOR-based VCS is proposed in this paper, which utilizes bit-plane slicing and run-length encoding to encode noise-like shares in a compressed and numeric form with two objectives – to reduce the transmission overhead and to secure the communication of the shares, at the same time. [ABSTRACT FROM AUTHOR]

Corona virus (covid-19) – an infectious illness caused by SARS-COV-2. It can be transmitted from one person to another when an infected person cough, sneeze, speak. sing or breathe. Thus, masking your face in general places is an effective method of protection. Globally, governments implemented lockdowns following the covid-19 pandemic. other transmission off the virus. However, the long period the lockdown affects peoples live hood. In order to overcome this, the government has announced partial lockdown with some rules & regulations. An efficient & economic approach of using AI and do setup a device to create a safe environment. This paper will present a hybrid face mask detection algorithm that utilizes deep learning. A device to detect masks entail of a dataset of images with mask or without mask, and with the help of open-CV in real time, a webcam stream is used to detect whether or not a face mask is worn by the person. Persons without face mask has been indicated in with an alert massage and door will not open using Arduino controller. [ABSTRACT FROM AUTHOR]

The ability to solve problems is one of the goals of teaching math at school. However, the purpose of education is not only to make students cognitively intelligent, but also to have good character values in their daily activities. The current state of the pandemic is affecting the learning process, and teachers struggle to conduct effective math lessons. This is certainly a teacher's effort to continue to study mathematics to enable students to develop problem-solving skills while internalizing the value of the student's character as they study during the pandemic will be needed. This paper contains an explanation of mathematical problem-based learning based on student character values and further discussion of various options for implementation during the Covid19 pandemic. [ABSTRACT FROM AUTHOR]

Since study from home policy was introduced as a consequence of the COVID-19 pandemic, academic activities in Indonesia have transformed into electronic learning. However, there is a limited study examining the factors confirming the application of electronic learning by the lecturer during the COVID-19 crisis. To fill the research gaps, this paper scrutinizes the factors that confirmed electronic learning in a time of COVID-19 pandemic using the unified theory of adoption and use of technology (UTAUT) model. Specifically, we inspect confirmatory factor analysis of five dimensions of UTAUT, including performance expectancy, effort expectancy, social influence, facilitating conditions, and adoption of electronic learning. The research performed a survey method using an online questionnaire. Data in this study were collected from a permanent lecturer in Universitas Andalas, Indonesia. Data were processed using structural equation modeling (SEM). A total of 330 respondents participated in this survey. Our findings show that all constructs and items of electronic learning adoption are valid and reliable. From the results, the current study contributes theoretically and practically further elaborated in the light of this paper. [ABSTRACT FROM AUTHOR]

The goal of this paper is to investigate students' condition during the first couple months of pandemic since it hit Indonesia. Since the beginning of 2020, the Covid-19 pandemic has imposed the use of technology in teaching and learning process, and nothing can enforce the use of technology in education as powerful as Covid-19 Pandemic. Schools and universities have been closed and the teaching and learning process must be done remotely through online learning to slow down the spread of the virus. Students must learn from home. Teacher has to adapt to using online learning platform during this pandemic. However, the e-learning process are still far from perfection as it still caused many problems for teachers and students as well; therefore, a suitable and appropriate learning environment needed to be created for improving the existing learning environment that is safe and effective for students and teacher during pandemic. This research aims to gain the basic inputs in designing an appropriate classroom/learning environment specifically for teaching during and, hopefully, after pandemic. An online survey is spread to reach more and wider respondents, because we would like to gain as much as possible data from the Z generation. There are as many as 4841 college students in Gorontalo responded to the survey. The Result of this research shows the students' condition on the first couple of months when the pandemic hit Indonesia, especially the province of Gorontalo, that effected the teaching and learning process in our university. The issues and problems surrounding the implementation of online learning as well as the students' life facing the covid-19 pandemic will be presented in more detail in this paper. [ABSTRACT FROM AUTHOR]

Although distinctive types of assistant robots developed for aging and handicapped people, the exploration in the research area of smart assistant robotics has been considered as the most noteworthy research theme till the past decennary. Here this paper showcases a robotic assistant to reduce the threat to treasurable human lives in the infectious surrounding. Taking the example of the ongoing COVID-19 pandemic where the doctors and other health workers are to be in regular contact with the patients intending to test and indulgence them, therefore the danger of a community spread increase. The main focus areas of this paper are the designing of a very cost-effective, human-friendly robot structure and analyses the structure for better, optimal design and stable performance on assisting patients, and remote supervision of patient's health condition. The proposed design of the Assistant Mobile Robot involves designing a very portable structure for easy transportation to the required place. Besides, to make the design more effective and cost-effective, did the calculation for power consumption. [ABSTRACT FROM AUTHOR]

The economic uncertainties due to Covid-19 pandemic has forced businesses to survive, maintain their long-term profitability and remain competitive through the unexpected market upsets. As businesses have to shut down, jobs are lost, people will suffer and economy will be shrinking. Thus, understanding the purchasing behavior of customer is a vital step not only in building but also in maintaining a business. Good customer management comes from good customer measurement. With the latest advent of customer analytics, businesses nowadays can thoroughly comprehend their consumers at all phases of the purchasing process, recognizing patterns in customer data, forecasting the actions that their customers will do, and then making decisions about how to enhance their business in order to attract new customers and retain existing ones. The objective of this paper is to perform customer profiling and customer segmentation of Starbucks Malaysia during the hit of Covid-19 pandemic in Malaysia. Dataset are collected during the second Conditional Movement Control Order (CMCO 2.0). Customer profiling tries to gain a deeper understanding of customers and describe their personalities types or personas, while customer segmentation is a powerful technique to understand the patterns that differentiate a customer. A customer segment is a grouping of customers that share certain characteristics. In this paper, k-means clustering algorithm is used to segment the customers of Starbucks Malaysia according to their income and spend data. From the clustering analysis, one can determine the optimal number of clusters and comprehend the underlying customer segments to identify the statistical patterns of Starbucks customers. This research will contribute both theoretically where this research can uplift the theoretical foundation of customer analytics and practically towards Starbucks Malaysia and other organization and marketing teams where they can understand their customers better and can increase their revenue with the improved marketing campaigns especially during this long-run Covid-19 crisis. [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]