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Clean water is one type of water-based resource that is of good quality and commonly used by humans for consumption or in carrying out their daily activities, including sanitation. The arrival of COVID-19 has increase water usage as hand washing is a must. However, according to the World Health Organization (WHO), several localities face higher infection risks due to water supply shortages resulted from the increased demand for treated water. Having a contingency plan to facilitate that change can reduce the probability of water supply shortages. However, existing literature lacks detailed insights on water usage changes during a pandemic and pandemic response model. Response plans that tackle changing water demands during a pandemic, using COVID-19 as a case study, are compelling. Hence, this paper aims to determine the impact of COVID-19 on treated water supply and demand in Pahang. The results reveal that the lockdown during COVID-19 has increased domestic water demand and decreased demand for non-domestic (i.e., commercial, industrial, and government building). The net effect of these changes varies from place to place, depending on the relative proportion of domestic and non-domestic water usage across the major economic sectors. The findings are helpful for future water management strategy plans in the study area. © 2023 American Institute of Physics Inc.. All rights reserved.
ABSTRACT
COVID-19 outbreak has significant impacts on education system as almost all countries shift to new way of teaching and learning;online learning. In this new environment, various innovative teaching methods have been created to deliver educational material in ensuring the learning outcomes such as video content. Thus, this research aims to implement machine learning prediction models for video-based learning in higher education institutions. Using survey data from 103 final year accounting students at Malaysian public university, this paper presents the fundamental frameworks of evaluating three machine learning models namely generalized linear model, random forest and decision tree. Besides demography attributes, the performance of each machine learning algorithm on the video-based learning usage has been observed based on the attributes of technology acceptance model namely perceived ease of use, perceived usefulness and attitude. The findings revealed that the perceived ease of use has given the highest weight of contributions to the generalized linear model and random forest while the major effects in decision tree has been given by the attitude variable. However, generalized linear model outperformed the two algorithms in term of the prediction accuracy. © 2023 Institute of Advanced Engineering and Science. All rights reserved.
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Most people preferred e-commerce ensuing the Coronavirus Disease-2019 (COVID-19) outbreak, resulting in delivery companies receiving large quantities of parcels to be delivered to clients. Hurdle emerges when delivery person needs to convey items to a large number of households in a single journey as they never face this situation before. As a result, they seek the quickest way during the trip to reduce delivery costs and time. Since the delivery challenge has been classified as an NP-hard (non-deterministic polynomial-time hard)) problem, this study aims to search the shortest distance, including the runtime for the real case study located in Melaka, Malaysia. Hence, two metaheuristic approaches are compared in this study namely, Ant-Colony Optimization (ACO) and Genetic Algorithm (GA). The results show that the GA strategy outperforms the ACO technique in terms of distance, price, and runtime for moderate data sizes that is less than 90 locations. © 2022, International Journal of Advanced Computer Science and Applications. All Rights Reserved.
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The aim of this project is to construct portable smart farming management tools that could be helpful for the farmer involved in the pineapple industry. The project also aims to focus on the productivity of the plant by varying the fertilizer contents. During the Covid-19 pandemic that impacts all industries especially the agriculture industry, the farmers had an issue related to precision in terms of monitoring the soil condition of their crops due to limitations on the mobility of people across borders and lockdowns are contributing to labor shortages. Therefore, this study expected to look at the possibilities of the Smart Farming Management Tool Internet-of-Things based to be implemented in helping farmers to keep on track of the soil conditions in their crops via smartphones. © 2022 IEEE.
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In this chapter, we describe the application of Time Series techniques such as ARIMA and ARIMA-GARCH Models to model and forecast the stock prices and the usage of some statistical techniques such as Paired t-Test and Wilcoxon Signed-Rank Test to assess the impact of the COVID-19. The findings provide significant insights into the benefits of mathematical and statistical modeling for real life problem. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The existence of small-scale food enterprises helps a lot in increasing the country's income, as well as providing many employment opportunities to the community. This study was to examine how small-scale food entrepreneurs strive to survive in the enterprise when faced with the effects of COVID-19. Factor analysis was used to form the resilience factor and descriptive analysis was used to look demography, resilience practices, and to analyze the assistance in improving entrepreneurial resilience. This study has developed resilience factors and improved resilience. The government needs to be vigilant in providing the assistance needed by entrepreneurs to rehabilitate businesses affected by the COVID-19 pandemic.
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Purpose: Policymakers are developing government-level pandemic response strategies (GPRS) to assist architecture, engineering and construction (AEC) enterprises. However, the effectiveness of the GPRS has not been assessed. Therefore, this study aims to investigate the interrelationships between GPRS and AEC enterprises. To achieve that aim, the study objectives are to compare GPRS effectiveness between small-medium and large AEC enterprises, develop groupings to categorize interrelated GPRS and evaluate the effectiveness of the GPRS and interrelated constructs. Design/methodology/approach: A systematic literature review and semi-structured interviews with 40 AEC industry professionals were carried out, generating 22 GPRS. Then, questionnaire survey data was collected among AEC professionals. In total, 114 valid survey answers were received and analyzed using the Kruskal–Wallis H test, normalized mean analysis, factor analysis and fuzzy synthetic evaluation. Findings: Small-medium enterprises have four distinct critical GPRS: “form a special task force to provide support in maneuvering COVID-19,” “provide infrastructure investment budgets to local governments,” “develop employee assistance programs that fit all types of working groups” and “diversify existing supply chain.” Large enterprises have two distinct critical GPRS: “provide help in digitalizing existing construction projects” and “mandate COVID-19 as force majeure.” Eighteen GPRS can be categorized into the following five constructs: “market stability and financial aid,” “enterprise capability management,” “supply chain improvement,” “law and policy resources” and “information and workforce management.” The former two constructs are more effective than other GPRS constructs. Originality/value: This is the first paper that evaluates the effectiveness of GPRS for AEC enterprises, providing new evidence to policymakers for well-informed decision-making in developing pandemic response strategies. © 2022, Emerald Publishing Limited.
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— The mobile devices are used to execute the teaching-learning-evaluation process in Mobile Learning (m-learning) methodology. M-learning is a trending field in educational organizations, companies, and for individual study. With the explosion of mobile device ownership among the users aged within 18–29 years who are also the attendees of the higher learning institution (HLI), gives us the opportunity to consider the use of m-learning methodology to be embedded in the HLI beside traditional methodologies. Exceptional circumstances such as the COVID-19 pandemic when traditional face-to-face methodology suddenly changed to online paradigm, is also forcing us to strongly consider the m-learning approach. However, HLI may not have a general policy to implement m-learning into the traditional learning environment. A proper educational outcome needs to be configured to implement a new process into the traditional process. Therefore, a model integrating the m-learning aspects and the education supply chain management factors obtained from this study may benefit the stakeholders of HLI, especially educators and students. ©AJSE 2021
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Purpose: This study aims to investigate the interrelationships between COVID-19 pandemic impact and architectural, engineering and construction (AEC) organizations. To achieve that aim, the objectives are to: identify the critical pandemic impact (CPI) of COVID-19 on AEC organizations;compare the CPI between the different organization characteristics;and analyze the interrelationships between the CPI. Design/methodology/approach: A systematic literature review of 519 articles and in-depth interviews with 40 AEC practitioners were carried out, yielding 12 COVID-19 impacts. Then, data on the 12 impact’s criticality were collected through a survey among AEC practitioners. In total, 127 valid responses were received and analyzed using mean ranking analysis, analysis of variance and Spearman’s correlation. The findings were also compared with pandemic impacts from prior works. Findings: Five CPI exist among the 12 impacts, namely, “reduced construction productivity,” “reduced foreign investment in the construction industry,” “reduced demand on construction-related works,” “disruption in the supply chain” and “reduced number of public projects.” “Reduced foreign investment in the construction industry” and “reduced demand on construction-related works” significantly impact small-medium enterprises than large enterprises. Also, “disruption in the supply chain” and “reduced construction productivity” are recurring impacts in all countries compared. Finally, moderate relationships exist between “reduced foreign investment in the construction industry” and “reduced demand on construction-related works” and “disruption in the supply chain” and “reduced construction productivity.” Originality/value: The findings can be used to prioritize available resources in developing short-term responses for COVID-19. Also, action plans can be developed to mitigate the CPI from recurring. © 2021, Emerald Publishing Limited.
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Traditional food represents the cultural identity that becomes income sources for Small and Mid-size enterprises (SMEs) entrepreneurs in Sabah. The sudden presence of the COVID-19 since March 2020 has impacted traditional food entrepreneurs. This research examines what strategies SMEs entrepreneurs are implementing. Factor Analysis is used to analyse 21 parameters of a new norm for the traditional food business. This study succeeded in developing three dimensions: enhancing existing business, new norm business and improving business skills. Entrepreneurs need to prepare strategies to meet new business norms. Support from the government and various agencies is required to enhance SME entrepreneurs' business capabilities.
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The construction industry plays significant roles in the country's economic development and growth. There would be a domino impact on the economy if any construction projects are being delayed. As the pandemic of COVID-19 had arisen into our global that had affected the construction industry, including building projects. Identifying the underlying problems caused by COVID-19 can provide the best solution to reduce the pandemic's impact. Consequently, emphasizing the impact of COVID-19 and the strategies to address those problems in the building construction industry becomes vital. Thus, this research objective is to identify problems caused by COVID-19 in the building construction industry and mechanisms to reduce COVID-19's negative impact. The data collection involved individual interviews with 20 contractor companies that are engaged in building construction projects. Then, the data is analyzed using the thematic analysis approach. The findings show that COVID-19 is causing operational and financial issues, while financial aids and complete information is needed to overcome those impacts. These findings will help policymakers improve existing strategic plans and create new policies to cope with the circumstances caused by COVID-19 among building construction organizations. © Published under licence by IOP Publishing Ltd.
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The COVID-19 pandemic has affected the overall economy and the construction industry badly. The Movement Control Order (MCO) caused the suspension of the construction sector, including infrastructure projects. Contractors are suffering losses and facing many problems caused by the pandemic, even with the on-going government financial aids. By identifying the right approaches to improve existing government policies and strategies, contractors could better manage the problems. Thus, this research aims to explore mechanisms for reducing COVID-19's negative impact on the infrastructure construction industry. To achieve that objective, this study involves collecting and analyzing interview data with industry practitioners. The significant findings from the analysis are: (1) COVID-19 affects the infrastructure construction industry by causing financial and productivity problems;and (2) mechanisms to address those problems include legal, financial, productivity, and environmental support. This paper's finding is valuable for the government in determining the right actions in assisting contractors in this critical period. © Published under licence by IOP Publishing Ltd.