Utilization of Industry 4.0 during COVID-19 Pandemic in the Targeted (S-Curve) Industries of Thailand

The first COVID-19 is discovered in December 2019 in Wuhan, China and rapidly spread to millions of people all over the world. COVID-19 heavily affects the industrial business and economy of many countries, including Thailand. This study aims at exploring the effects of COVID-19 on the targeted (S-Curve) industries of Thailand and investigating the ways to improve business operations with the utilization of the appropriate Industry 4.0 technologies. The paper presents (1) Industry 4.0 background and the First S-Curve and the New S-Curve industries of Thailand (2) Data collection and analysis (3) The effects of COVID-19 on business operations. The characteristics of each industry, the requirements of business and operator to cope with Industry 4.0, and the implementations of Industry 4.0 technologies during the situation of COVID-19 are analyzed by using a focus group, online questionnaires and interviews. Results show that customer behavior is a major issue on business operations and IoT is the most critical technology in supporting business operations and reducing the impacts of COVID-19. It has also been found that the functions of technologies depend on the characteristics of each industry. Results from this study can assist companies to obtain a better understanding of the critical functions of technologies that suit their characteristics best and develop operator's skills properly for increasing business competitiveness. © 2021 IEEE.

Applying diffusion of innovations theory to social networks to understand the stages of adoption in connective action campaigns

This research proposes a conceptual framework for determining the adoption trajectory of information diffusion in connective action campaigns. This approach reveals whether an information campaign is accelerating, reached critical mass, or decelerating during its life cycle. The experimental approach taken in this study builds on the diffusion of innovations theory, critical mass theory, and previous s-shaped production function research to provide ideas for modeling future connective action campaigns. Most social science research on connective action has taken a qualitative approach. There are limited quantitative studies, but most focus on statistical validation of the qualitative approach, such as surveys, or only focus on one aspect of connective action. In this study, we extend the social science research on connective action theory by applying a mixed-method computational analysis to examine the affordances and features offered through online social networks (OSNs) and then present a new method to quantify the emergence of these action networks. Using the s-curves revealed through plotting the information campaigns usage, we apply a diffusion of innovations lens to the analysis to categorize users into different stages of adoption of information campaigns. We then categorize the users in each campaign by examining their affordance and interdependence relationships by assigning retweets, mentions, and original tweets to the type of relationship they exhibit. The contribution of this analysis provides a foundation for mathematical characterization of connective action signatures, and further, offers policymakers insights about campaigns as they evolve. To evaluate our framework, we present a comprehensive analysis of COVID-19 Twitter data. Establishing this theoretical framework will help researchers develop predictive models to more accurately model campaign dynamics. © 2022

Accelerated Virus Spread Driven by Randomness in Human Behavior

In this paper is demonstrated that the morphology of infection’s curve is a consequence of the entropic behavior of macro-systems that are entirely dependent on the nonlinearity of social dynamics. Thus in the ongoing pandemic the so-called curve of cases would acquire an exponential morphology as consequence of the human mobility and the intensity of randomness that it exhibits still under social distancing and other types of social protection adopted in most countries along the first wave of spreading of Covid-19. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Virus spreading and heat spreading

Here we propose a heat transfer framework for how human-to-human interaction spreads everything on the landscape: disease, goods, knowledge, news, technology, science, language and culture. We show that the phenomenon of “human spreading” shares key features with phenomena that are fundamental in physics (heat, electricity, species, Darcy fluid flow), which spread through continua. As example for discussion and illustration, we construct this theoretical framework by using the early phase of the coronavirus outbreak, from before May 2020. The human spreading phenomenon (S curve) is unveiled systematically by using a minimum of measurable parameters: the number of persons with whom one person comes in contact, the radial size of each step in the growth of the swept territory, the radial scale of the inhabited territory, and the directions in which infrastructure (e.g., air routes) are available for long and fast spreading. The resulting configuration of spreading is a multiscale assembly of clusters of fast channels embedded in interstices with slow diffusion. The configuration is dendritic, where each direction of long and fast spreading is covered by a finger of clusters, and each finger generates its own ramifications. The similarities between this configuration and the dendritic architectures for heat and fluid flow through heterogeneous media are discussed.

Sustainable production and waste management policies for COVID-19 medical equipment under uncertainty: A case study analysis.

Unfortunately, an abrupt corona-virus disease (COVID-19) outbreak brought a drastic change in human lives. Almost every sector of human-beings and their related activities are severely infected and affected by this COVID-19 pandemic. As days are passing, the impact of the COVID-19 epidemic is going to be more severe. The fundamental needs for personal protective equipment (PPEs) are rising drastically all over the world. In India, many non-pharmaceutical companies or organizations such as automobile companies are engaged in producing the PPEs at a very marginal rate. Thus this paper proposes a modeling and optimization framework for sustainable production and waste management (SPWM) decision-making model for COVID-19 medical equipment under uncertainty. To quantify the uncertainties among parameter values, we have taken advantage of the intuitionistic fuzzy set theory. A robust ranking function is presented to obtain a crisp version of it. Furthermore, a novel interactive intuitionistic fuzzy programming approach is developed to solve the proposed SPWM model. An ample opportunity to generate the desired solution sets are also depicted. The performance analysis based on multiple criteria such as savings from baseline, co-efficient of variations, and desirability degrees is also introduced. Practical managerial implications are also discussed based on the significant findings after applying to the real case study data-set. Finally, conclusive remarks and the future research direction are also addressed on behalf of the current contributing study.

Poorly known aspects of flattening the curve of COVID-19.

A negative correlation between the final ceiling of the logistic curve and its slope, established long time ago via a simulation study, motivated this closer look at flattening the curve of COVID-19. The diffusion of the virus is analyzed with S-shaped logistic-curve fits on the 25 countries most affected in which the curve was more than 95% completed at the time of the writing (mid-May 2020.) A negative correlation observed between the final number of infections and the slope of the logistic curve corroborates the result obtained long time ago via an extensive simulation study. There is both theoretical arguments and experimental evidence for the existence of such correlations. The flattening of the curve results in a retardation of the curve's midpoint, which entails an increase in the final number of infections. It is possible that more lives are lost at the end by this process. Our analysis also permits evaluation of the various governments' interventions in terms of rapidity of response, efficiency of the actions taken (the amount of flattening achieved), and the number of days by which the curve was delayed. Not surprisingly, early decisive response-such as countrywide lockdown-proves to be the optimum strategy among the countries studied.