Modeling COVID-19 Transmission Dynamics With Self-Learning Population Behavioral Change

Many regions observed recurrent outbreaks of COVID-19 cases after relaxing social distancing measures. It suggests that maintaining sufficient social distancing is important for limiting the spread of COVID-19. The change of population behavior responding to the social distancing measures becomes an important factor for the pandemic prediction. In this paper, we develop a SEAIR model for studying the dynamics of COVID-19 transmission with population behavioral change. In our model, the population is divided into several groups with their own social behavior in response to the delayed information about the number of the infected population. The transmission rate depends on the behavioral changes of all the population groups, forming a feedback loop to affect the COVID-19 dynamics. Based on the data of Hong Kong, our simulations demonstrate how the perceived cost after infection and the information delay affect the level and the time period of the COVID-19 waves.

Information and material delays effect on price setting, operating contribution margins and cash conversion cycles in feed ingredients supply chain

PurposeThe purpose of this report was to evaluate the effectiveness and practicality of system dynamics modeling in integrating econometric equations to describe the effects of supply chain material and information delays on pricing decisions and consequent financial results in an animal feed export business.Design/methodology/approachAn empirical dynamic model, loaded with econometric theory of price effect on competitive demand, was used to describe the input data.FindingsThe model simulation outputs proved themselves relevant in analyzing the complex interconnections of multiple variables affecting the profitability in a commercial routine, supporting the decision process among sales managers. The impact of information delay on price decisions and business financial results were estimated using the model proposed.Originality/valueThis paper describes an empirical model, based on system dynamics, that predicts operating contribution margins and cash conversion cycles based on estimation of information and material delays in a supply chain. The method is pragmatic and simple for business routine implementation.

IFC-Based 4D Construction Management Information Model of Prefabricated Buildings and Its Application in Graph Database

Effective data interoperability and schedule analysis play a significant role in improving the management of prefabricated buildings. However, there is a lack of efficient strategies and comprehensive approaches for data interoperability and data-based automated schedule analysis. This paper intends to promote prefabricated buildings’ management by solving these two problems via developing an IFC-based framework consisting of three parts. Firstly, this framework proposed a mechanism to establish an IFC-based 4D construction management information model of prefabricated buildings. Furthermore, a non-relational database—graph database—is introduced to twin this model into a task-centered network to realize the interoperation of construction information among different participants. Finally, graph database-based strategies to update data, automatically analyze construction schedules and visualize the 4D construction management information model are described. The proposed framework is validated in a prefabricated engineering case. In this case, an IFC-based and graph database-based 4D construction management information model is established through IFC standard’s extension. The graph database-based analysis of the model automatically recognizes the engineering case’s critical path information, delay analysis information, and schedule network analysis information. It is illustrated that this framework can successfully establish a unified IFC-based information model of prefabricated buildings’ construction management to prompt effective data interoperability. In addition, the application of this IFC-based information model in graph database can automatically analyze the construction schedules to prevent possible delays in advance. In short, the significance of this paper is to innovatively propose an IFC-based and graph data-based information model to solve the difficulties of ineffective data interoperation and unautomated schedule analysis in prefabricated buildings’ construction management. This study can be the digital foundation of further IFC-based digital twin.

Delay Impact of COVID-19 Pandemic on Malaysia's Oil and Gas Projects

COVID-19 pandemic has extremely affected people and businesses around the world. Oil and gas industry are not exempted, and negatively impacted by the unprecedent crisis of COVID-19. This pandemic has also caused delays in the oil and gas projects. In an attempt to control the spread of COVID-19, Malaysian government has introduced Movement Control Order (MCO) in the whole country to be closed and lockdown all premises except essential services to operate. This has resulted major delays in the project execution. Researchers have conducted studies to identify factors that causing project delays. Approximately 75 delay factors were found from previous studies and it revealed that most delay factors were not caused by COVID-19. In the current research, the delay factors due to COVID-19 were identified and some delay factors were found to have similarity with literature. Additionally, interview sessions were organized with oil and gas professionals involving in the oil and gas industry. Delay factors due to COVID-19 and mitigation strategies were identified from the interview sessions. Moreover, this result has used in the designing of survey questionnaire and distributed to project practitioners working in the oil and gas industry in Malaysia. 110 Oil and gas professionals include 52 Clients, 25 consultants, 23 contractors, 5 subcontractors and 5 vendors/suppliers have participated in the survey. Data collected from survey was analyzed and interpreted by means of median and Relative Importance Index (RII). Based on this information, delay factors and mitigation strategies were ranked according to their importance and impact to project. It is observed that the higher value of the RII the more critical cause or impact factor. Top seven (7) delay factors were identified and top seven (7) mitigation measures were proposed as recommendations for future implementation in the oil and gas project.

A Cyber Collaborative Protocol for Real-Time Communication and Control in Human-Robot-Sensor Work

Real-time communication and control are essential parts of the Cyber Physical System (CPS) to optimize effective performance and reliability. To gain a sustainable competitive advantage with Automation 5.0, as needed in Work-of-the-Future, this article addresses the concept of real-time communication and control in the case of an agricultural work setting, along with a newly designed Cyber Collaborative Protocol, called CCP-RTC2. The developed protocol aims to minimize information delay and maximize JIN (Just In Need) information sharing, to enable collaborative decisions among system agents. Two experiments are conducted to compare the designed protocol’s performance in agricultural CPS against the current non-CPS practice. The results demonstrate that the CCP-RTC2 is superior compared with current practice in terms of information sharing in a normal operation scenario. When the system obtains an unplanned request, the CCP-RTC2 can integrate such a request to the original work plan while minimizing the system’s objective function (lower is better). Hence, the system has relatively smaller information delays, as well as better timely information shared with system agents that need it.

The Effects of Different Supply Chain Integration Strategies on Disruption Recovery: A System Dynamics Study on the Cheese Industry

Long and complex supply chains are vulnerable to disruptions. One way to solve this problem is to successfully manage supply chain integration (SCI). A system dynamics simulation is thus applied to study a cheese supply chain with three individual firms: a producer, a logistics service provider (LSP), and a retailer. Our purpose is to study the effects of SCI strategies with different dimensional focuses, i.e., information integration (Scenario 1), relational integration (Scenario 2), and operational integration (Scenario 3), on the recovery of three types of disruptions, i.e., a producer capacity disruption, an LSP capacity disruption, and a demand disruption. Tests of parameter scenarios are further applied to provide solutions for supply chains using different strategies. Our results indicate that Scenario 3 is the best practice, regardless of any type of disruption, while Scenario 1 usually achieves the worst performance. This is consistent with an evolutionary perspective of supply chain integration: information integration gives firms a competitive advantage as the first step. Working as partners to share the most appropriate information leads to greater benefits. We extend this perspective by showing that further elimination of information delay helps the supply chain achieve the best performance.

A Survey of Road Accident Reporting and Driver’s Behavior Awareness Systems: The Case of Tanzania

Road traffic accidents are a leading cause of death in developed and developing countries. It has been shown that road accident reporting systems could reduce their effects by minimizing response time and mapping road accident-prone areas. This paper provides an overview of the systems and applications for road accident reporting and drivers’ behavior awareness. A field survey, conducted in Dar es Salaam region in Tanzania, investigated the current state of road traffic accident reporting. Findings showed that the main means of reporting road accidents were physical reporting and police emergency phone calls. The absence of alternative means for reporting road accidents causes information delay and lack of precise accident location for the emergency first responders. This paper concludes by proposing a mobile application system for road accident reporting and drivers’ over-speed awareness, in order to improve road safety in developing countries.

Mathematical analysis of a time-delayed model on brucellosis transmission with disease testing information

Testing–culling is one of the important prevention and control measures considered in the study of animal infectious diseases. However, the process of finding infected animals (animal testing) is still not well studied through the kinetic model. In this paper, based on the characteristics of animal testing, a time-delayed model on brucellosis transmission is established. Under the general hypothesis of biological significance, the existence and stability of equilibria are first investigated. The results find that the global stability of equilibria depends on the basic reproduction number [Formula: see text] without the information delay: if [Formula: see text], the disease dies out; if [Formula: see text], the endemic equilibrium exists and the disease persists. Next, the impact of information delay on the dynamics of the model is analyzed and Hopf bifurcation is found in the established model when the information delay is greater than a critical value. Finally, the theoretical results are then further explained through numerical analysis and the significance of these results for the development of risk management measures is elaborated.