Using Advanced Analytics to Predict Vehicle Registrations and Help in Business Continuity Planning

Dramatic changes happen in the world. People and organizations face problems with these changes. The ones who have everything planned in case of emergencies; survive, and the ones who do not plan it right, have a chance of falling. Today, a lot of organizations suffer because of the Covid-19 global pandemic, even the largest organizations in Dubai like Roads and Transport Authority. Roads and Transport Authority (RTA) is one of the largest government entities and the sole planner and executer of all transport, road, and traffic projects in Dubai. It has happiness centers which register all the cars that are in Dubai. Those centers capacity is reduced because of this disease which led to making the long queues for customers. Customer’s satisfaction is one the main priorities of these centers. Not having this problem solved; will increase the number of unsatisfied customers. In this capstone project, I propose to explore the data of the registered cars then predict the upcoming customers. By predicting customers, we will solve all the problems that the organization is facing in this pandemic and plan for future dramatic scenarios

Emergency medical supplies scheduling during public health emergencies: algorithm design based on AI techniques

Based on AI technology, this study proposes a novel large-scale emergency medical supplies scheduling (EMSS) algorithm to address the issues of low turnover efficiency of medical supplies and unbalanced supply and demand point scheduling in public health emergencies. We construct a fairness index using an improved Gini coefficient by considering the demand for emergency medical supplies (EMS), actual distribution, and the degree of emergency at disaster sites. We developed a bi-objective optimisation model with a minimum Gini index and scheduling time. We employ a heterogeneous ant colony algorithm to solve the Pareto boundary based on reinforcement learning. A reinforcement learning mechanism is introduced to update and exchange pheromones among populations, with reward factors set to adjust pheromones and improve algorithm convergence speed. The effectiveness of the algorithm for a large EMSS problem is verified by comparing its comprehensive performance against a super-large capacity evaluation index. Results demonstrate the algorithm's effectiveness in reducing convergence time and facilitating escape from local optima in EMSS problems. The algorithm addresses the issue of demand differences at each disaster point affecting fair distribution. This study optimises early-stage EMSS schemes for public health events to minimise losses and casualties while mitigating emotional distress among disaster victims

A Commons for a Supply Chain in the Post-COVID-19 Era: The Case for a Reformed Strategic National Stockpile

The article of record as published may be found at http://dx.doi.org/10.1111/1468-0009.12485Policy Points: Reflecting on current response deficiencies, we offer a model for a na- tional contingency supply chain cell (NCSCC) construct to manage the medical materials supply chain in support of emergencies, such as COVID-19. We develop the following: a framework for governance and response to enable a globally independent supply chain; a flexible structure to accommodate the requirements of state and r county health systems for receiving and distributing materials; and a national material "control tower" to improve transparency and real- time access to material status and location.Office of Naval Research grants N00014-04-1-0118, N00014-10- 1-0200, N00014-11-1-0783, N00014-10-1-0811, N00014-16-1-2567, and N00014-04-1-0018. A.N. acknowledges support from an NSF CAREER and NOAA OGP. A.B.M. acknowledges support from the Mexican National Council for Science and Technology (CONACyT).Office of Naval Research grants N00014-04-1-0118, N00014-10- 1-0200, N00014-11-1-0783, N00014-10-1-0811, N00014-16-1-2567, and N00014-04-1-0018

Logistics Preparedness During Health Emergencies in Ghana

This paper sought to investigate logistics preparedness of Ghanaian institutions during health emergencies.Two hundred and fifty-seven (257)respondents drawn from the security and other agencies within the EffutuMunicipality in the Central region of Ghana constituted the sample size. The authors used structural equation modelling (SEM) to test the study’s model and hypotheses.The study revealedthat, the availability of logistical support during emergencies is inadequate for efficient emergency management. Regarding logistical preparedness of health professionals and security agencies, there is much needs to be doneto attain the minimum acceptable standards. Thestudy further discovered that logistical resources are critical to the collaborative effort of health workers and security agencies.However, it was evident that collaboration among institutions does not necessarily enhance the success of emergency management.The study is significant because the steady rise in Ghana’s population coupled withurbanization has brought in its wake challenges that successive governments have struggled to surmount.The occurrence of frequent disasters meant that a study of this nature is important to bring to the fore the human and material costs, thus awakening the sensitivities of policy makers and authorities mandated to ensure the safety and wellbeing of the citizenry

Climate Change Triage

Climate change is the first global triage crisis. It is caused by the overuse of a severely limited natural resource—the atmosphere’s capacity to absorb greenhouse gases—and millions of lives depend on how international law allocates this resource among nations. This Article is the first to explore solutions for climate change mitigation through the lens of triage ethics, drawing on law, philosophy, moral theory, and economics. The literature on triage ethics—developed in contexts such as battlefield trauma, organ donation, emergency medicine, and distribution of food and shelter—has direct implications for climate change policy and law, yet it has been overlooked by climate change scholars. The triage lens rules out climate policies—including the current emissions path—that will lead to catastrophic warming, and it puts options on the table that are marginalized in the current United Nations negotiations on a climate change agreement. This Article examines three allocation principles that could potentially apply in climate change triage—utilitarianism, egalitarianism, and a market-based distribution—and it concludes that egalitarianism is the preferable allocation principle from the standpoint of ethics and international law. This Article ends by exploring four major policy implications that emerge from viewing climate change through the lens of triage