ABSTRACT
The global pandemic has significantly accelerated the need for remote monitoring and diagnostics of airline operations and assets. As passenger and cargo flights are impacted from all directions, maintenance can be the steady, reliable part of the puzzle that helps get things back on track. This chapter explores the aircraft safety challenges that can be addressed with better maintenance technology and human factor modeling. Aircraft safety relies heavily on maintenance. During the COVID-19 recovery phase, airline operators need to focus on the application of a robust management of change process to implement better maintenance technology, identify new aircraft safety risks, determine effective mitigation measures, and implement strategies for deploying changes accordingly. For years aircraft maintenance routines have been carried out in the same manner without change, now with international travel restrictions, social distancing, reduced staff, and limited maintenance funding, the need for smarter ways of doing maintenance is obvious. In this regard smart technology has an important role to play. For instance, IoT data generates the capacity for predictive aircraft maintenance, AI introduces the capacity for smart, deep-learning machines to make predictive maintenance more accurate, actionable, and automatic. AI-enabled predictive maintenance leverages IoT data to predict and prevent aircraft failures. While smart technology enhances aircraft safety through better maintenance performance on the one hand, there are technical and human factor problems induced by COVID-19 on the other. The Safe Aircraft System (SAS) model, based on the Dirty Dozen and SHELL human factor models, is an initiative proposed to minimize such COVID-19 problems. This work shows through a case illustration that SAS modeling is a useful tool in identifying potential hazards/consequences associated with any major or minor changes in flight operations. Hence the synergistic effect of smart maintenance and the SAS model in enhancing aircraft system safety are demonstrated. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
The pandemic situation (Covid 19) brought new challenges in the education sector while simultaneously presenting unique opportunities for technology enabled services. The use of Mobile Robotic Telepresence systems in educational sector is promising as it provides means to significantly enhance the involvement and benefits to stakeholders involved in such interactions. An immersive user interaction with such a system depends on many aspects which are both static and dynamic. We approach the dynamic aspect of such interactions recognizing that the video and audio aspects of such a system will require fine tuning and adaptation. Closely related is the aspect of maintaining the necessary quality of network connection. Considering each of these aspects a reinforcement learning mechanism is incorporated to improve the overall user experience with such a system. A working system is built and experiments performed to demonstrate the effectiveness of the approach. Reward generation matrix, a crucial piece of data gathering from the environment, takes about 45 minutes, offline training time is less than a second, while the robot is able to cover the workspace in slightly less than a minute. The system is not limited to educational sector alone and provides a foundational framework to extend the concepts and principles to adjacent markets. © 2023 IEEE.
ABSTRACT
The years since 2000 have been a golden age in in situ ocean observing with the proliferation and organization of autonomous platforms such as surface drogued buoys and subsurface Argo profiling floats augmenting ship-based observations. Global time series of mean sea surface temperature and ocean heat content are routinely calculated based on data from these platforms, enhancing our understanding of the ocean's role in Earth's climate system. Individual measurements of meteorological, sea surface, and subsurface variables directly improve our understanding of the Earth system, weather forecasting, and climate projections. They also provide the data necessary for validating and calibrating satellite observations. Maintaining this ocean observing system has been a technological, logistical, and funding challenge. The global COVID-19 pandemic, which took hold in 2020, added strain to the maintenance of the observing system. A survey of the contributing components of the observing system illustrates the impacts of the pandemic from January 2020 through December 2021. The pandemic did not reduce the short-term geographic coverage (days to months) capabilities mainly due to the continuation of autonomous platform observations. In contrast, the pandemic caused critical loss to longer-term (years to decades) observations, greatly impairing the monitoring of such crucial variables as ocean carbon and the state of the deep ocean. So, while the observing system has held under the stress of the pandemic, work must be done to restore the interrupted replenishment of the autonomous components and plan for more resilient methods to support components of the system that rely on cruise-based measurements. © 2023 American Meteorological Society.
ABSTRACT
As current production and consumption patterns exceed planetary boundaries, many leaders have stressed the need to adopt green economic stimulus policies in the aftermath of the COVID-19 pandemic. This paper provides an integrated multi-stakeholder framework to design an economic recovery strategy aligned with climate stabilisation objectives. We first employ quantitative energy and economic models, and then a multi-criteria decision process in which we engage social actors from government, enterprises and civil society. As a case study, we select green recovery measures that are relevant for a European Union country and assess their appropriateness with numerous criteria related to climate resilience and socio-economic sustainability. Results highlight trade-offs between immediate and long-run effects, economic and environmental objectives, and expert evidence and societal priorities. Importantly, we find that a ‘return-to-normal' economic stimulus is environmentally unsustainable and economically inferior to most green recovery schemes. © 2022 The Author(s)
ABSTRACT
The major ports along the coast of China that undertake container transportation are all facing problems in collection and dispatching to a certain extent. In particular, due to the recent impact of the COVID-19 epidemic, truck drivers have difficulty moving across regions, and there was once a phenomenon of no containers being transported by vehicles. This paper sorted out the basic situation of container port collection and dispatching methods all over the world. Taking Shenzhen Port as an example, this paper focused on the analysis of the structural characteristics of container transportation and the impact on the rear urban traffic and atmospheric environment. Then it proposed a intermodal transportation network and established the 'Port Shuttle Hub System' model, which would closely link the port with the railway and inland port, and integrate the transportation organization mode, which greatly improves the efficiency of port containers' transportation. © 2021 IEEE.
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The number of refugees in the world peaked at 26.3 million as of mid-2020. More than 75 percent of these refugees are in a protracted situation, one in which refugees find themselves in a long-lasting and intractable state of limbo. However, the budget for refugee protection and care has not been sufficient for years. Due to the limited humanitarian and developmental budget, the role of refugee-related businesses is gaining more attention. The aim of this study is to show the feasibility of the partially online systems-based Evolutionary Learning Laboratory (ELLab) approach in the COVID-19 era via a case study of Uganda and to identify the current systems model of refugee-related businesses, their leverage points, and the action plans necessary for the development of an optimal systems model for refugee-related businesses. The authors suggested the efficacy of the online system-based ELLab and provided new ways for the application of the ELLab method in the COVID-19 era. They also managed to identify the current systems model of refugee-related businesses, their leverage points, and their action plans through the ELLab process. © ISSS 2021. All right reserved.
ABSTRACT
The study's purpose is to create an LMS model that is adapted to the characteristics of university students to enhance the learning experience by utilizing various multidimensional learning resources in Cyber Pedagogy. This research and development study used the Analyze, Design, Develop, Implement, and Evaluate (ADDIE) instructional design framework as well as the Waterfall system development model to develop learning materials and infrastructure. The study involves 50 students from the Bali Institute of Technology and Business, as well as five lecturers and six judges at the expert test stage, namely learning media experts, learning design experts, and teaching experts, who were chosen through purposive sampling. The SMILE Model (Simple, Multidimensional, and Interactive Learning Ecosystem) is designed to meet the learning needs and expectations of today's largest market share of higher education, the millennial generation. The SMILE Model was developed successfully with ongoing assistance from researchers' students, particularly in the E-Tourism course. The implementation is accomplished through the combination of university E-Learning and the use of Microsoft Teams as a virtual learning platform alternative. During the COVID-19 pandemic, this was considered the new face-to-face norm. © 2022. All Rights Reserved.
ABSTRACT
This paper presents the Live Interactive Streaming Classroom (LISC) system model which can be applied to the Problem-Based Learning (PBL) and motivate students to solve problems in a real-life setting with guidance from teachers via online learning. In this study, the students used self-learning methods for interactive class. The class was managed through the online streaming system by the video conference applications. The study showed that the students' coding and real-life problem solving skills were improved from hand-on experience. The LISC system model stimulated students' learning levels. This was proved by applying the proposed method to the Data Science class at Silpakorn University, Thailand, joined by an instructor from Japan. When the course ended, the evaluation from the participating students showed that they were much satisfied that their skills were up-leveled for coding and real-life problem solving, and their attitudes towards the Data Science class improved. It implied and confirmed that the proposed method was efficient to the students' practical learning level, among the new normal living period in the Coronavirus pandemic. © 2022 ACM.
ABSTRACT
The worldwide spread of COVID-19 has greatly hit global economy by now. The world’s major economies including both developed and developing countries have felt the resulting impact on their financial markets. Accordingly, learning residents’ consumption structure is significant for boosting consumption demand and recovering financial market. In this paper, the Extend Linear Expenditure System (ELES) model is explored to learn both urban and rural residents’ consumption structures of China during COVID-19. In specific, the indices of marginal propensity to consume, income elasticity of demand, and price elasticity can be yielded via the ELES model based on the disposable income and the consumption data. Furthermore, the consumption structures before and during the corona virus epidemic can be quantitatively compared. Extensive experimental results demonstrate that the epidemic has made profound impacts on the consumption structure of residents. Among them, the marginal propensities on food and medical services have greatly increased, while the proportions of other expenditures have been decreased. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
At the end of first quarter of 2020 it was seen in most countries statistics the beginning of an imminent second wave of pandemic. On January of 2021 it was seen in the data a rapid growth of new infections. In this paper, a geometry-based scheme is presented. In concrete the rectangle and trapezoid shapes are analyzed. From this, a relation between both geometries is extracted in terms of polynomial functions. The resulting characterization of a pandemic in terms of geometric variables is presented. Thus the present model is confronted with official data of USA and India. From the results of this paper, it is strongly believed that entropy might be behind of a global pandemic dynamics. © 2021 IEEE.
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The article presents the original methodology of using agent-based modeling (ABM) for the numerical simulations of the COVID-19 pandemic's development. The proposed solution makes it possible to analyze changes in the number of cases both in space and time. The devised methodology enables considering spatial conditions in terms of population distribution, such as places of work, rest, or residence, and uses multi-agent modeling to consider spatial interactions. Numerical simulations utilize the spatial and demographic data in GIS databases and the GAMA environment that enables the parameterization of the epidemiological model. Testing the developed methodology on a test area also allowed for checking the effects of a potential decrease or increase in social restrictions numerically. The simulations performed show a high correlation between the level of social distancing and the number of COVID-19 cases. © 2021 IEEE.
ABSTRACT
Material production drives an increasingly large fraction of CO2-equivalent emissions. Material efficiency strategies such as recycling serve to reduce these emissions. However, prior analyses of such strategies do not include economically induced rebound effects, overestimating the associated environmental benefits. We present a dynamic supply chain simulation model for copper through 2040 incorporating inventory-driven price evolution, dynamic material flow analysis, and life cycle assessment alongside mine-level economic evaluation of opening, closing, and capacity utilization decisions. We show that increases in recycling suppress raw material prices, driving increases in demand that limit primary production reduction and offset ~45% of the potential environmental benefits. Sufficiently small recycling increases and policy reversals were found capable of increasing mining and CO2-equivalent emissions. This model was expanded to accommodate regional variations and assess the impacts of China’s solid waste import ban and the COVID-19 pandemic, demonstrating the need for further investment in secondary markets. © 2022, The Minerals, Metals & Materials Society.
ABSTRACT
The article analyzes the research, which was carried out for several years to model the system of internal certification of educational resources for blended and e-learning in Higher education. The authors describe the prerequisites for the internal certification system modeling and the features of recent changes in the process of internal certification of educational resources, approved by the university regulations, which is related to the requirements of the situation with COVID-19. The article describes the current model of the system of internal certification of educational resources, which is based on the approbation of the pilot model of e-learning courses (hereinafter - ELC) certification. The key components of the internal certification system are three mandatory expertise (professional, resource and technical). Based on the results of which, the methodological commission decides on the quality of educational resources of the ENC and its certification. Expectations from the current system of internal certification of ELC implementation were justified to a high degree, in particular, we have the following advantages of their use: the creation of quality educational resources, expanding access to various categories of participants in the educational process to educational content;ensuring the individualization of the educational process under the needs, characteristics and capabilities of learners;improving the quality and efficiency of the educational process through the use of digital and innovative educational technologies;ensuring systematic monitoring of the quality of education, implementation of blended and e-learning in higher education. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
ABSTRACT
Attendance system has evolved along with the industrial revolution that now has reached a new era. Furthermore, nowadays with the struck of COVID-19, the government issued a prohibition policy towards companies to urge their employees to work from home (WFH). Several issues have come across the Human Resources Development (HRD) manager regarding this policy. Employees' taking vacation when they are obliged to work from home and employees' faking their attendance are two of many problems regarding this policy. Hence, this study aims to design a relevant attendance system model that will overcome these problems with the integration of face recognition and geolocation through mobile platform. The study built the proposed attendance system with the approach of User-Centered Design (UCD) methodology. The findings within the study shows that above 80% of participants are satisfied with the proposed model and are ready to implement the designed system in their organizations respectively. © 2021 IEEE.
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With the sudden changes brought about with the COVID-19 pandemic, primarily the new legitimacy of online education, the traditional college and university boards are all actively discussing how the institutions can reform themselves in a strategic sense. This article presents a conceptual framework for viewing education institutions as an open system using the General Systems Theory (GST) and discusses how it could help improve the higher education system. The author concludes that the education institutions must carefully select the institution's components;should carefully and strategically manage the internal and external stakeholder network including all communications and informed decisions;accept that change of student perceptions is a norm and promote agility in the system operations, and also highlights that it is natural for systems to have specialized, outperforming departments/sections. The concepts discussed here could be further researched and would hopefully be of use for policy makers and administrators of higher education systems, while the author also wishes to spark a conversation amongst the citizens. © American Society for Engineering Management, 2021
ABSTRACT
With the advancement of the Internet of Things in our smart environment, smart devices are working without human intervention. So home can be converted to intelligent home automation systems to perform its computation automatically. In a pandemic situation, the majority of people have spent their maximum time at home. So indoor air quality, insider's and outsider's health monitoring has become an important issue. As respiratory diseases are the main concern for pandemics, we have to develop an intelligent home system model to monitor healthy environmental conditions for the users. This paper proposes an energy-efficient smart system model to monitor the health and environmental condition by measuring the carbon monoxide threat level that indirectly affects other atmospheric parameters. Our system alerts when the carbon monoxide level exceeds the safe level. Remote monitoring of the home and health parameters is done in real-time with the help of the system model. For this purpose, we are adopting Dempster-Shafer evidence theory as a mathematical model to aggregate the data coming from different sensors. The sensor nodes track the home and health parameters such as room temperature, humidity, carbon monoxide level, SpO2 level, body temperature, and pulse rate. The smartphone app updates the user's real-time sensor data through the display and indirectly helps to maintain the physical distance. The proposed intelligent home-health system model is compact, cost-effective, energy-efficient for the user, and is especially useful for the quarantined covid affected people in a pandemic situation. © 2022 ACM.
ABSTRACT
Since COVID-19, the already fragile food system has become even more overburdened, and food security has become an urgent issue. Due to the excessive pursuit of efficiency and profit, the food system in the past has created various problems, the most prominent problem is the inability to find a balance between profit and ecological environment. Therefore, this article focuses on how to build a model that includes both aspects. In order to analyse the existing food system and introduce new ones, firstly, divide the food system into four subsystems of profitability, efficiency, sustainability, and equity, and set up several secondary indicators under each subsystem, and select appropriate countries as samples. Use the AHP, EWM, and CEM to calculate the corresponding index of each subsystem to form a new comprehensive evaluation model for the food system. © 2021 ACM.