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Item type:Publication, Incorporating the six aims for quality in the analysis of trauma care(Taylor & Francis, 2021-07-20)The Institute of Medicine proposed six aims for healthcare quality improvement. Nevertheless, trauma care quality research still focuses on one aim at a time. This research investigates how to incorporate all aims into trauma care quality assessments using data from the Michigan Trauma Quality Improvement Program. Through a literature review, we identified quantifiable metrics for most aims, except for equity and patient-centeredness. We proposed two approaches to build composite scores accounting for equity via an adjustment procedure based on observed disparities. The single- and multi-aim approaches were compared through correlation, concordance of trauma centre categorisations, and hypothetical incentives. The differences in the approaches stemmed mainly from the weights allocated to the different aims. Results indicated the potential value of multi-aim quality assessment and provided insights about implementation challenges and opportunities. The methods are applicable to the preferred metrics; nevertheless, further research is needed in measuring patient-centeredness. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Optimization approaches for multiple conflicting objectives in sustainable green supply chain management(MDPI, 2022-10-01)Over the years, the global supply chain has evolved into a more extensive interconnected complex network with multiple suppliers, manufacturers, and customers. Since environmental issues have become a burning question in recent years, the focus has shifted to attaining sustainability in supply chain management. The green supply chain or sustainable network is a concept to reduce environmental impacts in the life cycle of a product. However, green supply chain management is often challenged with additional operating costs and difficulty monitoring the implications within the complex network system. Additionally, many stakeholders are unaware of the importance of sustainability analysis, which eventually complicates adopting green cultures in actual applications. Since green supply chain management deals with multiple aspects, such as cost and carbon emission, the multiobjective optimization method is widely used to evaluate supply chain performance. This paper intensively reviews the state-of-the-art literature on applying multiobjective optimization techniques in green supply chain management. The study highlights aspects of green supply chain structures, model formulation techniques considering multiple objectives simultaneously, and solution methods for multiobjective optimization problems. Finally, a conclusion is drawn with the scope of the potential research opportunities for integrating economic and environmental considerations in sustainable supply chain management practice. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Location optimization strategies for corn production and distribution towards sustainable green supply chain(Multidisciplinary Digital Publishing Institute (MDPI), 2024-09-01)The corn supply chain is vital for food security and economic stability regionally and globally. This study integrates sustainable supply chain management with location optimization to address trade-offs from climate change, economic viability, and environmental impact while assuming the constant social obligation inherent in the supply chain structure. Methods: This study employs a mixed-integer programming (MIP) framework to optimize facility locations in North Dakota, including corn production zones as suppliers and ethanol plants as consumers. Primary objectives include cost minimization and greenhouse gas reduction, enabling the prioritization of economic or environmental goals as per organizational strategies and regulations. This approach ultimately maximizes resource utilization by ensuring efficient production and distribution practices. Results: The case study results highlight the optimal selection of 20 out of 30 corn production zones to meet statewide ethanol plant demand efficiently. Using compressed natural gas (CNG) instead of diesel could potentially save USD 2 million annually and cut carbon emissions by up to 1148 thousand tons per year, demonstrating meaningful progress toward economic and environmental sustainability within the supply network. Conclusions: The presented work offers a systematic methodology for designing sustainable supply chains for various agricultural products, aligning with the broader goal of promoting sustainability and resilience for efficient agricultural production and distribution systems. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Advancements in UAV-enabled intelligent transportation systems: A three-layered framework and future directions(Multidisciplinary Digital Publishing Institute (MDPI), 2024-10-01)Featured Application: This paper addresses the practical application of unmanned aerial vehicles (UAVs) in modern transportation systems, mainly focusing on how UAVs can be effectively integrated into intelligent transportation systems (ITSs) to improve efficiency, safety, and decision-making in smart cities. It offers a framework for understanding current advancements and guides future research and development in this evolving field. Integrating unmanned aerial vehicles (UAVs) into intelligent transportation systems (ITSs) will be pivotal in shaping next-generation smart cities. This paper proposes a novel three-layered framework for integrating UAVs into intelligent transportation systems (ITSs) and reviews the current developments, challenges, and future directions in this emerging field. This framework provides a comprehensive overview of the key components of UAV-integrated ITSs, encompassing UAV specifications and deployment strategies, communication networks, and data utilization for traffic management. The first layer explores UAVs’ technical specifications, deployment strategies, and trajectory optimization, essential for maximizing UAV performance in transportation contexts. The second layer addresses the communication networks between UAVs and vehicles, along with the use of UAVs for responsive traffic monitoring. This includes the development of robust communication protocols and real-time traffic analysis to enhance system efficiency. The third layer focuses on advanced data collection processing techniques and complexities, reviewing the methods for analyzing the traffic data collected by UAVs for decision-making in transportation management. Moreover, the paper presents the current UAV-enabled ITS implementation, highlighting key challenges and future research directions. By providing a comprehensive overview of UAV-enabled ITSs, this study presents a significant portrayal of the current landscape of UAV integration in ITSs and serves as a foundation for future advancements in smart city infrastructure.Scopus© Citations 23 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An Integrated Data-Driven Predictive Resilience Framework for Disaster Evacuation Traffic Management(MDPI, 2023-06-01)Maintaining smooth traffic during disaster evacuation is a lifesaving step. Traffic resilience is often used to define the ability of a roadway during disaster evacuation to withstand and recover its functionality from disturbances in terms of traffic flow caused by a disaster. However, a high level of variances due to system complexity and inherent uncertainty associated with disaster and evacuation risks poses great challenges in predicting traffic resilience during evacuation. To fill this gap, this study aimed to propose a new integrated data-driven predictive resilience framework that enables incorporating traffic uncertainty factors in determining road traffic conditions and predicting traffic performance using machine learning approaches and various space and time (spatiotemporal) data sources. This study employed an augmented Long Short-Term Memory (LSTM)-based approach with correlated spatiotemporal traffic data to predict traffic conditions, then to map those conditions to traffic resilience levels: daily traffic, segment traffic, and overall route traffic. A case study of Hurricane Irma’s evacuation traffic was used to demonstrate the effectiveness of the proposed framework. The results indicated that the proposed method could effectively predict traffic conditions and thus help to determine traffic resilience. The data also confirmed that the traffic infrastructures along the US I-75 route remained resilient despite the disturbances during the disaster evacuation activities. The findings of this study suggest that the proposed framework is applicable to other disaster management scenarios to obtain more robust decisions for the emergency response during disaster evacuation. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Assessing sustainability risks in natural gas pipeline infrastructure: a systems-based incident analysis framework for social, environmental, and economic impacts(Springer Science+Business Media, 2026-06-01)As global energy demands grow, the sustainability of non-renewable energy infrastructures, such as natural gas pipelines, poses critical challenges to society, the environment, and the economy. This study adopts a systems-based incident analysis (SIA) framework to assess sustainability risks in natural gas pipeline infrastructure, focusing on social, environmental, and economic impacts and highlighting how failure events in pipeline operations contribute to sustainability concerns. With more than a decade of incident data (2010–2013) from the Pipeline and Hazardous Materials Safety Administration (PHMSA) as a case study, the framework highlights how pipeline failures contribute to sustainability concerns. Key risk factors, including failure causes, frequencies, and consequences, are examined across pipeline segments: gathering, transmission, and distribution. The analysis reveals that social risks are more prominent in distribution pipelines, environmental risks are a key concern for gathering pipelines, and economic risks affect all pipeline segments. Additionally, the sustainability risk matrix shows corrosion failure as the highest risk for gathering pipelines (78.5%), equipment damage for transmission pipelines (15.8%), and excavation damage in distribution pipelines (33.6%). This sustainability risk assessment emphasizes the need for integrated mitigation strategies that address these interconnected risks to ensure the resilience and sustainability of natural gas infrastructure during the energy transition.