The complexity of coupled risks, which refer to the compounded effects of interacting uncertainties across multiple interdependent objectives, is inherent to cities functioning as dynamic, interdependent systems. A di...
The complexity of coupled risks, which refer to the compounded effects of interacting uncertainties across multiple interdependent objectives, is inherent to cities functioning as dynamic, interdependent systems. A disruption in one domain ripples across various urban systems, often with unforeseen consequences. Central to this complexity are people, whose behaviors, needs, and vulnerabilities shape risk evolution and response effectiveness. Realizing cities as complex systems centered on human needs and behaviors is essential to understanding the complexities of coupled urban risks. This paper adopts a complex systems perspective to examine the intricacies of coupled urban risks, emphasizing the critical role of human decisions and behavior in shaping these dynamics. We focus on two key dimensions: cascading hazards in urban environments and cascading failures across interdependent exposed systems in cities. Existing risk assessment models often fail to capture the complexity of these processes, particularly when factoring in human decision-making. To tackle these challenges, we advocate for a standardized taxonomy of cascading hazards, urban components, and their interactions. At its core is a people-centric perspective, emphasizing the bidirectional interactions between people and the systems that serve them. Building on this foundation, we argue the need for an integrated, people-centric risk assessment framework that evaluates event impacts in relation to the hierarchical needs of people and incorporates their preparedness and response capacities. By leveraging real-time data, advanced simulations, and innovative validation methods, this framework aims to enhance the accuracy of coupled urban risk modeling. To effectively manage coupled urban risks, cities can draw from proven strategies in real complex systems. However, given the escalating uncertainties and complexities associated with climate change, prioritizing people-centric strategies is crucial. This ap
Recent methods based on mid-level visual concepts have shown promising capability in human action recognition field. Automatically discovering semantic entities such as parts for an action class remains challenging. I...
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This paper proposes a improved non-local means (NLM) filter for image denoising. Due to the drawback that the similarity is computed based on the noisy image, the traditional NLM method easily generates the artifacts ...
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This paper presented a control design methodology for a proton exchange membrane fuel cell (PEMFC) generation system for residential applications. The dynamic behavior of the generation system is complex in such appli...
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This paper presented a control design methodology for a proton exchange membrane fuel cell (PEMFC) generation system for residential applications. The dynamic behavior of the generation system is complex in such applications. A comprehensive control design is very important for achieving a steady system operation and efficiency. The control strategy for a 60 kW generation system was proposed and tested based on the system dynamic model. A two-variable single neuron proportional-integral (PI) decoupling controller was developed for anode pressure and humidity by adjusting the hydrogen flow and water injection. A similar controller was developed for cathode pressure and humidity by adjusting the exhaust flow and water injection. The desired oxygen excess ratio was kept by a feedback controller based on the load current. An optimal seeking controller was used to trace the unique optimal power point. Two negative feedback controllers were used to provide AC power and a suitable voltage for residential loads by a power conditioning unit. control simulation tests showed that 60 kW PEMFC generation system responded well for computer-simulated step changes in the load power demand. This control methodology for a 60 kW PEMFC generation system would be a competitive solution for system level designs such as parameter design, performance analysis, and online optimization.
This paper develops a method to learn very few discriminative part detectors from training videos directly, for action recognition. We hold the opinion that being discriminative to action classification is of primary ...
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This paper studies the synchronization problem of coupled delayed multistable neural networks (NNs) with directed topology. To begin with, several sufficient conditions are developed in terms of algebraic inequalities...
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Bus driver rostering is a world-wide problem, which is NP-hard. Two objectives exist in the problem: (1) minimizing the number of drivers;(2) minimizing excess workload of each driver and balancing excess workload amo...
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Vehicle scheduling plays a crucial role in public transport bus companies. An efficient schedule can help bus companies reduce operating costs while being an essential guide to daily operations. However, the precompil...
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ISBN:
(纸本)9781538629185
Vehicle scheduling plays a crucial role in public transport bus companies. An efficient schedule can help bus companies reduce operating costs while being an essential guide to daily operations. However, the precompiled schedule is usually hard to be adhered to in practice due to the diversity of traffic and driving conditions. Therefore, dynamic vehicle scheduling becomes an important supplement to the daily operations. In this paper, a dynamic vehicle scheduling approach based on Hierarchical Task Network(HTN) is proposed. In the approach, two dynamic vehicle scheduling strategies are devised according to the practical scheduling philosophy. The first is to reschedule for individual vehicle independently, the objective is to maximize the execution of the precompiled schedule. The second is to reschedule for multiple vehicles simultaneously, which aims to maintain the scheduled headways. The two strategies are achieved in the HTN planning through different task decomposition processes, which are constrained by vehicle resources currently available. To verify the feasibility, this approach is implemented based on the Simple Hierarchical Ordered Planner 2(SHOP2), which is a domainindependent and state-based forward HTN planner. Experimental results show that the approach has good adaptability to solve dynamic vehicle schedule problem, meanwhile, it can be helpful to deal with the abnormal services agilely and hence to increase the service quality of public transit.
Labor division provides an adaptive and scalable technique for unmanned systems. However, its designing process usually relies heavily on the manually crafted paradigms, leading to inefficiencies and insufficient perf...
Labor division provides an adaptive and scalable technique for unmanned systems. However, its designing process usually relies heavily on the manually crafted paradigms, leading to inefficiencies and insufficient performance. To overcome these challenges, this paper introduce an evolutionary approach to labor division algorithm design. Drawing inspiration from the regulatory behaviors observed in natural lion populations, we propose a bipolar feedback-guided attraction–repulsion mechanism. A formal model is developed to encapsulate this mechanism, and we provide an in-depth analysis of the algorithm’s evolution through the framework of systems science. In addition, we leverage prompt engineering techniques to integrate a large language model (LLM) with our proposed mechanism, facilitating a bidirectional enhancement between the two. This integration culminates in the development of the ARE-LLM framework, a robust and adaptive solution for designing labor division algorithms. To demonstrate the practical applicability of our approach, we apply the ARE-LLM framework to the UAV-based task allocation problem for enemy air defense suppression. The experimental results indicate that our method outperforms several advanced approaches. In a scenario involving 50 UAVs tasked with completing 300 assignments, the total distance traveled is only 9 % of that required by the ALPDA algorithm, while the processing time is reduced to 8 % of that used by ALPDA.
This paper presents a novel approach to compute DCT-I, DCT-III, and DCT-IV. By using a modular mapping and truncating, DCTs are approximated by linear sums of discrete moments computed fast only through additions. Thi...
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