This study focuses on exploring the effects of geometrical imperfections and different analysis methods on the optimum design of Double-Layer Grids(DLGs),as used in the construction industry.A total of 12 notable meta...
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This study focuses on exploring the effects of geometrical imperfections and different analysis methods on the optimum design of Double-Layer Grids(DLGs),as used in the construction industry.A total of 12 notable metaheuristics are assessed and contrasted,and as a result,the Slime Mold Algorithm is identified as the most effective approach for size optimization of *** evaluate the influence of geometric imperfections and nonlinearity on the optimal design of real-size DLGs,the optimization process is carried out by considering and disregarding geometric nonlinearity while incorporating three distinct forms of geometrical imperfections,namely local imperfections,global imperfections,and combinations of *** light of the uncertain nature of geometrical imperfections,probabilistic distributions are used to define these imperfections randomly in direction and *** results demonstrate that it is necessary to account for these imperfections to obtain an optimal ***’s worth noting that structural imperfections can increase the maximum stress ratio by up to 70%.The analysis also reveals that the initial curvature of members has a more significant impact on the optimal design of structures than the nodal installation error,indicating the need for greater attention to local imperfection issues in space structure construction.
The pixel-wise dense prediction tasks based on weakly supervisions currently use Class Attention Maps(CAMs)to generate pseudo masks as ***,existing methods often incorporate trainable modules to expand the immature cl...
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The pixel-wise dense prediction tasks based on weakly supervisions currently use Class Attention Maps(CAMs)to generate pseudo masks as ***,existing methods often incorporate trainable modules to expand the immature class activation maps,which can result in significant computational overhead and complicate the training *** this work,we investigate the semantic structure information concealed within the CNN network,and propose a semantic structure aware inference(SSA)method that utilizes this information to obtain high-quality CAM without any additional training ***,the semantic structure modeling module(SSM)is first proposed to generate the classagnostic semantic correlation representation,where each item denotes the affinity degree between one category of objects and all the ***,the immature CAM are refined through a dot product operation that utilizes semantic structure ***,the polished CAMs from different backbone stages are fused as the *** advantage of SSA lies in its parameter-free nature and the absence of additional training costs,which makes it suitable for various weakly supervised pixel-dense prediction *** conducted extensive experiments on weakly supervised object localization and weakly supervised semantic segmentation,and the results confirm the effectiveness of SSA.
Implementing quantum wireless multi-hop network communication is essential to improve the global quantum network system. In this paper, we employ eight-level GHZ states as quantum channels to realize multi-hop quantum...
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Implementing quantum wireless multi-hop network communication is essential to improve the global quantum network system. In this paper, we employ eight-level GHZ states as quantum channels to realize multi-hop quantum communication, and utilize the logical relationship between the measurements of each node to derive the unitary operation performed by the end node. The hierarchical simultaneous entanglement switching(HSES) method is adopted, resulting in a significant reduction in the consumption of classical information compared to multi-hop quantum teleportation(QT)based on general simultaneous entanglement switching(SES). In addition, the proposed protocol is simulated on the IBM Quantum Experiment platform(IBM QE). Then, the data obtained from the experiment are analyzed using quantum state tomography, which verifies the protocol's good fidelity and accuracy. Finally, by calculating fidelity, we analyze the impact of four different types of noise(phase-damping, amplitude-damping, phase-flip and bit-flip) in this protocol.
Industrial cyber-physical systems closely integrate physical processes with cyberspace, enabling real-time exchange of various information about system dynamics, sensor outputs, and control decisions. The connection b...
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Industrial cyber-physical systems closely integrate physical processes with cyberspace, enabling real-time exchange of various information about system dynamics, sensor outputs, and control decisions. The connection between cyberspace and physical processes results in the exposure of industrial production information to unprecedented security risks. It is imperative to develop suitable strategies to ensure cyber security while meeting basic performance *** the perspective of control engineering, this review presents the most up-to-date results for privacy-preserving filtering,control, and optimization in industrial cyber-physical systems. Fashionable privacy-preserving strategies and mainstream evaluation metrics are first presented in a systematic manner for performance evaluation and engineering *** discussion discloses the impact of typical filtering algorithms on filtering performance, specifically for privacy-preserving Kalman filtering. Then, the latest development of industrial control is systematically investigated from consensus control of multi-agent systems, platoon control of autonomous vehicles as well as hierarchical control of power systems. The focus thereafter is on the latest privacy-preserving optimization algorithms in the framework of consensus and their applications in distributed economic dispatch issues and energy management of networked power systems. In the end, several topics for potential future research are highlighted.
Utilizing the ballast layer with more durable and stable characteristics can help avoid significant expenses due to decreased maintenance *** the ballast layer with different types of reinforcements or substituting th...
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Utilizing the ballast layer with more durable and stable characteristics can help avoid significant expenses due to decreased maintenance *** the ballast layer with different types of reinforcements or substituting the stone aggregates with the appropriate granular materials could potentially help to achieve this goal by reducing the ballast *** of the exquisite and most effective solutions to eliminate these challenges is to use waste materials such as steel slag aggregates and useless *** these waste materials in the ballasted railway track will contribute to sustainable development,an eco-friendly system,and green *** in a state-of-the-art insightful,the ballast aggregates,including a mixture of steel slag and stone aggregates,are reinforced with a novel kind of geo-grid made of waste tire strips known as *** laboratory research tried to explain the shear strength behavior of the introduced mixing slag-stone ballast reinforced with tire *** achieve this goal,a series of large-scale direct shear tests were performed on the ballast which is reinforced by tire geo-scrap and included various combinations of slag and stone *** concluded results indicate that the optimal mixing ratio is attained by a combination of 75%slag and 25%stone aggregates which is reinforced by tire geo-scrap at a placing level of 120 *** this case,the shear strength,internal friction angle,vertical displacement,and dilatancy angle of stone–slag ballast reinforced with geo-scraps exhibited average changes of+28%,+9%,-28%,and-15%,respectively.
Recently,weak supervision has received growing attention in the field of salient object detection due to the convenience of ***,there is a large performance gap between weakly supervised and fully supervised salient o...
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Recently,weak supervision has received growing attention in the field of salient object detection due to the convenience of ***,there is a large performance gap between weakly supervised and fully supervised salient object detectors because the scribble annotation can only provide very limited foreground/background ***,an intuitive idea is to infer annotations that cover more complete object and background regions for *** this end,a label inference strategy is proposed based on the assumption that pixels with similar colours and close positions should have consistent ***,k-means clustering algorithm was first performed on both colours and coordinates of original annotations,and then assigned the same labels to points having similar colours with colour cluster centres and near coordinate cluster ***,the same annotations for pixels with similar colours within each kernel neighbourhood was set *** experiments on six benchmarks demonstrate that our method can significantly improve the performance and achieve the state-of-the-art results.
We present the models implemented by the NICA group for the Quantum Computing (QuantumCLEF) Shared Task at CLEF 2024. Our participation focused on Task 1A: Feature Selection (Information Retrieval Task). We propose a ...
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The layered nature of the parts produced by 3D printing makes them susceptible to freeze-thaw *** investigates the effect of the freeze-thaw cycles on the tensile,bending,and fracture resistance of samplesmade of Poly...
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The layered nature of the parts produced by 3D printing makes them susceptible to freeze-thaw *** investigates the effect of the freeze-thaw cycles on the tensile,bending,and fracture resistance of samplesmade of Polylactic acid *** this purpose,the samples with 100,75,50,and 25 infill percentages weresubjected to 4,8,and 12 freeze-thaw *** results show that the infill percentage and cycle affect freeze-thaw ***,although for 100%infill samples,the 4,8,and 12 cycles averagely reduce the tensile strengthby 5,15,and *** same trends can also be seen for flexural strength and,more severely,fracture *** the microstructure with a Scanning electron microscopy device shows freezethaw’s destructive effect(both the strand’s surface and their joints).In the end,simple statistical analyses were presented to evaluate amodel for anticipating the effect of freeze-thaw on mechanical resistance.
As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention...
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As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention on privacy-preserving model explanations. This article presents the first thorough survey about privacy attacks on model explanations and their countermeasures. Our contribution to this field comprises a thorough analysis of research papers with a connected taxonomy that facilitates the categorization of privacy attacks and countermeasures based on the targeted explanations. This work also includes an initial investigation into the causes of privacy leaks. Finally, we discuss unresolved issues and prospective research directions uncovered in our analysis. This survey aims to be a valuable resource for the research community and offers clear insights for those new to this domain. To support ongoing research, we have established an online resource repository, which will be continuously updated with new and relevant findings.
In the wake of rapid advancements in artificial intelligence(AI), we stand on the brink of a transformative leap in data systems. The imminent fusion of AI and DB(AI×DB) promises a new generation of data systems,...
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In the wake of rapid advancements in artificial intelligence(AI), we stand on the brink of a transformative leap in data systems. The imminent fusion of AI and DB(AI×DB) promises a new generation of data systems, which will relieve the burden on end-users across all industry sectors by featuring AI-enhanced functionalities, such as personalized and automated in-database AI-powered analytics, and selfdriving capabilities for improved system performance. In this paper, we explore the evolution of data systems with a focus on deepening the fusion of AI and DB. We present NeurDB, an AI-powered autonomous data system designed to fully embrace AI design in each major system component and provide in-database AI-powered analytics. We outline the conceptual and architectural overview of NeurDB, discuss its design choices and key components, and report its current development and future plan.
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