3,781 research outputs found
Vibration suppression of suspended cables with three-to-one internal resonances via time-delay feedback
No full textBased on the time-delay feedback control, the vibration suppression of suspended cables with three-to-one internal resonances are investigated. Initially, the nonlinear differential equation of motion for a suspended cable under time-delay feedback control is considered, and a discrete model is derived using the Galerkin method. Subsequently, the method of multiple scales is employed to perturbatively solve the discrete time-delay differential equation, determining the modulation equations around the first primary resonance. Steady-state and periodic solutions of the modulation equations are detected numerically. Numerical results indicate that the internal resonance enhances the nonlinear dynamical complexity of the controlled suspended cable. It is observed that the time delay and control gain affect the controlled system: in particular, an increase in control gain leads to a reduction in response amplitude. By adjusting the time delay and control gain, the critical excitation can be altered, an aspect that could be very useful from a practical point of view. This research sheds light on the intricate dynamics of suspended cable and provides a theoretical foundation for designing more effective control strategies in engineering applications
Adaptive and Efficient Qubit Allocation Using Reinforcement Learning in Quantum Networks
No full textHow to classify microclimates more validly and finely? A novel method for mapping local climate zone (LCZ) on micro-scales
No full textGlobal climate change and rapid urbanization are driving microclimate variations in urban areas, intensifying the formation of urban heat islands (UHIs) vulnerable to extreme weather. The local climate zone (LCZ) framework, using remote sensing (RS) and geographic information system (GIS), has advanced with the World Urban Database and Access Portal Tool (WUDAPT), enabling microclimate understanding for improved urban planning and climate adaptation. However, mapping LCZs at the micro-scale relies on locally available GIS data or RS imagery, data gaps, authenticity issues, and low-resolution imagery often lead to inaccurate microclimate classifications. To enhance the validity and sophistication of microclimate classification, this study introduces a novel method for mapping LCZ using unmanned aerial vehicle (UAV) photogrammetry at the micro-scale (LCZ-UAV-MS), which constructs detailed land use and land cover (LULC) and 3D real scene (3DRS) models, calculates urban surface parameters (USPs) for each basic spatial unit (BSU) through spatial statistical analysis, and employs a decision-making classifier to categorize each BSU. This study validates the proposed method using Gulangyu as the study area, employing image overlay, temperature observation, and expert knowledge, with the following results: 1) Spatial percentage showing 51 % natural environments (LCZ A, B, C, and D), 27 % neutral environments (LCZ 7, 8, 9, 10, and Y), and 22 % built environments (LCZ 1, 2, 3, 4, 5, and 6) in Gulangyu. 2) The variance in mean LST across different LCZs was 1.02 in January and 5.18 in August 2024, with temperature differences more pronounced in summer, where the built environment had a higher mean LST of 41.3 °C compared to 35.2 °C in the natural environment and 38.3 °C in the neutral environment. 3) Field research at 22 random sample sites showed that 95 % of LCZ-UAV-MS classifications matched the field, outperforming WUDAPT LCZ, which matched only 10 %. These demonstrate that the LCZ-UAV-MS accurately captures microclimate temperature variations and provides a more precise micro-scale description than the WUDAPT LCZ. This study bridges the gap of LCZ studies in specific regions and scales, enhances the applicability of the LCZ framework at the micro-scale, and provides technical support for urban blue-green infrastructure management and resilient climate design strategies
Video Content Placement at the Network Edge: Centralized and Distributed Algorithms
No full textIn the traditional video streaming service paradigm, content providers typically provision the requested video content to viewers through a central content delivery network (CDN). However, remote viewers usually experience long video streaming delay due to uncertain wide area network delay, which severely affects the quality of experience. Multi-Access Edge Computing (MEC) offers a way to shorten the video streaming delay by building small-scale cloud infrastructures at the network edge, which are in close proximity to the viewers. In this paper, we present novel centralized and distributed algorithms for the video content placement problem in MEC. In the proposed centralized video content placement algorithm, we leverage the Lyapunov optimization technique to formulate the video content placement problem as a series of one-time-slot optimization problems and apply an Alternating Direction Method of Multipliers (ADMM)-based method to solve each of them. We further devise a distributed Multi-Agent Reinforcement Learning (MARL)-based method with value decomposition mechanism and parallelization policy update method to solve the video content placement problem. The value Decomposition mechanism deals with the credit assignment among multiple agents, which promotes the cooperative optimization of the global target and reduces the frequency of information exchange. The parallelization of policy network can speed up the convergence process. Simulation results verify the effectiveness and superiority of our proposed centralized and distributed algorithms in terms of performance.</p
Molecular dynamics simulation of the interfacial thermal resistance between phosphorene and silicon substrate
No full textPhosphorene is a recently discovered member of the two-dimensional (2D) monolayer materials, which has been reported to exhibit unique characteristics on mechanical and thermal properties. This study is the first time to show the exceptional thermal conductance between phosphorene and crystalline silicon substrate through classical molecular dynamics (MD) simulations. MD simulations revealed that under conventional conditions, the interfacial thermal resistance (R) between phosphorene and silicon is very low and independent on the thickness (h) of silicon substrate when h is larger than 3.12 nm. It was also found that R decreases remarkably with the increases in system temperature (Tie) and contact strength (χ). To further explicitly display the superiority of phosphorene on interfacial heat transfer, R of other two popular 2D monolayer materials, i.e., graphene and silicene, were calculated for comparison. The comparisons revealed that R of phosphorene shows two distinct advantages over graphene and silicene. On one hand, within the studied ranges of Tie and χ, R between phosphorene and silicon substrate is about quarter of that between graphene and silicon substrate, which proves that phosphorene is really a high-performance 2D monolayer material for interfacial heat transfer. On the other hand, with the increases in Tie and χ, R between phosphorene and silicon substrate decreases more sharply than that between silicene and silicon substrate, indicating that phosphorene is more sensitive to environmental variations
Search by Image: Deep Learning Based Image Visual Feature Extraction
No full textIn recent years, the expansion of the Internet has brought an explosion of visual information, including social media, medical photographs, and digital history. This massive amount of visual content generation and sharing presents new challenges, especially when searching for similar information in databases —— Content-Based Image Retrieval (CBIR). Feature extraction is the foundation of image retrieval, making research into obtaining concrete features and representations of image content a vital concern. In the feature extraction module, We first pre-process the target image and input it into a CNN to obtain feature maps for different channels. These feature maps can be aggregated into compact and global uniform descriptors by pooling. Then these global descriptors are further dimensionalised and normalized by whitening methods to obtain image feature vectors that are easy to compute and compare. In this process, the accuracy of the retrieval depends on how accurately the final feature vectors represent the meaning expressed by the target image. Therefore, various CNN network structures, pooling and whitening methods are proposed to get more concrete feature vectors.In this thesis, our study (1) fine tunes the pre-trained CNNs, (2) optimizes the application of second-order attention information in feature map, (3) applies and compares popular feature enhancement methods in both aggregating and whitening, (4) explores how to combine all strengths, and (5) propose a new model \textit{ResNet-SOI}, which achieves 53.4(M) and 59.2(M) mAP on the challenging benchmark \textit{ROxford5k+1M} and\textit{ RParis6k+1M}, and outperforms the state-of-art methods. Our prototype GUI is available on GitHub (https://github.com/yanan-huu/Image-Search-Engine-for-Historical-Research).Electrical Engineering | Circuits and System
Wind turbine blade trailing edge crack detection based on airfoil aerodynamic noise: An experimental study
No full textIn recent years, with the development of the wind power industry and the increase in the number of wind turbines, the condition monitoring of blades and the detection of damage are increasingly important. In this work, a new non-contact damage-detection approach is experimentally investigated based on the measurement of airfoil aerodynamic noise. A NACA 0018 airfoil with chord of 200 mm with different trailing edge crack sizes, 0.2, 0.5, 1.0 and 2.0 mm, is investigated. Experiments are conducted at different mean flow velocities, inflow turbulence intensities and angles of attack. Far-field noise scattered from the airfoil is measured by means of a microphone array. The spectral differences of sound pressure level between the damaged cases and the baseline (without any damage) are compared. As expected, at small angles of attack, with clean or low turbulence intensities (e.g. ∼ 4% in the experiment) flow, by increasing the size of the crack, tonal noise appears at trailing-edge thickness-based Strouhal number,Sth , approximatively equal to 0.1. However, at higher angles of attack (e.g. ± 10° and ± 15°) or under conditions of high turbulence intensity (e.g. ∼ 7%), the amplitude of the tonal peak diminishes suggesting that complementary measurements or longer acquisition time to remove inflow turbulence effects are needed to monitor trailing edge cracks.Wind Energ
sj-pdf-1-imr-10.1177_03000605221089503 - Supplemental material for MicroRNAs as potential biomarkers for the diagnosis of inflammatory bowel disease: a systematic review and meta-analysis
No full textSupplemental material, sj-pdf-1-imr-10.1177_03000605221089503 for MicroRNAs as potential biomarkers for the diagnosis of inflammatory bowel disease: a systematic review and meta-analysis by Lina Sun, Yanan Han, Hua Wang, Huanyu Liu, Shan Liu, Hongbin Yang, Xiaoxia Ren and Ying Fang in Journal of International Medical Research</p
sj-pdf-1-imr-10.1177_03000605221121940 - Supplemental material for Type 1 diabetes mellitus induced by PD-1 inhibitors in China: a report of two cases
No full textSupplemental material, sj-pdf-1-imr-10.1177_03000605221121940 for Type 1 diabetes mellitus induced by PD-1 inhibitors in China: a report of two cases by Jingmei Luo, Jiagang Feng, Chunyan Liu, Zhongce Yang, Dong Zhan, Yanan Wu, Li Pan and Lihua Zhang in Journal of International Medical Research</p
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