Independent cascade(IC)models,by simulating how one node can activate another,are important tools for studying the dynamics of information spreading in complex ***,traditional algorithms for the IC model implementatio...
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Independent cascade(IC)models,by simulating how one node can activate another,are important tools for studying the dynamics of information spreading in complex ***,traditional algorithms for the IC model implementation face significant efficiency bottlenecks when dealing with large-scale networks and multi-round *** settle this problem,this study introduces a GPU-based parallel independent cascade(GPIC)algorithm,featuring an optimized representation of the network data structure and parallel task scheduling ***,for this GPIC algorithm,we propose a network data structure tailored for GPU processing,thereby enhancing the computational efficiency and the scalability of the IC *** addition,we design a parallel framework that utilizes the full potential of GPU's parallel processing capabilities,thereby augmenting the computational *** results from our simulation experiments demonstrate that GPIC not only preserves accuracy but also significantly boosts efficiency,achieving a speedup factor of 129 when compared to the baseline IC *** experiments also reveal that when using GPIC for the independent cascade simulation,100-200 simulation rounds are sufficient for higher-cost studies,while high precision studies benefit from 500 rounds to ensure reliable results,providing empirical guidance for applying this new algorithm to practical research.
A spectro-polarimetric imaging approach leverages optical rotatory dispersion in natural crystals to encode spectral information into polarization *** system demonstrates effectiveness in laboratory and outdoor field ...
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A spectro-polarimetric imaging approach leverages optical rotatory dispersion in natural crystals to encode spectral information into polarization *** system demonstrates effectiveness in laboratory and outdoor field experiments,showing potential for biological microscopy,machine vision,and remote sensing applications.
In foggy traffic scenarios, existing object detection algorithms face challenges such as low detection accuracy, poor robustness, occlusion, missed detections, and false detections. To address this issue, a multi-scal...
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In foggy traffic scenarios, existing object detection algorithms face challenges such as low detection accuracy, poor robustness, occlusion, missed detections, and false detections. To address this issue, a multi-scale object detection algorithm based on an improved YOLOv8 has been proposed. Firstly, a lightweight attention mechanism, Triplet Attention, is introduced to enhance the algorithm’s ability to extract multi-dimensional and multi-scale features, thereby improving the receptive capability of the feature maps. Secondly, the Diverse Branch Block (DBB) is integrated into the CSP Bottleneck with two Convolutions (C2F) module to strengthen the fusion of semantic information across different layers. Thirdly, a new decoupled detection head is proposed by redesigning the original network head based on the Diverse Branch Block module to improve detection accuracy and reduce missed and false detections. Finally, the Minimum Point Distance based Intersection-over-Union (MPDIoU) is used to replace the original YOLOv8 Complete Intersection-over-Union (CIoU) to accelerate the network’s training convergence. Comparative experiments and dehazing pre-processing tests were conducted on the RTTS and VOC-Fog datasets. Compared to the baseline YOLOv8 model, the improved algorithm achieved mean Average Precision (mAP) improvements of 4.6% and 3.8%, respectively. After defogging pre-processing, the mAP increased by 5.3% and 4.4%, respectively. The experimental results demonstrate that the improved algorithm exhibits high practicality and effectiveness in foggy traffic scenarios.
Nanofluidic memristors,which use ions in electrolyte solutions as carriers,have been developed rapidly and brought new opportunities for the development of neuromorphic *** the transport and accumulation of ions in na...
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Nanofluidic memristors,which use ions in electrolyte solutions as carriers,have been developed rapidly and brought new opportunities for the development of neuromorphic *** the transport and accumulation of ions in nanochannels to process information is an endeavor to realize the nanofluidic *** this study,we report a new nanofluidic memristor,which is a polydimethylsiloxane(PDMS)-glass chip with two platinum(Pt)electrodes and well-aligned multi-nanochannels within PDMS for ion enrichment and *** device not only exhibits typical bipolar memristive behavior and ion current rectification(ICR)but also demonstrates excellent endurance,maintaining stable performance after 100 sweep *** systematically investigate the key factors affecting ion transport behavior in this *** results show that the ICR ratio of the current-voltage(I-V)hysteresis curves decreases with increasing scan rate and solution *** potential measurements are introduced to reveal that the PDMS surface carries more negative charges in higher pH solutions,resulting in more pronounced memristive and ICR ***,our memristor can simulate short-term synaptic plasticity,such as paired-pulse facilitation(PPF)and paired-pulse depression(PPD),with a relatively low energy consumption of 12 pJ per spike per ***,the inherent accessibility and robustness of our nanofluidic memristors facilitate the optimization of device structure and *** important observations and investigations lay a foundation for advancing energy-saving and efficient neuromorphic computing.
Accurately detecting objects and their interrelationships for Video Scene Graph Generation (VidSGG) confronts two primary challenges. The first involves the identification of active objects interacting with humans fro...
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With the widespread use of blockchain technology for smart contracts and decentralized applications on the Ethereum platform, the blockchain has become a cornerstone of trust in the modern financial system. However, i...
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With the widespread use of blockchain technology for smart contracts and decentralized applications on the Ethereum platform, the blockchain has become a cornerstone of trust in the modern financial system. However, its anonymity has provided new ways for Ponzi schemes to commit fraud, posing significant risks to investors. Current research still has some limitations, for example, Ponzi schemes are difficult to detect in the early stages of smart contract deployment, and data imbalance is not considered. In addition, there is room for improving the detection accuracy. To address the above issues, this paper proposes LT-SPSD (LSTM-Transformer smart Ponzi schemes detection), which is a Ponzi scheme detection method that combines Long Short-Term Memory (LSTM) and Transformer considering the time-series transaction information of smart contracts as well as the global information. Based on the verified smart contract addresses, account features, and code features are extracted to construct a feature dataset, and the SMOTE-Tomek algorithm is used to deal with the imbalanced data classification problem. By comparing our method with the other four typical detection methods in the experiment, the LT-SPSD method shows significant performance improvement in precision, recall, and F1-score. The results of the experiment confirm the efficacy of the model, which has some application value in Ethereum Ponzi scheme smart contract detection.
Carbon-based foams with a three-dimensional structure can serve as a lightweight template for the rational design and control-lable preparation of metal oxide/carbon-based composite microwave absorption *** this study...
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Carbon-based foams with a three-dimensional structure can serve as a lightweight template for the rational design and control-lable preparation of metal oxide/carbon-based composite microwave absorption *** this study,a flake-like nickel cobaltate/re-duced graphene oxide/melamine-derived carbon foam(FNC/RGO/MDCF)was successfully fabricated through a combination of solvo-thermal treatment and high-temperature *** indicated that RGO was evenly distributed in the MDCF skeleton,providing ef-fective support for the load growth of FNC on its *** S3,the FNC/RGO/MDCF composite prepared by solvothermal method for 16 h,exhibited a minimum reflection loss(RL_(min))of-66.44 dB at a thickness of 2.29 *** the thickness was reduced to 1.50 mm,the optimal effective absorption bandwidth was 3.84 *** of the absorption mechanism of FNC/RGO/MDCF revealed that its excellent absorption performance was primarily attributed to the combined effects of conduction loss,multiple reflection,scattering,in-terface polarization,and dipole polarization.
Robot teleoperation plays an important role in industrial manufacturing in unknown and dangerous environments beyond human *** telerobotic manufacturing tasks,environmental interaction forces may vary significantly fr...
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Robot teleoperation plays an important role in industrial manufacturing in unknown and dangerous environments beyond human *** telerobotic manufacturing tasks,environmental interaction forces may vary significantly from task to ***,it is crucial to provide operators with the specific proportional feedback of environmental interaction forces to enhance their environmental awareness and manipulation ***,variable time delays and various scales of environmental interaction force feedback seriously affect the system stability,which should be rigorously addressed when designing control *** cope with these difficulties,a position and scaled force tracking control framework is proposed and the LyapunovKrasovskii theory is used to obtain a simple algebraic stability criterion with the scaling factor of the environmental interaction force *** addition,a low-pass filter-based radial basis function neural network is designed to avoid the effect of the measurement noise and the sudden change of the non-passive environmental interaction force on the system *** with different controllers in various telerobotic manufacturing tasks such as heavy lifting,cutting,and polishing,our proposed method achieves better position and scaled force tracking performance.
In the realm of nonlinear integrable systems,the presence of decompositions facilitates the establishment of linear superposition solutions and the derivation of novel coupled systems exhibiting nonlinear *** focusing...
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In the realm of nonlinear integrable systems,the presence of decompositions facilitates the establishment of linear superposition solutions and the derivation of novel coupled systems exhibiting nonlinear *** focusing on single-component decompositions within the potential BKP hierarchy,it has been observed that specific linear superpositions of decomposition solutions remain consistent with the underlying ***,through the implementation of multi-component decompositions within the potential BKP hierarchy,successful endeavors have been undertaken to formulate linear superposition solutions and novel coupled Kd V-type systems that resist decoupling via alterations in dependent variables.
Cohesive subgraph search is a fundamental problem in bipartite graph *** integers k andℓ,a(k,ℓ)-biplex is a cohesive structure which requires each vertex to disconnect at most k orℓvertices in the other ***(k,ℓ)-biple...
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Cohesive subgraph search is a fundamental problem in bipartite graph *** integers k andℓ,a(k,ℓ)-biplex is a cohesive structure which requires each vertex to disconnect at most k orℓvertices in the other ***(k,ℓ)-biplexes has been a popular research topic in recent years and has various ***,most existing studies considered the problem of finding(k,ℓ)-biplex with the largest number of *** this paper,we instead consider another variant and focus on the maximum vertex(k,ℓ)-biplex problem which aims to search for a(k,ℓ)-biplex with the maximum *** first show that this problem is Non-deterministic Polynomial-time hard(NP-hard)for any positive integers k andℓwhile max{k,ℓ}is at least *** by this negative result,we design an efficient branch-and-bound algorithm with a novel *** particular,we introduce a branching strategy based on whether there is a pivot in the current set,with which our proposed algorithm has the time complexity ofγ^(n)n^(O(1)),whereγ<*** addition,we also apply multiple speed-up techniques and various pruning ***,we conduct extensive experiments on various real datasets which demonstrate the efficiency of our proposed algorithm in terms of running time.
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