Graph sampling is a very effective method to deal with scalability issues when analyzing largescale graphs. Lots of sampling algorithms have been proposed, and sampling qualities have been quantified using explicit pr...
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Graph sampling is a very effective method to deal with scalability issues when analyzing largescale graphs. Lots of sampling algorithms have been proposed, and sampling qualities have been quantified using explicit properties(e.g., degree distribution) of the sample. However, the existing sampling techniques are inadequate for the current sampling task: sampling the clustering structure, which is a crucial property of the current networks. In this paper, using different expansion strategies, two novel top-leader sampling methods(i.e., TLS-e and TLS-i) are proposed to obtain representative samples, and they are capable of effectively preserving the clustering structure. The rationale behind them is to select top-leader nodes of most clusters into the sample and then heuristically incorporate peripheral nodes into the sample using specific expansion strategies. Extensive experiments are conducted to investigate how well sampling techniques preserve the clustering structure of graphs. Our empirical results show that the proposed sampling algorithms can preserve the population's clustering structure well and provide feasible solutions to sample the clustering structure from large-scale graphs.
This paper introduces the Surrogate-assisted Multi-objective Grey Wolf Optimizer(SMOGWO)as a novel methodology for addressing the complex problem of empty-heavy train allocation,with a focus on line utilization *** in...
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This paper introduces the Surrogate-assisted Multi-objective Grey Wolf Optimizer(SMOGWO)as a novel methodology for addressing the complex problem of empty-heavy train allocation,with a focus on line utilization *** integrating surrogate models to approximate the objective functions,SMOGWO significantly improves the efficiency and accuracy of the optimization *** effectiveness of this approach is evaluated using the CEC2009 multi-objective test function suite,where SMOGWO achieves a superiority rate of 76.67%compared to other leading multi-objective ***,the practical applicability of SMOGWO is demonstrated through a case study on empty and heavy train allocation,which validates its ability to balance line capacity,minimize transportation costs,and optimize the technical combination of heavy *** research highlights SMOGWO's potential as a robust solution for optimization challenges in railway transportation,offering valuable contributions toward enhancing operational efficiency and promoting sustainable development in the sector.
It is a common military activity to carry out joint fire strike against sea/air-based targets with high threat/value but strong defense ability. The especially high time sensitivity requires immediate actions, leaving...
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The proliferation of consumer electronics in the Internet of Things (IoT) has led to the expanding applications in various fields with increasing demand for large-scale connections. Spectrum scarcity has become a cruc...
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In order to address the issue of limited data samples for the deployment of pre-trained models in unseen environments, this paper proposes a residual channel-based data augmentation strategy for Radio Frequency Finger...
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In emerging consumer healthcare, high-performance and robust medical image segmentation methods are essential for personalized diagnosis and treatment. Thus, early screening of aneurysms reduces the risk of aneurysm r...
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Dear editor,Robots are often conceived as human-like machines that can interact with humans naturally and safely. Human-robot interaction means that robots can communicate with people,understand their needs, and act a...
Dear editor,Robots are often conceived as human-like machines that can interact with humans naturally and safely. Human-robot interaction means that robots can communicate with people,understand their needs, and act accordingly [1]. This interaction is critical when two people are needed to finish a task cooperatively.
Brain tumor is a global issue due to which several people suffer,and its early diagnosis can help in the treatment in a more efficient *** different types of brain tumors,including gliomas,meningiomas,pituitary tumors...
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Brain tumor is a global issue due to which several people suffer,and its early diagnosis can help in the treatment in a more efficient *** different types of brain tumors,including gliomas,meningiomas,pituitary tumors,as well as confirming the absence of tumors,poses a significant challenge using MRI *** approaches predominantly rely on traditional machine learning and basic deep learning methods for image *** methods often rely on manual feature extraction and basic convolutional neural networks(CNNs).The limitations include inadequate accuracy,poor generalization of new data,and limited ability to manage the high variability in MRI *** the EfficientNetB3 architecture,this study presents a groundbreaking approach in the computational engineering domain,enhancing MRI-based brain tumor *** approach highlights a major advancement in employing sophisticated machine learning techniques within Computer science and engineering,showcasing a highly accurate framework with significant potential for healthcare *** model achieves an outstanding 99%accuracy,exhibiting balanced precision,recall,and F1-scores across all tumor types,as detailed in the classification *** successful implementation demonstrates the model’s potential as an essential tool for diagnosing and classifying brain tumors,marking a notable improvement over current *** integration of such advanced computational techniques in medical diagnostics can significantly enhance accuracy and efficiency,paving the way for wider *** research highlights the revolutionary impact of deep learning technologies in improving diagnostic processes and patient outcomes in neuro-oncology.
With the development of camera technology,high-speed cameras have greatly contributed to capturing the movement and posture of animals,which has dramatically promoted experimental biology *** the same time,with the co...
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With the development of camera technology,high-speed cameras have greatly contributed to capturing the movement and posture of animals,which has dramatically promoted experimental biology *** the same time,with the concept of bionics gradually gaining popularity among researchers,the design of robots is absorbing more and more biological features,where the interest in the bio-inspired robot is hewed *** with the traditional robot,the bio-inspired robot imitates the motion pattern to achieve similar propulsion features,which may be more effective and *** this paper,the motion patterns of aquatic animals are divided into four categories according to their propulsion mechanisms:drag-based,lift-based,jet-based,and *** bio-inspired robots imitating aquatic prototypes are introduced and ***,the prospect of aquatic bio-inspired robots is discussed.
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