Predicting faults in a software system can be performed using software reliability models. Reliability is a real- world aspect that is related to several real-life issues which depends on several factors. Different al...
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A cyber-physical energy system consists of information and communication technology, advanced power electronic devices, energy sources, and smart appliances. A simulator is required for research and to further enhance...
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The Industrial-Internet-of-Things (IIoT) is a product of the extensive use of the Internet-of-Things(IoT) in vital industries including manufacturing and industrial production. To improve industrial and manufacturing ...
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Recently, the development of Industrial Internet of Things hastaken the advantage of 5G network to be more powerful and more ***, the upgrading of 5G network will cause a variety of issues increase,one of them is the ...
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Recently, the development of Industrial Internet of Things hastaken the advantage of 5G network to be more powerful and more ***, the upgrading of 5G network will cause a variety of issues increase,one of them is the increased cost of coverage. In this paper, we proposea sustainable wireless sensor networks system, which avoids the problemsbrought by 5G network system to some extent. In this system, deployingrelays and selecting routing are for the sake of communication and *** main aim is to minimize the total energy-cost of communication underthe precondition, where each terminal with low-power should be charged byat least one relay. Furthermore, from the perspective of graph theory, weextract a combinatorial optimization problem from this system. After that,as to four different cases, there are corresponding different versions of theproblem. We give the proofs of computational complexity for these problems,and two heuristic algorithms for one of them are proposed. Finally, theextensive experiments compare and demonstrate the performances of thesetwo algorithms.
作者：
Wang, BohanNew York University
Tandon School of Engineering Department of Computer Science and Engineering BrooklynNY United States
Computational Fluid Dynamics (CFD) is crucial in engineering applications such as aerospace and bioengineering, but it often require substantial computational resources. Learning-based simulation methods have the pote...
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Agriculture is an important component of every country's economy, supplying the necessary resources to farmers and their families. The livelihoods of farmers are greatly threatened by crop diseases, which highligh...
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Emotion recognition through facial expressions and gesture analysis has emerged as a key area of research in computer vision and human-computer interaction. The ability to automatically detect and classify human emoti...
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Real-world datasets often exhibit long-tailed distributions, compromising the generalization and fairness of learning-based models. This issue is particularly pronounced in Image Aesthetics Assessment (IAA) tasks, whe...
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Real-world datasets often exhibit long-tailed distributions, compromising the generalization and fairness of learning-based models. This issue is particularly pronounced in Image Aesthetics Assessment (IAA) tasks, where such imbalance is difficult to mitigate due to a severe distribution mismatch between features and labels, as well as the great sensitivity of aesthetics to image variations. To address these issues, we propose an Enhancer against Long-Tail for Aesthetics-oriented models (ELTA). ELTA first utilizes a dedicated mixup technique to enhance minority feature representation in high-level space while preserving their intrinsic aesthetic qualities. Next, it aligns features and labels through a similarity consistency approach, effectively alleviating the distribution mismatch. Finally, ELTA adopts a specific strategy to refine the output distribution, thereby enhancing the quality of pseudo-labels. Experiments on four representative datasets (AVA, AADB, TAD66K, and PARA) show that our proposed ELTA achieves state-of-the-art performance by effectively mitigating the long-tailed issue in IAA datasets. Moreover, ELTA is designed with plug-and-play capabilities for seamless integration with existing methods. To our knowledge, this is the first contribution in the IAA community addressing long-tail. All resources are available in here. Copyright 2024 by the author(s)
This research study compares and examines the E-magazine application's data consumption across two distinct platforms the Web and iOS. Materials and Methods: The observed issue of slowly using up information provi...
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The multitude of airborne point clouds limits the point cloud processing *** are grouped based on similar points,which can effectively alleviate the demand for computing resources and improve processing ***,existing s...
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The multitude of airborne point clouds limits the point cloud processing *** are grouped based on similar points,which can effectively alleviate the demand for computing resources and improve processing ***,existing superpoint segmentation methods focus only on local geometric structures,resulting in inconsistent spectral features of points within a *** feature inconsistencies degrade the performance of subsequent ***,this study proposes a novel Superpoint Segmentation method that jointly utilizes spatial Geometric and Spectral Information for multispectral point cloud superpoint segmentation(GSI-SS).Specifically,a similarity metric that combines spatial geometry and spectral information is proposed to facilitate the consistency of geometric structures and object attributes within segmented *** the formation of the primary superpoints,an intersuperpoint pointexchange mechanism that maximizes feature consistency within the final superpoints is *** are conducted on two real multispectral point cloud datasets,and the proposed method achieved higher recall,precision,F score,and lower global consistency and feature classification *** experimental results demonstrate the superiority of the proposed GSI-SS over several state-of-the-art methods.
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