What people see on social media influences their affective state. Predictions of the affective reaction of an audience to a post could help posters creating content and viewers searching for it. this paper examines th...
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ISBN:
(纸本)9798350327434
What people see on social media influences their affective state. Predictions of the affective reaction of an audience to a post could help posters creating content and viewers searching for it. this paper examines the value of both real comments and artificially generated ones in predicting the affective responses of an audience. We built an affect prediction model based on Facebook anonymized public posts to predict affective responses (anger, amusement, and sadness affect) as indicated by three Facebook reaction clicks (Angry, Haha, and Sad). Using the content of the original post can predict reactions well (.71 to.87 F1-scores). Adding the text of real post comments improves F1-score by up to 11%. Surprisingly, generated comments improve predictions as much as real comments. these artificial comments were produced using a pre-trained sequence-to-sequence, BART natural language generation model given a post as input. Using artificial comments means that one can predict affect reactions early in the history of a discussion, before anyone has actually commented on a post.
Modern containerized applications deployed on Kubernetes demand efficient resource scaling to adapt to varying workloads. Auto-scaling reduces cloud infrastructure costs, increases application stability and improves t...
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ISBN:
(纸本)9798350377873;9798350377866
Modern containerized applications deployed on Kubernetes demand efficient resource scaling to adapt to varying workloads. Auto-scaling reduces cloud infrastructure costs, increases application stability and improves the Quality of Service from user perspective. this paper introduces an innovative approach for Kubernetes vertical pod autoscaling. the proposed model DTR-Max takes in consideration maximum resources limit of pods allocation using predictive Decision Tree Regression (DTR) policy. the system leverages predictive resource management, enabling proactive adjustments to pod resource requests based on historical utilization patterns and pods resources limit range. In experimental simulations, the system effectively manages resource scaling decisions and demonstrates its potential to adapt Kubernetes pods to dynamic workloads efficiently.
the proceedings contain 10 papers. the topics discussed include: replacing pivoting in distributed Gaussian elimination with randomized techniques;implementation and numerical techniques for one EFlop/s HPL-AI benchma...
ISBN:
(纸本)9781665422703
the proceedings contain 10 papers. the topics discussed include: replacing pivoting in distributed Gaussian elimination with randomized techniques;implementation and numerical techniques for one EFlop/s HPL-AI benchmark on Fugaku;performance analysis of a quantum Monte Carlo application on multiple hardware architectures using the HPX runtime;an integer arithmetic-based sparse linear solver using a GMRES method and iterative refinement;two-stage asynchronous iterative solvers for multi-GPU clusters;basic linear algebra operations on TensorCore GPU;a survey of singular value decomposition methods for distributed tall/skinny data;and a fast scalable iterative implicit solver with green’s function-based neural networks.
In this paper, we introduce the Hermite polynomial as a tool for computing graph Fourier transform centrality (GFTC), facilitating the identification of crucial nodes within a network. First, we begin by providing the...
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ISBN:
(纸本)9798350386851;9798350386844
In this paper, we introduce the Hermite polynomial as a tool for computing graph Fourier transform centrality (GFTC), facilitating the identification of crucial nodes within a network. First, we begin by providing the definition of GFTC and delve into the computation process using conventional eigen-decomposition method. Second, recognizing the computational complexity inherent in eigen-decomposition, the paper explores the application of a graph filter method. this method transforms the spectral-domain task into a more manageable vertex-domain task. third, to achieve an optimal spectral response, the Hermite polynomial is employed in designing the graph filter. this ensures that the desired spectral characteristics are met. the closed-form solution for filter coefficients is then derived by leveraging the orthogonal relation of the Hermite polynomial. Fourth, an implementation structure is derived by using the recursion relation of Hermite polynomial. this structure facilitates the distributed computation of GFTC. Finally, the proposed method's efficacy is exemplified through its application to identify important stations within the Taipei metro network. this practical demonstration serves to underscore the utility and effectiveness of the presented method.
this paper focuses on dataset class imbalances to address Named Entity Recognition (NER) difficulties in low-resource languages like Malayalam. the main goal is to draw attention to how important data sampling is for ...
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A remote organization comprises of the many organization geographies that are broadly circulated, associated by moving hubs alluded to as portable hubs. Transfer innovation is utilized to upgrade parcel conveyance and...
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the proceedings contain 27 papers. the topics discussed include: architecting a SDS for microservices-based distributed edge computing systems;holon programming model: a software-defined approach for system of systems...
ISBN:
(纸本)9798331518325
the proceedings contain 27 papers. the topics discussed include: architecting a SDS for microservices-based distributed edge computing systems;holon programming model: a software-defined approach for system of systems;towards a metamorphic testing architecture for software-defined drone systems;mitigating security vulnerabilities in offline USSD payments in non-smartphones;towards a resilient multi-agent controller: securing and mitigating overhead in tactical SDN;resilient software defined satellite networks: combining clustering techniques with efficient routing protocols;toward automating Cooja experiment workflows for dataset generation;and software-defined support for the execution of task-graph-based applications on cloud environments.
In distributed Software Defined networking (SDN), multiple controllers need to maintain a consistent view of the network state among the controllers using consensus algorithms, which introduces additional communicatio...
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Withthe progress of digital transformation in society, an increasing number of documents are now stored as digital data. therefore, the development of more intelligent and flexible search techniques than lexical sear...
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High performance computing makes many contemporary pervasive computing interactions possible such as increasingly accurate weather forecasts, market-scale financial services on demand, and big data analysis for highly...
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ISBN:
(纸本)9783031346675;9783031346682
High performance computing makes many contemporary pervasive computing interactions possible such as increasingly accurate weather forecasts, market-scale financial services on demand, and big data analysis for highly personalized services. However, access to high performance computing resources is not necessarily equitable. Not everyone is uplifted by this computational power. Rather, high performance computing access can be seen as another aspect of the digital divide. We acknowledge the ways in which equitable access to high performance computing resources has improved over time while also identifying potential threats to access of these resources. We provide considerations from the perspective of two popular ethical theories (contractarianism and utilitarianism) for reasoning about how these threats may be overcome or prevented from coming to pass. these perspectives can be extended to inform policy created by high performance computing providers.
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