In a cloud-edge collaborative environment, diverse equipment types and operating conditions yield disparate data distribution. This negatively impacts fault diagnosis model accuracy and generalization. To tackle this ...
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We present an efficient algorithm for the planar k-center problem for points in convex position under the Euclidean distance. Given n points in convex position in the plane, our algorithm computes k congruent disks of...
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Quality assessment of agricultural produce is a crucial step in minimizing food stock wastage. However, this is currently done manually and often requires expert supervision, especially in smaller seeds like corn. We ...
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ISBN:
(数字)9783031127007
ISBN:
(纸本)9783031126994;9783031127007
Quality assessment of agricultural produce is a crucial step in minimizing food stock wastage. However, this is currently done manually and often requires expert supervision, especially in smaller seeds like corn. We propose a novel computer vision-based system for automating this process. We build a novel seed image acquisition setup, which captures both the top and bottom views. Dataset collection for this problem has challenges of data annotation costs/time and class imbalance. We address these challenges by i.) using a Conditional Generative Adversarial Network (CGAN) to generate real-looking images for the classes with lesser images and ii.) annotate a large dataset with minimal expert human intervention by using a Batch Active Learning (BAL) based annotation tool. We benchmark different image classification models on the dataset obtained. We are able to get accuracies of up to 91.6% for testing the physical purity of seed samples.
Predictive modelling can be a huge benefit when it comes to optimizing patient flows in a hospital. Hospital beds are considered critical resources, thus the need for optimizing patient flow is evident. This paper foc...
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Cyber-physical systems (CPSs) have been used in different domains to enable automation, increase efficiency and effectiveness, and reduce the operational costs of traditional systems. CPSs come with several limitation...
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Rule-induction models have demonstrated great power in the inductive setting of knowledge graph completion. In this setting, the models are tested on a knowledge graph entirely composed of unseen entities. These ...
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This paper presents an approach to no-code development based on the interplay of formally defined (graphical) Domain-Specific Languages and informal, intuitive Natural Language which is enriched with contextual inform...
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This paper introduces an efficient streaming algorithm for a well-known Minimum cost Submodular Cover (MSC) problem. Our algorithm makes O(logn) passes over the ground set, takes O(nlogn) query complexity and returns ...
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Bond graphs represent the structure and functionality of mechatronic systems from a power flow perspective. Unfortunately, presentations of bond graphs are replete with ambiguity, significantly impeding understanding....
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The Atiyah-Bott localization formula is a powerful tool for calculating the degree of equivariant classes of the moduli space of rational stable maps (M) over bar (0,m)(X, beta), where X denotes a smooth toric variety...
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ISBN:
(纸本)9783031645280;9783031645297
The Atiyah-Bott localization formula is a powerful tool for calculating the degree of equivariant classes of the moduli space of rational stable maps (M) over bar (0,m)(X, beta), where X denotes a smooth toric variety, m is a non-negative integer, and beta is an effective 1-cycle. Implementation of the formula entails intricate computational challenges, involving graph theory, colorings, partitions, and other discrete objects. Furthermore, the computed solution is a large summation of rational numbers, underscoring the imperative nature of computational efficiency. This formula has been applied in very specific cases for computing Gromov-Witten invariants, addressing enumerative problems, and determining the small quantum ring of X, among other applications. A comprehensive implementation as a Julia package has been recently presented by the author. We show the features of the package with a particular emphasis to the noteworthy contribution of the package ***. Finally, we delve into the fundamental prerequisites for extending the implementation to encompass algebraic GKM manifolds.
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