A Feasible Algorithm for Designing Biorthogonal Bivariate Vector-valued Finitely Supported Wavelets

AbstractWavelet analysis has been developed a new branch for over twenty years. The concept of vector-valued binary wavelets with two-scale dilation factor associated with an orthogonal vector-valued scaling function is introduced. The existence of orthogonal vector-valued wavelets with two-scale is discussed. A necessary and sufficient condition is provided by means of vector-valued multiresolution analysis and paraunitary vector filter bank theory. An algorithm for constructing a sort of orthogonal vector-valued wavelets with compact support is proposed, and their orthogonal properties are investigated

An Improved Entity Similarity Measurement Method

To facilitate the integration of learning resources categorized under different ontology representations, the techniques of ontology mapping can be applied. Through many algorithms and systems have been proposed for ontology mapping, they do not have an automatic weighting strategy on class features to automate the ontology mapping process. A novel method of computing the feature weights is proposed by feature semantic analysis, defining characteristics of the different entities similarity calculation model and weight calculation model. The results show that it makes the ontology mapping process more automatic while retaining satisfying accuracy. Improve ontology mapping effectiveness

Counterfactual Cross-modality Reasoning for Weakly Supervised Video Moment Localization

Video moment localization aims to retrieve the target segment of an untrimmed video according to the natural language query. Weakly supervised methods gains attention recently, as the precise temporal location of the target segment is not always available. However, one of the greatest challenges encountered by the weakly supervised method is implied in the mismatch between the video and language induced by the coarse temporal annotations. To refine the vision-language alignment, recent works contrast the cross-modality similarities driven by reconstructing masked queries between positive and negative video proposals. However, the reconstruction may be influenced by the latent spurious correlation between the unmasked and the masked parts, which distorts the restoring process and further degrades the efficacy of contrastive learning since the masked words are not completely reconstructed from the cross-modality knowledge. In this paper, we discover and mitigate this spurious correlation through a novel proposed counterfactual cross-modality reasoning method. Specifically, we first formulate query reconstruction as an aggregated causal effect of cross-modality and query knowledge. Then by introducing counterfactual cross-modality knowledge into this aggregation, the spurious impact of the unmasked part contributing to the reconstruction is explicitly modeled. Finally, by suppressing the unimodal effect of masked query, we can rectify the reconstructions of video proposals to perform reasonable contrastive learning. Extensive experimental evaluations demonstrate the effectiveness of our proposed method. The code is available at \href{https://github.com/sLdZ0306/CCR}{https://github.com/sLdZ0306/CCR}.Comment: Accepted by ACM MM 202

Raman scattering study of electron-doped Prx_xCa1−x_{1-x}Fe2_2As2_2 superconductors

Temperature-dependent polarized Raman spectra of electron-doped superconducting Pr$_x$Ca$_{1-x}$Fe$_2$As$_2$ ($x \approx 0.12$) single crystals are reported. All four allowed by symmetry even-parity phonons are identified. Phonon mode of B$_{1g}$ symmetry at 222 cm$^{-1}$, which is associated with the c-axis motion of Fe ions, is found to exhibit an anomalous frequency hardening at low temperatures, that signals non-vanishing electron-phonon coupling in the superconducting state and implies that the superconducting gap magnitude $2\Delta_c < 27$meV.Comment: 4 pages, 3 figure