Abstract Interdisciplinary research is increasingly recognized as one of the solutions to today’s challenging scientific and societal issues. Many studies have aimed explore relationship between interdisciplinarity attention they receive from community well society. However, policy documents remains unclear. In this study, we utilize publications data on COVID-19 topic such a relationship. Through analysis interpretation empirical datasets, finds that there positive correlation in almost all...

A novel feature region selection method for robust digital image watermarking is proposed in this paper. This aims to select a nonoverlapping set, which has the greatest robustness against various attacks and can preserve quality as much possible after watermarked. It first performs simulated attacking procedure using some predefined evaluate of every candidate region. According evaluation results, it then adopts track-with-pruning search minimal primary set resist most attacks. In order...

In this paper, a feature-based robust digital image watermarking algorithm is proposed to achieve the goal of authentication and protection simultaneously. The Hessian-Affine feature detector at first adopted extract characteristic regions an in watermark embedding scheme. Then copyright embedded into these according local orientation each pixel. Moreover, remainder are applied for by using block-wise fragile method. Similarly, detection scheme follows above procedure authentic information...

In the field of scientometrics, principal purpose for author co-citation analysis (ACA) is to map knowledge domains by quantifying relationship between co-cited pairs. However, traditional ACA has been criticized since its input insufficiently informative simply counting authors' frequencies. To address this issue, paper introduces a new method that reconstructs raw matrices regarding document unit counts and keywords references, named as Document- Keyword-Based Author Co-Citation Analysis...

In this paper, we propose to use contexts of superpixels as a prior improve semantic segmentation by the CRF framework. A graphical model is constructed on over-segmented images. Our main contribution take concept "superpixel embedding" into consideration, which formalized potential item for optimizing energy whole graph. We also introduce two ways calculating embedding potential. Experiments several popular datasets, e.g., MRSC-21 and PASCAL VOC, illustrate that our approach enhances...

Learning path offers personalized guidance in order to improve learners' performance e-learning systems. With the growth of learning resources, workload manually planning paths is increasing accordingly, which becomes a burden experts and teachers. Knowledge graph capable describing characteristics knowledge providing inspirations generate path. In this paper, we propose method generator based on graph, firstly generates sequence points by self-designed topological ranking algorithm then...

Set Partitioning in Hierarchical Trees (SPIHT) is a highly efficient technique for compressing Discrete Wavelet Transform (DWT) decomposed images. Though its compression efficiency little less famous than Embedded Block Coding with Optimized Truncation (EBCOT) adopted by JPEG2000, SPIHT has straight forward coding procedure and requires no tables. These make more appropriate algorithm lower cost hardware implementation. In this paper, modified presented. The modifications include...

Digital content is easily spread out in the era of cloud computing. However, challenge providing an identity-based access control mechanism to carry rating system for preventing specific digital from being obtained by inappropriate users. In this paper, we proposed a novel approach based on ciphertext-policy attribute-based encryption (iDAC). iDAC, still works even duplicated another server. Moreover, only one copy encrypted required share with multiple This could efficiently reduce overhead...

Business taxonomies are indispensable tools for investors to do equity research and make professional decisions. However, identify the structure of industry sectors in an emerging market is challenging two reasons. First, existing designed mature markets, which may not be appropriate classification small companies with innovative business models. Second, markets fast-developing, thus static cannot promptly reflect new features. In this article, we propose a method construct automatically...

A novel neural network based method for halftoning and inverse of digital images is presented. We first start from half-toning produced error diffusion methods using an RBF plus MLP network. The restored contone have had good quality already. Then, SLP used to refine the processing training process also involved. combined procedure produces half-tone corresponding continuous tone at same time. It found that these even better PSNR performance. Furthermore, resulted are visually sharper...

In modern information retrieval systems, the thesaurus is playing an increasingly important role. order to better describe and analyze domain news, this paper proposes a method of keyword extraction, further constructs effective thesaurus. Compared with previous research, grasps core in field by extracting combining keywords, improves effectiveness addition, conducts both manual analysis automated processing construct high-quality thesaurus, which has practical application value. The final...

Set partitioning in hierarchical trees (SPIHT) is a highly efficient technique for compressing discrete wavelet transform (DWT) decomposed images. Though its compression efficiency little less than famous embedded block coding with optimized truncation (EBCOT) adopted by JPEG2000, codec standard still images, SPIHT has straightforward procedure and requires no tables. These make more appropriate algorithm hardware implementation. In this paper, modified presented. The modifications include...