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The blockchain technology that underlies many cryptocurrencies, such as Bitcoin and Ethereum, is demanded to raise for more efficient transactions. Thus, in the last decade, many solutions have been proposed to improve the propagation ...

• A new block propagation protocol significantly improves the TPS.
• The protocol ...

Based on the new demand of national strategic development and the new situation of international competition, the construction of first-class universities and first-class majors and the realization of the higher education connotative development shall ...

Cross-modal hashing has received a lot of attention because of its unique characteristic of low storage cost and high retrieval efficiency. However, these existing cross-modal retrieval approaches often fail to align effectively semantic ...$$$$$$$$

This paper investigates the fuzzy control design problem for reaction-diffusion memristive neural networks (MNNs). Initially, by introducing the logical switched functions, the original reaction-diffusion MNN is transformed into ...

This article presents a 16-bit 2.5-MS/s successive approximation register (SAR) analog-to-digital converter (ADC) with on-chip foreground calibration, including two digital-to-analog converters (DACs). Apart from the traditional ...

Cross-modal hashing has attracted a great deal of attention due to its unique low storage cost and high retrieval efficiency. However, these existing cross-modal retrieval methods fail to deal with global semantic relational redundancy, leading to ...$$$$$$$$

BERT-style models pre-trained on the general corpus (e.g., Wikipedia) and fine-tuned on specific task corpus, have recently emerged as breakthrough techniques in many NLP tasks: question answering, text classification, sequence labeling and so on. ...

Field-programmable gate arrays (FPGAs) are one attractive hardware platform for computing the eigenvalue decomposition of low-dimensional symmetric matrices. For this, one popular method is using the parallel Jacobi algorithm based on coordinate ...

Generally, the performance of evolutionary algorithms (EAs) greatly depends on the setting of their control parameters. Many adaptive setting technologies have been developed to solve the time-consuming task of parameter settings. However, the ...

We address a long-standing lacuna in the Information Management literature on the relationships among security breaches, organization response strategy as well as consumers’ threat and coping appraisal. Security breaches can involve ...

• Security breach announcements have a negative impact on consumers’ perceived risk.

Hand gesture recognition is an important research field in computer vision. To effectively solve the problem of low hand gesture recognition accuracy, we propose two modules by using atrous convolution in this paper. One is Multi-Scale Fusion (MSF)...

Image segmentation is a fundamental task that has benefited from recent advances in machine learning. One type of segmentation, of particular interest to computer vision, is that of urban segmentation. Although recent solutions have ...

• A framework improves regularities, fuses multi-views, and generates complete results.

Identification of product attributes (product type, brand, color, gender, etc.) from a query is critically important for e-commerce search systems, especially the identification of brand intent. Recently, Named Entity Recognition (NER) method has ...

Shadow removal is a fundamental and pivotal task to build the high-level cognition in the computer vision field. Due to the fact that the existing shadow removal methods cannot effectively remove shadows from the outdoor image and deal with ...

Digitalization brings challenges and new opportunities to the development of landscape gardening, “smart gardening,” which is a product of landscape gardening in response to the development of the digital era. Based on the multimodal intelligent computing ...

Emotion recognition is a vital but challenging step in creating passive brain-computer interface applications. In recent years, many studies on electroencephalogram (EEG)-based emotion recognition have been conducted. Ensemble learning ...

• Thirteen different linear and nonlinear features are extracted from EEG signals, and L1 regularization is used to select effective features.

Recently, Electroencephalography (EEG) is wildly used in depression detection. Researchers have successfully used machine learning methods to build depression detection models based on EEG signals. However, the scarcity of samples and individual ...

We consider a problem of ranking and selection via simulation in the context of personalized decision making, in which the best alternative is not universal, but varies as a function of some observable covariates. The goal of ranking and selection with ...

We present Persona, a real-time human face-oriented visual effect solution on mobile devices. Persona consists of a 3D face tracker with multi-scale reconstruction models for different-level of mobile devices and a visual effect authoring tool. Our ...

The customized products such as electromechanical prototype products are a type of product with research and trial manufacturing characteristics. The BOM structures and processing parameters of the products vary greatly, making it difficult for a single ...