Search Results

Bitcoin transaction analysis is valuable for examining Bitcoin events. However, most of the existing methods are inadequate for dealing with transactions involving multiple entities. Furthermore, existing Bitcoin transaction analysis methods neglect to ...

Service discovery and recommendation has been considered an effective technique for freeing workflow developers out from time-consuming work of manually selecting suitable software services from a sea of service candidates. Facing complex ...

The weakly supervised semantic segmentation (WSSS) training based on image-level labels in convolutional neural network (CNN) is usually divided into two stages: multi-label classification and semantic segmentation. However, most of the existing ...

In multi-view multi-label (MVML) learning, each sample is represented by several heterogeneous distinct feature representations while associated with a set of class labels simultaneously. To achieve MVML learning, most of the existing methods ...

• A consistent and specific learning framework is proposed to handle MVML data.
• We exploit the multi-view consistency by leveraging low-rank constraint.
• Our proposal can recover specific subspace from each view.
• We provide a ...

Abnormal email bounces seriously disrupt user lives and company transactions. Proliferating security protocols and protection strategies have made email delivery increasingly complex. A natural question is how and why email delivery fails in the wild. ...

Purpose: Through the visualization analysis of the knowledge graph, this study explores the paper publication status, journal distribution, research strength, research hotspots and development trend of the research field of the work of college and ...

The continual advancements in Generative Artificial Intelligence have created substantial hurdles for accurate deepfake detection, leading to limitations of currently popular detection methods across content-driven video-level deepfake detection ...

Domain Name System (DNS) establishes clear responsibility boundaries among nameservers for managing DNS records via authoritative delegation. However, the rise of third-party public services has blurred this boundary. In this paper, we uncover a novel ...

Neural operators, as a powerful approximation to the non-linear operators between infinite-dimensional function spaces, have proved to be promising in accelerating the solution of partial differential equations (PDE). However, it requires a large ...

Nowadays, numerous mobile devices (MDs) provide nearly anytime and anywhere services, running on top of various computation-intensive applications. However, bearing limited battery, bandwidth, computing, and storage resources, MDs cannot ...

• A hybrid system architecture is designed and characterized by triple queueing models.
• A constrained total cost minimization problem with multiple constraints is formulated.
• The cost minimization problem is solved by a hybrid ...

The recognition of human gait states holds paramount importance for disease diagnosis and the formulation of rehabilitation protocols. Compared to traditional methods, Wi-Fi-based gait recognition techniques offer the benefits of non-invasiveness ...$\mathrm{}$

Cross-network node classification aims to leverage the labeled nodes from a source network to assist the learning in a target network. Existing approaches work mainly in homogeneous settings, i.e., the nodes of the source and target networks are ...

Accurately identifying network intrusion cannot only help individuals and enterprises better deal with network security problems, but also maintain the Internet environment. This work proposes a new hybrid classification method named SABD for ...

Display Omitted

• A hybrid method named SABD is given for network intrusion detection.
• It uses stacked sparse contractive autoencoders to extract features in data.
• It uses an attention-based bidirectional LSTM to realize the classification.
• It ...

Multi-label learning tasks usually encounter the problem of the class-imbalance, where samples and their corresponding labels are non-uniformly distributed over multi-label data space. It has attracted increasing attention during the past decade, ...

• Provide a new method for semi-supervised imbalanced multi-label classification.
• Propose a label regularization matrix to handle the imbalanced multi-label problem.
• Leverage a collaborative manner to ensure the balanced outcomes.

Node classification is a popular and challenging task in graph neural networks, and existing approaches are mainly developed for a single network. With the advances in domain adaptation, researchers tend to leverage knowledge extracted from a ...

• TGAE is proposed to handle cross-network node classification problem.
• TGAE encodes local and global information and preserves structural graph information.
• Experimental results demonstrate the superior performance of the proposed ...

Mobile web services value a quick loading of contents in the first page, which is quantified by the above-the-fold time of the first page (first AFT) and is likely to fall into the slow start phase in congestion control. However, the widely deployed slow ...

Handwritten signature verification has become one of the most important document authentication methods that are widely used in the financial, legal, and administrative sectors. Compared with offline methods based on static signature images, online ...

Recently, with the improvement of per-capita income, the number of waste electronic and electrical equipment (WEEE) has increased significantly. The WEEE return prediction is an essential part of reverse logistics (RL) due to its helpfulness in ...

• The relationships among various types of WEEE are used for RL return prediction.
• Multi-time scale features and multi-task common features are extracted collaboratively.
• Polling host-task learning strategy is proposed to achieve ...

Accurate prediction of water quality indicators can effectively predict sudden water pollution events and reveal them to water users for reducing the impact of water quality pollution. Neural networks, e.g., Long Short-Term Memory (LSTM) and ...

• A hybrid prediction method VBAED is designed to predict water quality time series.
• VBAED combines VMD, bidirectional input attention, encoder–decoder, and BiLSTM.
• It uses bidirectional input attention to add weights to features in ...

Hilbert-Schmidt Independence Criterion (HSIC) has recently been introduced to the field of single-index models to estimate the directions. Compared with other well-established methods, the HSIC based method requires relatively weak conditions. ...$\mathtt{}$