Network dismantling is a process of identifying influential nodes that can decompose a network into disconnected sub-networks. This provides a novel approach to understanding and analyzing complex networks abstracted from the real world. State-of-...

Deep learning has recently demonstrated considerable promise for a variety of computer vision tasks. However, in many practical applications, large-scale labeled datasets are not available, which limits the deployment of deep learning. To address ...

When dealing with large bipartite graphs, butterfly counting is a crucial and time-consuming operation. Graphics processing units (GPUs) are widely used parallel heterogeneous devices that can significantly boost performance for data science ...$$

Deep learning-based automatic and accurate 3D pancreas segmentation plays a significant role in medical diagnosis and disease treatment, which has received a lot of attention from the medical image processing community. 3D pancreas segmentation ...

Energy rationing exerts a substantial influence on the landscape of manufacturing operations. When mandatory energy rationing occurs, manufacturers find themselves compelled to adapt their production strategies to align with the prescribed ...

• A multi-period production process is studied under energy uncertainty.
• Propose an operational decision model with a known rationing schedule.
• Propose a data-driven reinforcement learning algorithm for uncertain rationing schedules.

Developers and manufacturers provide configurable control parameters for flight control programs to support various environments and missions, along with suggested ranges for these parameters to ensure flight safety. However, this flexible mechanism can ...

Federated Learning (FL) is an emerging distributed machine learning paradigm crucial for ensuring privacy-preserving learning. In FL, a fair incentive mechanism is indispensable for inspiring more clients to participate in FL training. Nevertheless, ...

Forgery of facial images and videos has increased the concern about digital security. It has led to the significant development of detecting forgery data recently. However, the data, especially the videos published on the Internet, are usually compressed ...

Lossless data compression is an effective way to handle the huge transmission and storage overhead of massive text data. Its utility is even more significant today when data volumes are skyrocketing. The concept of operating on compressed data infuses ...

The five-year survival rate of pancreatic cancer is extremely low, and the survival time of patients can be extended by timely detection and treatment. Deep learning-based methods have been used to assist radiologists in diagnosis, with remarkable ...

Deep neural networks (DNNs) have achieved state-of-the-art performance on face recognition (FR) tasks in the last decade. In real scenarios, the deployment of DNNs requires taking various face accessories into consideration, like glasses, hats, and masks. ...

Authentication and cryptography are critical security functions and, thus, are very often included as part of code. These functions require using credentials, such as passwords, security tokens, and cryptographic keys. However, developers often ...

The tremendous computing capacity of GPU offers significant potential in processing hierarchically compressed text data without decompression. However, current GPU techniques offer only traversal-based text data analytics; random access is exceedingly ...

The graph neural networks (GNNs) are susceptible to adversarial perturbations and distribution biases, which pose potential security concerns for real-world applications. Current endeavors mainly focus on graph matching, while the subtle relationships ...

The rapid development of device-edge-cloud collaborative computing techniques has actively contributed to the popularization and application of intelligent service models. The intensity of knowledge transfer plays a vital role in enhancing the performance ...

Smartphone users are eliminating traditional QR codes as many apps have integrated QR code scanning as a built-in functionality. With the support of embedded QR code scanning components, apps can read QR codes and immediately execute relevant activities, ...

Android apps pervasively use third-party libraries (TPL) to reuse functionalities and improve development efficiency. The insufficient knowledge of the TPL internal exposes the developers and users to severe threats of security vulnerabilities. To ...

While password stuffing attacks (that exploit the direct password reuse behavior) have gained considerable attention, only a few studies have examined password tweaking attacks, where an attacker exploits users' indirect reuse behaviors (with edit ...

To motivate users&#x2019; assistance for protecting others&#x2019; location privacy by distributed <italic>K</italic>-anonymity in Location-Based Service (LBS), many incentive mechanisms have been proposed, where users obtain monetary compensation for ...

When enjoying mobile crowdsensing (MCS), it is vital to evaluate the trustworthiness of mobile users (MUs) without disclosing their sensitive information. However, the existing schemes ignore this requirement in the multiple crowdsourcers (CSs) scenario. ...