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In this article, the problem of seeking fixed points for global operators over the time-varying graphs in a real Hilbert space is studied. The global operator is a linear combination of local operators, each local operator being accessed ...

The r-component connectivity c κ r ( G ) of a noncomplete graph G is the size of a minimum set of vertices, whose deletion disconnects G such that the remaining graph has at least r components. When r = 2, c κ r ( G ) is reduced to the classic ...

• We study the r-component connectivity of the wheel network CWm.
• We prove that the 3-component connectivity of the wheel network is 4 m − 7.
• We prove that the 4-component connectivity of the wheel network is 6 m − 13.
• We prove ...

Exemplar-free class incremental learning is a highly challenging setting where replay memory is unavailable. Methods relying on frozen feature extractors have drawn attention recently in this setting due to their impressive performances and lower ...

Large-scale text-to-image (T2I) diffusion models have been extended for text-guided video editing, yielding impressive zero-shot video editing performance. Nonetheless, the generated videos usually show spatial irregularities and temporal inconsistencies ...

SQL injection is a significant and persistent threat to web services. Most existing protections against SQL injections rely on traffic-level anomaly detection, which often results in high false-positive rates and can be easily bypassed by attackers. This ...

Theory-of-Mind (ToM) possessed by Large Language Models (LLMs) has been shown to be limited. Most existing methods for improving ToM in LLMs adopt zero-shot prompting, and they have poor performance in complex ToM reasoning tasks. We propose a ...

In today’s data-driven era, deriving meaningful insights from documents poses a considerable challenge. The task of Document-level Relation Extraction (DocRE) seeks to discern relationships among multiple entities within documents, mirroring real-...

Reinforcement Learning (RL) is gaining importance in automating penetration testing as it reduces human effort and increases reliability. Nonetheless, given the rapidly expanding scale of modern network infrastructure, the limited testing scale ...

The rapid progress in Deep Learning (DL) and Large Language Models (LLMs) has exponentially increased demands of computational power and bandwidth. This, combined with the high costs of faster computing chips and interconnects, has significantly inflated ...

The action anticipation task refers to predicting what action will happen based on observed videos, which requires the model to have a strong ability to summarize the present and then reason about the future. Experience and common sense suggest that there ...

A scientific paper recommender system (RS) is very helpful for literature searching in that it (1) helps novice researchers explore their own field and (2) helps experienced researchers explore new fields outside their area of expertise. However, ...

The explosive growth of the Internet has elevated social networks to a pivotal role in information propagation, reshaping conventional paradigms of information distribution. Utilizing the vast amount of data available online to model and predict ...

Solving inverse kinematics (IK) is an excellent challenge for redundant manipulators due to their highly non-linear and complex coupling, which is not amenable to analytical solutions by conventional methods. In this paper, the conventional ...

Modern, automated quality control systems for speciality crops utilise computer vision together with a machine learning paradigm exploiting large datasets for learning efficient crop assessment components. To model anomalous visuals, data ...

• Channel Randomisation augments images for self-supervised representation learning.
• Classifying augmented images leads to neural representations of colour irregularities.
• Learnt representations better detect unhealthy crops than ...

The global trade disproportion results in the accumulation of containers in import-dominated ports and shortages in export-dominated ports, causing congestion and high freight costs, thus hindering maritime shipping economy development. To ...

• Developed a stochastic programming model for the integrated scheduling problem.
• Employed the p-median method to improve computational efficiency.
• Introduced the Benders decomposition algorithm with acceleration techniques.
• The ...

Depression is a prevalent mental health disorder that significantly impacts individuals' lives and well-being. Early detection and intervention are crucial for effective treatment and management of depression. Recently, there are many end-to-end deep ...

Voice is one of the most widely used media for information transmission in human society. While high-quality synthetic voices are extensively utilized in various applications, they pose significant risks to content security and trust building. Numerous ...

The open-vocabulary human-object interaction (Ov-HOI) detection aims to identify both base and novel categories of human-object interactions while only base categories are available during training. Existing Ov-HOI methods commonly leverage knowledge ...

Withdrawable signature, the new notion of signature recently introduced, enables the retraction of a digital signature without revealing the signer’s private key or compromising the security of other signatures the signer created before. This ...

Enabling various parties to share data enhances online fraud detection capabilities considering fraudsters tend to reuse resources attacking multiple platforms. Multi-party computation (MPC) techniques, such as secret sharing, offer potential privacy-...