- Research Article
- 10.1016/j.jpdc.2026.105252
Security-aware task scheduling for improving the user satisfaction in hybrid clouds
- Jun 01, 2026
- Journal of Parallel and Distributed Computing
- Bo Wang + 4 more +4
Publications from 2021 to 2026
Showing 10 of 217 papers
Security-aware task scheduling for improving the user satisfaction in hybrid clouds
Microstructural regulation and property enhancement mechanisms of laser cladding FeCoCrNiCu HEA via Ti/Al lightweight element
Engineering marine-anticorrosive coatings to protect NdFeB via Ti3C2Tx@MoS2 heterojunction
Enhancing Self-Healing Performance of Cement-Based Materials Through Sodium Silicate and SAP Composite Incorporation.
Conventional admixture-based self-healing technologies are often limited by inadequate internal water supply and a scarcity of unhydrated gel particles. Therefore, this study proposes a new self-healing method that leverages the synergistic interplay between the chemical repair of sodium silicate and the physical clogging of superabsorbent polymers (SAPs) to overcome the aforementioned limitations. The healing efficiency of cement mortar was assessed through compressive strength recovery, capillary water absorption, and ultrasonic pulse velocity (UPV). Microstructural evolution and healing mechanisms were elucidated using scanning electron microscopy (SEM) and X-ray diffraction (XRD). Results indicate that at an optimal dosage (0.5 wt.% for both admixtures), the healing performance is significantly enhanced: the compressive strength recovery rate reaches 103.1%, the capillary water absorption coefficient decreases by 16.57 × 10-3, and the UPV recovery achieves 95.4%. Microstructural analysis reveals that sodium silicate facilitates the reaction between Ca2+ and SiO32- ions, leading to the in situ precipitation of dense C-S-H gel at the crack interface, thereby enabling chemical repair. In contrast, SAP contributes to physical sealing via a swelling and release mechanism.
Read moreRegulating stress-induced martensitic transformation through primary α phase to enhance work hardening in a Ti-7Mo-3Al-3Cr-3Nb alloy
Spirulina-derived carbon dots with narrow-peak NIR emission for LED applications.
A New Clematis Cultivar, Ziqidonglai
Weak-to-strong boundary learning: leveraging pre-trained models to enhance large language models’ entity boundary recognition
Intelligent Data-Driven Precision Marketing
Amid the rise of the digital economy, intelligent data technologies—such as big data analytics and AI—are transforming precision marketing by enabling real-time user profiling, demand forecasting, and dynamic channel optimization. This study examines the three-layer technical framework (data collection, analytical modeling, and execution application) that underpins this transformation and presents empirical evidence from an e-commerce platform analyzing 180 million user logs (2022–2023). Results show a 43.8% increase in customer lifetime value for high-value users, 3.5–8.8% gains across marketing funnel stages, 38.7% revenue uplift from dynamic pricing, and 27% correction in channel attribution errors. Despite these advances, challenges persist—including data silos, privacy compliance, algorithmic bias, and accessibility barriers for SMEs. The paper concludes with recommendations for building ethical, transparent, and integrated intelligent marketing systems.
Read moreEavesdropping on the multiparty semi-quantum secret sharing protocol based on single qubit sequence and permutation
In the paper [Modern Phys. Lett. A 39 (2024) 2450084], Xin et al. proposed a multiparty semi-quantum secret sharing protocol based on the single qubit sequence and the permutations of the qubit locations. We study the security of the proposed protocol and point out that there exists a security loophole in it, that is, the first and last agents can collude to obtain Tom’s secret without the help of the other agents.
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