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In multi-end-to-end path request planning, the control plane may not be able to meet all path request requirements under limited bandwidth resources. Moreover, suboptimal path planning can lead to localized network congestion, which in turn causes an overall imbalance in network load. Therefore, the multi-domain control plane needs to consider more network resource states during the path selection, such as link weights, load saturation, and resource occupancy rates, in order to select the optimal paths to maximize the satisfaction of data plane requirements while maintaining network load balance. To address such issues, we first derive a cross-domain communication load balancing objective function based on network modeling. Through collaborative processing among multi-domain controllers, the coordinated planning of cross-domain paths and the collaborative installation of flow tables are achieved. Then, we transform the cross-domain path planning problem into a clique-finding problem under a set of backup paths. Finally, we provide a heuristic approximate solution method for this problem. In terms of cross-domain communication, we adopt a collaborative approach among multiple controllers to achieve coordinated planning of cross-domain paths and collaborative installation of flow tables. Simulation results show that our proposed scheme outperforms the traditional method in terms of path allocation success rate, network load balancing degree, and data transmission delay, especially in cross-domain communication under high-density path requests in SDN networks.
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http://dx.doi.org/10.3390/s25041080 | DOI Listing |
J Int Neuropsychol Soc
September 2025
Center for Health Assessment Research and Translation, University of Delaware, Newark, DE, USA.
Objective: Because of the complexity of Alzheimer's Disease (AD) clinical presentations across bio-psycho-social domains of functioning, data-reduction approaches, such as latent profile analysis (LPA), can be useful for studying profiles rather than individual symptoms. Previous LPA research has resulted in more precise characterization and understanding of patients, better clarity regarding the probability and rate of disease progression, and an empirical approach to identifying those who might benefit most from early intervention. Whereas previous LPA research has revealed useful cognitive, neuropsychiatric, or functional subtypes of patients with AD, no study has identified patient profiles that span the domains of health and functioning and that also include motor and sensory functioning.
View Article and Find Full Text PDFSensors (Basel)
August 2025
School of Computer Electronic and Information, Guangxi University, Nanning 530004, China.
This review systematically examines intelligent event perception in distributed acoustic sensing (DAS) systems. Beginning with the elucidation of the DAS principles, system architectures, and core performance metrics, it establishes a comprehensive theoretical framework for evaluation. This study subsequently delineates methodological innovations in both traditional machine learning and deep learning approaches for event perception, accompanied by performance optimization strategies.
View Article and Find Full Text PDFJ Int Neuropsychol Soc
August 2025
Psychology, School of Social Sciences, Nanyang Technological University, Singapore, Singapore.
Objective: Cognitive intra-individual variability (IIV) is a neuropsychological marker reflecting divergent performance across cognitive domains. In this brief communication, we examined whether clinical severity, apolipoprotein E () ε4 carriers, and higher polygenic risk were associated with higher cognitive IIV, and whether higher polygenic risk and cognitive IIV synergistically influence clinical severity.
Method: This large study involved up to 24,248 participants (mean age = 72) from the National Alzheimer's Coordinating Center (NACC) and multiple regression controlling for age, sex, and education was used to analyze the data.
Sci Rep
August 2025
Department of Computer Science and Engineering, Manipal University Jaipur, Jaipur, 303007, Rajasthan, India.
Large language models (LLMs) have significantly advanced in recent years, greatly enhancing the capabilities of retrieval-augmented generation (RAG) systems. However, challenges such as semantic similarity, bias/sentiment, and hallucinations persist, especially in domain-specific applications. This paper introduces MultiLLM-Chatbot, a scalable RAG-based benchmarking framework designed to evaluate five popular LLMs GPT-4-Turbo, CLAUDE-3.
View Article and Find Full Text PDFSensors (Basel)
August 2025
Department of Electronic and Communication Engineering, Beijing Electronic Science and Technology Institute, Beijing 100070, China.
Proxy re-signature enables transitive authentication of digital identities across different domains and has significant application value in areas such as digital rights management, cross-domain certificate validation, and distributed system access control. However, most existing proxy re-signature schemes, which are predominantly based on traditional public-key cryptosystems, face security vulnerabilities and certificate management bottlenecks. While identity-based schemes alleviate some issues, they introduce key escrow concerns.
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