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europepmc
2021
置信度 0.80
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europepmc
2020
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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Introduction Agentic AI systems integrate foundation models, prompt templates, tool connectors, orchestration logic, and containerised dependencies, creating exploitability conditions that cannot be inferred from static Software Bills of Materials (SBOMs). Art…
europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2025
置信度 0.80
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Unlike market-driven blockchain evolution paths observed globally, China follows a distinctive policy-guided trajectory integrating technology research, application scenarios, and regulatory governance. However, existing studies have seldom offered a systemati…
europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2024
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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The 2020 European Strategy for Data aims at developing Common European Data Spaces as a means to build a pan-European single market for data, thereby supporting economic growth and maximizing citizens' use of data. It demands data spaces in strategic sectors, …
europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2026
置信度 0.80
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Autonomous robot navigation within a dynamic environment is a complicated issue since environmental factors keep on changing, safety remains a factor, and issues of data privacy concern are also on the increase. The existing reinforcement learning (RL) navigat…
pubmed
Dewangan RR, Thombre D, Parganiha V, Verma M 等
2026
置信度 0.82
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europepmc
2025
置信度 0.80
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europepmc
2026
置信度 0.80
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Existing research focuses on data-driven algorithm optimization but overlooks the embodied nature of supply chains as physical and digital integrated systems, leading to a disconnect between AI and physical collaboration. This study introduces embodied intelli…
europepmc
2026
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2025
置信度 0.80
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Healthcare organizations face persistent tension between efficiency and human connection. Digital systems often fragment attention and unintentionally distance staff from patients. At Mayo Clinic, we developed a conversational artificial intelligence (AI) agen…
europepmc
2026
置信度 0.80
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Historically, critical water infrastructures have operated with limited digitalization, relying on legacy protocols designed without intrinsic security. The rapid integration of advanced IoT telemetry into Operational Technology (OT) networks has dissolved tra…
europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2024
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2025
置信度 0.80
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crossref
Dr. Heena Kousar
2026-04-04T19:15:57Z
置信度 0.70
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crossref
2025-06-22T09:47:32Z
置信度 0.70
-
crossref
Francisco Teixeira, Alberto Abad, Bhiksha Raj, Isabel Trancoso
2024-11-05T14:19:13Z
置信度 0.70
-
The insurance industry is exploring the use of machine learning (ML) models to leverage the huge volume of customer data for of-the-moment business decisions. It is, however, extremely sensitive information. From a design per- spective, data attribute utility …
crossref
Keerthi Amistapuram
2025-10-31T10:50:42Z
置信度 0.70
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Federated Learning (FL) enables privacy-preserving collaborative model training without sharing raw data but faces challenges in handling concept drift, non-IID data, and evolving tasks. Although Continual Learning (CL) supports lifelong knowledge adaptation a…
crossref
Lothar Collatz
2026-07-27T11:03:42Z
置信度 0.70
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crossref
Judith Sáainz-Pardo Díiaz, Álvaro López Garcíia
2026-07-29T19:14:52Z
置信度 0.70
-
crossref
Sijun Tan, Brian Knott, Yuan Tian, David J. Wu
2021-08-26T21:03:31Z
置信度 0.70
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crossref
Li Jiao, Hui Li
2024-04-16T22:11:20Z
置信度 0.70
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crossref
Joseph O'Neill, Lydia Bouzar-Benlabiod
2024-12-05T22:41:58Z
置信度 0.70
-
Aim/Purpose To explore the potential of Federated Machine Learning (FML) in developing predictive models while ensuring data privacy and security. Background The rise of data-driven technologies has led to an increased focus on privacy concerns associated with…
crossref
Samuel Sambasivam
2025-06-27T21:25:34Z
置信度 0.70
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Advances in digital medicine necessitate widespread use of patient data by hospitals and medical institutions for analytics, clinical research, and training of intelligent healthcare systems. Against the backdrop of stringent privacy concerns, data-minimizatio…
crossref
Sasi Kumar Kolla
2026-03-24T13:59:26Z
置信度 0.70
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crossref
Mark Jameson, Nate Wilson
2025-06-04T09:02:34Z
置信度 0.70
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crossref
Jun Sakuma, Shigenobu Kobayashi, Rebecca N. Wright
2008-08-12T18:30:36Z
置信度 0.70
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europepmc
2026
置信度 0.80
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Abstract The rapid growth of electric vehicle (EV) charging infrastructure has increased exposure to cyberattacks, while conventional centralized intrusion detection remains poorly suited to distributed and privacy-sensitive EVSE environments. This study propo…
europepmc
Mohammed Gamal Ragab, Hitham Alhussian, Said Jadid Abdulkadir, Majdy Eltahir 等
2026
置信度 0.80
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europepmc
2025
置信度 0.80
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europepmc
2025
置信度 0.80