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Earlier sources: Artificial Intelligence
Artificial intelligence covers systems that learn from data, generate content, perceive their surroundings, or act toward a goal. Follow model research, agent tooling, evaluation, and the infrastructure used to build and run these systems.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗6056 classified signals in the fourteen-day window. Recent momentum: steady. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- OpenAlex · Published · First archived
Next-Generation Modulation and Control of Power Electronic Systems: AI-Enabled Control, Digital Twins, Fault-Tolerant Operation, and Cyber-Physical Security ↗
Power electronic systems are evolving from conventional fixed-function converters toward intelligent, adaptive, and cyber-physical energy-conversion platforms in which modulation, predictive control, artificial intelligence (AI), digital twins (DTs), fault diagnosis, and cybersecurity increasingly interact within a unified closed-loop architecture. This paper presents an integrated review and mathematical framework for next-generation modulation and control of power electronic systems, with an emphasis on advanced modulation, predictive control, AI-assisted adaptation, converter-oriented digit…
- OpenAlex · Published · First archived
Validation of a Questionnaire to Explore Artificial Intelligence Use Among Upper-Secondary and Higher Education Teachers ↗
Research on generative artificial intelligence (AI) in education has shifted from students to teachers, yet available teacher instruments rest on technology acceptance models, professional knowledge frameworks, or AI literacy, and none articulates dispositional conditions, teaching activities, and contextual consequences within a single functional logic. This study extends to teachers an instrument previously validated with students and grounded in Functional Behavior Analysis and the Interbehavioral Model of Didactic Performance. Participants were 233 Mexican upper-secondary and higher educat…
- OpenAlex · Published · First archived
Universal physics-informed machine learning framework for the prediction of porosity defects in high-power laser beam welding with different metallic materials ↗
High-power laser beam welding (LBW) is a widely used joining technique for metallic materials. However, porosity defects frequently arise during the process, leading to significant degradation of weld properties. Accurate prediction of porosity remains challenging due to the highly nonlinear and material-dependent underlying physics. In this study, a universal physics-informed machine learning framework is proposed to predict porosity levels in the LBW of aluminum and steel. Systematic LBW experiments were conducted to quantify porosity ratios across a broad parametric space. In parallel, a we…
- OpenAlex · Published · First archived
Port-Agent: Structured Multimodal Reasoning for Port Disruption Analysis Using AIS, Satellite Imagery, and News ↗
Textual accounts establish essential context for port disruptions but can bias large language model synthesis before independent observations are examined. We present Port Agent, a remote-sensing agent that aligns Automatic Identification System (AIS) trajectories, Sentinel-2 vessel detections, and documents while retaining acquisition time, footprint, processing, and uncertainty. The evaluation follows the evidence chain from physical observation to agent synthesis across 12 views of 11 U.S. event-or-control groups, 24 quality-screened scenes, and 145,570,911 AIS positions. AIS first resolved…
- OpenAlex · Published · First archived
Multi-Objective Intelligent Optimization of Excavation and Support for Super-Large Cross-Section Small Clear Spacing Tunnels in Urban Sensitive Areas: An Integrated Study of Numerical Simulation and Machine Learning ↗
Coastal subsea tunnels often traverse shallow heterogeneous strata, creating significant deformation risks. Deformation control is therefore essential for safe urban construction. This study integrates FLAC3D, SSA-LSSVM, and NSGA-II for multi-objective excavation-support optimization. The Qingdao Jiaozhou Bay Second Subsea Tunnel serves as the case study. The results show that the large-span double central diaphragm method with vertical temporary supports provides the best deformation control. Ground surface grouting provides better control of ground and building settlements than the advanced…
- OpenAlex · Published · First archived
Resilience Evaluation of Urban Tunnel Operations Based on Multi-Source Data and Explainable Artificial Intelligence ↗
As critical nodes in urban transportation networks, the operational resilience of urban tunnels directly affects roadway network efficiency and public safety. Existing studies on tunnel resilience exhibit deficiencies in the attention paid to routine incidents, the interpretability of evaluation methods, and the robustness of underlying data. To address these gaps, this paper constructs a three-layer resilience evaluation framework (pre-event, during-event, and post-event) based on 1123 accident records, hourly traffic flow data, and expert scoring data from 10 urban tunnels in Shanghai in 202…
- OpenAlex · Published · First archived
From centralised AI to distributed intelligence: implications for bioinformatics ↗
This article examines a possible transition in artificial intelligence from centralised, cloud-based systems toward smaller, specialized models operating locally on personal devices, laboratory instruments, medical equipment, and industrial machinery. Drawing on the historical shift from mainframe computers to personal computing, it argues that local AI may complement, and in some applications partly replace large centralized models by providing lower latency, greater privacy, reduced operating costs, and less dependence on cloud connectivity. Although hyperscale data centers will remain essen…
- OpenAlex · Published · First archived
Machine learning prediction of chloride convection-zone depth in marine tidal concrete with model explainability and experimental validation ↗
Reliable prediction of chloride convection-zone depth is important for service-life assessment of tidal-zone concrete, but most data-driven chloride studies focus on surface concentration or diffusion-related indicators. This study proposes a data-driven prediction and explainability framework for chloride convection-zone depth. A database of 624 experimental measurements with 25 material, curing, exposure, and loading features was compiled from published studies. Seven machine-learning algorithms were evaluated under a unified training and testing procedure, and the regression outputs were fu…
- OpenAlex · Published · First archived
Intelligent Governance of Complex Social Systems: A Hybrid AI–System Dynamics Model for the Simulation and Projection of Sustainable Energy Transition ↗
Amidst growing uncertainty regarding global sustainable development goals and the increasing complexity of social systems, accurately characterizing long-term transition processes driven by the interactions of multiple agents and factors remains a critical challenge. Using China’s energy transition toward carbon neutrality as a proof-of-concept case, this paper constructs a bidirectional coupling framework based on a hybrid Artificial Intelligence–System Dynamics (AI-SD) approach. Within this framework, an axiomatic SD formal system imposes hard constraints on the nonlinear learning processes…
- OpenAlex · Published · First archived
Quantifying experience-based residential layout quality in floor-plan evaluation with knowledge-grounded LLM rules ↗
Residential floor-plan evaluation requires both computable geometric measures and experience-based judgments of layout quality, including lighting and ventilation, functional zoning, circulation design, and privacy. Existing automated methods often provide limited traceability when qualitative architectural knowledge is involved. This study presents an auditable and modular workflow for interpretable residential floor-plan evaluation. The workflow first converts parametric floor-plan geometry into structured spatial evidence describing room functions, daylight conditions, adjacency relations,…
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How to assess evidence about Artificial Intelligence
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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