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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 ↗5966 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.
- GitHub · Repository created · First archived
iretonsean/Omastrator ↗
A pro vector and interface design app built into Omarchy: frames and auto layout, pen and image trace, an AI agent at the core, and design mode over every window and live site. Alpha: testers and PRs welcome.
- OpenAlex · Published · First archived
RF-SPEA2 Hybrid Rule Inference and Optimization Architecture ↗
The high predictive performance of machine learning models in complex classification tasks often comes with limited transparency, particularly for black-box models whose decision processes cannot be directly inspected. In this study, a two-stage Random Forest–SPEA2 hybrid rule inference and optimization architecture is proposed to achieve high predictive performance while retaining an explicit rule-based decision structure. In the first stage, root-to-leaf decision paths extracted from Random Forest trees are converted into interval-based IF–THEN rules, and a class-balanced candidate rule pool…
- OpenAlex · Published · First archived
Spectral knowledge encoding and spatial anomaly localisation for interpretable power transformer fault detection ↗
Vibration-based fault detection for in-service power transformers is challenged by operating-condition variability, scarce confirmed fault labels, and the need for interpretable evidence to support maintenance decisions. This paper presents two complementary diagnostic modes and evaluates them on 4499 one-second vibration segments from 19 physical transformers across three substations. The primary evaluation is a three-fold transformer-grouped out-of-fold analysis of 15 physical transformers. SpecRas (Spectral Rasterisation) is a supervised approach for settings with representative labelled fa…
- OpenAlex · Published · First archived
Integrated Transformer approach for immersed-tunnel settlement prediction considering spatial heterogeneity and temporal degradation of sand filling compactness ↗
Settlement stability of immersed tunnels is strongly affected by the spatial heterogeneity and long-term degradation of sand filling compactness. Existing settlement prediction methods mainly rely on historical monitoring data while overlooking the time-dependent evolution of foundation compactness, resulting in insufficient prediction accuracy under heterogeneous geological and operational conditions. To overcome these limitations, this study develops an integrated Transformer-based approach that combines elastic wave detection, field monitoring data, and compactness degradation modeling for…
- OpenAlex · Published · First archived
Translational Barriers and AI‐Driven Challenges of Microfluidics‐Enabled Wearables and Implantable Systems in Personalized Medicine ↗
Wearable and implantable microfluidic systems have progressed from laboratory prototypes toward translational clinical deployment, enabling continuous, minimally invasive sampling of dynamic biomarkers across sweat, saliva, tears, and interstitial fluid. However, existing reviews often address materials chemistry or device fabrication in isolation, obscuring the systemic path to clinical translation. This review establishes a cohesive, translation-focused linear trajectory starting from foundational functional biomaterials and advanced fabrication techniques, transitioning into a performance b…
- OpenAlex · Published · First archived
Automatic binary security classification of arabic mobile app reviews using transformer models and active learning ↗
Mobile application user reviews provide valuable insights into user-reported issues, including security concerns that are critical for software engineering activities such as requirements analysis and system design. However, existing research has largely focused on English reviews and lacks systematic approaches for identifying security-related feedback in Arabic, a low-resource language in this domain. In this paper, we address this gap by developing an integrated approach for automated binary classification of security-related versus non-security-related Arabic mobile app reviews, grounded i…
- OpenAlex · Published · First archived
Automated pavement marking retroreflectivity estimation via computer vision and machine learning ↗
Pavement marking retroreflectivity is essential for nighttime road safety but deteriorates due to environmental and traffic factors. Traditional assessment methods are costly and labor-intensive. This paper introduces a sensor-independent, artificial intelligence driven methodology for predicting pavement-marking retroreflectivity using just Red, Green, and Blue (RGB) smartphone videos. The artificial intelligence contribution is through combining gray level co-occurrence matrix (GLCM) based texture and contrast features with a physics-informed synthetic labeling model that imitates material d…
- OpenAlex · Published · First archived
Examining the social validity of a Cybersecurity Awareness Training Program in AI-Supported Education (CATP-AIsE) for gifted students ↗
Despite the rapid integration of AI-supported tools into special education settings, empirical evidence regarding cybersecurity awareness among gifted students remains extremely limited. This mixed-methods study examined whether AI-supported, scenario-based educational interventions could produce measurable improvements in the cybersecurity awareness of gifted students (N = 50, aged 11–14) enrolled in a Science and Art Center program in Türkiye. Quantitative data were collected using the Cybersecurity Awareness Scale administered before and after a four-week intervention, while qualitative dat…
- OpenAlex · Published · First archived
Language as data, hate as task: The epistemic normalisation of hate speech in AI ↗
Automated hate speech detection is now a large technical field, but engages unevenly with linguistic and social-scientific work on how hate and discrimination are communicated. This article uses corpus-assisted discourse analysis of 322 publications (299 computer science, 23 social sciences and humanities) to compare how language, context, bias and hate speech are conceptualised. Computer science texts construct language as data and hate speech as a classification task, developing intricate taxonomies of model-side bias while largely sidelining racism, power and discourse context. Social scien…
- OpenAlex · Published · First archived
Leakage-aware machine learning framework for thermophysical property prediction of nanofluids and numerical modelling assisted radiator cooling channel optimization ↗
The study offers a machine learning approach that takes leakage into account for two separate but complementary tasks. The prediction of thermophysical properties were carried out for a deep eutectic solvent made up of benzophenone and biphenyl in which spherical aluminium oxide nanoparticles are dispersed. Further, surrogate models were developed, and optimization of an unmodified base-solvent radiator cooling channel were carried out. The density, viscosity, thermal conductivity and specific heat capacity were determined by means of baseline-plus-correction learning, using temperature-matche…
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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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