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Earlier sources: Hardware
Hardware is the physical foundation of computing: chips, sensors, devices, networks, and the processes that manufacture them. Follow semiconductor research, compute architectures, and engineering developments alongside their software and energy connections.
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 ↗523 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
Learning-Enhanced Belief Rule Base for Sensor-Based Bearing Health Condition Assessment ↗
The Belief Rule Base (BRB) provides explainable reasoning and uncertainty modeling capabilities, offering significant advantages in complex system modeling. However, the scope of its knowledge base is constrained by expert prior knowledge, rendering it incapable of encompassing fault categories that appear in the training data but lack expert-defined rules, thereby preventing post-construction expansion in line with data evolution. To this end, this paper proposes a learning-enhanced BRB model (LE-BRB), achieving a verifiable extension of the rule conclusion space within the BRB framework. Fir…
- OpenAlex · Published · First archived
Towards sustainable composite manufacturing: Impact of matrix variants on processing energy and mechanical performance of recycled glass fibre composites ↗
The transition to circular polymer manufacturing requires improved understanding of how recycled feedstock composition influences manufacturing energy demand and final material performance. While recycled fibre-reinforced thermoplastic composites have attracted increasing interest, the connected effects of material composition and processing conditions on specific energy consumption and mechanical properties remain insufficiently quantified. This study presents a systematic correlation-based analysis of post-industrial glass fibre-reinforced polypropylene (GFPP)-reinforced recycled polypropyle…
- OpenAlex · Published · First archived
Advanced In Vitro Platforms for Experimental Liver Research: From Organoids and Liver‐on‐Chip to Omics and Artificial Intelligence ↗
Hepatocytes perform essential physiological functions in the human body. Gaining more profound insight into the liver structure, diseases, and physiology by using in vitro models can help to propose more relevant clinical applications. Conventional in vitro liver models, such as two-dimensional (2D) cell cultures, fail to adequately replicate the hepatic microenvironment, even when improved by adding additional cell types and extracellular matrix (ECM). These models do not address all necessary key components to mimic in vivo conditions, particularly multicellularity, specific ECM, and proper…
- OpenAlex · Published · First archived
Stress-controlled transfer of high-mobility organic semiconductor nanosheets for thin-film transistors ↗
Organic thin-film transistors (TFTs) are key components for large-area and mechanically flexible electronic devices, and reliable fabrication methods beyond direct physical vapor deposition (PVD) are required, particularly for technical and non-planar surfaces. We fabricated organic TFTs by transferring organic small-molecule nanosheets. During the release and transfer process, the nanosheets experience significant mechanical stress, leading to plastic deformation or phase changes that can be quantified by X-ray diffraction (XRD). In accordance with classical bending theory, the mechanical str…
- OpenAlex · Published · First archived
Flexural performance recovery and failure-mode transition in continuous-fibre thermoplastic composites repaired by in-situ additive manufacturing: A combined numerical and experimental study ↗
In-situ continuous-fibre additive repair restores damaged thermoplastic composites without a separate adhesive layer, but how load transfer between the parent laminate and printed patch reconstructs load sharing and governs failure remains unclear. This study combines four-point bending tests with a finite element model that represents the parent laminate, printed patch and parent–patch interface and quantifies the distribution of interfacial load transfer. Circular and square in-situ additive repairs recovered 99.3% and 94.0% of the intact stiffness and 91.0% and 84.1% of the intact peak load…
- OpenAlex · Published · First archived
A Lightweight Multi-Sensor Feature-Level Fusion Framework for Noise-Robust Fault Diagnosis of High-Precision Milling Machines ↗
The operational reliability of milling machines is a critical factor affecting manufacturing quality and productivity in modern industrial systems. Although multi-sensor fusion can overcome the limitations of single-sensor monitoring, many existing methods rely on computationally intensive deep learning models, which restrict their applicability in resource-constrained industrial environments. To address this issue, this paper presents a multi-sensor feature-level fusion framework for fault diagnosis in high-precision milling machines. The proposed framework integrates vibration signals from t…
- OpenAlex · Published · First archived
Sports Activity Recognition Using Textile‐Based Sensor Fusion and Complex‐Valued Residual Convolutional Neural Networks ↗
Traditional human activity recognition systems in wearable technologies typically separate sensing modalities, using mechanical sensors for motion detection and biophysical sensors such as electrocardiography for health monitoring. This work challenges that division by demonstrating that electrocardiographic signals captured via textile electrodes inherently encode activity‐specific information, as motion‐induced signal deformations, traditionally dismissed as noise, carry discriminative patterns. A smart textile system was developed integrating textile‐based electrocardiographic electrodes an…
- OpenAlex · Published · First archived
Reliability-oriented sensor fault-tolerant strategy for hydraulic systems ↗
Sensor failures in hydraulic systems can generate erroneous measurements and false alarms, leading to unnecessary shutdowns and reduced operational reliability. To address this problem, a reliability-oriented sensor fault-tolerant strategy based on multi-source information fusion is proposed. Physical sensor measurements, model-based Kalman-filter predictions, and artificial intelligence-based Long Short-Term Memory predictions are integrated to provide complementary sensing information. The artificial intelligence component provides data-driven redundant information for sensor-state assessmen…
- OpenAlex · Published · First archived
A scalable process aware routing architecture for resilient wireless communication in industrial and control networks ↗
Industrial carbon-capture plants depend on timely and reliable communication among distributed sensors, controllers, and process models. Existing studies commonly examine fault recovery, energy-aware routing, reinforcement learning, or digital-twin monitoring as separate problems, leaving limited evidence on their coordinated use in one reproducible industrial communication framework. This study presents a process-aware MeshStar wireless sensor network (WSN) that combines low-overhead star clusters with redundant mesh links among cluster routers. A tabular Q-learning controller selects recover…
- OpenAlex · Published · First archived
A Two-Stage Ant Colony Optimization-Based Approach to the Storage Location Assignment Problem (SLAP): An Application in a Cable Manufacturing Facility ↗
In this study, a two-stage approach based on K-Means clustering and Ant Colony Optimization (ACO) is proposed for solving the rack storage location assignment problem (SLAP) in a cable manufacturing facility where automated transport robots are used. In the first stage, 184 cables were clustered using the K-Means algorithm according to their monthly usage quantities across six production machines; the optimal number of clusters was determined as k=7 (silhouette score of 0.554) by jointly evaluating the elbow and silhouette analyses. In the second stage, a cost matrix was constructed by taking…
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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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