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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 ↗521 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.
- Hacker News · Posted on Hacker News · First archived
Open-source ESP32-C3 DNS ad blocker supports over 500K domains without PSRAM ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Ask HN: What is needed to burn MiMo2.6Pro onto a chip ↗
I know this topic comes up frequently, and is immediately dismissed as the model will be outdated. But Opus5.5 is good enough for many people. So what is actually needed? The biggest model burned on a chip has 17b parameters. How many parameters does MiMo-V2.6-Pro have? MiMo-V2.6-Pro has 1.0 trillion parameters (42 billion active). What are the active parameters of MiMo-V2.6-Pro? MiMo-V2.6-Pro is a Mixture of Experts (MoE) model with 1.0 trillion…
- GitHub · Repository created · First archived
sorrycc/Mayoi ↗
A small, fast code editor written in Go, with a native GPU-drawn UI (no webview, no Electron)
- OpenAlex · Published · First archived
A Practical Fixed-Configuration, Training-Free Baseline for Within-Sensor Hyperspectral Anomaly Detection ↗
Hyperspectral anomaly detection (HAD) aims to identify rare targets without labeled anomaly samples, but many recent deep HAD approaches require scene-specific neural optimization, increasing deployment cost. This paper presents MASCR-UAF, a fixed-configuration baseline designed for training-free within-sensor HAD. Global hyperparameters are calibrated on a designated calibration split and frozen before evaluation. No target-scene labels, neural-network retraining, gradient-based adaptation, or target-label-based hyperparameter selection are used, although unlabeled statistical quantities are…
- OpenAlex · Published · First archived
Factoring some integers using Shor’s algorithm on real quantum hardware ↗
Experimental realizations of Shor’s integer factorization algorithm on NISQ devices often rely on heavy circuit compilation that inadvertently encodes prior knowledge of the solution, bypassing the core challenge of quantum arithmetic. In this work, we present a hardware-execution baseline for the quantum order-finding routine where modular exponentiation is kept explicit as a sequence of controlled modular multiplications. We explicitly acknowledge that our approach relies on strong prior structural knowledge: the moduli are deliberately chosen as products of Fermat primes, and that ensures t…
- OpenAlex · Published · First archived
Respiratory-rate features add modest modality-related information beyond heart-rate features in heterogeneous wearable sport recordings: a secondary analysis ↗
To test whether active-exercise features derived from respiratory rate (RR) add incremental modality-related information after accounting for heart rate (HR) features in heterogeneous wearable sport recordings. Observational secondary analysis of a public wearable exercise dataset. Of 126 source recordings, 124 recordings from 79 modality-qualified participant identifiers across 10 exercise modalities met the rule-based signal and annotation criteria. The primary feature set comprised four heart-rate and four respiratory-rate descriptors calculated on aligned active-exercise segments. Exercise…
- OpenAlex · Published · First archived
Polymer-Based Additive Manufacturing in Cervical Cancer Management: A Review ↗
Cervical cancer management increasingly requires patient-specific and locally adaptable technologies to address complex pelvic anatomy, heterogeneous tumor geometry, limited local drug retention, and the need for improved planning and education. Polymer-based additive manufacturing offers a promising strategy by integrating digital design, customizable three-dimensional geometry, and tunable material properties. This review summarizes recent progress in polymer-based additive manufacturing for cervical-cancer-related applications from a material–process–structure–function perspective. Four app…
- OpenAlex · Published · First archived
Hybrid Multi‐Gateway Authentication Protocol for 6LoWPAN‐Based Marine Wireless Sensor Networks ↗
ABSTRACT This paper proposes a secure and efficient three‐factor authentication scheme to address the security issues in the integration scenario of multi‐gateway wireless sensor networks (WSNs) and 6LoWPAN in marine Internet of Things (IoT). Existing approaches exhibit vulnerabilities to cryptographic breaches, single‐point failures, high computational costs, and inefficient long‐distance transmission in maritime settings. To mitigate these limitations, we integrate blockchain technology, elliptic curve cryptography (ECC), the Chinese Remainder Theorem (CRT), and a dynamic credential update m…
- OpenAlex · Published · First archived
Adaptive Thread Scheduling and Optimization Framework for the Multi-Core CPU with Large-Capacity Cache ↗
The continuous growth in processor speed and the persistent memory latency bottleneck make large-capacity cache critical for mitigating the “memory wall”. However, topology-oblivious OS scheduling frequently induces severe cache contention and cross-die migrations, diminishing these hardware benefits. To address this, we propose a thread scheduling framework driven by runtime microarchitectural feedback. Instead of treating performance profiling and thread placement as isolated steps, our approach directly uses hardware performance counters to guide thread configurations to maximize cache util…
- OpenAlex · Published · First archived
Stage-Wise Threshold Calibration for Early Defect Warning in Multi-Stage Manufacturing: A Cost-Sensitive Single-Line Automotive Case Study ↗
In multi-stage manufacturing, conformity is confirmed only at the final test, after the cost has been incurred. On an automotive assembly line (16,500 workpieces), a regression model per checkpoint predicts the final measurement; a threshold turns it into a Go/NoGo decision. On the holdout, the models ranked the defects (area under the curve, AUC, up to 0.81), yet at the inherited final-station limit they raised no alarm and missed all 15. The threshold was therefore calibrated per checkpoint on an earlier period under a cost-weighted objective with an explicit defect rate, and evaluated on a…
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
How to assess evidence about Hardware
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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