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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 ↗522 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
SeqCube-HT: state-cube-guided generation of sequential hardware Trojan benchmarks ↗
Abstract Hardware Trojan (HT) detector evaluation depends on benchmarks whose triggers are executable from a defined reset state and whose payload effects reach an observation boundary. Establishing both properties is difficult for sequential Trojans because rare events are coupled through state evolution across cycles. We present SeqCube-HT, a state-cube graph framework that incorporates temporal execution evidence into benchmark construction. Reset-consistent traces are compressed into pre- and post-state cubes, and directed compatibility organizes candidate event sequences. Selected paths a…
- OpenAlex · Published · First archived
Comparing mechanistic and data-driven models for predicting cutting force and chip morphology of γ-TiAl alloys ↗
γ-TiAl alloys are extensively utilized in the aerospace sector owing to their elevated specific strength and high-temperature capabilities; nonetheless, their inherent brittleness and complex work-hardening behavior often lead to significant discrepancies in traditional mechanistic models. This study presents a comprehensive comparative investigation between a data-driven constitutive framework and the conventional Johnson-Cook (J-C) mechanistic models. A neural network (ANN) model is proposed to adaptively map the highly nonlinear interplay among strain, strain rate, and temperature. To bridg…
- OpenAlex · Published · First archived
Dual-version and dual-scale CSRR loaded sensor for mining-based material characterization ↗
In this work, dual-version and dual-scale sensor is proposed for mining-based material characterization. The sensor structure is configured using a circular-shaped patch loaded with a 3 × 3 CSRR array. The ground plane was fully loaded with a perfect electric conductor. A strong resonance for the (S21) parameter is achieved by four rectangular slots created surrounding the CSRR array. The first version of the sensor had an overall size of 100 mm × 60 mm and resonated at a frequency of 1.5 GHz. Furthermore, the sensor size was optimized, and the second version achieved an overall size of 30 mm…
- OpenAlex · Published · First archived
Dynamic machine-level planning for Plug & Produce manufacturing ↗
Abstract Manufacturing industries face persistent challenges due to a shortage of skilled labor and growing demand for customized products, while established automation methods are not cost-effective for high-mix, low-volume manufacturing. An intelligent automation concept capable of daily reconfiguration to accommodate new manufacturing conditions is required. Manufacturers request digital configuration over detailed programming of operational sequences and process data. Sub-operations, such as material transport and resource switching, are preferably automatically planned. This paper introdu…
- OpenAlex · Published · First archived
Applying Deep Learning to Image and IMU Sensor Data for Real-Time Fatigue Recognition in Table Tennis Players ↗
Fatigue during table tennis training can impair performance and increase the risk of injury. This study proposes a real-time fatigue recognition system that integrates an embedded edge-AI racket with a camera for synchronized multimodal data acquisition. On the racket side, a neural network was deployed on an edge-AI microcontroller unit (MCU) to enable on-device inference, while the test data were transmitted to a computer for multimodal feature fusion. Given the continuous nature of fatigue development, the data were divided into three stages: non-fatigue, transition, and fatigue to facilita…
- OpenAlex · Published · First archived
Prompt-Shape- and Prefix-Cache-Aware CPU/NPU Routing for Large Language Model Inference on Edge SoCs ↗
Large language model (LLM) inference on edge systems must exploit heterogeneous central processing unit (CPU) and neural processing unit (NPU) resources under tight memory and latency constraints. Because prefilling and autoregressive decoding have different computational characteristics, the fastest backend depends on the request shape and prefix-cache reuse. This work proposes request-level CPU/NPU routing for the RK3588 system on chip (SoC). Prompt-shape-aware routing (PSR) uses prompt length and generation budget to select a backend for no-cache requests, while prefix-cache-aware routing (…
- OpenAlex · Published · First archived
Asymmetric CPW-fed dual band antenna sensor with reduced SAR for burn depth and severity classification ↗
In this paper, a dual band antenna sensor with an asymmetric CPW fed and metamaterial split ring structure is proposed for non-invasive Burn depth and severity classification. The antenna Sensor is termed as Asymmetric CPW-fed Dual band (ACD) antenna sensor. In Traditional noninvasive burn severity analysis methods use RGB images for classification of burn depth prediction and severity classification. RGB images-based classification provides less accuracy due to Skin tone and color variation. To solve the above problem, ACD antenna sensor is proposed and tested the performance in skin phantom…
- OpenAlex · Published · First archived
Structured Sensors With Tunable Sensing Properties ↗
ABSTRACT Pressure sensors are essential components in intelligent systems for applications in robotics, wearable electronics, and human–machine interfaces. Although pressure sensing originates from mechanically induced electrical changes under applied pressure, the mechanical–electrical relationship remains insufficiently understood and lacks a rigorous quantitative framework, limiting their predictive design and optimization. Here, we introduce an innovative structured‐sensor concept that integrates sensing and energy absorption and establish a corresponding mechanical–electrical coupling fra…
- OpenAlex · Published · First archived
Geometric digital twin for additive manufacturing (gDT-AM): In-process part surface reconstruction and shape monitoring ↗
Additive manufacturing (AM) faces critical challenges, particularly in achieving real-time quality control and precision. These challenges are heightened in complex geometries and high-deposition-rate robotic AM (HDR-RAM) processes such as robotic cold spray. Traditional quality control methods generally detect defects after the entire part is produced, leading to material waste and increased lead time and cost. The lack of real-time insight during production limits the ability to identify and correct the process variations as they occur. To address this, digital twin technology has emerged as…
- OpenAlex · Published · First archived
Characterising CPU-initiated High Bandwidth Memory Access ↗
Abstract An increasing number of high-performance computers are equipped with high bandwidth memory. Their CPUs have cache-coherent access to this memory type over high-speed interconnects or as unified memory. We analyse two such systems, NVIDIA’s GH200 and AMD’s MI300A. We discuss their memory setup and measure memory access latency and throughput. We evaluate weighted memory page interleaving and strided memory access as candidates for increasing the measured throughput. Weighted interleaving utilises CPU and GPU memory simultaneously and enables exceeding the measured throughput on only CP…
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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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