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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.
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Open in the map ↗525 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
Protecting Ports using Range-Free Triangulated Sensor Networks: A Case Study ↗
Range-free wireless sensor networks rely on sensors that detect only the bearing of an incoming signal, so that localizing a transmitter requires simultaneous detection by at least three sensors, a condition known as triangulated coverage. This paper extends a previously developed geospatial computational framework with a formal treatment of sensor activation and applies it to the protection of the port of Thessaloniki, Greece. Eleven sensors, in the presence of seven known transmitters that induce angular blind zones, monitor four areas of interest that form successive protection layers: the…
- OpenAlex · Published · First archived
Pyriscope: Precise and Low-Overhead Python Control Flow Tracing via Sparse Hardware-Based Events ↗
Capturing the control-flow and/or coverage profiles of Python code becomes a pressing need for Python development community, which is commonly used in a wide spectrum of tasks including program testing/fuzzing, debugging, understanding, and optimizations. Existing tracing approaches either suffer from prohibitively high overhead or only collect approximate information, which cannot satisfy the practical requirements. In this paper, we propose to leverage modern hardware tracing modules to achieve precise and low-overhead control-flow tracing for Python programs. To this goal, we develop Pyrisc…
- OpenAlex · Published · First archived
Chip-based characterization of machinability in post-machined directed energy deposition Ti-6Al-4V ↗
Chips generated during machining contain rich information on the machining history. Chip-level analysis has nevertheless remained underutilized for evaluating the machinability of additively manufactured materials. In this study, chip morphology and microstructure were analyzed to evaluate the machinability of directed energy deposition (DED) Ti-6Al-4V fabricated under various deposition conditions. The results showed that the deposition parameter, laser power, had a significant impact on changes in the deposited microstructure, influencing chip formation behavior, cutting force, and machined…
- OpenAlex · Published · First archived
A data-driven miniature water-flow vector sensor via dynamic pressure gradient inversion ↗
Accurate flow velocity and direction measurement is essential for AUV/UUV hydrodynamic awareness, supporting sideslip estimation, path planning, and flow field perception. To overcome existing limitations of large volume, high power consumption, and poor dynamic adaptability, this study proposes a method based on dynamic pressure gradient inversion. Using Bernoulli’s theorem, a circular sensor array (42 mm radius) with MS5837-30BA pressure sensors was constructed. A lightweight CNN-LSTM hybrid network extracts spatiotemporal pressure features for joint velocity–direction measurement. The 3.28…
- OpenAlex · Published · First archived
Distributed Artificial Intelligence for Agentic Intent-Based Networking in Mobile Networks ↗
Through intent-based networking (IBN), network objectives are specified declaratively, yet in mobile networks their realisation spans administrative domains that compete for coupled radio, transport and compute resources but cannot share local models and telemetry. A distributed artificial intelligence (DAI) controller with a Belief-Desire-Intention-eXecution (BDIX) cycle is presented, centred on shared-space coordination. The local decision of each domain agent is mapped through Gi into a common p-dimensional resource space, so that only resource contributions and a common price vector cross…
- OpenAlex · Published · First archived
Advances in self-powered wearable and flexible electronics: A review ↗
The rapid evolution of the Internet of Things (IoT), personalized healthcare, and human-machine interaction is driving a shift from rigid electronics toward flexible, body-conformable wearable systems. This review examines recent advances in self-powered flexible electronics by integrating perspectives from materials science, fabrication, energy technologies, sensing, and system-level design. Key functional materials, including stretchable conductive hydrogels, liquid-metal composites, graphene, MXenes, and polymer nanocomposites, are discussed alongside scalable manufacturing approaches such…
- OpenAlex · Published · First archived
Conductive Polyvinyl Alcohol-Based Hydrogels for Wearable Electronics: Preparation Strategies, Conductivity Enhancement, and Sensing Applications ↗
Conductive poly(vinyl alcohol) (PVA)-based hydrogels combine electrical functionality with the mechanical compliance and biocompatibility required for wearable bioelectronics. However, simultaneously achieving mechanical robustness, stable electrical conductivity, and long-term hydration stability remains challenging. Adopting a performance trade-off perspective focused on wearable sensing, this review examines recent advances in five interconnected areas: (1) fabrication strategies, including freeze–thaw cycling, the Hofmeister effect, mechanical training, and green synthesis routes; (2) cond…
- OpenAlex · Published · First archived
QUINN: Quantized Inference and Dataflow Characterization for Neural Networks on RISC-V Near-Memory Architectures ↗
Machine learning inference is moving to the edge due to latency, energy, and privacy constraints. The growing complexity of edge workloads places increasing pressure on memory hierarchies, making data movement a major limitation for both performance and energy efficiency. Fixed-function accelerators inherit the memory wall of the von Neumann model and lack the flexibility to follow evolving models. Programmable Vector Processing Unit (VPU)-based near-memory architectures alleviate this bottleneck using standard Complementary Metal-Oxide Semiconductor (CMOS) while remaining programmable, but st…
- OpenAlex · Published · First archived
Hybrid GA-DQN for opportunistic cluster head selection and routing in resource constraint Internet of Things networks ↗
Abstract Energy efficiency and reliable data transmission are two important challenges in Internet of Things (IoT) networks because of the limited energy resources of sensor nodes and their dynamic nature. Accordingly, this research develops a Genetic Algorithm Deep Q-Network (GA-DQN) based hybrid framework for intelligent cluster head selection and adaptive IoT Network routing to counter these threats. A Genetic Algorithm (GA) selects the best cluster heads based on residual energy, coverage ratio, inter-cluster distance, and node density. In turn, this ensures balanced cluster formation and…
- OpenAlex · Published · First archived
A multifunctional graphene-integrated double-network nanocomposite hydrogel for dual strain-temperature wearable sensing ↗
Abstract Inspired by the natural sensing capabilities of human skin, flexible and stretchable materials such as hydrogels have emerged as vital platforms for skin-interfaced and wearable electronics. A double-network chitosan/modified polyethylene glycol/graphene (Cs./mPEG/G) nanocomposite hydrogel is developed as a flexible, multifunctional platform for dual strain-temperature sensing. By leveraging the balanced mechanical properties of the double-network hydrogel and the exceptional electrical conductivity of graphene, the nanocomposite hydrogel possesses strong mechanical resilience and rel…
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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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