新兴技术
In intelligent transportation systems (ITSs), incorporating pedestrians and vehicles in-the-loop is crucial for developing realistic and safe traffic management solutions. However, there is falls short of simulating complex real-world ITS…
A key challenge for Deep Neural Network (DNN) algorithms is their vulnerability to adversarial attacks. Inherently non-deterministic compute substrates, such as those based on Analog In-Memory Computing (AIMC), have been speculated to…
Digital twin technology is a transformative innovation driving the digital transformation and intelligent optimization of manufacturing systems. By integrating real-time data with computational models, digital twins enable continuous…
Advances in novel hardware devices and architectures allow Spiking Neural Network evaluation using ultra-low power, mixed-signal, memristor crossbar arrays. As individual network sizes quickly scale beyond the dimensional capabilities of…
Advancements in nanosatellite technology lead to more Earth-observation satellites in low-Earth orbit. We explore using nanosatellite constellations to achieve low-latency detection for time-critical events, such as forest fires, oil…
Single ferroelectric memcapacitor-based time-domain (TD) content-addressable memory (CAM) is proposed and experimentally demonstrated for high reliability and density. The proposed TD CAM features the symmetric capacitance-voltage…
Reservoir computing (RC) is an innovative paradigm in neuromorphic computing that leverages fixed, randomized, internal connections to address the challenge of overfitting. RC has shown remarkable effectiveness in signal processing and…
The OmpSs-2 programming model is used in HPC programs to parallelize code and offload code to accelerators. In this work, we extend the offloading capability to quantum computers. We explain the necessary changes to the Clang compiler and…
Reservoir Computing is an Unconventional Computation model to perform computation on various different substrates, such as recurrent neural networks or physical materials. The method takes a 'black-box' approach, training only the outputs…
Low energy barrier magnet (LBM) technology has recently been proposed as a candidate for accelerating algorithms based on energy minimization and probabilistic graphs because their physical characteristics have a one-to-one mapping onto the…
This paper introduces a novel approach to demand estimation that utilizes partial observations of segment-level track counts. Building on established simulation-based demand estimation methods, we present a modified formulation that…
Many combinatorial problems can be mapped to Ising machines, i.e., networks of coupled oscillators that settle to a minimum-energy ground state, from which the problem solution is inferred. This work proposes DROID, a novel event-driven…
Setting out a path to use quantum computing within a company is not as straightforward as the implementation of classical ICT-projects. The technology is fundamentally different and not mature yet, which makes the development and use…
With the advent of the 6G mobile communication network era, the existing non-orthogonal multiple-access (NOMA) technology faces the challenge of high successive interference in multi-user scenarios, which limits its ability to support more…
Reconfigurable Intelligent Surface (RIS) technology has emerged as a transformative solution for enhancing satellite networks in next-generation wireless communication. The integration of RIS in satellite networks addresses critical…
It is recently shown that discrete $N\times N$ linear unitary operators can be represented by interlacing $N+1$ phase shift layers with a fixed intervening operator such as Discrete Fractional Fourier Transform (DFrFT). Here, we show that…
Recently, employing single-modality large language models based on mechanical vibration signals as Tuning Predictors has introduced new perspectives in intelligent fault diagnosis. However, the potential of these methods to leverage…
In the superparamagnetic regime, magnetic tunnel junctions switch between two resistance states due to random thermal fluctuations. The dwell time distribution in each state is exponential. We sample this distribution using a temporal…
Magnetic induction (MI) communication, with stable channel conditions and small antenna size, is considered as a promising solution for underwater communication network. However, the narrowband nature of the MI link can cause significant…
A feed-forward photonic neural network (PNN) is tested for chromatic dispersion compensation in Intensity Modulation/Direct Detection optical links. The PNN is based on a sequence of linear and nonlinear transformations. The linear stage is…