142 research outputs found
Copernicus high-resolution layers for land cover classification in Italy
The high-resolution layers (HRLs) are land cover maps produced for the entire Italian territory (approximately 30 million hectares) in 2012 by the European Environment Agency, aimed at monitoring soil imperviousness and natural cover, such as forest, grassland, wetland, and water surface, with a high spatial resolution of 20 m. This study presents the methodologies developed for the production, verification, and enhancement of the HRLs in Italy. The innovative approach is mainly based on (a) the use of available reference data for the enhancement process, (b) the reduction of the manual work of operators by using a semi-automatic approach, and (c) the overall increase in the cost-efficiency in relation to the production and updating of land cover maps. The results show the reliability of these methodologies in assessing and enhancing the quality of the HRLs. Finally, an integration of the individual layers, represented by the HRLs, was performed in order to produce a National High-Resolution Land Cover ma
CV32RT: Enabling Fast Interrupt and Context Switching for RISC-V Microcontrollers
Processors using the open RISC-V ISA are finding increasing adoption in the
embedded world. Many embedded use cases have real-time constraints and require
flexible, predictable, and fast reactive handling of incoming events. However,
RISC- V processors are still lagging in this area compared to more mature
proprietary architectures, such as ARM Cortex-M and TriCore, which have been
tuned for years. The default interrupt controller standardized by RISC-V, the
Core Local Interruptor (CLINT), lacks configurability in prioritization and
preemption of interrupts. The RISC-V Core Local Interrupt Controller (CLIC)
specification addresses this concern by enabling pre-emptible, low-latency
vectored interrupts while also envisioning optional extensions to improve
interrupt latency. In this work, we implement a CLIC for the CV32E40P, an
industrially supported open-source 32-bit MCU-class RISC-V core, and enhance it
with fastirq: a custom extension that provides interrupt latency as low as 6
cycles. We call CV32RT our enhanced core. To the best of our knowledge, CV32RT
is the first fully open-source RV32 core with competitive interrupt-handling
features compared to the Arm Cortex-M series and TriCore. The proposed
extensions are also demonstrated to improve task context switching in real-time
operating systems.Comment: 12 pages, submitted to IEEE Transactions on VLSI Systems (TVLSI
To Know or Not To Know: Strategic Inattention and Endogenous Market Structure
We model an industry in which a discrete number of firms choose the output of their differentiated products deciding whether or not to consider the impact of their decisions on aggregate output. We show that two threshold numbers of firms exist such that: below the lower one there is a unique equilibrium in which all firms consider their aggregate impact as in standard oligopoly; above the higher threshold
there is a unique equilibrium in which all firms disregard that impact as in standard monopolistic competition; between the two thresholds there are two equilibria, one in which all firms consider their aggregate impact and the other in which they do not. We then show that our
model of strategic inattention is isomorphic to a model of strategic delegation with managerial compensation based on relative profit performance
Dream jobs
Understanding why certain jobs are ‘better’ than others and what implications they have for a worker’s career is clearly an important but still relatively unexplored question. We provide both a theoretical framework and a number of empirical results that help distinguishing ‘good’ from ‘bad’ jobs in terms of their impact on a worker’s lifetime wage income profile through wage jumps occurring upon changing job (‘static effects’) or through increases in the wage growth rate (‘dynamic effects’). We find that the distinction between internationally active firms and domestic firms is a meaningful empirical dividing line between employers providing ‘good’ and ‘bad’ jobs. First, in internationally active firms the experience-wage profile is much steeper than in domestic firms, especially for managers as opposed to blue-collar workers. Second, the higher lifetime wage income for managers in internationally active firms relies on the stronger accumulation of experience that these firms allow for and on the (almost) perfect portability of the accumulated dynamic wage gains to other firms. Static effects are instead much more important for blue-collar workers. Finally, the distinction between internationally active and domestic firms is relevant also at a more aggregate level to explain cross-sectional differences in wages among workers and spatial differences in average wages across regions within a country.info:eu-repo/semantics/publishedVersio
Well-being Forecasting using a ParametricTransfer-Learning method based on the FisherDivergence and Hamiltonian Monte Carlo
Towards a RISC-V Open Platform for Next-generation Automotive ECUs
The complexity of automotive systems is increasing quickly due to the
integration of novel functionalities such as assisted or autonomous driving.
However, increasing complexity poses considerable challenges to the automotive
supply chain since the continuous addition of new hardware and network cabling
is not considered tenable. The availability of modern heterogeneous
multi-processor chips represents a unique opportunity to reduce vehicle costs
by integrating multiple functionalities into fewer Electronic Control Units
(ECUs). In addition, the recent improvements in open-hardware technology allow
to further reduce costs by avoiding lock-in solutions.
This paper presents a mixed-criticality multi-OS architecture for automotive
ECUs based on open hardware and open-source technologies. Safety-critical
functionalities are executed by an AUTOSAR OS running on a RISC-V processor,
while the Linux OS executes more advanced functionalities on a multi-core ARM
CPU. Besides presenting the implemented stack and the communication
infrastructure, this paper provides a quantitative gap analysis between an
HW/SW optimized version of the RISC-V processor and a COTS Arm Cortex-R in
terms of real-time features, confirming that RISC-V is a valuable candidate for
running AUTOSAR Classic stacks of next-generation automotive MCUs.Comment: 8 pages, 2023 12th Mediterranean Conference on Embedded Computing
(MECO
Well-being Forecasting using a Parametric Transfer-Learning method based on the Fisher Divergence and Hamiltonian Monte Carlo
INTRODUCTION: Traditional personalised modelling typically requires sufficient personal data for training. This is a challenge in healthcare contexts, e.g. when using smartphones to predict well-being.
OBJECTIVE: A method to produce incremental patient-specific models and forecasts even in the early stages of data collection when the data are sporadic and limited.
METHODS: We propose a parametric transfer-learning method based on the Fisher divergence, where information from other patients is injected as a prior term into a Hamiltonian Monte Carlo framework. We test our method on the NEVERMIND dataset of self-reported well-being scores.
RESULTS: Out of 54 scenarios representing varying training/forecasting lengths and competing methods, our method achieved overall best performance in 50 (92.6%) and demonstrated a significant median difference in45 (83.3%).
CONCLUSION: The method performs favourably overall, particularly when long-term forecasts are required given short-term data
Polaronic and Mott insulating phase of layered magnetic vanadium trihalide VCl3
Two-dimensional (2D) van der Waals (vdW) magnetic -transition metal
trihalides are a new class of functional materials showing exotic physical
properties useful for spintronic and memory storage applications. This letter
presents the synthesis and electromagnetic characterization of
single-crystalline vanadium trichloride, VCl, a novel 2D layered vdW Mott
insulator, which has a rhombohedral structure (R, No. 148) at
room temperature. VCl undergoes a structural phase transition at 103 K and
a subsequent antiferromagnetic transition at 21.8 K. Combining core levels and
valence bands X-ray Photoemission Spectroscopy (XPS) with first-principles
Density Functional Theory (DFT) calculations, we demonstrate the Mott Hubbard
insulating nature of VCl and the existence of electron small 2D magnetic
polarons localized on V atom sites by V-Cl bond relaxation. The polarons
strongly affect the electromagnetic properties of VCl promoting the
occupation of dispersion-less spin-polarized V-3d states and band
inversion with states. Within the polaronic scenario, it is
possible to interpret different experimental evidences on vanadium trihalides,
such as VI, highlighting the complex physical behavior determined by
correlation effects, mixed valence states, and magnetic states
A High-performance, Energy-efficient Modular DMA Engine Architecture
Data transfers are essential in today's computing systems as latency and
complex memory access patterns are increasingly challenging to manage. Direct
memory access engines (DMAEs) are critically needed to transfer data
independently of the processing elements, hiding latency and achieving high
throughput even for complex access patterns to high-latency memory. With the
prevalence of heterogeneous systems, DMAEs must operate efficiently in
increasingly diverse environments. This work proposes a modular and highly
configurable open-source DMAE architecture called intelligent DMA (iDMA), split
into three parts that can be composed and customized independently. The
front-end implements the control plane binding to the surrounding system. The
mid-end accelerates complex data transfer patterns such as multi-dimensional
transfers, scattering, or gathering. The back-end interfaces with the on-chip
communication fabric (data plane). We assess the efficiency of iDMA in various
instantiations: In high-performance systems, we achieve speedups of up to 15.8x
with only 1 % additional area compared to a base system without a DMAE. We
achieve an area reduction of 10 % while improving ML inference performance by
23 % in ultra-low-energy edge AI systems over an existing DMAE solution. We
provide area, timing, latency, and performance characterization to guide its
instantiation in various systems.Comment: 14 pages, 14 figures, accepted by an IEEE journal for publicatio
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