Hasil untuk "Semantics"

H. Ehrig, B. Mahr

David R. Dowty, R. Wall, S. Peters

R. Larson, R. Cooper

D. Scott

David Kaplan

R. J. Van Glabbeek, W. Weijland, W. Weijland et al.

C. Tenny

E. Dijkstra, C. S. Scholten

M. Stubbs

Richard Jensen, Q. Shen

C. Goddard, A. Wierzbicka

Karthika Poornachandran, Elakkiya Venkatachalam, Oh-Min Kwon et al.

In this work, we develop a disturbance suppression-oriented fuzzy sliding mode secured sampled-data controller for third-order parabolic partial differential equations that ought to cope with nonlinearities, hybrid cyber attacks, and modeled disturbances. This endeavor is mainly driven by formulating an observer model with a T–S fuzzy mode of execution that retrieves the latent state variables of the perceived system. Progressing onward, the disturbance observers are formulated to estimate the modeled disturbances emerging from the exogenous systems. In due course, the information received from the system and disturbance estimators, coupled with the sliding surface, is compiled to fabricate the developed controller. Furthermore, in the realm of security, hybrid cyber attacks are scrutinized through the use of stochastic variables that abide by the Bernoulli distributed white sequence, which combat their unpredictability. Proceeding further in this framework, a set of linear matrix inequality conditions is established that relies on the Lyapunov stability theory. Precisely, the refined looped Lyapunov–Krasovskii functional paradigm, which reflects in the sampling period that is intricately split into non-uniform intervals by leveraging a fractional-order parameter, is deployed. In line with this pursuit, a strictly <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><msub><mo>Φ</mo><mn>1</mn></msub><mo>,</mo><msub><mo>Φ</mo><mn>2</mn></msub><mo>,</mo><msub><mo>Φ</mo><mn>3</mn></msub><mo>)</mo><mo>−</mo><mi>ϱ</mi></mrow></semantics></math></inline-formula> dissipative framework is crafted with the intent to curb norm-bounded disturbances. A simulation-backed numerical example is unveiled in the closing segment to underscore the potency and efficacy of the developed control design technique.

Munindar P. Singh, M. Huhns

Roberto M. Amadio

The focus of these lecture notes is on abstract models and basic ideas and results that relate to the operational semantics of programming languages largely conceived. The approach is to start with an abstract description of the computation steps of programs and then to build on top semantic equivalences, specification languages, and static analyses. While other approaches to the semantics of programming languages are possible, it appears that the operational one is particularly effective in that it requires a moderate level of mathematical sophistication and scales reasonably well to a large variety of programming features. In practice, operational semantics is a suitable framework to build portable language implementations and to specify and test program properties. It is also used routinely to tackle more ambitious tasks such as proving the correctness of a compiler or a static analyzer.

Shengxi Li, Zifu Zhang, Mai Xu et al.

The emerging semantic compression has been receiving increasing research efforts most recently, capable of achieving high fidelity restoration during compression, even at extremely low bitrates. However, existing semantic compression methods typically combine standard pipelines with either pre-defined or high-dimensional semantics, thus suffering from deficiency in compression. To address this issue, we propose a novel hierarchical semantic compression (HSC) framework that purely operates within intrinsic semantic spaces from generative models, which is able to achieve efficient compression for consistent semantic restoration. More specifically, we first analyse the entropy models for the semantic compression, which motivates us to employ a hierarchical architecture based on a newly developed general inversion encoder. Then, we propose the feature compression network (FCN) and semantic compression network (SCN), such that the middle-level semantic feature and core semantics are hierarchically compressed to restore both accuracy and consistency of image semantics, via an entropy model progressively shared by channel-wise context. Experimental results demonstrate that the proposed HSC framework achieves the state-of-the-art performance on subjective quality and consistency for human vision, together with superior performances on machine vision tasks given compressed bitstreams. This essentially coincides with human visual system in understanding images, thus providing a new framework for future image/video compression paradigms. Our code shall be released upon acceptance.

Şaban Güvenç, Cihan Özgür

We investigate normal magnetic curves in <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><mn>2</mn><mi>n</mi><mo>+</mo><mi>s</mi><mo>)</mo></mrow></semantics></math></inline-formula>-dimensional homothetic <i>s</i>-th Sasakian manifolds as a generalization of <i>S</i>-manifolds. We show that a curve <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>γ</mi></semantics></math></inline-formula> is a normal magnetic curve in a homothetic <i>s</i>-th Sasakian manifold if and only if its osculating order satisfies <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>r</mi><mo>≤</mo><mn>3</mn></mrow></semantics></math></inline-formula> and it belongs to a family of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>θ</mi><mi>i</mi></msub></semantics></math></inline-formula>-slant helices. Additionally, we construct a homothetic <i>s</i>-th Sasakian manifold using generalized <i>D</i>-homothetic transformations and present the parametric equations of normal magnetic curves in this manifold.

Jiada Guan, Huaguo Zhang, Tong Han et al.

High-resolution water depth data are of great significance in island research and coastal ecosystem monitoring. However, the acquisition of high-resolution imagery has been a challenge due to the difficulties and high costs associated with obtaining such data. To address this issue, this study proposes a water depth inversion method based on Gaofen-1 (GF-1) satellite data, which integrates multi-source satellite data to obtain high-resolution bathymetric data. Specifically, the research utilizes bathymetric data derived from Sentinel-2 and Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) as prior information, combined with high-resolution imagery obtained from the GF-1 satellite constellation (GF-1B/C/D). Then, it employs a scale-invariant effect to map bathymetry with a spatial resolution of 2 m, applied to four study areas in the Pacific Islands. The results are further evaluated using ICESat-2 data, which demonstrate that the water depth inversion results from this study possess high accuracy, with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></semantics></math></inline-formula> values exceeding 0.85, root mean square error (RMSE) ranging from 0.56 to 0.90 m, with an average of 0.7125 m, and mean absolute error (MAE) ranging from 0.43 to 0.76 m, with an average of 0.55 m. Additionally, this paper discusses the applicability of the scale-invariant assumption in this research and the improvements of the quadratic polynomial ratio model (QPRM) method compared to the classical linear ratio model (CLRM) method. The findings indicate that the integration of multi-source satellite remote sensing data based on the scale-invariant effect can effectively obtain high-precision, high-resolution bathymetric data, providing significant reference value for the application of GF-1 satellites in high-resolution bathymetry mapping.

Assaf Katz, Shalom Bloch, Eliahu Cohen

Pseudo-entropy is a complex-valued generalization of entanglement entropy defined on non-Hermitian transition operators and induced by post-selection. We present a simulation-based protocol for detecting nonclassicality and coherent errors in quantum circuits using this pseudo-entropy measure <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mover accent="true"><mi>S</mi><mo>ˇ</mo></mover></semantics></math></inline-formula>, focusing on its imaginary part <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>ℑ</mo><mover accent="true"><mi>S</mi><mo>ˇ</mo></mover></mrow></semantics></math></inline-formula> as a diagnostic tool. Our method enables resource-efficient classification of phase-coherent errors, such as those from miscalibrated CNOT gates, even under realistic noise conditions. By quantifying the transition between classical-like and quantum-like behavior through threshold analysis, we provide theoretical benchmarks for error classification that can inform hardware calibration strategies. Numerical simulations demonstrate that 55% of the parameter space remains classified as classical-like (below classification thresholds) at hardware-calibrated sensitivity levels, with statistical significance confirmed through rigorous sensitivity analysis. Robustness to noise and comparison with standard entropy-based methods are demonstrated in a simulation. While hardware validation remains necessary, this work bridges theoretical concepts of nonclassicality with practical quantum error classification frameworks, providing a foundation for experimental quantum computing applications.

Giacomo Giannetti, Marco Badii, Giovanni Lasagni et al.

This work presents an Internet of Things (IoT) node designed for low-power agrifood chain tracking in remote areas, where long-range terrestrial communication is either unavailable or severely limited. The novelty of this study lies in the development and characterization of an IoT node prototype that leverages direct-to-satellite connectivity through a geostationary Earth orbit (GEO) satellite, using long-range frequency-hopping spread spectrum (LR-FHSS) modulation in the licensed S-band. The prototype integrates a microcontroller unit that manages both the radio modem and a suite of sensors, enclosed in a plastic box suitable for field deployment. Characterization in an anechoic chamber demonstrated a maximum effective isotropic radiated power (EIRP) of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>27.5</mn></mrow></semantics></math></inline-formula> dBm, sufficient to establish a reliable satellite link. The onboard sensors provide global positioning as well as measurements of acceleration, temperature, humidity, and solar radiation intensity. Prototype performance was assessed in two representative scenarios: stationary and mobile. Regarding energy consumption, the average charge drained by the radio modem per transmission cycle was measured to be 356 mC. With a battery pack composed of four 2500 mAh NiMH cells, the estimated upper bound on the number of transmitted packets is approximately 25,000.

R. Akkiraju, J. Farrell, John A. Miller et al.