Entropy最新文献

{"title":"Shannon Entropy Computations in Navier-Stokes Flow Problems Using the Stochastic Finite Volume Method.","authors":"Marcin Kamiński, Rafał Leszek Ossowski","doi":"10.3390/e27010067","DOIUrl":"10.3390/e27010067","url":null,"abstract":"<p><p>The main aim of this study is to achieve the numerical solution for the Navier-Stokes equations for incompressible, non-turbulent, and subsonic fluid flows with some Gaussian physical uncertainties. The higher-order stochastic finite volume method (SFVM), implemented according to the iterative generalized stochastic perturbation technique and the Monte Carlo scheme, are engaged for this purpose. It is implemented with the aid of the polynomial bases for the pressure-velocity-temperature (PVT) solutions, for which the weighted least squares method (WLSM) algorithm is applicable. The deterministic problem is solved using the freeware OpenFVM, the computer algebra software MAPLE 2019 is employed for the LSM local fittings, and the resulting probabilistic quantities are computed. The first two probabilistic moments, as well as the Shannon entropy spatial distributions, are determined with this apparatus and visualized in the FEPlot software. This approach is validated using the 2D heat conduction benchmark test and then applied for the probabilistic version of the 3D coupled lid-driven cavity flow analysis. Such an implementation of the SFVM is applied to model the 2D lid-driven cavity flow problem for statistically homogeneous fluid with limited uncertainty in its viscosity and heat conductivity. Further numerical extension of this technique is seen in an application of the artificial neural networks, where polynomial approximation may be replaced automatically by some optimal, and not necessarily polynomial, bases.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11765385/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simulation of Flow Around a Finite Rectangular Prism: Influence of Mesh, Model, and Subgrid Length Scale.","authors":"Xutong Zhang, Maxime Savoie, Mark K Quinn, Ben Parslew, Alistair Revell","doi":"10.3390/e27010065","DOIUrl":"10.3390/e27010065","url":null,"abstract":"<p><p>This study investigates the flow field around a finite rectangular prism using both experimental and computational methods, with a particular focus on the influence of the turbulence approach adopted, the mesh resolution employed, and different subgrid length scales. Ten turbulence modelling and simulation approaches, including both 'scale-modelling' Reynolds-Averaged Navier-Stokes (RANS) models and 'scale-resolving' Delayed Detached Eddy Simulation (DDES), were tested across six different mesh resolutions. A case with sharp corners allows the location of the flow separation to be fixed, which facilitates a focus on the separated flow region and, in this instance, the three-dimensional interaction of three such regions. The case, therefore, readily enables an assessment of the 'grey-area' issue, whereby some DDES methods demonstrate delayed activation of the scale-resolving model, impacting the size of flow recirculation. Experimental measurements were shown to agree well with reference data for the same geometry, after which particle image velocimetry (PIV) data were gathered to extend the reference dataset. Numerical predictions from the RANS models were generally quite reasonable but did not show improvement with further refinement, as one would expect, whereas DDES clearly demonstrated continuous improvement in predictive accuracy with progressive mesh refinement. The shear-layer-adapted (SLA) subgrid length scale (ΔSLA) displayed consistently superior performance compared to the more widely used length scale based on local cell volume, particularly for moderate mesh resolutions commonly employed in industrial settings with limited resources. In general, front-body separation and reattachment exhibited greater sensitivity to mesh refinement than wake resolution. Finally, in order to correlate the observed DDES mesh requirements with the observations from the converged RANS solutions, an approximation for the Taylor microscale was explored as a potential tool for mesh sizing.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11764473/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Introducing ActiveInference.jl: A Julia Library for Simulation and Parameter Estimation with Active Inference Models.","authors":"Samuel William Nehrer, Jonathan Ehrenreich Laursen, Conor Heins, Karl Friston, Christoph Mathys, Peter Thestrup Waade","doi":"10.3390/e27010062","DOIUrl":"10.3390/e27010062","url":null,"abstract":"<p><p>We introduce a new software package for the Julia programming language, the library ActiveInference.jl. To make active inference agents with Partially Observable Markov Decision Process (POMDP) generative models available to the growing research community using Julia, we re-implemented the pymdp library for Python. ActiveInference.jl is compatible with cutting-edge Julia libraries designed for cognitive and behavioural modelling, as it is used in computational psychiatry, cognitive science and neuroscience. This means that POMDP active inference models can now be easily fit to empirically observed behaviour using sampling, as well as variational methods. In this article, we show how ActiveInference.jl makes building POMDP active inference models straightforward, and how it enables researchers to use them for simulation, as well as fitting them to data or performing a model comparison.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11765463/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quadratic Forms in Random Matrices with Applications in Spectrum Sensing.","authors":"Daniel Gaetano Riviello, Giusi Alfano, Roberto Garello","doi":"10.3390/e27010063","DOIUrl":"10.3390/e27010063","url":null,"abstract":"<p><p>Quadratic forms with random kernel matrices are ubiquitous in applications of multivariate statistics, ranging from signal processing to time series analysis, biomedical systems design, wireless communications performance analysis, and other fields. Their statistical characterization is crucial to both design guideline formulation and efficient computation of performance indices. To this end, random matrix theory can be successfully exploited. In particular, recent advancements in spectral characterization of finite-dimensional random matrices from the so-called <i>polynomial ensembles</i> allow for the analysis of several scenarios of interest in wireless communications and signal processing. In this work, we focus on the characterization of quadratic forms in unit-norm vectors, with unitarily invariant random kernel matrices, and we also provide some approximate but numerically accurate results concerning a non-unitarily invariant kernel matrix. Simulations are run with reference to a peculiar application scenario, the so-called spectrum sensing for wireless communications. Closed-form expressions for the moment generating function of the quadratic forms of interest are provided; this will pave the way to an analytical performance analysis of some spectrum sensing schemes, and will potentially assist in the rate analysis of some multi-antenna systems.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11764828/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wealth Distribution Involving Psychological Traits and Non-Maxwellian Collision Kernel.","authors":"Daixin Wang, Shaoyong Lai","doi":"10.3390/e27010064","DOIUrl":"10.3390/e27010064","url":null,"abstract":"<p><p>A kinetic exchange model is developed to investigate wealth distribution in a market. The model incorporates a value function that captures the agents' psychological traits, governing their wealth allocation based on behavioral responses to perceived potential losses and returns. To account for the impact of transaction frequency on wealth dynamics, a non-Maxwellian collision kernel is introduced. Applying quasi-invariant limits and Boltzmann-type equations, a Fokker-Planck equation is derived. We obtain an entropy explicit stationary solution that exhibits exponential convergence to a lognormal wealth distribution. Numerical experiments support the theoretical insights and highlight the model's significance in understanding wealth distribution.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11765462/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Efficient Retinal Fluid Segmentation Network Based on Large Receptive Field Context Capture for Optical Coherence Tomography Images.","authors":"Hang Qi, Weijiang Wang, Hua Dang, Yueyang Chen, Minli Jia, Xiaohua Wang","doi":"10.3390/e27010060","DOIUrl":"10.3390/e27010060","url":null,"abstract":"<p><p>Optical Coherence Tomography (OCT) is a crucial imaging modality for diagnosing and monitoring retinal diseases. However, the accurate segmentation of fluid regions and lesions remains challenging due to noise, low contrast, and blurred edges in OCT images. Although feature modeling with wide or global receptive fields offers a feasible solution, it typically leads to significant computational overhead. To address these challenges, we propose LKMU-Lite, a lightweight U-shaped segmentation method tailored for retinal fluid segmentation. LKMU-Lite integrates a Decoupled Large Kernel Attention (DLKA) module that captures both local patterns and long-range dependencies, thereby enhancing feature representation. Additionally, it incorporates a Multi-scale Group Perception (MSGP) module that employs Dilated Convolutions with varying receptive field scales to effectively predict lesions of different shapes and sizes. Furthermore, a novel Aggregating-Shift decoder is proposed, reducing model complexity while preserving feature integrity. With only 1.02 million parameters and a computational complexity of 3.82 G FLOPs, LKMU-Lite achieves state-of-the-art performance across multiple metrics on the ICF and RETOUCH datasets, demonstrating both its efficiency and generalizability compared to existing methods.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11764744/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transient Voltage Information Entropy Difference Unit Protection Based on Fault Condition Attribute Fusion.","authors":"Zhenwei Guo, Ruiqiang Zhao, Zebo Huang, Yongyan Jiang, Haojie Li, Yingcai Deng","doi":"10.3390/e27010061","DOIUrl":"10.3390/e27010061","url":null,"abstract":"<p><p>Transient protection has the advantage of ultra-high-speed action, but traditional transient protection is susceptible to the influence of two fault condition attributes, namely, transition resistance and initial angle of fault, and there are the problems of insufficient sensitivity and insufficient reliability under weak faults. To this end, the propagation characteristics of high-frequency components of transient voltage in bus and line systems are explored, and a new method of unit protection based on the entropy difference in transient voltage information is proposed. In order to solve the problem of single-ended transient protection not being able to reliably distinguish line faults from bus faults and adjacent line first-end faults, the difference between the entropy of line voltage and the entropy of bus voltage was introduced as a fault characteristic. Aimed at the susceptibility of transient protection to the influence of fault condition attributes, composite fault characteristics containing fault attribute information were obtained by integrating fault characteristics with fault condition attributes to overcome the adverse influence of fault condition attributes on transient protection and improve the reliability of the protection. The algorithm solved 38.9% of the original cross-data, 36.1% of the false actions, and 6.1% of the rejected actions. Finally, the accuracy and reliability of the proposed algorithm were verified by extensive ATP-Draw simulation tests.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11764891/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Group-Algebraic Formalism of Quantum Probability and Its Applications in Quantum Statistical Mechanics.","authors":"Yan Gu, Jiao Wang","doi":"10.3390/e27010059","DOIUrl":"10.3390/e27010059","url":null,"abstract":"<p><p>We show that the theory of quantum statistical mechanics is a special model in the framework of the quantum probability theory developed by mathematicians, by extending the characteristic function in the classical probability theory to the quantum probability theory. As dynamical variables of a quantum system must respect certain commutation relations, we take the group generated by a Lie algebra constructed with these commutation relations as the bridge, so that the classical characteristic function defined in a Euclidean space is transformed to a normalized, non-negative definite function defined in this group. Indeed, on the quantum side, this group-theoretical characteristic function is equivalent to the density matrix; hence, it can be adopted to represent the state of a quantum ensemble. It is also found that this new representation may have significant advantages in applications. As two examples, we show its effectiveness and convenience in solving the quantum-optical master equation for a harmonic oscillator coupled with its thermal environment, and in simulating the quantum cat map, a paradigmatic model for quantum chaos. Other related issues are reviewed and discussed as well.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11764469/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Invariant Representation Learning in Multimedia Recommendation with Modality Alignment and Model Fusion.","authors":"Xinghang Hu, Haiteng Zhang","doi":"10.3390/e27010056","DOIUrl":"10.3390/e27010056","url":null,"abstract":"<p><p>Multimedia recommendation systems aim to accurately predict user preferences from multimodal data. However, existing methods may learn a recommendation model from spurious features, i.e., appearing to be related to an outcome but actually having no causal relationship with the outcome, leading to poor generalization ability. While previous approaches have adopted invariant learning to address this issue, they simply concatenate multimodal data without proper alignment, resulting in information loss or redundancy. To overcome these challenges, we propose a framework called M³-InvRL, designed to enhance recommendation system performance through common and modality-specific representation learning, invariant learning, and model merging. Specifically, our approach begins by learning modality-specific representations along with a common representation for each modality. To achieve this, we introduce a novel contrastive loss that aligns representations and imposes mutual information constraints to extract modality-specific features, thereby preventing generalization issues within the same representation space. Next, we generate invariant masks based on the identification of heterogeneous environments to learn invariant representations. Finally, we integrate both invariant-specific and shared invariant representations for each modality to train models and fuse them in the output space, reducing uncertainty and enhancing generalization performance. Experiments on real-world datasets demonstrate the effectiveness of our approach.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11764824/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unified Analysis of Viscoelasticity and Viscoplasticity Using the Onsager Variational Principle.","authors":"Kwang Soo Cho","doi":"10.3390/e27010055","DOIUrl":"10.3390/e27010055","url":null,"abstract":"<p><p>This study is the application of the Onsager variational principle to viscoelasticity and viscoplasticity with the minimization of the assumptions which are popularly used in conventional approaches. The conventional approaches assume Kröner-Lee decomposition, incompressible plastic deformation, flowing rule, stress equation and so on. These assumptions have been accumulated by many researchers for a long time and have shown many successful cases. The large number of successful assumptions leads to the conjecture that the mechanics can be described with a smaller number of assumptions. This paper shows that this conjecture is correct by using the Onsager variational principle.</p>","PeriodicalId":11694,"journal":{"name":"Entropy","volume":"27 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11764575/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143032659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}