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Hybrid Classical–Quantum Branch-and-Bound Algorithm for Solving Integer Linear Problems Entropy (IF 2.7) Pub Date : 2024-04-19 Claudio Sanavio, Edoardo Tignone, Elisa Ercolessi
Quantum annealers are suited to solve several logistic optimization problems expressed in the QUBO formulation. However, the solutions proposed by the quantum annealers are generally not optimal, as thermal noise and other disturbing effects arise when the number of qubits involved in the calculation is too large. In order to deal with this issue, we propose the use of the classical branch-and-bound
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Evaluating the Gilbert–Varshamov Bound for Constrained Systems Entropy (IF 2.7) Pub Date : 2024-04-19 Keshav Goyal, Han Mao Kiah
We revisit the well-known Gilbert–Varshamov (GV) bound for constrained systems. In 1991, Kolesnik and Krachkovsky showed that the GV bound can be determined via the solution of an optimization problem. Later, in 1992, Marcus and Roth modified the optimization problem and improved the GV bound in many instances. In this work, we provide explicit numerical procedures to solve these two optimization problems
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Simulation of Natural Convection with Sinusoidal Temperature Distribution of Heat Source at the Bottom of an Enclosed Square Cavity Entropy (IF 2.7) Pub Date : 2024-04-19 Min Zeng, Zhiqiang Wang, Ying Xu, Qiang Ma
The lattice Boltzmann method is employed in the current study to simulate the heat transfer characteristics of sinusoidal-temperature-distributed heat sources at the bottom of a square cavity under various conditions, including different amplitudes, phase angles, initial positions, and angular velocities. Additionally, a machine learning-based model is developed to accurately predict the Nusselt number
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Time-Varying GPS Displacement Network Modeling by Sequential Monte Carlo Entropy (IF 2.7) Pub Date : 2024-04-18 Suchanun Piriyasatit, Ercan Engin Kuruoglu, Mehmet Sinan Ozeren
Geodetic observations through high-rate GPS time-series data allow the precise modeling of slow ground deformation at the millimeter level. However, significant attention has been devoted to utilizing these data for various earth science applications, including to determine crustal velocity fields and to detect significant displacement from earthquakes. The relationships inherent in these GPS displacement
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Friston, Free Energy, and Psychoanalytic Psychotherapy Entropy (IF 2.7) Pub Date : 2024-04-18 Jeremy Holmes
This paper outlines the ways in which Karl Friston’s work illuminates the everyday practice of psychotherapists. These include (a) how the strategic ambiguity of the therapist’s stance brings, via ‘transference’, clients’ priors to light; (b) how the unstructured and negative capability of the therapy session reduces the salience of priors, enabling new top-down models to be forged; (c) how fostering
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Multilingual Hate Speech Detection: A Semi-Supervised Generative Adversarial Approach Entropy (IF 2.7) Pub Date : 2024-04-18 Khouloud Mnassri, Reza Farahbakhsh, Noel Crespi
Social media platforms have surpassed cultural and linguistic boundaries, thus enabling online communication worldwide. However, the expanded use of various languages has intensified the challenge of online detection of hate speech content. Despite the release of multiple Natural Language Processing (NLP) solutions implementing cutting-edge machine learning techniques, the scarcity of data, especially
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On the Supposed Mass of Entropy and That of Information Entropy (IF 2.7) Pub Date : 2024-04-15 Didier Lairez
In the theory of special relativity, energy can be found in two forms: kinetic energy and rest mass. The potential energy of a body is actually stored in the form of rest mass, the interaction energy too, but temperature is not. Information acquired about a dynamical system can be potentially used to extract useful work from it. Hence, the “mass–energy–information equivalence principle” that has been
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Irradiation-Hardening Model of TiZrHfNbMo0.1 Refractory High-Entropy Alloys Entropy (IF 2.7) Pub Date : 2024-04-17 Yujun Fan, Xuejiao Wang, Yangyang Li, Aidong Lan, Junwei Qiao
In order to find more excellent structural materials resistant to radiation damage, high-entropy alloys (HEAs) have been developed due to their characteristics of limited point defect diffusion such as lattice distortion and slow diffusion. Specially, refractory high-entropy alloys (RHEAs) that can adapt to a high-temperature environment are badly needed. In this study, TiZrHfNbMo0.1 RHEAs are selected
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Distinction of Chaos from Randomness Is Not Possible from the Degree Distribution of the Visibility and Phase Space Reconstruction Graphs Entropy (IF 2.7) Pub Date : 2024-04-17 Alexandros K. Angelidis, Konstantinos Goulas, Charalampos Bratsas, Georgios C. Makris, Michael P. Hanias, Stavros G. Stavrinides, Ioannis E. Antoniou
We investigate whether it is possible to distinguish chaotic time series from random time series using network theory. In this perspective, we selected four methods to generate graphs from time series: the natural, the horizontal, the limited penetrable horizontal visibility graph, and the phase space reconstruction method. These methods claim that the distinction of chaos from randomness is possible
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Side Information Design in Zero-Error Coding for Computing Entropy (IF 2.7) Pub Date : 2024-04-16 Nicolas Charpenay, Maël Le Treust, Aline Roumy
We investigate the zero-error coding for computing problems with encoder side information. An encoder provides access to a source X and is furnished with side information g(Y). It communicates with a decoder that possesses side information Y and aims to retrieve f(X,Y) with zero probability of error, where f and g are assumed to be deterministic functions. In previous work, we determined a condition
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Advances in Adjoint Functions of Connection Number in Water Resources Complex Systems: A Systematic Review Entropy (IF 2.7) Pub Date : 2024-04-16 Liangguang Zhou, Juliang Jin, Rongxing Zhou, Yi Cui, Chengguo Wu, Yuliang Zhou, Shibao Dai, Yuliang Zhang
The adjoint function of connection number has unique advantages in solving uncertainty problems of water resource complex systems, and has become an important frontier and research hotspot in the uncertainty research of water resource complex problems. However, in the rapid evolution of the adjoint function, some problems greatly limit the application of the adjoint function in the research of water
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Dynamical Tunneling in More than Two Degrees of Freedom Entropy (IF 2.7) Pub Date : 2024-04-14 Srihari Keshavamurthy
Recent progress towards understanding the mechanism of dynamical tunneling in Hamiltonian systems with three or more degrees of freedom (DoF) is reviewed. In contrast to systems with two degrees of freedom, the three or more degrees of freedom case presents several challenges. Specifically, in higher-dimensional phase spaces, multiple mechanisms for classical transport have significant implications
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CAC: Confidence-Aware Co-Training for Weakly Supervised Crack Segmentation Entropy (IF 2.7) Pub Date : 2024-04-12 Fengjiao Liang, Qingyong Li, Xiaobao Li, Yang Liu, Wen Wang
Automatic crack segmentation plays an essential role in maintaining the structural health of buildings and infrastructure. Despite the success in fully supervised crack segmentation, the costly pixel-level annotation restricts its application, leading to increased exploration in weakly supervised crack segmentation (WSCS). However, WSCS methods inevitably bring in noisy pseudo-labels, which results
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Multi-Time-Scale Optimal Scheduling Strategy for Marine Renewable Energy Based on Deep Reinforcement Learning Algorithm Entropy (IF 2.7) Pub Date : 2024-04-14 Ren Xu, Fei Lin, Wenyi Shao, Haoran Wang, Fanping Meng, Jun Li
Surrounded by the Shandong Peninsula, the Bohai Sea and Yellow Sea possess vast marine energy resources. An analysis of actual meteorological data from these regions indicates significant seasonality and intra-day uncertainty in wind and photovoltaic power generation. The challenge of scheduling to leverage the complementary characteristics of various renewable energy sources for maintaining grid stability
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Benefits of Zero-Phase or Linear Phase Filters to Design Multiscale Entropy: Theory and Application Entropy (IF 2.7) Pub Date : 2024-04-14 Eric Grivel, Bastien Berthelot, Gaetan Colin, Pierrick Legrand, Vincent Ibanez
In various applications, multiscale entropy (MSE) is often used as a feature to characterize the complexity of the signals in order to classify them. It consists of estimating the sample entropies (SEs) of the signal under study and its coarse-grained (CG) versions, where the CG process amounts to (1) filtering the signal with an average filter whose order is the scale and (2)decimating the filter
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Improvement of Z-Weighted Function Based on Fifth-Order Nonlinear Multi-Order Weighted Method for Shock Capturing of Hyperbolic Conservation Laws Entropy (IF 2.7) Pub Date : 2024-04-14 Jinwei Bai, Zhenguo Yan, Meiliang Mao, Yankai Ma, Dingwu Jiang
Based on a 5-point stencil and three 3-point stencils, a nonlinear multi-order weighted method adaptive to 5-3-3-3 stencils for shock capturing is presented in this paper. The form of the weighting function is the same as JS (Jiang–Shu) weighting; however, the smoothness indicator of the 5-point stencil adopts a special design with a higher-order leading term similar to the τ in Z weighting. The design
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Bayesian Non-Parametric Inference for Multivariate Peaks-over-Threshold Models Entropy (IF 2.7) Pub Date : 2024-04-14 Peter Trubey, Bruno Sansó
We consider a constructive definition of the multivariate Pareto that factorizes the random vector into a radial component and an independent angular component. The former follows a univariate Pareto distribution, and the latter is defined on the surface of the positive orthant of the infinity norm unit hypercube. We propose a method for inferring the distribution of the angular component by identifying
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Dwell Times, Wavepacket Dynamics, and Quantum Trajectories for Particles with Spin 1/2 Entropy (IF 2.7) Pub Date : 2024-04-14 Bill Poirier, Richard Lombardini
The theoretical connections between quantum trajectories and quantum dwell times, previously explored in the context of 1D time-independent stationary scattering applications, are here generalized for multidimensional time-dependent wavepacket applications for particles with spin 1/2. In addition to dwell times, trajectory-based dwell time distributions are also developed, and compared with previous
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Harnessing Information Thermodynamics: Conversion of DNA Information into Mechanical Work in RNA Transcription and Nanopore Sequencing Entropy (IF 2.7) Pub Date : 2024-04-11 Tatsuaki Tsuruyama
Recent advancements in information thermodynamics have revealed that information can be directly converted into mechanical work. Specifically, RNA transcription and nanopore sequencing serve as prime examples of this conversion, by reading information from a DNA template. This paper introduces an information thermodynamic model in which these molecular motors can move along the DNA template by converting
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Corrections to the Bekenstein–Hawking Entropy of the HNUTKN Black Hole Due to Lorentz-Breaking Fermionic Einstein–Aether Theory Entropy (IF 2.7) Pub Date : 2024-04-11 Xia Tan, Cong Wang, Shu-Zheng Yang
A hot NUT–Kerr–Newman black hole is a general stationary axisymmetric black hole. In this black hole spacetime, the dynamical equations of fermions at the horizon are modified by considering Lorentz breaking. The corrections to the Hawking temperature and Bekenstein–Hawking entropy at the horizon of the black hole are studied in depth. Based on the semiclassical theory correction, the Bekenstein–Hawking
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Unveiling Human Values: Analyzing Emotions behind Arguments Entropy (IF 2.7) Pub Date : 2024-04-12 Amir Reza Jafari, Praboda Rajapaksha, Reza Farahbakhsh, Guanlin Li, Noel Crespi
Detecting the underlying human values within arguments is essential across various domains, ranging from social sciences to recent computational approaches. Identifying these values remains a significant challenge due to their vast numbers and implicit usage in discourse. This study explores the potential of emotion analysis as a key feature in improving the detection of human values and information
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Functional Formulation of Quantum Theory of a Scalar Field in a Metric with Lorentzian and Euclidean Signatures Entropy (IF 2.7) Pub Date : 2024-04-12 Zbigniew Haba
We study the Schrödinger equation in quantum field theory (QFT) in its functional formulation. In this approach, quantum correlation functions can be expressed as classical expectation values over (complex) stochastic processes. We obtain a stochastic representation of the Schrödinger time evolution on Wentzel–Kramers–Brillouin (WKB) states by means of the Wiener integral. We discuss QFT in a flat
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Major Role of Multiscale Entropy Evolution in Complex Systems and Data Science Entropy (IF 2.7) Pub Date : 2024-04-12 Shahid Nawaz, Muhammad Saleem, Fedor V. Kusmartsev, Dalaver H. Anjum
Complex systems are prevalent in various disciplines encompassing the natural and social sciences, such as physics, biology, economics, and sociology. Leveraging data science techniques, particularly those rooted in artificial intelligence and machine learning, offers a promising avenue for comprehending the intricacies of complex systems without necessitating detailed knowledge of underlying dynamics
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Enhancing Zero-Shot Stance Detection with Contrastive and Prompt Learning Entropy (IF 2.7) Pub Date : 2024-04-11 Zhenyin Yao, Wenzhong Yang, Fuyuan Wei
In social networks, the occurrence of unexpected events rapidly catalyzes the widespread dissemination and further evolution of network public opinion. The advent of zero-shot stance detection aligns more closely with the characteristics of stance detection in today’s digital age, where the absence of training examples for specific models poses significant challenges. This task necessitates models
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Characterizing Microheterogeneity in Liquid Mixtures via Local Density Fluctuations Entropy (IF 2.7) Pub Date : 2024-04-09 Michael Lass, Tobias Kenter, Christian Plessl, Martin Brehm
We present a novel approach to characterize and quantify microheterogeneity and microphase separation in computer simulations of complex liquid mixtures. Our post-processing method is based on local density fluctuations of the different constituents in sampling spheres of varying size. It can be easily applied to both molecular dynamics (MD) and Monte Carlo (MC) simulations, including periodic boundary
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MinimumInformation Variability in Linear Langevin Systems via Model Predictive Control Entropy (IF 2.7) Pub Date : 2024-04-10 Adrian-Josue Guel-Cortez, Eun-jin Kim, Mohamed W. Mehrez
Controlling the time evolution of a probability distribution that describes the dynamics of a given complex system is a challenging problem. Achieving success in this endeavour will benefit multiple practical scenarios, e.g., controlling mesoscopic systems. Here, we propose a control approach blending the model predictive control technique with insights from information geometry theory. Focusing on
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Lossless and Near-Lossless Compression Algorithms for Remotely Sensed Hyperspectral Images Entropy (IF 2.7) Pub Date : 2024-04-05 Amal Altamimi, Belgacem Ben Youssef
Rapid and continuous advancements in remote sensing technology have resulted in finer resolutions and higher acquisition rates of hyperspectral images (HSIs). These developments have triggered a need for new processing techniques brought about by the confined power and constrained hardware resources aboard satellites. This article proposes two novel lossless and near-lossless compression methods, employing
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Some Constructions and Mathematical Properties of Zero-Correlation-Zone Sonar Sequences Entropy (IF 2.7) Pub Date : 2024-04-05 Xiaoxiang Jin, Gangsan Kim, Sangwon Chae, Hong-Yeop Song
In this paper, we propose the zero-correlation-zone (ZCZ) of radius r on two-dimensional m×n sonar sequences and define the (m,n,r) ZCZ sonar sequences. We also define some new optimality of an (m,n,r) ZCZ sonar sequence which has the largest r for given m and n. Because of the ZCZ for perfect autocorrelation, we are able to relax the distinct difference property of the conventional sonar sequences
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Research on a Critical Link Discovery Method for Network Security Situational Awareness Entropy (IF 2.7) Pub Date : 2024-04-04 Guozheng Yang, Yongheng Zhang, Yuliang Lu, Yi Xie, Jiayi Yu
Network security situational awareness (NSSA) aims to capture, understand, and display security elements in large-scale network environments in order to predict security trends in the relevant network environment. With the internet’s increasingly large scale, increasingly complex structure, and gradual diversification of components, the traditional single-layer network topology model can no longer
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Distinguishing the Leading Agents in Classification Problems Using the Entropy-Based Metric Entropy (IF 2.7) Pub Date : 2024-04-05 Evgeny Kagan, Irad Ben-Gal
The paper addresses the problem of distinguishing the leading agents in the group. The problem is considered in the framework of classification problems, where the agents in the group select the items with respect to certain properties. The suggested method of distinguishing the leading agents utilizes the connectivity between the agents and the Rokhlin distance between the subgroups of the agents
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A Color- and Geometric-Feature-Based Approach for Denoising Three-Dimensional Cultural Relic Point Clouds Entropy (IF 2.7) Pub Date : 2024-04-05 Hongjuan Gao, Hui Wang, Shijie Zhao
In the acquisition process of 3D cultural relics, it is common to encounter noise. To facilitate the generation of high-quality 3D models, we propose an approach based on graph signal processing that combines color and geometric features to denoise the point cloud. We divide the 3D point cloud into patches based on self-similarity theory and create an appropriate underlying graph with a Markov property
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Multi-Modal Latent Diffusion Entropy (IF 2.7) Pub Date : 2024-04-05 Mustapha Bounoua, Giulio Franzese, Pietro Michiardi
Multimodal datasets are ubiquitous in modern applications, and multimodal Variational Autoencoders are a popular family of models that aim to learn a joint representation of different modalities. However, existing approaches suffer from a coherence–quality tradeoff in which models with good generation quality lack generative coherence across modalities and vice versa. In this paper, we discuss the
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Research on a Framework for Chinese Argot Recognition and Interpretation by Integrating Improved MECT Models Entropy (IF 2.7) Pub Date : 2024-04-06 Mingfeng Li, Xin Li, Mianning Hu, Deyu Yuan
In underground industries, practitioners frequently employ argots to communicate discreetly and evade surveillance by investigative agencies. Proposing an innovative approach using word vectors and large language models, we aim to decipher and understand the myriad of argots in these industries, providing crucial technical support for law enforcement to detect and combat illicit activities. Specifically
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Adaptive Space-Aware Infotaxis II as a Strategy for Odor Source Localization Entropy (IF 2.7) Pub Date : 2024-03-29 Shiqi Liu, Yan Zhang, Shurui Fan
Mobile robot olfaction of toxic and hazardous odor sources is of great significance in anti-terrorism, disaster prevention, and control scenarios. Aiming at the problems of low search efficiency and easily falling into a local optimum of the current odor source localization strategies, the paper proposes the adaptive space-aware Infotaxis II algorithm. To improve the tracking efficiency of robots,
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Consistent Treatment of Quantum Systems with a Time-Dependent Hilbert Space Entropy (IF 2.7) Pub Date : 2024-04-03 Ali Mostafazadeh
We consider some basic problems associated with quantum mechanics of systems having a time-dependent Hilbert space. We provide a consistent treatment of these systems and address the possibility of describing them in terms of a time-independent Hilbert space. We show that in general the Hamiltonian operator does not represent an observable of the system even if it is a self-adjoint operator. This is
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pRR30, pRR3.25% and Asymmetrical Entropy Descriptors in Atrial Fibrillation Detection Entropy (IF 2.7) Pub Date : 2024-03-28 Bartosz Biczuk, Szymon Buś, Sebastian Żurek, Jarosław Piskorski, Przemysław Guzik
Background: Early detection of atrial fibrillation (AF) is essential to prevent stroke and other cardiac and embolic complications. We compared the diagnostic properties for AF detection of the percentage of successive RR interval differences greater than or equal to 30 ms or 3.25% of the previous RR interval (pRR30 and pRR3.25%, respectively), and asymmetric entropy descriptors of RR intervals. Previously
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Shared Protentions in Multi-Agent Active Inference Entropy (IF 2.7) Pub Date : 2024-03-29 Mahault Albarracin, Riddhi J. Pitliya, Toby St. Clere Smithe, Daniel Ari Friedman, Karl Friston, Maxwell J. D. Ramstead
In this paper, we unite concepts from Husserlian phenomenology, the active inference framework in theoretical biology, and category theory in mathematics to develop a comprehensive framework for understanding social action premised on shared goals. We begin with an overview of Husserlian phenomenology, focusing on aspects of inner time-consciousness, namely, retention, primal impression, and protention
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Some Theoretical Foundations of Bare-Simulation Optimization of Some Directed Distances between Fuzzy Sets Respective Basic Belief Assignments Entropy (IF 2.7) Pub Date : 2024-04-01 Michel Broniatowski, Wolfgang Stummer
It is well known that in information theory—as well as in the adjacent fields of statistics, machine learning and artificial intelligence—it is essential to quantify the dissimilarity between objects of uncertain/imprecise/inexact/vague information; correspondingly, constrained optimization is of great importance, too. In view of this, we define the dissimilarity-measure-natured generalized φ–divergences
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Efficient Implementation of Discrete-Time Quantum Walks on Quantum Computers Entropy (IF 2.7) Pub Date : 2024-04-02 Luca Razzoli, Gabriele Cenedese, Maria Bondani, Giuliano Benenti
Quantum walks have proven to be a universal model for quantum computation and to provide speed-up in certain quantum algorithms. The discrete-time quantum walk (DTQW) model, among others, is one of the most suitable candidates for circuit implementation due to its discrete nature. Current implementations, however, are usually characterized by quantum circuits of large size and depth, which leads to
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PIS-Net: Efficient Medical Image Segmentation Network with Multivariate Downsampling for Point-of-Care Entropy (IF 2.7) Pub Date : 2024-03-26 Changrui Zhang, Jia Wang
Recently, with more portable diagnostic devices being moved to people anywhere, point-of-care (PoC) imaging has become more convenient and more popular than the traditional “bed imaging”. Instant image segmentation, as an important technology of computer vision, is receiving more and more attention in PoC diagnosis. However, the image distortion caused by image preprocessing and the low resolution
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Revisiting the Surface Brightness Profile of the Stellar Disk with the Statistical Mechanics of the Self-Gravitating System with the Central Body Entropy (IF 2.7) Pub Date : 2024-03-28 Dong-Biao Kang
We have explored the exponential surface brightness profile (SBP) of stellar disks, a topic extensively discussed by many authors yet seldom integrated with the study of correlations between black holes, bulges, and entire disks. Building upon our prior work in the statistical mechanics of disk-shaped systems and aligning with methodologies from other research, we analyze the influence of the central
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Chaos in Opinion-Driven Disease Dynamics Entropy (IF 2.7) Pub Date : 2024-03-28 Thomas Götz, Tyll Krüger, Karol Niedzielewski, Radomir Pestow, Moritz Schäfer, Jan Schneider
During the COVID-19 pandemic, it became evident that the effectiveness of applying intervention measures is significantly influenced by societal acceptance, which, in turn, is affected by the processes of opinion formation. This article explores one among the many possibilities of coupled opinion–epidemic systems. The findings reveal either intricate periodic patterns or chaotic dynamics, leading to
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Entropy-Based Methods for Motor Fault Detection: A Review Entropy (IF 2.7) Pub Date : 2024-03-28 Sarahi Aguayo-Tapia, Gerardo Avalos-Almazan, Jose de Jesus Rangel-Magdaleno
In the signal analysis context, the entropy concept can characterize signal properties for detecting anomalies or non-representative behaviors in fiscal systems. In motor fault detection theory, entropy can measure disorder or uncertainty, aiding in detecting and classifying faults or abnormal operation conditions. This is especially relevant in industrial processes, where early motor fault detection
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Mechanism for High-Precision Control of Movement at Maximum Output in the Vertical Jump Task Entropy (IF 2.7) Pub Date : 2024-03-28 Hiroki Murakami, Norimasa Yamada
Human movements are governed by a tradeoff between speed and accuracy. Previous studies that have investigated the tradeoff relationship in sports movements involving whole-body movements have been limited to examining the relationship from the perspective of competition-specific movements, and the findings on whether the relationship is valid have not been unified. Therefore, this study incorporated
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Influential Metrics Estimation and Dynamic Frequency Selection Based on Two-Dimensional Mapping for JPEG-Reversible Data Hiding Entropy (IF 2.7) Pub Date : 2024-03-29 Haiyong Wang, Chentao Lu
JPEG Reversible Data Hiding (RDH) is a method designed to extract hidden data from a marked image and perfectly restore the image to its original JPEG form. However, while existing RDH methods adaptively manage the visual distortion caused by embedded data, they often neglect the concurrent increase in file size. In rectifying this oversight, we have designed a new JPEG RDH scheme that addresses all
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Fuzzy Entropy-Assisted Deconvolution Method and Its Application for Bearing Fault Diagnosis Entropy (IF 2.7) Pub Date : 2024-03-29 Di Pei, Jianhai Yue, Jing Jiao
Vibration signal analysis is an important means for bearing fault diagnosis. Affected by the vibration of other machine parts, external noise and the vibration transmission path, the impulses induced by a bearing defect in the measured vibrations are very weak. Blind deconvolution (BD) methods can counteract the effect of the transmission path and enhance the fault impulses. Most BD methods highlight
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Entanglement-Based CV-QKD with Information Reconciliation over Entanglement-Assisted Link Entropy (IF 2.7) Pub Date : 2024-03-29 Ivan B. Djordjevic, Vijay Nafria
An entanglement-based continuous variable (CV) QKD scheme is proposed, performing information reconciliation over an entanglement-assisted link. The same entanglement generation source is used in both raw key transmission and information reconciliation. The entanglement generation source employs only low-cost devices operated in the C-band. The proposed CV-QKD scheme with information reconciliation
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Structural Properties of the Wyner–Ziv Rate Distortion Function: Applications for Multivariate Gaussian Sources Entropy (IF 2.7) Pub Date : 2024-03-29 Michail Gkagkos, Charalambos D. Charalambous
The main focus of this paper is the derivation of the structural properties of the test channels of Wyner’s operational information rate distortion function (RDF), R¯(ΔX), for arbitrary abstract sources and, subsequently, the derivation of additional properties for a tuple of multivariate correlated, jointly independent, and identically distributed Gaussian random variables, {Xt,Yt}t=1∞, Xt:Ω→Rnx,
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Robust Free-Space Optical Communication Utilizing Polarization for the Advancement of Quantum Communication Entropy (IF 2.7) Pub Date : 2024-03-30 Nicholas Savino, Jacob Leamer, Ravi Saripalli, Wenlei Zhang, Denys Bondar, Ryan Glasser
Free-space optical (FSO) communication can be subject to various types of distortion and loss as the signal propagates through non-uniform media. In experiment and simulation, we demonstrate that the state of polarization and degree of polarization of light passed though underwater bubbles, causing turbulence, is preserved. Our experimental setup serves as an efficient, low cost alternative approach
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Non-Thermal Solar Wind Electron Velocity Distribution Function Entropy (IF 2.7) Pub Date : 2024-03-30 Peter H. Yoon, Rodrigo A. López, Chadi S. Salem, John W. Bonnell, Sunjung Kim
The quiet-time solar wind electrons feature non-thermal characteristics when viewed from the perspective of their velocity distribution functions. They typically have an appearance of being composed of a denser thermal “core” population plus a tenuous energetic “halo” population. At first, such a feature was empirically fitted with the kappa velocity space distribution function, but ever since the
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Prediction Consistency Regularization for Learning with Noise Labels Based on Contrastive Clustering Entropy (IF 2.7) Pub Date : 2024-03-30 Xinkai Sun, Sanguo Zhang, Shuangge Ma
In the classification task, label noise has a significant impact on models’ performance, primarily manifested in the disruption of prediction consistency, thereby reducing the classification accuracy. This work introduces a novel prediction consistency regularization that mitigates the impact of label noise on neural networks by imposing constraints on the prediction consistency of similar samples
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PyDTS: A Python Toolkit for Deep Learning Time Series Modelling Entropy (IF 2.7) Pub Date : 2024-03-31 Pascal A. Schirmer, Iosif Mporas
In this article, the topic of time series modelling is discussed. It highlights the criticality of analysing and forecasting time series data across various sectors, identifying five primary application areas: denoising, forecasting, nonlinear transient modelling, anomaly detection, and degradation modelling. It further outlines the mathematical frameworks employed in a time series modelling task,
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Conformity and Mass Media Influence in the Sznajd Model on Regular Lattices Entropy (IF 2.7) Pub Date : 2024-03-30 Maciej Wołoszyn
The polarization of opinions and difficulties in reaching a consensus are central problems of many modern societies. Understanding the dynamics governing those processes is, therefore, one of the main aims of sociophysics. In this work, the Sznajd model of opinion dynamics is investigated with Monte Carlo simulations performed on four different regular lattices: triangular, honeycomb, and square with
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Study on the Tip Leakage Loss Mechanism of a Compressor Cascade Using the Enhanced Delay Detached Eddy Simulation Method Entropy (IF 2.7) Pub Date : 2024-03-28 Shiyan Lin, Ruiyu Li, Limin Gao
The leakage flow has a significant impact on the aerodynamic losses and efficiency of the compressor. This paper investigates the loss mechanism in the tip region based on a high-load cantilevered stator cascade. Firstly, a high-fidelity flow field structure was obtained based on the Enhanced Delay Detached Eddy Simulation (EDDES) method. Subsequently, the Liutex method was employed to study the vortex
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Why Does Cross-Sectional Analyst Coverage Incorporate Market-Wide Information? Entropy (IF 2.7) Pub Date : 2024-03-26 Yunfei Hou, Changsheng Hu
This paper shows that the empirical distribution of cross-sectional analyst coverage in China’s stock markets follows an exponential law in a given month from 2011 to 2020. The findings hold in both the emerging (Shanghai) and the developed market (Hong Kong). Moreover, the unique distribution parameter (i.e., mean) is directly related to the amount of market-wide information. Average analyst coverage
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Irruption and Absorption: A ‘Black-Box’ Framework for How Mind and Matter Make a Difference to Each Other Entropy (IF 2.7) Pub Date : 2024-03-27 Tom Froese
Cognitive science is confronted by several fundamental anomalies deriving from the mind–body problem. Most prominent is the problem of mental causation and the hard problem of consciousness, which can be generalized into the hard problem of agential efficacy and the hard problem of mental content. Here, it is proposed to accept these explanatory gaps at face value and to take them as positive indications
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Markov Blankets and Mirror Symmetries—Free Energy Minimization and Mesocortical Anatomy Entropy (IF 2.7) Pub Date : 2024-03-27 James Wright, Paul Bourke
A theoretical account of development in mesocortical anatomy is derived from the free energy principle, operating in a neural field with both Hebbian and anti-Hebbian neural plasticity. An elementary structural unit is proposed, in which synaptic connections at mesoscale are arranged in paired patterns with mirror symmetry. Exchanges of synaptic flux in each pattern form coupled spatial eigenmodes
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A Unifying Generator Loss Function for Generative Adversarial Networks Entropy (IF 2.7) Pub Date : 2024-03-27 Justin Veiner, Fady Alajaji, Bahman Gharesifard
A unifying α-parametrized generator loss function is introduced for a dual-objective generative adversarial network (GAN) that uses a canonical (or classical) discriminator loss function such as the one in the original GAN (VanillaGAN) system. The generator loss function is based on a symmetric class probability estimation type function, Lα, and the resulting GAN system is termed Lα-GAN. Under an optimal
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Non-Projective Two-Weight Codes Entropy (IF 2.7) Pub Date : 2024-03-27 Sascha Kurz
It has been known since the 1970’s that the difference of the non-zero weights of a projective Fq-linear two-weight code has to be a power of the characteristic of the underlying field. Here, we study non-projective two-weight codes and, e.g., show the same result under mild extra conditions. For small dimensions we give exhaustive enumerations of the feasible parameters in the binary case.
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Lagrangian Partition Functions Subject to a Fixed Spatial Volume Constraint in the Lovelock Theory Entropy (IF 2.7) Pub Date : 2024-03-27 Mengqi Lu, Robert B. Mann
We evaluate here the quantum gravity partition function that counts the dimension of the Hilbert space of a simply connected spatial region of a fixed proper volume in the context of Lovelock gravity, generalizing the results for Einstein gravity. It is found that there are sphere saddle metrics for a partition function at a fixed spatial volume in Lovelock theory. Those stationary points take exactly