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The Composition and Characteristics of Logistics Capability Based on Distributed Platform in Multimedia Supply Chain Environment Fluct. Noise Lett. (IF 1.8) Pub Date : 2024-02-29 Shaojun Sheng
One of the challenges that businesses have always paid more attention to is supply chain logistics competence. The conditions of supply chain logistics capabilities management have also altered in light of the quick development of multimedia, and there will undoubtedly be certain management issues. Logistics competence is expressed in both real and intangible capabilities in the context of the supply
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Two New Estimators for the Autocorrelation Function Through Singular Spectrum Analysis Fluct. Noise Lett. (IF 1.8) Pub Date : 2024-02-28 Rahim Mahmoudvand
It is around a century that sample autocorrelation function has been introduced and used as a standard tool in time series analysis. A vast literature can be found on the statistical properties of the sample autocorrelation function. However, it has been highlighted recently that the sum of the sample autocorrelation function over the lags 1 to T−1 is −0.5 for all time series of length T. This property
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Innovative Deep Learning Strategies for Chaotic Data Classification: A Multi-Algorithm Comparison in the Presence of Noise Fluct. Noise Lett. (IF 1.8) Pub Date : 2024-02-24 Shih-Lin Lin
Chaos is prevalent in both nature and science, appearing in data, time series and complex systems. Chaotic systems exhibit numerous uncertainties, akin to noise, which challenge researchers to distinguish or analyze potential underlying patterns or even identify the type of system involved. However, determining the kind of chaotic system is essential, as it enables prediction, synchronization, control
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Crypto Analysis of the Key Distribution Scheme Using Noise-Free Resistances Fluct. Noise Lett. (IF 1.8) Pub Date : 2024-02-24 Laszlo B. Kish
Known key exchange schemes offering information-theoretic (unconditional) security are complex and costly to implement. Nonetheless, they remain the only known methods for achieving unconditional security in key exchange. Therefore, the explorations for simpler solutions for information-theoretic security are highly justified. Lin et al. [1] proposed an interesting hardware key distribution scheme
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Jump Risk Contagion and Determinants Driven by COVID-19 in Sino-US Stock Market: An Empirical Analysis from a Dependence Perspective Fluct. Noise Lett. (IF 1.8) Pub Date : 2024-02-23 Xinyu Du, Zhengyang Lv, Ying Yuan, Xinning Xu, Chong Zhao
This paper examines the jump risk contagion between the US and China during the financial crisis driven by COVID-19, and the impact of a series of determinants to detect the transmission mechanisms. Specifically, we employ the ARJI–GARCH model to capture jump behavior and apply the Clayton Copula to construct lower tail jump contagion. Furthermore, we conduct regression analysis on variables related
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A New and Effective Classification Method for Complex Time Series Based on Information Measure Fluct. Noise Lett. (IF 1.8) Pub Date : 2024-02-23 Ang Li, Pengjian Shang
The growing importance of time series information measure raises questions about how to effectively cluster a large number of nonlinear complex time series data and accurately extract more hidden information from them. In this paper, a clustering measurement and classification method for complex time series, the symmetrical exponential Tsallis relative information (SETRI) measure, is proposed, which
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Interplay Multifractal Dynamics Among Carbon Trading Market, Geopolitical Risk and Economic Policy Uncertainty Fluct. Noise Lett. (IF 1.8) Pub Date : 2024-02-17 You-Shuai Feng, Mei-Jun Ling, Jing Gao
This paper explores the variations in cross-correlations among the carbon trading market, geopolitical risk (GPR) and economic policy uncertainty (EPU), focusing on their multifractality and asymmetric properties. Therefore, the study employs the multifractal detrended cross-correlation analysis (MF-DCCA) and multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA) approaches to examine
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A generalization of the Lindley Distribution Fluct. Noise Lett. (IF 1.8) Pub Date : 2024-02-17 Kamel Ourabah
The Lindley distribution is useful in a wide variety of fields, such as biology and astronomy. Many generalizations of the Lindley distribution have been introduced in the literature, with various motivations. Inspired by the concept of superstatistics in nonequilibrium statistical mechanics, we introduce here a novel generalization of the Lindley distribution, by regarding its shape parameter as a
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Numerical Investigation of the Flow Structure and Acoustical Noise in a Suppressor Fluct. Noise Lett. (IF 1.8) Pub Date : 2024-02-16 Ezedin Ayaliew Yimam, Tolga Demircan
The noise created when a firearm is fired has a lot of adverse effects on humans and the environment, so analyzing and attenuating this noise is essential. This study aimed to examine propellant flow and the sound generated by this flow using a hybrid computational fluid dynamics and computational aeroacoustics method. The compatibility of this numerical study was also validated by comparing it with
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Enhancing Economic Stability with Innovative Crude Oil Price Prediction and Policy Uncertainty Mitigation in USD Energy Stock Markets Fluct. Noise Lett. (IF 1.8) Pub Date : 2024-02-09 Umar Islam, Emad Mahrous Awwad, Nadia Mohamed Sarhan, Mohamed Abdel Fattah Sharaf, Ijaz Ali, Inayat Khan, Shehzad Ahmad, Faheem Khan
In today’s globalized economic landscape, the assurance of economic stability is of paramount importance, necessitating precise financial decision-making and policy formulation. This assurance is significantly augmented by innovative approaches to predicting crude oil prices, particularly in the context of energy stock markets denominated in USD. This paper delves into the transformative effect of
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Stock Market Volatility Prediction Based on Robust GBM-GRU Model Fluct. Noise Lett. (IF 1.8) Pub Date : 2024-02-09 Chuyue Liao, Guoqing Chen, Siyang Cai
In this study, a corrective learning technique is proposed to enhance the time series forecasting accuracy of traditional intelligent algorithms and address issues with engineering data adaptability. The financial world makes substantial use of volatility, and forecasting stock market volatility has great significance. Because stock price time series are nonstationary and nonlinear, predicting stock
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Tree Seed Algorithm-based Feature Selection with Optimal Deep Learning Model for Supply Chain Management Fluct. Noise Lett. (IF 1.8) Pub Date : 2024-02-03 Jaber S. Alzahrani, Mashael Maashi, Haya Mesfer Alshahrani, Abdulkhaleq Q. A. Hassan, Jahangir khan, Ashit Kumar Dutta, Yasir A. M. Eltahir, Hussam Eldin Hussein Saad, Rafiulla Gilkaramenthi
In recent days, supply chain and logistic industries have been going through a transformational wave of automation and digitization. Supply chain management (SCM) can involve machine learning (ML) abilities and prediction models to ensure that the demands are satisfied at a minimum cost. Intelligent models can be developed to determine whether adequate inventory is accessible to encounter the predictable
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Deep Learning-Based Cause-Related Marketing and the Impact of the Internet on MICE Events in the Context of the Epidemic Fluct. Noise Lett. (IF 1.8) Pub Date : 2024-02-01 Kun Shi, Boshi Cui, XinTong Zhao, Yuwei Ma, Yang Yang, Zewen Du
Since 2019, novel coronavirus pneumonia has been rampant around the world, and when outbreaks occur, Meetings, Incentives, Conferences and Exhibitions (MICE) events are often affected to varying degrees. In addition, in the context of the epidemic, consumers have increasingly taken the participation of MICE in charitable activities as a measure of their social responsibility and judged MICE events
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Forecasting Financial Market Trends in a Complex Business Environment Fluct. Noise Lett. (IF 1.8) Pub Date : 2024-01-24 Xiuyan Wang
Applications for the stock market that can be relied upon to provide the information regular and professional investors need to make better-informed purchases are a boon to both. A well-thought-out sales approach may help buyers mitigate risk, zero in on the companies most likely to provide the highest returns, and increase their chances of making a purchase. Due to numerous interrelationships between
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Constructing Signal from Imperfect Data without Prior Information and Training Data Fluct. Noise Lett. (IF 1.8) Pub Date : 2024-01-12 Pichid Kittisuwan, Kampol Woradit
In many situations, the signal can be disrupted not only by noise but also by missing data. Many works present deep learning techniques to solve the noise and missing-data problems. These techniques give good efficiency for removing adulterated things. However, many deep learning techniques do not give good efficiency in computational time because these methods require large architecture and training
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Under the Background of Economic Structure Optimization, Environmental Governance Promotes Macroeconomic Structural Adjustment Measures Fluct. Noise Lett. (IF 1.8) Pub Date : 2024-01-05 Jincai Zhang, Xiangyu Cai
Along with the implementation of reform and opening up in the 1970s, China’s economy entered a period of rapid development. During this period, the economic structure of our country has gradually changed from the primary industry to the secondary industry. Even today, the industrial industry still plays a very important role in the economic structure of our country. The industrial chain such as the
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Enhancing Stock Price Prediction with Deep Cross-Modal Information Fusion Network Fluct. Noise Lett. (IF 1.8) Pub Date : 2024-01-05 Rabi Chandra Mandal, Rajnish Kler, Anil Tiwari, Ismail Keshta, Mohamed R. Abonazel, Elsayed M. Tageldin, Mekhmonov Sultonali Umaralievich
Stock price prediction is considered a classic and challenging task, with the potential to aid traders in making more profitable trading decisions. Significant improvements in stock price prediction methods based on deep learning have been observed in recent years. However, most existing methods are reliant solely on historical stock price data for predictions, resulting in the inability to capture
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Dynamic Properties for Time-Delayed Grazing Ecosystem Driven by Lévy Noise and Gaussian Noise Fluct. Noise Lett. (IF 1.8) Pub Date : 2024-01-05 Yongfeng Guo, Lina Mi, Jiaxin Ding
In this paper, we establish a stochastic dynamical grazing ecosystem with time delays and fluctuations. The effects of time delay, Gaussian noise and Lévy noise on the stationary probability distribution (SPD), the mean first passage time (MFPT) and stochastic resonance (SR) are analyzed. Our research results show the following: (i) For small time delay, the increasing Gaussian noise intensity leads
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Dual-Attention Based Multi-Path Approach for Intensifying Stock Market Forecasting Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-12-29 Sachin R. Jadhav, Aashima Bishnoi, Nodira Safarova, Faheem Khan, Khursheed Aurangzeb, Musaed Alhussein
In light of the existing challenges in capturing short-term fluctuations and achieving accurate predictions in stock market time series data, this research presents the “Dual-Attention MDWT-CVT-LSTM,” a revolutionary financial time series forecasting model. This model makes use of a dual-attention mechanism in conjunction with a Variant Transformation-Gated Long Short-Term Memory (LSTM) network. The
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Effect of Nitrogen Ion Diffusion Jumps in Nanometer-Sized Si3N4 Memristors Investigated by Low-Frequency Noise Spectroscopy Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-12-20 Arkady V. Yakimov, Alexey V. Klyuev, Dmitry O. Filatov, Oleg N. Gorshkov, Dmitry A. Antonov, Alexey N. Mikhaylov, Viktor S. Kochergin, Nikolaos Vasileiadis, Panagiotis Dimitrakis
The elementary jumps in the electron current through conducting filaments of two nanometer-sized virtual memristor structures consisting of a contact of a conductive atomic force microscope probe to the Si3N4 layer with the thickness of 6nm deposited onto the n++-Si(001) conductive substrates are investigated. These structures are: (S1) the Si3N4/Si film; (S2) the Si3N4/SiO2/Si stack, a similar structure
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Graphical Deep Learning Prediction Model for Stock Risk Management Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-12-20 Haewon Byeon, Shyamsunder Chitta, Shavkatov Navruzbek Shavkatovich, Ghulam Jillani Ansari, Majed Alhaisoni, Yu-Dong Zhang
Forecasting the future movements of stock market indexes by utilizing historical transaction data is a prominent concern within the realm of finance. The application of graph convolutional networks to incorporate the interrelationships among various indices’ patterns is a highly advanced subject within this field. Addressing the inconsistency between historical and future dynamic graphs in current
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Enhancing Personalization of Customer Services in E-Commerce System using Predictive Analytics Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-12-20 Deepshikha Bhargava, Amitabh Bhargava, Romel P. Melgarejo-Bolivar, Abigail M. Montes de Oca-Nina, Sushovan Chaudhury
The extensive study was conducted to enhance the prediction of customer turnover in an online retail and distribution organization. The study combines data from surveys, consumer comments, and financial records to uncover themes from textual assessments using state-of-the-art methodologies. Methods such as Dirichlet Multilayer Perceptron Mixing, Latent Dirichlet Allocation and Random Sampling fall
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Navigation Services and Urban Sustainability Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-12-20 Giuliano Cornacchia, Mirco Nanni, Dino Pedreschi, Luca Pappalardo
The The rise of socio-technical systems in which humans interact with various forms of Artificial Intelligence, including assistants and recommenders, multiplies the possibility for the emergence of large-scale social behavior, possibly with unintended negative consequences. In this work, we discuss a particularly interesting case, i.e., navigation services’ impact on urban emissions, showing through
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Ternary Instantaneous Noise-Based Logic with Exponential Hilbert Space Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-12-20 Laszlo B. Kish
A tree-valued instantaneous noise-based logic with exponential Hilbert space is proposed. The third value is an uncertain bit value, which can be useful in artificial intelligence applications. The signal carrying the ternary universe has a significant advantage over the signal of the standard binary universe: its amplitude is never zero during any clock period. All known binary logic gates for exponential
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Empirical Analysis of SSE 50 Index Volatility Based on GARCH Model Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-12-18 Shiwang Huang, Niukun Liu, Zhichao Wang
Volatility is an important index for measuring the risk in the financial market. The research on the volatility of the financial market is the basis of risk prevention and asset pricing. The volatility of the market is predicted by using financial time series analysis and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model. This paper uses the 5 min closing price of the Shanghai
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Employing Machine Learning to Deduce a Causal Link Between Corporate Social Responsibility and Financial Performance Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-12-18 Zhiyan Huang, Kwen Liew, Mamnoon Rahman
Incorporating Corporate Social Responsibility (CSR) into business strategy has become noteworthy, as that pertains to the discretionary initiatives a business entity undertakes to enhance its operational sphere’s societal and ecological circumstances. The evaluation of a company’s success is closely tied to its financial performance, which pertains to its capacity to produce earnings and enhance shareholder
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Research on the Influence of Depth and Breadth of Equity Reform on the Performance of State Owned Enterprises Based on Dynamic Panel Data Model Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-12-07 Guilin Yang, Guihua Yang, Wanping Yang
In order to explore the necessity of mixed ownership reform of state-owned enterprises and clarify the direction of mixed ownership reform of state-owned enterprises in China, this paper uses dynamic panel data model and bootstrap-DEA method to study the impact of “depth” and “breadth” of equity reform of state-owned enterprises in China on the performance of state-owned enterprise. The results show
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A Novel Two-Dimensional Quad-Stable Stochastic Resonance System for Bearing Fault Detection Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-12-07 Gang Zhang, Jiaqi Xu, Xiaoxiao Huang, Zhaorui Li
A novel two-dimensional Quad-stable stochastic resonance (NTDQSR) system is proposed in this paper to address the poor signal detection capability of the original one-dimensional Quad-stable stochastic resonance (ODQSR) system. Firstly, expressions for the equivalent potential function and the steady-state probability density (SPD) function of the system are derived to study the impact of parameters
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Dynamical Behavior of Two Coupled Two-Stroke Relaxation Oscillators Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-11-27 Daniele Ducci, Riccardo Meucci, Stefano Euzzor, Jean-Marc Ginoux, Angelo Di Garbo
Starting from [J.-M. Ginoux et al., Torus breakdown in a uni junction memristor, Int. J. Bifurcation Chaos 28(10) (2018) 1850128; J.-M. Ginoux et al., Torus breakdown in a two-stroke relaxation memristor, Chaos Solitons Fractals 153 (2021) 111594], we define a model which describes the dynamical behavior of a class of two-stroke oscillators (i.e., nonlinear oscillators with two distinct phases per
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Sustainable Finance Factors in Indian Economy: Analysis on Policy of Climate Change and Energy Sector Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-11-24 Rakesh Kumar, Richa Goel, Tilottama Singh, Sachi Mohanty Mohanty, Deepak Gupta, Ahmed Alkhayyat, Rupa Khanna
In the current era, entire global economies are transitioning to sustainable development because of global warming and climate change. Due to turbulence in environmental issues such as weather shocks, climate change and basic infrastructure and industrial planning, many countries are changing their approach and taking green steps. This paper assesses sustainable finance in India and the ways in which
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Large Fluctuations in Amplifying Graphs Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-11-23 Stefano Lepri
In this paper, we consider a model for chaotic diffusion with amplification on graphs associated with piecewise-linear maps of the interval [S. Lepri, Chaotic fluctuations in graphs with amplification, Chaos, Solitons & Fractals 139 (2020) 110003]. We determine the conditions for having fat-tailed invariant measures by considering approximate solution of the Perron–Frobenius equation for generic graphs
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Relaxation Dynamics and Finite-Size Effects in a Simple Model of Condensation Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-11-23 Gabriele Gotti, Stefano Iubini, Paolo Politi
In this paper, we consider a simple, purely stochastic model characterized by two conserved quantities (mass density a and energy density h) which is known to display a condensation transition when h>2a2: in the localized phase a single site hosts a finite fraction of the whole energy. Its equilibrium properties in the thermodynamic limit are known and in a recent paper [G. Gotti, S. Iubini and P.
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Transient Attacks Against the VMG-KLJN Secure Key Exchanger Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-11-18 Shahriar Ferdous, Laszlo B. Kish
The security vulnerability of the Vadai, Mingesz, and Gingl (VMG) Kirchhoff–Law–Johnson–Noise (KLJN) key exchanger, as presented in the publication “Nature, Science Report 5 (2015) 13653”, has been exposed to transient attacks. Recently an effective defense protocol was introduced (Appl. Phys. Lett. 122 (2023) 143503) to counteract mean-square voltage-based (or mean-square current-based) transient
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Automated Deep Learning Model with Optimization Mechanism for Segmenting Leukemia from Blood Smear Images Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-11-11 Anjani Kumar Rai, P. Ganeshan, Hesham S. Almoallim, Sulaiman Ali Alharbi, S. S. Raghavan
The advancement of digital microscopic scanning has made the study of image processing as well as categorization an exciting field of diagnostic studies. The literature describes a number of methods for detecting acute lymphocytic leukemia (ALL) using blood smear pictures. The goal of this research is to create an efficient approach for segmenting and detecting leukemia. This research has created a
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Multifractal Analysis of Chinese Industry and Stock Markets Fluctuation Under the COVID-19 Pandemic Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-11-11 Pan-Ting Liu, Xin-Bang Cao, Hong-Yong Wang
Researchers and authorities have become increasingly interested in how the COVID-19 pandemic has profoundly impacted the real economy and financial markets around the world since its outbreak in late 2019. Applying the methods of multifractal analysis, this paper investigates the fluctuation characteristics and market risks of Chinese industry and stock markets under the COVID-19 pandemic, and reveals
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A Frequency-Weighting Digital Filter in Sound Level Meter Based on Neural Computing Method Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-11-09 Haiyun Lin, Xinjie Shen, Gang Long, Haijun Lin
Frequency weighting networks are a critical component of a sound level meter (SLM), and their error characteristics directly determine the performances of SLM. For reducing the high-frequency error of the A∕C frequency-weighting filters with the bilinear transformation method (BTM), a design method for A∕C frequency-weighting filters based on neural computing method (NCM) is proposed. A detailed algorithm
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Parrondo-Like Behavior in Continuous-Time Random Walks with Periodically Alternating Jumps Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-11-09 Jiyeon Lee
As a natural generalization of the discrete-time random walk, the continuous-time random walk (CTRW) has been applied to stochastic models with random dynamics in various fields. In this paper, we show that the deterministic alternation of two unbiased CTRWs can lead to a phenomenon similar to the Parrondo paradox, in which the asymptotic mean drift of the combined CTRW becomes positive or negative
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Existence and Internal Structure of the Deterministic Attracting Set for a Random Ant Colonies Model Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-11-04 Hongcui Wang, Chaoqun Xu
This paper is concerned with the attracting set of an ant colonies model with bounded noisy perturbation. This perturbation is modeled by the well-known Ornstein–Uhlenbeck process and the arc tangent function. For the random model, we first verify the existence and uniqueness of the global positive solution, and then prove the existence of the deterministic attracting set. Furthermore, in order to
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Weak Signal Detection in the Hodgkin–Huxley Neural Network with Channel Blocks under Electromagnetic Stimulus Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-11-04 Huilan Yang, Guizhi Xu, Shuxiang Tian, Haijun Zhu, Yixuan Shan
Neurons can detect weak signals in noisy cellular environments and complex backgrounds. Channel blocks have a great impact on the initiation and propagation of action potentials for neurons. The effects of channel blocks and electromagnetic stimulus on weak signal detection are studied in Hodgkin–Huxley neuronal network. The results suggest that the weak signal detection and the neural discharge behaviors
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Analyzing the Effects of White Noise on Software Release Planning Using SDE-Based SRGM Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-10-14 Anu G. Aggarwal, Sameer Anand, Ritu Bibyan, Vibha Verma
The efficiency and performance of a software application largely depend on the testing strategy adopted by the firm. Apart from the tools, techniques, and skills used for testing, the duration also plays an important influence in establishing software reliability. This defines the operational performance of the software. The testing duration decision is dependent on the failure behavior depicted by
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Impact of Non-Gaussian Noise and Time Delay on Stability and Stochastic Resonance for a FitzHugh-Nagumo Neural System Subjected to a Multiplicative Periodic Signal Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-10-09 Yun-Feng Chen, Kang-Kang Wang, Hui Ye, Ya-Jun Wang
In this paper, we focus on the investigations on the stochastic stability and the stochastic resonance (SR) phenomena for a FitzHugh-Nagumo system with time delay induced by a multiplicative non-Gaussian colored noise and an additive Gaussian colored noise. By use of the fast descent method, the unified colored noise approximation and the two-state theory for the SR, the stationary probability density
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Nonlinear Dynamic Analysis of the U.S. Defense Stock Markets under the Russia–Ukraine Conflict Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-10-09 Xinpei Wu, Heming Xu, Shuo Wu, Menghao Huang, Jian Wang
In this paper, we adopt multifractal detrended fluctuation analysis (MF-DFA) to explore relationships between the Russia–Ukraine conflict and defense stock markets. Specifically, we analyze the behaviors of 20 U.S. defense stock markets confronting with the Russia–Ukraine conflict. By using the stock price charts, combined with multifractal spectra and singularity exponents calculated by MF-DFA, we
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Correlation Structure of the Solution to the Reaction-Diffusion Equation in Respond to Random Fluctuations of the Boundary Conditions Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-09-29 Karl Sabelfeld
In this paper, we deal with the reaction-diffusion equation subject to Dirichlet and Neumann boundary conditions where the input function on the boundary is randomly fluctuated. First we study the fundamental case when this function is a white noise. Explicit form of the correlation function is derived for the reaction-diffusion equation in a half-plane. In this case we obtain the Karhunen–Loève expansion
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Does COVID-19 Epidemic Change the Risk Spillover Characteristics of Chinese Carbon Markets with Energy, Non-Energy Commodity and Stock Markets? Evidence from a Novel Network Method Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-09-29 Pengfei Zhu, Tuantuan Lu
This paper investigates the multi-dimensional risk spillover effects of carbon markets with energy, non-energy commodity and stock markets in China before and after the COVID-19 outbreak, through the DY network with GARCHSK-VaR method. The empirical results denote that the total bidirectional risk spillovers of carbon markets become larger after the COVID-19 outbreak than before the COVID-19 outbreak
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Blockchain-Based Secure Stock Market Price Prediction Using Next Generation Optimized LSTM Model Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-09-29 Amol Dattatray Dhaygude, Ihtiram Raza Khan, Pavitar Parkash Singh, Mukesh Soni, Salman A. AlQahtani, Yudong Zhang
Stock forecasting has long drawn people’s attention because the stock market is a crucial source of financing for publicly traded corporations and a sizable investment market. To fully use the evidence from dissimilar typical prices and recover the stock forecasting effect, a Blockchain-based secure stock value forecasting model TL-EMD-LSTM-MA (TELM) is projected. Other methods are selected for prediction
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Application of Artificial Neural Network Unified with Fuzzy Logic for Systematic Stock Market Prediction Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-09-22 Akhilesh Kumar, Ismail Keshta, Jyoti Bhola, Mohammed Wasim Bhatt, Salman A. AlQahtani, Manvitha Gali
Prediction of the stock market can play a vital role in everyone’s life to attain sustainable growth. This can also lead to an attractive profit by making the proper choices in the financial stock market. The stock market prediction is a big challenge which requires extensive advanced tools and techniques to analyze the future and present data. The modern stock market institutions provide better self-trading
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Relaxing Daily Price Limits and Stock Market Cross-Correlation: Evidence from MF-X-DMA Analysis Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-08-16 Qingsong Ruan, Sumiya Hu, Jiarui Zhang, Xiaolin Chu, Dayong Lv
The daily price limits in the ChiNext stock market were relaxed from ±10% to ±20% on 24 August 2020. Using the multifractal detrended moving average cross-correlation analysis (MF-X-DMA) method, we find that relaxing daily price limits leads to a greater degree of multifractality of the ChiNext stock market, suggesting that the relaxation of daily price limits harms stock market efficiency. In addition
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Optimization of Design Parameters for X̄ Control Charts with Independent Multiple Assignable Causes Based on Continuous Flow Processes Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-08-16 Aitin Saadatmellia, Asghar Seif, M. Bameni Moghadam
The economic design of control charts depends on the process shock model distribution due to difficulties from both theoretical and practical aspects. This paper pursues to develop the economic design of X̄ control chart for monitoring continuous flow processes under Bur XII shock model. The Burr XII distribution is flexible and its hazard rate can take many forms like fixed, increasing, decreasing
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Analysis of Vibration Characteristics and Noise Reduction for 10kV Oil-Immersed Transformer Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-08-16 Jingzhu Hu, Bing Zhou, Yanzhao Wang, Ni Li, Yuan Ni, Zheyuan Gan
Distribution transformers are usually located near residential buildings, which cause serious noise pollution. This paper focuses on reducing the vibration noise of 10kV oil-immersed transformer by optimization of transformer case structure. Based on the analysis of the vibration characteristics for the transformer case surface, the noise reduction measures were put forward for the 10kV oil-immersed
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Time-Varying and Scale-Dependent Informational Efficiency of the European CO2 Emissions Market: An Analysis Based on Singular Value Decomposition Entropy Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-08-04 Monica Meraz, Jose Alvarez-Ramirez, Eduardo Rodriguez, Luis Castro
This work examined the informational efficiency of the European CO2 emission trading market for the different implementation phases in the period 2008–2022:Q3. The approach is based on a bootstrap singular value decomposition (SVD) approach and the analysis was conducted for a rolling window to assess the time-varying efficiency and over different time scales. The impact of the COVID-19 lockdown and
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The Complex Connectedness of Global Large-Scale Assets and the Visualization of Their Return Spillover Paths Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-08-04 Sha Zhu, Tianhao Wen, Qinglin Du, Fujun Lai
Due to the increasing connectedness of international financial markets, the measurement of dynamic connectedness among large-scale assets has become a key component of modern financial risk regulation and asset allocation principles. We quantify the dynamic connectedness among large-scale assets and visualize the return spillover paths using cutting-edge complex network spillover measurement theory
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Exploring the Multifractality in the Precious Metal Market Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-08-04 Itır Doğangün, Emrah Oral, Erkut Akkartal, Nida Turegun
This study proposes a novel approach to investigating the multifractality of time series using the multifractal cross-correlation detrended moving average analysis (MF-X-DMA). The study demonstrates the behavioral differences of MF-X-DMA in coherent and non-coherent time periods. Due to the lack of a mechanism to capture the dynamical cross-correlation in time series, correlated time series with multifractal
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Impact of Double Time Delays on Regime Shift and Stochastic Resonance for a Species Population System Driven by Colored Correlated Multiplicative and Additive Noises Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-07-29 Kang-Kang Wang, Hui Ye, Ya-Jun Wang, Sheng-Hong Li
In this paper, the characteristics for the state transition between the boom state and the extinction one, various stochastic resonance (SR) phenomena for a species population system induced by double time delays and colored cross-correlated Gaussian noises are investigated. The control of the species population system has an important effect on ecological balance and the development of human living
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Measuring Economic Uncertainty Synchrony with Cross-Sample Entropy Under Common External Factors: The Case of Chile Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-07-26 Nicolás Troncoso, Javier E. Contreras-Reyes, Byron J. Idrovo-Aguirre
In this paper, we measured the uncertainty synchrony level of Chilean business economic perception and consumer economic perception, both affected by common external factors reflected in the Global Economy Perception Index (GEPI), unemployment, inflation, interest rate, Monthly Economic Activity (MEAI) and the Economic Policy Uncertainty (EPUI) indexes. We propose using the Composite Multiscale Partial
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Co-movement between RMB and Bitcoin with Effects of DCEP Using Wavelet Coherence Analysis Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-07-25 Liang Wu, Weifang Zhang
Utilizing wavelet coherence analysis, we investigate the correlation of fluctuations and phase differences between Bitcoin and RMB to identify capital flows between the two currencies. The effects of Digital Currency Electronic Payment (DCEP) on their co-movement are further analyzed. Our findings reveal that the RMB exchange rate leads the price of Bitcoin in all significant co-movement areas. Furthermore
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A Proposal to Analyze Muscle Dynamics Under Fatiguing Contractions Using Surface Electromyography Signals and Fuzzy Recurrence Network Features Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-07-21 Divya Sasidharan, Venugopal Gopinath, Ramakrishnan Swaminathan
The analysis of surface electromyography (sEMG) signals is significant in the detection of muscle fatigue. These signals exhibit a great degree of complexity, nonlinearity, and chaos. Also, presence of high degree of fluctuations in the signal makes its analysis a difficult task. This study aims to analyze the nonlinear dynamics of muscle fatigue conditions using Fuzzy recurrence networks (FRN). Dynamic
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Satellite and Aerial Image Restoration Using Deep Reinforcement Learning Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-07-19 S. Hanis, S. Abinav Narayanan, P. Abishek Viswanath, V. Bhooshan
In this paper, we present a deep reinforcement learning-based method for effectively denoising satellite and aerial imagery data. Noise of various kinds and with varying noise levels contaminates satellite imagery data. The image’s quality and readability suffer when there is noise present. Therefore, it is crucial to create a network that can effectively and efficiently remove noise from the image
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XOR and XNOR Gates in Instantaneous Noise-Based Logic Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-06-27 Mohammad B. Khreishah, Walter C. Daugherity, Laszlo B. Kish
In this paper, we propose a new method of applying the XOR and XNOR gates on exponentially large superpositions in Instantaneous Noise-Based Logic. These new gates are repeatable, and they can achieve an exponential speedup in computation with polynomial hardware complexity.
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Reconsidering Electroluminescence Cooling of a Heated Diode Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-06-16 Alexander P. Kirk
Electroluminescence cooling of a heated infrared-emitting diode has been claimed [P. Santhanam, D. J. Gray, Jr. and R. J. Ram, Thermoelectrically pumped light-emitting diodes operating above unity efficiency, Phys. Rev. Lett.108 (2012) 097403]. After analyzing the operating characteristics of this diode, it is evident that electroluminescence cooling was not demonstrated.
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On the Fluctuation–Dissipation of the Oxide Trapped Charge in a MOSFET Operated Down to Deep Cryogenic Temperatures Fluct. Noise Lett. (IF 1.8) Pub Date : 2023-06-16 G. Ghibaudo
In this paper, an analysis of the oxide trapped charge noise in a MOSFET operated down to deep cryogenic temperatures is proposed. To this end, a revisited derivation of the interface trap conductance Gp and oxide trapped charge noise SQt at the SiO2/Si MOS interface is conducted under very low temperature condition, where Fermi–Dirac statistics applies. A new relation between the oxide trapped charge