Chaos Patterns Research Articles

Detection of failures in HV surge arrester using chaos pattern with deep learning neural network

Detection of failures in HV surge arrester using chaos pattern with deep learning neural network

Chaotic Pattern and Solitary Solutions for the (21)-Dimensional Beta-Fractional Double-Chain DNA System

The dynamical behavior of the double-chain deoxyribonucleic acid (DNA) system holds significant implications for advancing the understanding of DNA transmission laws in the realms of biology and medicine. This study delves into the investigation of chaos patterns and solitary wave solutions for the (2+1) Beta-fractional double-chain DNA system, employing the theory of planar dynamical systems and the method of complete discrimination system for polynomials (CDSP). The results demonstrate a diverse spectrum of solitary wave solutions, sensitivity to perturbations, and manifestations of chaotic behavior within the system. Through the utilization of the complete discrimination system for polynomials, a multitude of novel solitary wave solutions, encompassing periodic, solitary wave, and Jacobian elliptic function solutions, were systematically constructed. The influence of Beta derivatives on the solutions was elucidated through parameter comparison analysis, emphasizing the innovative nature of this study. These findings underscore the potential of this system in unraveling various biologically significant DNA transmission mechanisms.

Dynamic behaviors analysis of fraction-order neural network under memristive electromagnetic induction

The dynamic behaviors of coupled neurons with different mathematical representations have received more and more attention in recent years. The coupling among heterogeneous neurons can show richer dynamic phenomena, which is of great significance in understanding the function of the human brain. In this paper, we present a fraction-order heterogeneous network with three neurons, which is built by coupling an FN neuron with two HR neurons. Complex electromagnetic surroundings have meaningful physical influence on the electrical activities of neurons. To imitate the effects of electromagnetic induction on the three-neuron heterogeneous network, we introduce a fraction-order locally active memristor in the neural network. The characteristics of this memristor are carefully analyzed by pinched hysteresis loops and its locally active characteristic is proved by the power-off plot and the DC <i>v-i</i> plot. Then, the parameter-dependent dynamic activities are investigated numerically by using several dynamical analysis methods, such as the phase diagrams, bifurcation diagrams, Lyapunov exponent spectra, and attraction basins. In addition, the network also reveals rich dynamic behaviors, including coexisting activities, anti-monotonicity phenomena, transient chaos and firing patterns, providing support for further investigating the firing patterns of the human brain. In particular, complex dynamics, including coexisting attractors, anti-monotonicity, and firing patterns, can be influenced by the order and strength of electrical synaptic coupling and electromagnetic induction. The control of the bistable state can be realized through the time feedback control method, so that the bistable state can be transformed into an ideal monostable state. The study of the fraction-order memristive neural network may expand the field of view for understanding the collective behaviors of neurons. Finally, based on the ARM platform, we give a digital implementation of the fraction-order memristive neural network, which can verify the consistency with the numerical simulation results. In the future, we will explore more interesting memristive neural networks and study different types of methods to control the firing behaviors of the networks.

Partition’s Shadow:

Assam’s Barak Valley is an example of how the 1947 Partition of India and Pakistan left behind long-term conflicts and issues pertaining to identity, place, and belonging that have created turmoil in the geo-political space that we refer to as India’s Northeast. The transformation of this space from a frontier during colonial times to a borderland in 1947 is not only significant for the genealogy and configuration of states within the region but also because this understanding subverts common assumptions about 1947, particularly on issues of communal polarizations, the formation of the border as well as the participation of non-political groups like the tribal populations who had very little stake in the playing out of the Radcliffe Line. Siddhartha Deb’s 2002 novel The Point of Return looks at some of these questions of identity and belonging that so plague the region. The novel is an exploration of the life journeys of Dr. Dam and his son Babu and their relationship to the geographical locations they come to inhabit. The spatial and temporal realities that came into being in the Northeastern region is charted through this text in the postcolonial state making practices that produce irreversible patterns of social and political chaos. Issues of ethnicity, language, and belonging that are contentious questions in this region are represented in this narrative as the continued precarity of people who had come to live here. This essay presents an analysis of the novel through the optics of history and literature, using tools from the Phenomenological analysis of Time by Paul Ricouer, to investigate how the interface of events and memory transform and complicate our understandings of a contentious divided past.

Multiband absorber design and optimization with Lorenz chaotic attractor

Metamaterials are artificial materials that don’t come from nature and have unusual electromagnetic properties. It has applications in many fields such as medical, image processing, signal absorption, invisibility cloak, sensor, and antenna. In this study, signal absorption of metamaterials was discussed and a simulation study was carried out. The most important difference of the proposed structure is that the pattern obtained from the Lorenz chaotic attractor was used in the resonator’s design, unlike the geometric shaped works. The chaos pattern consists of units that have both random shapes and sizes. Chaos can be defined as the order of disorder, which is extremely sensitive to initial conditions and has a broad power spectrum like noise. In addition, this study aims to contribute to the science of chaos. The resonator structure used in the proposed structure showed similar results with the studies in the literature. Rogers RT5870 material was used as substrate in the design. The proposed design is an eight-band structure with excellent signal absorption, partially insensitive to polarization and angle of incidence. The results show that the proposed design absorbs signals in the infrared region of the spectrum at 14.24, 15.44, 19.72, 21.04, 33.92, 35.16, 36.44 and 38.79 THz. Near-perfect signal absorption at the indicated frequencies is 97.98%, 98.73%, 99.85%, 92.03%, 95.62%, 92.56%, 96.21% and 97.09%, respectively. The proposed design includes heat sensor and thermal imaging etc can be used in application areas.

Chaos and firing patterns in a discrete fractional Hopfield neural network model

Chaos and firing patterns in a discrete fractional Hopfield neural network model

Lady Shallot and Her Nature in the Men's Fence; An Interdisciplinary Approach to Tennyson’s Poetry and Waterhouse Paintings

Alfred Lord Tennyson’s “The Lady of Shallot” is the portrayal of a woman’s active confrontation with the patriarchal society. By the woman’s seclusion from the social interactions, Tennyson debunks the bitter reality embedded within the social structure and by the lady’s manifestation of bravery in her social activism so as to prove her individuality, he depicts the annihilation of the woman in revolting against patriarchy. Parallel to the subjugation of femininity in the poem, ecology shows a pattern of tranquility and chaos through which masculine cultural codes reveal themselves. John William Waterhouse, a contemporary painter with Tennyson, has portrayed three suggestive scenes of the poem; how he portrays femininity and nature is the manifestation of patriarchal manipulation of the two aforementioned concepts. In congruence with the mentioned analysis, ecofeminism, by attributing resemblances to femininity and ecology, aims to divulge the patriarchal injustice inflicted upon them; by giving awareness about the rights of women and nature, it tries to rehabilitate their genuine identity. With the application of ecofeminism on Tennyson’s poem and Waterhouse’s paintings, with an interdisciplinary approach, the author discloses the patriarchal subordination of women and nature. I do hope that by the ecofeminist reading of “The Lady of Shallot” and its projected paintings, the authentic rights of femininity and ecology are defended, the importance of interdisciplinary studies is highlighted and the awareness about the original identity of these concepts is created.

Qualitative analysis of stochastic Schrödinger–Hirota equation in birefringent fibers with spatiotemporal dispersion and parabolic law nonlinearity

In this paper, the stochastic Schrödinger–Hirota equation in birefringent fibers with spatiotemporal dispersion and parabolic law nonlinearity is studied, which is usually used to describe the mathematical model of optical soliton propagation in dispersive optical fibers from the field of nonlinear optics. Firstly, the stochastic Schrödinger–Hirota equation is converted into two-dimensional planar dynamic system by using the traveling wave transformation. Secondly, the qualitative analysis of the stochastic Schrödinger–Hirota equation is discussed by using the theory of planar dynamical systems. Finally, the chaos pattern of the stochastic Schrödinger–Hirota equation with perturbed system is considered. What is more, phase portraits and sensitivity analysis of the perturbed system are plotted by using the Maple software.

Rossler’s system using piecewise derivative

This article deals with a piecewise system named piecewise Rossler’s system which exhibits a concept of piecewise derivatives based on Classical-power-law randomness, Classical Mittag-Leffler-law-randomness, and Classical fading memory randomness fractional operators. To examine the crossover and chaos patterns for Rossler’s system, we have revisited and modified Rossler’s system using the concept of a piecewise system. This paper focuses also on growing a forecasting piecewise system to establish states in chaotic aspects. The existence and uniqueness are obtained for piecewise Rossler’s system with the Caputo derivative. The numerical solutions are based on Newton interpolation. Numerical solutions have been developed to approximate these piecewise derivatives. The obtained results show real-world behaviors of Rossler’s systems with piecewise patterns at various values of order α.

Exploring the recent trends in Big Data Analysis

Big Data is a collection of technologies developed to store, analyze and manage this data. It is a macro tool. Today it is used in fields as diverse as medicine, agriculture, gambling and environmental protection. Machine learning, forecasting Companies use big data to streamline their marketing campaigns and techniques. Modeling and other advanced analytics applications enable big data organizations to generate valuable insights. Companies use it in machine learning. Programs cannot balance large data in any particular database. When datasets are large in size, velocity, and volume, the following three distinct dimensions constitute "big data." Examples of big data analytics include stock markets, social media platforms, and jet engines. But it is growing exponentially with time. Traditional data management tools cannot store or process it efficiently. It is a large scale technology developed by Story, Analysis and Manoj, Macro-Tool. Find patterns of exploding confusion in information about smart design, however, implying that various big data structures are structured, whether this includes the amount of information, the speed with which it is generated and collected, or the variety or scope of related data points. In the past, data was collected only from spreadsheets and databases of large, disparate information that grew at an ever-increasing rate. Very large, complex data refers to large amounts of data for sets that are impossible to analyze with traditional data processing applications. Is software configuration used to handle the problem? Apache is an advanced application for storing and processing large, complex data sets and analyzing big data. Analytical techniques against very large, heterogeneous databases containing varying amounts of data, big data analytics help businesses gain insights from today's massive data sources. Defined as software tools for processing and extraction. People, companies and more and more machines are now developing technologies to analyze more complex and large databases that cannot be handled by traditional management tools. It is designed to discover patterns of chaos that explode in information in order to design smart solutions.

Chaos, Complexity and Resilience: A Review and Research Agenda

The objectives of this paper are (a) to purposively review recent literature based on chaos, complexity and resilience theories and (b) to indicate the applicability of these theories to wider business and social contexts. We believe that the pandemic of Covid-19 has introduced an additional dimension to various decision making process in different forms of social and business organisations. At the least, the concepts of social distancing and its practice is the delta change of the theory of chaos with wider and meaningful repercussions. Secondly, as postulated by the theory of chaos and complexity, the path traversed from one state to another is not exactly reversible. The pandemic related changes may not be reversible in future. There is a need for discussion on various possibilities of outcomes, finding patterns in chaos and complexity. During the Covid-19 pandemic many individuals have undergone the trauma of personal suffering, loss of near and dear ones. The delay in access to medical supervision due to capacity mismatch, inadequate knowledge, confusion regarding the policy response, and public response to rules are some of the additional dimensions of complexities experienced. At the same time, individuals and organisations have demonstrated resilience to overcome adversities. There is a contextual necessity and opportunity to extend our knowledge base. This review discusses illustrative but non-exhaustive researches conducted so far in different social science and business organisations to help conceptualisation of future researches. The structure of the paper includes a brief introduction, the theories, application and conclusion.

Modeling third waves of Covid-19 spread with piecewise differential and integral operators: Turkey, Spain and Czechia

Several collected data representing the spread of some infectious diseases have demonstrated that the spread does not really exhibit homogeneous spread. Clear examples can include the spread of Spanish flu and Covid-19. Collected data depicting numbers of daily new infections in the case of Covid-19 from countries like Turkey, Spain show three waves with different spread patterns, a clear indication of crossover behaviors. While modelers have suggested many mathematical models to depicting these behaviors, it becomes clear that their mathematical models cannot really capture the crossover behaviors, especially passage from deterministic resetting to stochastics. Very recently Atangana and Seda have suggested a concept of piecewise modeling consisting in defining a differential operator piece-wisely. The idea was first applied in chaos and outstanding patterns were captured. In this paper, we extend this concept to the field of epidemiology with the aim to depict waves with different patterns. Due to the novelty of this concept, a different approach to insure the existence and uniqueness of system solutions are presented. A piecewise numerical approach is presented to derive numerical solutions of such models. An illustrative example is presented and compared with collected data from 3 different countries including Turkey, Spain and Czechia. The obtained results let no doubt for us to conclude that this concept is a new window that will help mankind to better understand nature.

Application of particle swarm optimization with ANFIS model for double scroll chaotic system

The predictions for the original chaos patterns can be used to correct the distorted chaos pattern which has changed due to any changes whether from undesired disturbance or additional information which can hide under chaos pattern. This information can be recovered when the original chaos pattern is predicted. But unpredictability is most features of chaos, and time series prediction can be used based on the collection of past observations of a variable and analysis it to obtain the underlying relationships and then extrapolate future time series. The additional information often prunes away by several techniques. This paper shows how the chaotic time series prediction is difficult and distort even if Neuro-Fuzzy such as Adaptive Neural Fuzzy Inference System (ANFIS) is used under any disturbance. The paper combined particle swarm (PSO) and (ANFIS) to exam the prediction model and predict the original chaos patterns which comes from the double scroll circuit. Changes in the bias of the nonlinear resistor were used as a disturbance. The predicted chaotic data is compared with data from the chaotic circuit.

Spatiotemporal Complexity Analysis for a Space-Time Discrete Generalized Toxic-Phytoplankton-Zooplankton Model with Self-Diffusion and Cross-Diffusion

In this paper, a couple map lattice (CML) model is used to study the spatiotemporal dynamics and Turing patterns for a space-time discrete generalized toxic-phytoplankton-zooplankton system with self-diffusion and cross-diffusion. First, the existence and stability conditions for fixed points are obtained by using linear stability analysis. Second, the conditions for the occurrence of flip bifurcation, Neimark–Sacker bifurcation and Turing bifurcation are obtained by using the center manifold reduction theorem and bifurcation theory. The results show that there exist two nonlinear mechanisms, flip-Turing instability and Neimark–Sacker–Turing instability. Moreover, some numerical simulations are used to illustrate the theoretical results. Interestingly, rich dynamical behaviors, such as periodic points, periodic or quasi-periodic orbits, chaos and interesting patterns (plaques, curls, spirals, circles and other intermediate patterns) are found. The results obtained in the CML model contribute to comprehending the complex pattern formation of spatially extended discrete generalized toxic-phytoplankton-zooplankton system.

A Case of Pigmented Bowen Disease on the Finger Mimicking Melanoma Showing a Chaos Pattern on Dermoscopy.

A Case of Pigmented Bowen Disease on the Finger Mimicking Melanoma Showing a Chaos Pattern on Dermoscopy.

Seeking Patterns in Chaos: Transactional Federalism in the Trump Administration’s Response to the COVID-19 Pandemic

The federal government’s response the novel coronavirus (COVID-19) pandemic has been marked by a series of apparently disjointed, chaotic, and confusing statements and actions on the part of both the White House and federal agencies charged with coordinating the federal response. These actions have left many state governors (and citizens) in a position to address the effects of the pandemic in a haphazard and atomistic manner. In this essay, we contend that the actions of the Trump administration, and its relationships with states and local governments, can best be understood through a lens of what we refer to as “transactional federalism,” in which federalism relationships are governed by a set of exchanges between the president and states, and between states. We conclude by discussing the ramifications of this form of federalism.

Narratives of Gestational Diabetes Provide a Lens to Tailor Postpartum Prevention and Monitoring Counseling.

Women with gestational diabetes mellitus (GDM) have a marked increased risk of early onset type 2 diabetes, but less than half initiate postpartum glucose testing or connect with a primary care provider for continued follow-up after giving birth. This study analyzed women's narratives about their GDM-affected pregnancies to (1) identify different patterns (narrative archetypes) that capture the GDM experience; (2) explore how these patterns relate to awareness of ongoing risk after pregnancy and affect participation in self-care, monitoring, and preventive health care going forward; and (3) explore the use of identified patterns to tailor conversations with patients during prenatal and postpartum care to their actual perceptions and concerns about future risk. Open-ended interviews elicited women's experiences and perspectives about GDM and its management. A narrative analysis first identified segments of text related to risk and behaviors and then applied Frank's narrative archetypes (restitution, chaos, quest) as an interpretive lens. Interviews were completed in English (n = 15), Spanish (n = 7), and Haitian Creole (n = 7). We found distinct patterns: stories of restitution (n = 13), quest (n = 4), chaos (n = 4), and mixed narratives (n = 7). Using these archetypes, we found differences in how women respond to challenges related to disease complexity, treatment, and future risks. These patterns led to marked differences in the steps women took to prevent early onset type 2 diabetes. Frank's narrative types provided insight into women's responses to clinical protocols, health care advice, and subsequent prevention actions. A restitution pattern may result in premature closure and lack of awareness of risk. Similarly, a chaos pattern may contribute to a sense of helplessness to implement follow-up recommendations, despite risk awareness. Understanding these patterns can help clinicians tailor individualized support as women transition from GDM with its focus on a healthy fetus and newborn to preventive self-care to protect their health.

Recurrence Behavior Statistics of Blast Furnace Gas Sensor Data in Industrial Internet of Things

Blast furnace gas (BFG) produced from steel industries is generally one of the most important energy supplies in enterprises. Due to a great deal of output, fluctuation, and heterogeneity in data, it is very difficult to provide profound insights into its internal dynamic. In this article, a novel analysis framework is developed for the BFG data processing, considering the recurrence plot (RP) and the recurrence quantification analysis (RQA). The specific aim is to investigate the relationship between BFG output and its potential influencing factors. This framework can be deemed as a uniform and consistent system with functional components of qualitative visualization and quantitative analysis. Concretely, the BFG outputs related to five factors are separately projected to high-dimensional spaces, followed by that their internal dynamics can be embodied through a 2-D recurrence representation of states. Finally, five RQA parameters are used to quantify the influence of these factors on the BFG output. This is the first attempt revealing the relations among the BFG data from the qualitative and quantitative perspectives. The experimental results show that RP can discover the BFG output patterns of laminar state, chaos, and instability over given three states of influencing factors, and the ranked influential degree can be given by a two-stage standard deviation of all considered RQA measures. Besides, we also demonstrate that the temperature of the hot-blast stove is most relevant to the BFG output, while the influence of considered other factors directly depends on the selected series length.

Chaos in the switched reluctance motor drive employing digital speed and current control

Adjustable speed motor drives are among the most representative types of non-linear systems which can exhibit rich varieties of complex dynamic behaviours. This study presents the investigation of chaotic phenomena in the switched reluctance (SR) motor drive employing digital speed regulator and hysteresis current controller. For conducting stability analysis, a small signal discrete-time model of the SR drive has been derived and analysed for a range of control parameters. The simulation results of time-domain and frequency-domain analysis and phase portraits of the SR drive system are also demonstrated and discussed. Two influencing factors for chaotic behaviour in the SR drive system are identified and examined in detail: the feedback delay of the speed regulator and measurement imperfection from a rotary incremental encoder. For verification, an 8/6 pole 2.3 kW SR drive is employed in experimental tests. The bifurcation diagrams of the reference signal, waveforms of phase current, and the corresponding frequency spectra are recorded and illustrated for both normal and chaotic operations, which reveal the pattern of chaos exhibited from this type of electric drive system.

Thermocapillary convection of a binary mixture with the Soret effect in a shallow annular pool heated from below

In order to reveal the features of the thermocapillary convection of a binary mixture (toluene/n-hexane mixture with an initial mass fraction of 0.2627) with the Soret effect in a shallow annular pool, a large number of unsteady numerical simulations were conducted. The shallow annular pool is heated from below with an increasing linear temperature from the inner to outer cylinders, and lateral cylinders are adiabatic. The upper free surface is open to the atmosphere. Biot (Bi) number varies from 0 to 2. Results indicate that the increasing Biot number enhances thermocapillary convection and has an obvious influence on the solute concentration profile generated by the Soret effect. As Biot number is increased, the solute concentration difference from the inner to outer cylinders increases; thus, the critical thermal capillary Reynolds number for the destabilization of the basic flow and the fundamental oscillation frequency near the critical point decrease. After the three-dimensional oscillatory flow appears, thermocapillary convection bifurcates continually from the hydrothermal waves to the flower patterns at a large thermal capillary Reynolds number when Bi = 0. At 0 < Bi ≤ 0.6, the flow evolves from the hydrothermal waves to chaos directly. However, at 0.6 < Bi ≤ 2, the multicellular state, the hydrothermal waves and chaos patterns appear orderly. Furthermore, the fundamental oscillation frequency rises up with the thermal capillary Reynolds number for all Biot numbers.