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Chaos theory offers a unique lens to understand the intricate relationships between economic growth and energy supply pricing. Existing economic theories often emphasize energy prices' inherent randomness, unpredictability, and economic growth. A deeper comprehension can be achieved by applying chaos theory to this complex system. Developing a dynamic model that captures the causal relationships among the various variables impacting economic growth, energy supply, and pricing is crucial for unraveling this complexity. This study aims to delve into the chaotic nature of the energy economy system within the context of economic growth. The research methodology is rooted in a fundamental-applied approach. By employing numerical simulation techniques, specifically utilizing the Simulink MATLAB toolbox, the study seeks to explore and potentially control chaos within the system. The findings highlight the system's nonlinear dynamics, showcasing its sensitivity to initial conditions and exhibiting chaotic behavior, limit cycles, and stable equilibrium points across varying initial values. This research endeavor contributes to a more nuanced understanding of the interplay between energy economics, economic growth, and pricing dynamics.

The present paper provides a historical context for chaos theory, originating in the 1960s with Edward Norton Lorenz's efforts to predict weather patterns. It introduces chaos theory, fractal geometry, nonlinear dynamics, and the butterfly effect, highlighting their exploration of complex systems. The authors aim to bridge the gap between chaos theory and oral and maxillofacial surgery (OMFS) through a literature review, exploring its applications and emphasizing the prevention of minor deviations in OMFS to avoid significant consequences. A comprehensive literature review was conducted on PubMed, Web of Science, and Google Scholar databases. The selection process adhered to the PRISMA-ScR guidelines and Leiden Manifesto principles. Articles focusing on chaos theory principles in health sciences, published in the last two decades, were included. The review encompassed 37 articles after screening 386 works. It revealed applications in outcome variation, surgical planning, simulations, decision-making, and emerging technologies. Potential applications include predicting infections, malignancies, dental fractures, and improving decision-making through disease prediction systems. Emerging technologies, despite criticisms, indicate advancements in AI integration, contributing to enhanced diagnostic accuracy and personalized treatment strategies. Chaos theory, a distinct scientific framework, holds potential to revolutionize OMFS. Its integration with advanced techniques promises personalized, less traumatic surgeries and improved patient care. The interdisciplinary synergy of chaos theory and emerging technologies presents a future in which OMFS practices become more efficient, less traumatic, and achieve a level of precision never seen before. [ABSTRACT FROM AUTHOR]

ABSTRACT:This Research enables the studying of scientific essence and extracting their laws to the artist for perceiving the relationships and the systems that enriching both oF Innovation and creativity to him , In goth century , It appeared many of intellectual and philosophical theories and the chaos theory is an important of them that considered as of mathe and physical recently theary that took a curriculum in thinring throughout the total cognitive integration and recomstruction of the elements and the trace structural systems associated with shape and randomness , the research problem was identified in the followting question IS it possible to reveal some athetic solutions to the systems on which the chaos theory is based to be anew entry point for updating intellectual and technical practices in the fields of drawing and painting ? and the research was aimed to enriching and developing mental imagination broadening the artistic vision and variety of the students , and the importance of the research becomes clear to comtribute to opening the field of becomes clear to comtribute to opening the field of experimentation as one of the important entrances to finding plastic solutions based om benefiting from the chaos theory as an experimental basis for con structing contem porary porary figurative paintings .The research adopts the descriptive analyticai and empirical approach one of the results of the research is that the chaos theory is replete with aesthetic solutions that enrich intellectual and technical practices . The research recommends deepening the study of scientific theories and searching for innovative performance methods in various branches of plastic art in general and in the field of drawing and painting in particular .

Starting from the contribution of such thinkers as the famous Giordano Bruno (1583) and the great mathematician and physicist Henri Poincaré (1889) and the surprising discovery of the meteorologist Edward Lorenz (1963), we consider the expansion of the mathematics of chaos in this article, paying attention to topology, qualitative geometry, and Catastrophe Theory, on the one hand, and addressing the possibilities derived from the new Computer Science as Quantum Algorithms and the advances in Artificial Intelligence, on the other. We especially highlight the section on computing chaos, which we consider to be new calculation and analysis instruments, such as machine learning and its algorithm called reservoir computing, through which we can know the dynamics of a chaotic system. With past data, with equations like Karamoto–Sivashinsky, one can improve predictions of the system eight times further ahead than in previous methods. Integrating the machine learning approach and traditional model-based prediction, one could obtain accurate predictions twelve Lyapunov times. As we know, in the framework of chaos theory, it is habitually accepted that the idea of long-term prediction seems impossible because we live under a veil of uncertainty. But with technological advances, the landscape begins to change, both in chaos theory and in its applications, especially in the field of economics, to which we devote particular attention, carrying out as an example the analysis of the evolution of the Madrid Stock Exchange in the 2006–2013 crisis. Above all this, a reflection of a general nature is necessary to enlighten us on the possibility of opening a new horizon. [ABSTRACT FROM AUTHOR]

Chaos theory studies the irregular, the discontinuous, the non-linear. Shifting away from determinism and scientific explanations rooted in reductionistic models, it brings a revolution by revealing that the universe has an inherent contradictory nature. Chaos raises philosophical questions and confronts us with paradox. How can we live in a universe ruled by physical laws and yet is unpredictable? How can certainty and uncertainty, stability and turbulence, simplicity and complexity co-exist? The insights of chaos are inherent to existentialism. Two radical theories – one scientific, one philosophical – reach similar conclusions by questioning our current understanding and our connection to the familiar. I would like to highlight how they can be an inspiration and a paradigm as models that challenge assumptions and the dominant scientific traditions using creative doubt and humble curiosity, and immerse into their mutual offerings and perceptions. [ABSTRACT FROM AUTHOR]

The security of patient data is a critical problem for health networks due to the rising popularity of telehealth services and the requirements for clinical data sharing between surgeons, consultants, and medical groups. In contrast to protecting medical data, which includes the cover (i.e., clinical picture), the requirements for protecting other pertinent data are more general. The paper advocates for data encryption before concealment as a robust strategy to uphold patient privacy during medical information exchange. The primary focus of this analysis revolves around a comprehensive exploration of different steganography methods. Through a meticulous examination of various steganographic techniques, including LSB, PVD, and transform domain approaches, this paper provides a detailed analysis of their strengths and limitations. Objective metrics like PSNR and SSIM are employed to dissect the trade-offs between data security and visual fidelity. The research leads to the conclusion that the diagonal queue-based steganog-raphy methodology, supported by chaotic methods, the Linear Feedback Shift Register (LFSR), and the durable Rabin encryption system, is the best course of action. This method enables autonomous data transmission among numerous contacts while ensuring the highest level of confidentiality and integrity of patient data inside e-health networks. In summary, this study provides a comprehensive solution that protects patient data and speeds data transmission inside the expanding framework of e-health networks in order to meet urgent data security concerns in telemedicine and healthcare data exchange. [ABSTRACT FROM AUTHOR]

Abstract This article introduces and formalizes a novel stochastic method that combines inverse simulation with the theory of generalized Polynomial Chaos (gPC) to solve and study inverse problems under uncertainty in energy system design applications. The method is particularly relevant to design tasks where only a deterministic forward model of a physical system is available, in which a target design quantity is an input to the model that cannot be obtained directly, but can be quantified reversely via the outputs of the model. In this scenario, the proposed method offers an analytical and direct approach to invert such system models. The method puts emphasis on user-friendliness, as it enables its users to conduct the inverse simulation under uncertainty directly in the gPC domain by redefining basic algebra operations for computations. Moreover, the method incorporates an optimization-based approach to integrate supplementary constraints on stochastic quantities. This feature enables the solution of inverse problems bounding the statistical moments of stochastic system variables. The authors exemplify the application of the proposed method with proof-of-concept tests in energy system design, specifically performing uncertainty quantification and sensitivity analysis for a Multi-Energy System (MES). The findings demonstrate the high accuracy of the method as well as clear advantages over conventional sampling-based methods when dealing with a small number of stochastic variables in a system or model. However, the case studies also highlight the current limitations of the proposed method such as slow execution speed due to the optimization-based approach and the challenges associated with, for example, the curse of dimensionality in gPC.

In this study, collaboration has been revisited between an American faculty member and an international graduate teaching assistant during a unique faculty-student mentoring model within principles of chaos theory. The role of culture, beliefs about language learning and teaching had been studied closely to improve faculty/international students' cooperation in academic settings. The research focused on the nature of the collaborative experience of a faculty member and a graduate teaching assistant in designing and implementing an authentic language learning experience into a graduate level linguistic course and the role of dynamism and chaos theory evident in this mentoring model. Participants engaged in collaborative planning of a language learning experience embedded into a graduate level linguistic course. Reflective journals of participants and assignments were analyzed to better understand the experiences of the collaborators and the ways their culture, beliefs, and mentoring model impacted andragogical choices for instruction and learning of participants and students. Through self-study, the researchers explored their professional identity and their academic flexibility within the organizational boundaries. The results of the study unveiled the complexity and chaos of each phase of cooperation and how the participants applied flexibility to achieve a more linear teaching/learning process. The collaboration between American faculty and international GTA under the shadow of chaos twisted by culture, beliefs, and hierarchy could still generate novice andragogical practices in higher education to contribute implications for collaborative work across cultures and hierarchies.

Abstract Background This research delves into the complexity management of collaborative networks and interorganizational systems in the health innovation ecosystem on the basis of a best practice in the coronavirus disease 2019 (COVID-19) crisis. The objective is to offer specific solutions and guidelines to stakeholders in the health innovation ecosystem to control the chaos resulting from unexpected events along the ecosystem development and evolution path. Methods For this purpose, the performance of the Health Innovation Ecosystem in Iran (the Every Home is a Health Base plan) has been examined through a detailed and in-depth analysis of events and actions taken using documents, reports and interviews with experts. The practical application of chaos and complex adaptive system features (adaptation, time horizons, edge of chaos, sensitivity to initial conditions, state space and strange attractors) is introduced to identify and manage the transition from a state where the health innovation ecosystem is on the edge of chaos and prone to failure. Data were collected through studying documents, reports and interviews with experts, and then analysed using qualitative content analysis techniques, open and axial coding and metaphors derived from complexity and chaos theories. Results The findings indicate that to understand and embrace the complexity of the health innovation ecosystem throughout its development and evolution and manage and lead it through the edge of chaos towards successful interorganizational systems performance, it is necessary to use gap analysis to achieve consensus, establish a highly interactive governance structure with key stakeholders of the ecosystem, maintain flexibility to control bifurcations (butterfly effect), prevent transforming emergency solutions into standard routines and ensure the sustainability of the ecosystem against future threats by long-term financial security. Conclusions This research provides insights into the dynamics of complex health systems and offers strategies for promoting successful innovation through collaborative networks and interorganizational systems in the development and evolution of the health innovation ecosystem. By embracing complexity and chaos, healthcare professionals, policy-makers and researchers can collaboratively address complex challenges and improve outcomes in health network activities. The conclusion section provides guidelines for successfully managing the complexity of the ecosystem and offers suggestions for further research.

Institutional and Chaos Theory are frameworks in organizational behavior that have existed for many years. Given their long-term popularity in said field, it is important to have a strong working knowledge of each theory and be able to compare and contrast them. Both theories are wholly applicable to current world happenings, such as the COVID-19 pandemic and the Black Lives Matter movement. By inspecting this paper, readers will learn about Institutional and Chaos Theory, be able to identify how they relate to timely world occurrences, discover their implications in regard to public policy and public administrations, and reflect upon how they can be useful in respect to other organizational and global matters.

Swarm robotics can cooperatively perform large, multiple tasks by controlling a swarm composed of many robots. Currently, approaches for operating multiple robot swarms are being studied for further evolution of this system. This study addresses a multiple movement task in which robot swarms move collectively in the same environment. In this task, the movement paths of robot swarms must pass each other in a cooperative manner when they intersect. The robots in this system behave under autonomous distributed control, thus must consider a passing behavior suitable for their own situation. This study proposes a turning behavior based on the chaos theory to ensure that a robot swarm avoids other approaching robot swarms. Each robot swarm applying the proposed method passes other swarms while autonomously deciding its turning direction and continuing its own collective movement task. In addition, the decision making based on the chaos theory predicts future values according to the current value. Therefore, it is expected to be useful for task scheduling. The performance of multiple robots passing each other is evaluated with the proposed method using numerical simulations. This performance shows that the robot swarms can avoid each other without collision using the closest inter-robot distance as the evaluation metric. Finally, robot swarms with varying shapes and scales complete their own movements in an environment where these movement paths intersect at a single point. [ABSTRACT FROM AUTHOR]

In acknowledging the contribution of the Australian Journal of Career Development (AJCD's) continuing work to the career development field, this paper briefly outlines the Chaos Theory of Careers (CTC) and its empirical support. Issues relating to closed and open system validation are canvassed. Two types of COVID-19 case study are analysed: a diary study and the pandemic event itself. COVID-19 confirms the CTC's claim that we all live on the edge of chaos.

Feature selection is a knowledge discovery tool to understand the problem by analysing features. In particular, the application of feature selection in data mining can not only improve the quality of extracted patterns and knowledge but also decrease computational costs. Various techniques have been applied to this complex optimization problem, in which metaheuristics have been validated to be superior. This study introduces a new metaheuristic known for having lean and fast programming, inspired by the sunflower's motions for feature selection for the first time. It is equipped with a v‐shaped transfer function and associated with the KNN classifier to become the binary sunflower optimization (BSFO). A total of 12 variants of BSFO are designed based on the chaos theory and Lévy flights, called improved binary sunflower optimization (IBSFO). A discussion between these improvement theories for feature selection has also not been made yet, and it is performed in this paper using 15 benchmark datasets from the UCI repository. The experimental results show that all variants can advance the fitness value of BSFO, and nine of them considerably decrease the computational costs. Furthermore, the chaotic BSFO with the Chebyshev function, taking replacement to normal rand, has the lowest fitness value (−11.37%) and execution time (−9.31%) than the original BSFO. Further, IBSFO is compared with another eight metaheuristics and outperforms these competitors on average fitness value and execution time. Overall, IBSFO proved to find subsets with reduced dimension and high accuracy with meagre computational cost due to its robust explorative and exploitative capacities. [ABSTRACT FROM AUTHOR]

The marketplace of ideas is the Supreme Court’s dominant tool for rationalizing expansive First Amendment safeguards. The model, however, is fundamentally flawed. Enlightenment-based assumptions about truth and human rationality that justices installed into the theory’s foundations have been criticized by scholars and, in the era of powerful algorithms and generative AI, are becoming even more suspect. The space is in a state of chaos. Perhaps chaos theory can help. The theory provides a lens through which to revise marketplace theory and therefore re-examine First Amendment free-expression rationales. Chaos theory identifies that Enlightenment-era positivistic, reductionist thinking fails to account for variables and does not allow for linear outcomes. A chaosinfused marketplace accounts for human diversity and revises truth assumptions. [ABSTRACT FROM AUTHOR]

The number of studies based on chaos theory is quite high. Therefore, it is important to analyze chaos theory’s development over the years deeply. However, there is no study in the literature examining the research status of this field. The article presents the bibliometric analysis of the studies on the keywords “Chaos Theory” and “Applications” indexed in Scopus between 1987 and 2021. This study aims to quantitatively evaluate the academic output in chaos theory research, make sense of the data, reveal the state of scientific knowledge in the field, and provide scientists with a general perspective on the subject. Bibliometrix and Microsoft Excel programs were used for bibliometric analysis. Nine thousand one hundred different authors identified a total of 5088 studies. Of these studies, 60.3% were research articles, and 32.9% were conference papers. Chaos Solitons and Fractals was the most published journal, with 206 articles. Only China and the USA contributed 39.7% to the studies. Vaidyanathan, S. was the most prolific author with 72 articles. Vel Tech Rangarajan Dr. Sagunthala R D Institute of Science and Technology was the most productive institution with 74 studies. The most cited article was the econometrics of financial markets.