Homographic Research Articles

A refined grey Verhulst model for accurate degradation prognostication of PEM fuel cells based on inverse hyperbolic sine function transformation

A refined grey Verhulst model for accurate degradation prognostication of PEM fuel cells based on inverse hyperbolic sine function transformation

A Mobius transformation-based liftoff effect reduction method for crack classification and prediction in eddy current testing

In eddy current (EC) defect evaluation, accurate determination of the crack depth is crucial. The lift-off signal on the complex impedance plane is not necessarily horizontal and mostly arc-shaped, which makes it difficult to separate from crack signals, which can have various orientations depending on probe characteristics and frequencies. Phase rotation is normally used to align the lift-off signal to the real axis and defect signal is read from the imaginary axis. However, this approach proves challenging to separate lift-off and defect signals within the complex plane in many cases.To address this issue, this study proposes and implements a Mobius transformation that linearizes the arc-shaped lift-off signals on the complex plane, enabling more accurate extraction of crack signals unaffected by lift-off signal height. Furthermore, it is demonstrated through k-nearest neighbors (kNN) that the transformed crack signals can still be effectively quantified.

A multi-stakeholder engagement framework for material-building-city synergy through circular transformation

Scholars, industrial stakeholders, and governmental institutions are developing the circular economy paradigm. However, the emergence of multiple perspectives has challenged its implementation. As the industry that is the biggest contributor to the negative impacts on the environment, the construction industry stakeholders are paving the way for more sustainable as well as circular and regenerative construction by considering all actors in the system. Yet, the construction industry has a complex supply chain that requires clear strategies and stakeholder engagement across materials, buildings, and cities for efficient flows in the supply chain. Nonetheless, there is a need for improvement in the engagement of construction stakeholders for circular transformation. Therefore, this study aims to develop a multi-stakeholder engagement framework through circular transformation to guide the decision-makers for circular city governance. It has identified critical success factors by considering the construction stakeholders. The framework includes strategies at the micro (material), meso (building), and macro (city) scales to strengthen the material-building-city synergy. It's a significant step toward advancing circular city governance by bridging the gap between theoretical understanding and practical implementation and establishing a robust engagement for material-building-city synergy. The study employs a systematic literature review to extract strategies and natural language processing to analyze the strategies by topic modeling and defines critical success factors for multi-stakeholder engagement at multiscale. The outcome introduces the REVERT framework, bridging resource, envisagement, validation, entity, regulation, and technology, to facilitate a seamless transition by material-building-city synergy advancing circular city governance.

Automated long-term monitoring of stereotypical movement in polar bears under human care using machine learning

The welfare of animals under human care is often assessed by observing behaviours indicative of stress or discomfort, such as stereotypical behaviour (SB), which often shows as repetitive, invariant pacing. Traditional behaviour monitoring methods, however, are labour-intensive and subject to observer bias. Our study presents an innovative automated approach utilising computer vision and machine learning to non-invasively detect and analyse SB in managed populations, exemplified by a longitudinal study of two polar bears. We designed an animal tracking framework to localise and identify individual animals in the enclosure. After determining their position on the enclosure map via homographic transformation, we refined the resulting trajectories using a particle filter. Finally, we classified the trajectory patterns as SB or normal behaviour using a lightweight random forest approach with an accuracy of 94.9 %. The system not only allows for continuous, objective monitoring of animal behaviours but also provides insights into seasonal variations in SB, illustrating its potential for improving animal welfare in zoological settings. Ultimately, we analysed 607 days for the occurrence of SB, allowing us to discuss seasonal patterns of SB in both the male and female polar bear monitored. This work advances the field of animal welfare research by introducing a scalable, efficient method for the long-term, automated detection and monitoring of stereotypical behaviour, paving the way for its application across various settings and species that can be continuously monitored with cameras. We made the code publicly available at https://github.com/team-vera/stereotypy-detector.

Gravitational wavefunctions in JT supergravity

We determine explicit expressions for the continuous two-sided gravitational wavefunctions in supersymmetric versions of JT gravity, focusing mainly on N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{N} $$\\end{document} = 2 JT supergravity. Our approach is based on representation theory of the associated supergroup, for which we determine the relevant mixed parabolic matrix elements that implement asymptotic AdS boundary conditions at the quantum level. We match our expressions with those found by solving the energy-eigenvalue equation [1]. We discuss gravitational applications by computing several amplitudes of interest, and address how our framework can be generalized further.

Asymptotic behaviour of the confidence region in orbit determination for hyperbolic maps with a parameter

When dealing with an orbit determination problem, uncertainties naturally arise from intrinsic errors related to observation devices and approximation models. Following the Least Squares Method and applying approximation schemes such as the differential correction, uncertainties can be geometrically summarized in confidence regions and estimated by confidence ellipsoids. We investigate the asymptotic behaviour of the confidence ellipsoids while the number of observations and the time span over which they are performed simultaneously increase. Numerical evidences suggest that, in the chaotic scenario, the uncertainties decay at different rates whether the orbit determination is set up to recover the initial conditions alone or along with a dynamical or kinematical parameter, while in the regular case there is no distinction. We show how to improve some of the results in Marò and Bonanno (2021), providing conditions that imply a non-faster-than-polynomial rate of decay in the chaotic case with the parameter, in accordance with the numerical experiments. We also apply these findings to well known examples of chaotic maps, such as piecewise expanding maps of the unit interval or affine hyperbolic toral transformations. We also discuss the applicability to intermittent maps.

Supply chain transformative capabilities and their microfoundations for circular economy transition: A qualitative study in Made in Italy sectors

AbstractIn today's rapidly evolving landscape, supply chains must develop specific dynamic capabilities for initiating and successfully governing their transformations toward new configurations to withstand pressures arising from competitions and global changes. Differently from dynamic capabilities that enable adaptation, supply chain transformative capabilities include four core dimensions: triggering, envisioning, navigating, and stabilizing capabilities. By using a multiple‐case study approach involving six Italian companies related to fashion and furniture sectors, we investigate these concepts and identify the microfoundations of supply chain transformative capabilities for circularity. They are classified with reference to individuals, processes, and structures. Our findings illustrate how supply chains can facilitate and effectively govern their circular transformation by developing the transformative capabilities and their microfoundations. This paper provides valuable theoretical insights and managerial perspectives, advancing the concept of transformative supply chain management.

Mapping Service-Based Retailing to Improve Sustainability Practices in the Fashion Industry

The fashion industry is recognized among the most impactful industries in relation to environmental and social damage due to unsustainable models. While countless research studies focus on the supply chain and product innovation, the presented inquiry studies the fashion retail sector with the goal of systematizing existing sustainable practices based on service offerings. We present the results of an extensive case-study analysis conducted on 370 initiatives of different natures gathered among international companies and local actors in the European context that offer services oriented toward sustainability. As a result, we propose an ontology that encompasses three areas (services for environmental sustainability, culture of sustainability, and implementation of social sustainability) and comprehensively describes existing sustainability strategies for helping retailers preserve the environment, while promoting socially inclusive practices and disseminating the culture of sustainability. The innovation of retailing from a similar perspective aims at rendering businesses more resilient to survive market and social transformations, especially in consideration of the boost to sustainable and circular transformation advocated by recent European legislation.

A note on the dislocation hyperbolic transformation function

In work of Roman A. Polyak [R.A. Polyak, Math. Program. 92 (2002) 197–235.], the Modified Chen-Harker-Kanzow-Smale (CHKS) function was studied to relate a multiplier method and an Interior Prox method with the second order distance function. Independently, the dislocated hyperbolic penalty function (DHPF) was proposed by A.E. Xavier (1992). DHPF was rewritten and studied in [L. Mallma Ramirez, N. Maculan, A.E. Xavier and V.L. Xavier, RAIRO:RO 57 (2023) 2941–2950.] and [L. Mallma Ramirez, N. Maculan, A.E. Xavier and V.L. Xavier, J. Convex Anal. To appear (2024).]. Thus, this function was called the dislocated hyperbolic function (DHF). In this work, we note that DHF is a particular case of CHKS function. Then we will call the DHF function as the dislocation hyperbolic transformation function.

Building a model for evaluating the efficiency of circular transformations in the context of technology transfer

The object of this study is the process of circular transformations in the context of technology transfer. It has been proven that circular transformations in the context of technology transfer are a new challenge in the global directions of harmonization of economic processes. The relevance of the study is determined by the fact that the development of technologies, in particular "green" technologies under modern conditions has become a catalyst for changes in production, consumption, and management of resources, which contributes to the achievement of the goals of sustainable development of enterprises. This involves focusing on the formation and support of social integration of the production sector and society, reducing emissions into the environment, and ensuring the balanced development of business entities at different levels of management. The characteristics of the level of circular transformations in the countries of the world were studied. The relationship between technology transfer and circular transformations was established through indicators of the degree of greening of the economy. A SWOT analysis of circular transformations was conducted to identify key opportunities and threats that would affect the business environment. A model for evaluating the effectiveness of circular transformations has been built. Based on the proposed model, the GDP change forecast for the EU countries for 2023–2027 was calculated. Carbon dioxide emission trends were predicted under optimistic and pessimistic scenarios, which made it possible to justify the need to transition to a carbon-neutral model of economic development and the feasibility of implementing "green" technologies. The transition to a new model of economic development will allow for optimal management of depleted resources, wider use of resource-saving technologies and will reduce pressure on the environment

Полихудожественное взаимодействие обучающихся во время построения лингвокультурных сценариев как средство обогащения тематического словарного запаса студентов – будущих переводчиков (на примере английского языка)

The purpose of the study is to determine the influence of poly-artistic methodological support for the study of linguistic and cultural scenarios on the formation of lexical and grammatical foreign language skills among students at the Faculty of Translation. The initial understanding of the cognitive approach to teaching foreign languages in a narrow sense (only as a system-theoretical support for processes) led to its underestimation and oblivion. The article examines the current trends towards borrowing individual components of the cognitive approach for the development of a communicative method of learning foreign languages. The scientific novelty of the research consists in the introduction of a poly-artistic approach in the training of students – future translators through the adaptation of professional highly specialized exercises for the training of future actors, directors and theater critics for their subsequent integration into the process of studying English-language frame models and scenarios, which had not previously become the object of research. The relevance of the study lies in the fact that, despite many years of experience using a communicative approach in teaching foreign languages, many students still face difficulties activating passive thematic vocabulary and grammatical rules and, as a result, a language barrier. As a result of the study, it was found that in conditions of meaningful operation of language and speech skills, students present the educational process not as a set of rules or a set of information, but as a toolkit for independent creative language activity. Using the Kolmogorov-Smirnov λ-criterion and the Fisher φ*-criterion (circular transformation), the beneficial effect of artistic and methodological support for the construction of linguistic and cultural scenarios on the expansion of the thematic vocabulary of students within the framework of the theme “At the Restaurant” has been experimentally confirmed.

Improving the Efficacy of Continuous Monitoring of Patients with Parkinson's Disease Through the Use of an Intelligent Computing Architecture Within the Medical Internet of Things

Telemonitoring has grown in popularity these days, particularly to assist patients with serious illnesses such as Parkinson's disease (PD). This study relies on the Daphnet dataset, which was trained and utilized to track five patients' whereabouts for an extensive dataset. Fuzzy logic was used in conjunction with a linear and Mobius map as part of the fog computing freezing of gait (FoG) detection system to provide a multi-level output (MLFM-map) that takes advantage of various spatial resolutions in motion data processing. Two improved Salp Swarm Algorithms with Fuzzy Logic (Fuzzy-ISSA) and transient search optimization algorithm (TSO) have been employed for the methodical training of this tool at the level of fog computing. When compared to other machine learning techniques, this one trains the FOG detection system quite quickly. In order to maximize performance while lowering computational complexity and testing time, the model architecture and parameters have been carefully considered. On average, the suggested method detected over 90% of FoG occurrences with extremely low latency in the original (test) dataset, demonstrating good to exceptional classification performance. In addition, the algorithm demonstrated a specificity of over 90% when tested on the test set. Various algorithms are used to train this design.

A Novel Multi-camera Fusion Approach at Plant Scale: From 2D to 3D

Non-invasive crop phenotyping is essential for crop modeling, which relies on image processing techniques. This research presents a plant-scale vision system that can acquire multispectral plant data in agricultural fields. This paper proposes a sensory fusion method that uses three cameras, Two multispectral and a RGB depth camera. The sensory fusion method applies pattern recognition and statistical optimization to produce a single multispectral 3D image that combines thermal and near-infrared (NIR) images from crops. A multi-camera sensory fusion method incorporates five multispectral bands: three from the visible range and two from the non-visible range, namely NIR and mid-infrared. The object recognition method examines about 7000 features in each image and runs only once during calibration. The outcome of the sensory fusion process is a homographic transformation model that integrates multispectral and RGB data into a coherent 3D representation. This approach can handle occlusions, allowing an accurate extraction of crop features. The result is a 3D point cloud that contains thermal and NIR multispectral data that were initially obtained separately in 2D.

Influence of building spatial patterns on wind environment and air pollution dispersion inside an industrial park based on CFD simulation.

The "spatial pattern-wind environment-air pollution" within building clusters is closely interconnected, where different spatial pattern parameters may have varying degrees of impact on the wind environment and pollutant dispersion. Due to the complex spatial structure within industrial parks, this complexity may lead to the accumulation and retention of air pollutants within the parks. Therefore, to alleviate the air pollution situation in industrial parks in China and achieve the circular transformation and construction of parks, this study takes Hefei Circular Economy Demonstration Park as the research object. The microscale Fluent model in computational fluid dynamics (CFD) is used to finely simulate the wind flow field and the diffusion process of pollutants within the park. The study analyzes the triad relationship and influence mechanism of "spatial pattern-wind environment-air pollution" within the park and studies the influence of different spatial pattern parameters on the migration and diffusion of pollutants. The results show a significant negative correlation between the content of pollutants and wind speed inside the industrial park. The better the wind conditions, the higher the air quality. The spatial morphology parameters of the building complex are the main influences on the condition of its internal wind environment. Building coverage ratio and degree of enclosure have a significant negative correlation with wind conditions. Maintaining them near 0.23 and 0.37, respectively, is favorable to the quality of the surrounding environment. Moreover, the average height of the building is positively correlated with the wind environment condition. The rate of transport and dissipation of pollutants gradually increases as the average building height reaches 16 m. Therefore, a reasonable building planning strategy and arrangement layout can effectively improve the wind environment condition inside the park, thus alleviating the pollutant retention situation. The obtained results serve as a theoretical foundation for optimizing morphological structure design within urban industrial parks.

Circular supply chain management: Antecedent effect of social capital and big data analysis capability and their impact on sustainable performance

AbstractThe circular economy era has begun, and circular supply chain management (CSCM) is widely acknowledged as a management paradigm that promotes firm sustainability. Through previous research, we have learned that the key challenge in the circular transformation of manufacturing firms is to encourage supply chain partners to collaborate and effectively participate in resource cycles. Drawing inspiration from social capital theory and resource‐based views, we explored how social capital effect sustainable performance through CSCM and the moderating effect of big data analytics capability (BDAC). We tested this by collecting data from 414 Chinese manufacturing firms. The results indicate that both internal and external social capital are positively correlated with CSCM. In addition, CSCM mediates the relationship between social capital and organizational environmental and social sustainability. The results also indicate that BDAC strengthen the impact of external social capital on CSCM, but the moderating effect on the relationship between internal social capital and CSCM is not significant. This essay advances the theory and practice of CSCM by offering fresh perspectives on how social capital influences sustainable performance of firms.

Parabolic Tamari Lattices in Linear Type B

We study parabolic aligned elements associated with the type-$B$ Coxeter group and the so-called linear Coxeter element. These elements were introduced algebraically in (Mühle and Williams, 2019) for parabolic quotients of finite Coxeter groups and were characterized by a certain forcing condition on inversions. We focus on the type-$B$ case and give a combinatorial model for these elements in terms of pattern avoidance. Moreover, we describe an equivalence relation on parabolic quotients of the type-$B$ Coxeter group whose equivalence classes are indexed by the aligned elements. We prove that this equivalence relation extends to a congruence relation for the weak order. The resulting quotient lattice is the type-$B$ analogue of the parabolic Tamari lattice introduced for type $A$ in (Mühle and Williams, 2019).

An energy estimate and a stabilized Lagrange–Galerkin scheme for a multiphase flow model

Multiphase flow models are commonly employed for understanding complex fluid flows, while few mathematical discussions exist. For a general multiphase flow model in Gidaspow (1994), an energy decay property is proved. A stabilized Lagrange–Galerkin scheme for the model and its stability property are presented. Here, a hyperbolic tangent transformation is employed to preserve the boundedness of the volume fraction. A novel artificial term is added to obtain the stability property. Two-dimensional numerical examples exhibit the experimental order of convergence and applicability in modelling sedimentation phenomena.

Restaurants without Bins: How Does a Circular Restaurant Operate?

The circular economy is seen as a potential solution to tackle the environmental concerns of the restaurant industry, offering a set of practices to support the industry in achieving more efficient use of resources and becoming more sustainable. However, studies that focus on the circular economy as a theoretical framework in the restaurant context are scarce. Thus, this study aims to increase understanding of how a circular restaurant operates in practice and provide insight into the circular transformation of restaurants. This article adopts a qualitative, multiple case study methodology, assessing six pioneer restaurants fully embracing a circular economy. The results show that a circular restaurant can be defined as a restaurant based on a systemic design that eliminates waste and keeps materials in circulation. A circular restaurant redesigns and reverses the supply chain, designs circular menus, is committed to closed-loop cooking, and reprocesses the remaining waste. In addition, a circular restaurant features a circular approach to interior design and embraces its social capital. The article includes various practical implications for chefs who can lead the transition to a more circular food system by adopting relevant practices.

PAPR reduction using model‐driven hybrid algorithms in the 6G NOMA waveform

AbstractIn the evolving landscape of sixth‐generation (6G) network technologies, Non‐Orthogonal Multiple Access (NOMA) systems are pivotal for achieving enhanced spectral efficiency and network capacity. However, a significant challenge in NOMA systems is the high Peak‐to‐Average Power Ratio (PAPR), which undermines system efficiency by necessitating high‐power amplifiers (HPAs) to operate in their less efficient, non‐linear range. Addressing this, we introduce a novel hybrid approach, the Selective Mapping‐Circular Transformation Method (SLM‐CTM), which ingeniously amalgamates the strengths of Selective Mapping (SLM) and the Circular Transformation Method (CTM) to mitigate PAPR issues. SLM is renowned for its peak power reduction capabilities without adding to system complexity, whereas CTM is valued for its simplicity and controlled signal distortion. The proposed SLM‐CTM strategy employs a blend of linear and nonlinear techniques to effectively lower PAPR in non‐orthogonal NOMA configurations, thereby reducing high‐power peaks while simultaneously enhancing signal quality. This paper delineates the application of the SLM‐CTM algorithm to evaluate critical NOMA parameters such as Power Spectral Density (PSD), Bit Error Rate (BER), and PAPR. Simulation results highlight the efficacy of SLM‐CTM over conventional SLM, demonstrating a significant throughput improvement of 3.2 dB and a PAPR reduction of 4.6 dB, underscoring the potential of SLM‐CTM in elevating the performance of NOMA systems within 6G network.

Licensing Scheme in the Green Industry Sector: The Case of Georgia Tree Care Service Providers

AbstractTree care license requirements are expected to improve service quality and provider competencies. The study elicits the licensing fee Georgia firms would pay using survey data from 153 tree care firms. An empirical relationship identifies firm characteristics that influence the fee size using the inverse hyperbolic sine transformation function. Results show that respondents who propose higher annual licensing fees are on average younger, more educated, male, and likely to agree that mandatory licensing is necessary to establish professionalism in the tree care industry. Also, those often engaged in tree trimming services and firms with higher annual revenues contemplate paying higher licensing fees.