Sep 2026· Earthline Journal of Mathematical Sciences· 51 references
Fractional Differential Equations Solutions
Abstract
Nonlinear Volterra integral equations model several phenomena in a variety of fields, including epidemiology, population growth theory, diffusion and heat transfer problems. In this paper, the analytical solution of a class of nonlinear Volterra integral equations of the second kind is presented using a power series method based on the generalised Cauchy product. The nonlinear terms $\Phi(U(\xi))$ in the proposed problem are given by normalised Jacobi polynomials $\mathsf{P}_{\ell}^{(\phi, \varphi)}(U(\xi))$ ($\ell=1,2,3,\dots;\phi,\varphi>-1$) in the unknown $U(\xi)$. The proposed method first expresses the nonlinear terms as a power series in the unknown $U$, and then uses the generalised Cauchy product to convert the series into power series in the independent variable $\xi$. Subsequently, recurrence relations for the expansion coefficients of the series solution are obtained in terms of the nonlinear terms and their higher derivatives evaluated at the constant term of the series solution. Specialising the nonlinear terms to Gegenbauer or ultraspherical polynomials, Legendre polynomials, and Chebyshev polynomials, several nonlinear Volterra integral equations and their solutions are introduced. Considering the normalised Jacobi polynomials as spherical functions on rank one symmetric spaces of compact type, a number of novel nonlinear integral equations are presented. To validate the proposed method, some known nonlinear Volterra integral equations are solved and the series solutions converge to the known exact solutions. The convergence of the series solutions shows that the proposed power series method is accurate and reliable for solving such nonlinear Volterra integral problems.
The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.
Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al.· IEEE Transactions on Softwar...· 178 citations· ⚡14
Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.
M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al.· e-Informatica Software Engin...· 157 citations· ⚡17
This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.
Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al.· Empirical Software Engineeri...· 127 citations· ⚡15
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
The application of agile software methods and more recently the integration of Lean practices contribute to the trend of continuous improvement in the software industry. One such area warranting proper empirical evidence is a project’s operational efficiency when using the Kanban method. This short paper takes a new an...
Marko Ikonen, Petri Kettunen, Nilay V. Oza et al.· EUROMICRO Conference on Soft...· 67 citations· ⚡9
Related blog posts
MIT News · Artificial Intelligence· news.mit.eduOct 15, 2026
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
Microsoft Research Blog· microsoft.comOct 12, 2026
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.