Hasil untuk "Mathematics"

R. W. H. T. H.

Kusum Singh, Monique Granville, Sandra L. Dika

E. Wigner

J. Tukey

W. Ames

E. Weisstein

F. P. Ramsey

Frank Pajares, Laura R. Graham

M. Stein, M. Smith, M. Henningsen et al.

Jiang-Hua Lu

J. LeFevre, Lisa A. Fast, Sheri-Lynn Skwarchuk et al.

D. Meltzer

M. Alibali, Mitchell J. Nathan

I. F. D. Bos, Sanne H. G. van der Ven, E. Kroesbergen et al.

Mareike Kunter, J. Baumert, W. Blum et al.

LI Wenwen, YUAN Ruiming, ZHOU Hui et al.

Aiming at the influence of the fast, large range and random change of dynamic load current on the electricity metering, this paper firstly establishes a non-stationary random process modulation model and bimodal modulation model for complex dynamic power signal, and derives model parameters such as quasi-steady term and dynamic term amplitude. Based on the first spline least squares empirical mode decomposition (FS-EMD) method, a parameter extraction method for the amplitude model of quasi-steady and dynamic terms is proposed, the correctness of the method is demonstrated through the decomposition of power signals from electrified railway traction substations and arc furnaces. By mapping the amplitude domain model parameters, the important characteristic parameters in amplitude domain representing complex dynamic electric energy signals are constructed, and four important features are extracted. Finally, the dynamic error tests conducted on electricity meters reveal that the four significant parameters identified herein act as critical factors triggering the meter's performance to exceed tolerance thresholds.

Kamilla L. Lomborg, Carolina Cucart-Mora, Jan-Olaf Reschke et al.

In a world of drastic climatic and ecological changes, our knowledge of how the environment influenced hominin behaviour is of the utmost importance. Archaeology plays a key role in this domain, as it is the only discipline that studies empirical evidence of past societies’ responses to environmental change. Computational models generating predictions about past climatic and ecological conditions are vital for understanding the archaeological record and how these factors shaped the dispersal of hominins out of Africa and into Eurasia during the Early and early Middle Pleistocene. In this paper, various models for past reconstructions of climatic and ecological conditions and simulation techniques are presented to provide an overview of the diverse approaches, possibilities, advantages and constraints of using computational reconstructions in archaeological research. Focusing on studies of hominin dispersals out of Africa and into Eurasia during the Early and early Middle Pleistocene, this paper discusses the links between environmental factors and hominin dispersal behaviour. The use of simulation techniques to represent hominin populations, such as cellular automata or agent-based modelling, can contribute to connecting small-scale environment-induced influences on hominins to large-scale patterns, supported by ecological theories of species survival and spatial behaviour. Collectively, these approaches provide an elaborate foundation for understanding environmental influences on past hominin dispersals.

L. Kuipers, R. Timman, J. Cohen

Linh Thi Hoai Nguyen, Ton Viet Ta, Atsushi Yagi

This note reviews our mathematical models for fish schooling, considered in free space, and in space with obstacle and food resource. These models are performed by stochastic differential equations or stochastic partial differential equations. We then present an example for the model in the last case.

Yurong Dong, Hua Liu, Jianhua Ye et al.

In this paper, an eco-epidemiological model with a weak Allee effect and prey disease dynamics is discussed. Mathematical features such as non-negativity, boundedness of solutions, and local stability of the feasible equilibria are discussed. Additionally, the transcritical bifurcation, saddle-node bifurcation, and Hopf bifurcation are proven using Sotomayor’s theorem and Poincare–Andronov–Hopf theorems. In addition, the correctness of the theoretical analysis is verified by numerical simulation. The numerical simulation results show that the eco-epidemiological model with a weak Allee effect has complex dynamics. If the prey population is not affected by disease, the predator becomes extinct due to a lack of food. Under low infection rates, all populations are maintained in a coexistent state. The Allee effect does not influence this coexistence. At high infection rates, if the prey population is not affected by the Allee effect, the infected prey is found to coexist in an oscillatory state. The predator population and the susceptible prey population will be extinct. If the prey population is affected by the Allee effect, all species will be extinct.