Institution
University of Maribor
Education•Maribor, Slovenia•
About: University of Maribor is a education organization based out in Maribor, Slovenia. It is known for research contribution in the topics: Population & KEKB. The organization has 3987 authors who have published 13077 publications receiving 258339 citations. The organization is also known as: Univerza v Mariboru.
Papers published on a yearly basis
Papers
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TL;DR: The introduced concept of noise-guided evolution via the exploitation of threshold duality is not limited to predator–prey cyclical interactions, but may apply to models of evolutionary game theory as well, thus indicating its applicability in several different fields of research.
Abstract: We study a stochastic predator-prey model on a square lattice, where each of the six species has two superior and two inferior partners. The invasion probabilities between species depend on the predator-prey pair and are supplemented by Gaussian noise. Conditions are identified that warrant the largest impact of noise on the evolutionary process, and the results of Monte Carlo simulations are qualitatively reproduced by a four-point cluster dynamical mean-field approximation. The observed noise-guided evolution is deeply routed in short-range spatial correlations, which is supported by simulations on other host lattice topologies. Our findings are conceptually related to the coherence resonance phenomenon in dynamical systems via the mechanism of threshold duality. We also show that the introduced concept of noise-guided evolution via the exploitation of threshold duality is not limited to predator-prey cyclical interactions, but may apply to models of evolutionary game theory as well, thus indicating its applicability in several different fields of research.
97 citations
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TL;DR: The review reveals that despite the relative simplicity of all reviewed models, the regression analysis is still widely used and efficient for long-term forecasting and machine learning or artificial intelligence-based models such as Artificial Neural Networks, Support Vector Machines, and Fuzzy logic are favored.
Abstract: Electric load forecasting (ELF) is a vital process in the planning of the electricity industry and plays a crucial role in electric capacity scheduling and power systems management and, therefore, it has attracted increasing academic interest. Hence, the accuracy of electric load forecasting has great importance for energy generating capacity scheduling and power system management. This paper presents a review of forecasting methods and models for electricity load. About 45 academic papers have been used for the comparison based on specified criteria such as time frame, inputs, outputs, the scale of the project, and value. The review reveals that despite the relative simplicity of all reviewed models, the regression analysis is still widely used and efficient for long-term forecasting. As for short-term predictions, machine learning or artificial intelligence-based models such as Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Fuzzy logic are favored.
97 citations
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TL;DR: A systematic and comprehensive review of papers published over the last two decades of synthesis of non-isothermal water networks using systematic methods based on pinch analysis, mathematical programming, and their combination is presented.
97 citations
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TL;DR: In this article, a review of work in the field of miniature fiber-optic sensors that allow independent and simultaneous measurements of two or more different physical or chemical parameters is presented and compared.
Abstract: Needs for sensor miniaturization, versatile sensing solutions, and improved measurements’ performances in difficult operating environments have recently driven considerable research in optical fiber sensor for multiparameter measurements. Multiparameter sensors not only enable new sensors’ functionalities, but can also improve achievable measurement performances for some frequently measured parameters considerably. This study provides a review of work in the field of miniature fiber-optic sensors that allows independent and simultaneous measurements of two or more different physical or chemical parameters. Sensor designs and corresponding signal processing schemes are reviewed and compared.
97 citations
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TL;DR: Hierarchical chiral structures with coupling of chirality at different levels in a system with achiral constituents are observed.
Abstract: Complex materials often exhibit a hierarchical structure with an intriguing mechanism responsible for the 'propagation' of order from the molecular to the nano- or micro-scale level. In particular, the chirality of biological molecules such as nucleic acids and amino acids is responsible for the helical structure of DNA and proteins, which in turn leads to the lack of mirror symmetry of macro-bio-objects. To fully understand mechanisms of cross-level order transfer there is an intensive search for simpler artificial structures exhibiting hierarchical arrangement. Here we present complex systems built of achiral molecules that show four levels of structural chirality: layer chirality, helicity of a basic repeating unit, mesoscopic helix and helical filaments. The structures are identified by a combination of hard and soft x-ray diffraction measurements, optical studies and theoretical modelling. Similarly to many biological systems, the studied materials exhibit a coupling between chirality at different levels.
97 citations
Authors
Showing all 4077 results
Name | H-index | Papers | Citations |
---|---|---|---|
Ignacio E. Grossmann | 112 | 776 | 46185 |
Mirjam Cvetič | 89 | 456 | 27867 |
T. Sumiyoshi | 88 | 855 | 62277 |
M. Bračko | 87 | 738 | 30195 |
Xin-She Yang | 85 | 444 | 61136 |
Matjaž Perc | 84 | 400 | 22115 |
Baowen Li | 83 | 477 | 23080 |
S. Nishida | 82 | 678 | 27709 |
P. Križan | 78 | 749 | 26408 |
S. Korpar | 78 | 615 | 23802 |
Attila Szolnoki | 76 | 231 | 20423 |
H. Kawai | 76 | 477 | 22713 |
John Shawe-Taylor | 72 | 503 | 52369 |
Matjaz Perc | 57 | 148 | 12886 |
Mitja Lainscak | 55 | 287 | 22004 |