scholarly journals Fractal dimension analogous scale-invariant derivative of Hirsch’s index

2022 ◽  
Vol 7 (1) ◽  
Author(s):  
Yuji Fujita ◽  
Noritaka Usami
Keyword(s):  
Fractal Dimension ◽  
Natural Disasters ◽  
Objective Evaluation ◽  
Economic Opportunity ◽  
Institutional Performance ◽  
Scale Invariant ◽  
Research Activities ◽  
Research Institutes ◽  
Academic Activities ◽  
Self Similar

AbstractWe propose a scale-invariant derivative of the h-index as “h-dimension”, which is analogous to the fractal dimension of the h-index for institutional performance analysis. The design of h-dimension comes from the self-similar characteristics of the citation structure. We applied this h-dimension to data of 134 Japanese national universities and research institutes, and found well-performing medium-sized research institutes, where we identified multiple organizations related to natural disasters. This result is reasonable considering that Japan is frequently hit by earthquakes, typhoons, volcanoes and other natural disasters. However, these characteristic institutes are screened by larger universities if we depend on the existing h-index. The scale-invariant property of the proposed method helps to understand the nature of academic activities, which must promote fair and objective evaluation of research activities to maximize intellectual, and eventually economic opportunity.

scholarly journals Features of Spatial-Temporal Hierarchical Structures Formation

2021 ◽  
Vol 60 (2) ◽  
pp. 66-70
Author(s):  
Anna Dulfan ◽  
Iryna Voronko
Keyword(s):  
Fractal Dimension ◽  
Physical Properties ◽  
Large Scale ◽  
Chaotic Behavior ◽  
Hierarchical Structures ◽  
Scale Invariant ◽  
Temporal Dimension ◽  
Time Space ◽  
Wide Range ◽  
Self Similar

The degree of ordering of the structure of technologically important materials formed as a result of the evolution of complex physicochemical systems determines their physical properties, in particular optical. In this regard, the primary task for the theoretical study of methods for obtaining materials with predetermined physical properties is to develop approaches to describe the evolution of fractal (scale-invariant) objects in the formation of self-similar structures in systems exhibiting chaotic behavior. The paper forms an idea of the processes of evolution in materials formed as a result of stochastic processes. It is established that the conduct of ultrametrics in time space allows to characterize the time of the evolutionary process of fractal dimension, which is calculated either theoretically or model. The description of evolutionary processes in a condensed medium, accompanied by topological transformations, is significantly supplemented by the method of describing the stages of evolution of structures, which makes it possible to analyze a wide range of materials and can control their properties, primarily optical. It is shown that the most large-scale invariant structures, due to the investigated properties, can be used as information carriers. It is demonstrated that the presence in physical systems of fractal temporal dimension and generates a self-similar (consisting of parts in a sense similar to the whole object) evolutionary tree, which, in turn, generates spatial objects of non-integer dimension, observed in real situations. On the other hand, temporal fractality provides analysis of systems with dynamic chaos, leading to universal relaxation functions. In particular, in systems with a large-scale invariant distribution of relaxation characteristics, an algebraic law of relaxation is manifested, which leads to rheological models and equations of states, which are characterized by fractional derivatives. It is argued that the fractal dimension of time hierarchies stores information that determines the process of self-organization. Developed in the paper ideas about the processes of building the structure of materials, which lead to the fractal geometry of objects, can be used to predict their properties, in particular, optical.

Higher education for sustainable development: stakeholders benefits

2020 ◽  
pp. 121-136 ◽  
Author(s):  
O.V. Kotomina ◽  
A.I. Sazhina
Keyword(s):  
Sustainable Development ◽  
Active Agent ◽  
Education For Sustainable Development ◽  
Special Role ◽  
Stakeholder Approach ◽  
Research Activities ◽  
Academic Activities ◽  
Key Stakeholders ◽  
The One ◽  
Significant Factors

Education is one of the key goals of sustainable development (SD), which establishes the basis for the improvement of the people’s living conditions. In this logic a special role is played by universities that create an institutional framework for educating citizens on sustainable development, offering a new understanding of social problems. On the one hand, universities can create and promote knowledge about SD by their educational, expert and research activities, hence developing relevant values among people. On the other hand, universities can become an active agent in implementing the concept of SD by introducing it into its own academic activities. The article considers stakeholder approach as one of the approaches to the implementation of the concept of education for sustainable development (ESD). Therefore based on this approach, the article explores the benefits of the key stakeholders of the sustainable university. Low awareness among key stakeholders is one of the significant factors that hindering the implementation of the SD concept. Due to the lack of a sufficient research focused on studying the interests of the main stakeholders in the framework of ESD, this article is an attempt to narrow this gap.

Multi-disciplinarity as a way to strengthen the positions of Russian technical universities in international rankings

2021 ◽  
Vol 20 (10) ◽  
pp. 1798-1817
Author(s):  
Leonid B. SOBOLEV
Keyword(s):  
Research Universities ◽  
Multidisciplinary Research ◽  
Global Trends ◽  
Russian Academy Of Sciences ◽  
Research Activities ◽  
Research Institutes ◽  
Integrated Research ◽  
World Class ◽  
Academy Of Sciences ◽  
Russian Research

Subject. The article is devoted to the problem of improving the ranking of the leading Russian technical universities by transforming them into multidisciplinary research universities with the limitation of technical faculties (programs) to 40–50% of the admission plan of entrants. Objectives. The study focuses on improving the position of Russian technical universities in international rankings, providing an opportunity for students to change their specialty or shape it, according to the requirements of the employer. Methods. I analyzed the structure of world-class technical universities in terms of differentiation of specialties and methods of improving the rankings. Results. The analysis shows that the leading positions in international rankings belong to multidisciplinary research universities that provide training and conduct integrated research at the intersection of different sciences. Conclusions. There is a need for gradual reforms of Russian research technical universities, in terms of compliance with global trends in multidisciplinarity, differentiation of funding, and research activities. Such reforms can be carried out in the form of mergers and creation of network structures on the basis of agreements on cooperation between technical universities and research institutes of the Russian Academy of Sciences.

Fractal and Convolutional Analysis for Deep Atmospheric Turbulence Using Machine Learning

2021 ◽  
Author(s):  
Nicholas Dudu ◽  
Arturo Rodriguez ◽  
Gael Moran ◽  
Jose Terrazas ◽  
Richard Adansi ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Atmospheric Turbulence ◽  
Isotropic Turbulence ◽  
Passive Scalar ◽  
Counting Method ◽  
Data Set ◽  
Box Counting ◽  
Box Counting Dimension ◽  
Self Similar ◽  
Box Counting Method

Abstract Atmospheric turbulence studies indicate the presence of self-similar scaling structures over a range of scales from the inertial outer scale to the dissipative inner scale. A measure of this self-similar structure has been obtained by computing the fractal dimension of images visualizing the turbulence using the widely used box-counting method. If applied blindly, the box-counting method can lead to misleading results in which the edges of the scaling range, corresponding to the upper and lower length scales referred to above are incorporated in an incorrect way. Furthermore, certain structures arising in turbulent flows that are not self-similar can deliver spurious contributions to the box-counting dimension. An appropriately trained Convolutional Neural Network can take account of both the above features in an appropriate way, using as inputs more detailed information than just the number of boxes covering the putative fractal set. To give a particular example, how the shape of clusters of covering boxes covering the object changes with box size could be analyzed. We will create a data set of decaying isotropic turbulence scenarios for atmospheric turbulence using Large-Eddy Simulations (LES) and analyze characteristic structures arising from these. These could include contours of velocity magnitude, as well as of levels of a passive scalar introduced into the simulated flows. We will then identify features of the structures that can be used to train the networks to obtain the most appropriate fractal dimension describing the scaling range, even when this range is of limited extent, down to a minimum of one order of magnitude.

scholarly journals Thermal and Wet Comfort of Fabrics Based on Fractal Dimension of Silicone Coating

2018 ◽  
Vol 13 (1) ◽  
pp. 155892501801300
Author(s):  
Yunlong Shi ◽  
Liang Wang ◽  
Wenhuan Zhang ◽  
Xiaoming Qian
Keyword(s):  
Fractal Dimension ◽  
Thermal Insulation ◽  
Coating Layer ◽  
Fractal Theory ◽  
Barrier Effect ◽  
Evaporative Resistance ◽  
Silicone Coating ◽  
Self Similar ◽  
Warmth Retention ◽  
Coated Fabrics

In this paper, thermal and wet comforts of silicone coated windbreaker shell jacket fabrics were studied. Both thermal insulation and evaporative resistance of fabric increased with an increase in coating area due to the barrier effect of the silicone coating layer. Moreover, the coated fabrics with self-similar structures showed different thermal insulation and evaporative resistance under the same total coating area. Fractal theory was used to explain this phenomenon. Optimal thermal-wet comfort properties were obtained when the fractal dimension (D=1.599) was close to the Golden Mean (1.618). When the fractal dimension of coating was lower than 1.599, fabric warmth retention was not high enough. In contrast, fabric evaporative resistance was beyond the value at which people would feel comfortable when the fractal dimension was greater than 1.599.

scholarly journals On the fractal nature of complex syntax and the timescale problem

2020 ◽  
Vol 10 (4) ◽  
pp. 697-721
Author(s):  
D. Reid Evans
Keyword(s):  
Complex Systems ◽  
Dynamic Systems Theory ◽  
Self Similarity ◽  
Scale Invariant ◽  
Complex Dynamic Systems ◽  
Complex Syntax ◽  
Dynamic Relationship ◽  
Self Similar ◽  
Multiple Component ◽  
Dynamic Relationships

Fundamental to complex dynamic systems theory is the assumption that the recursive behavior of complex systems results in the generation of physical forms and dynamic processes that are self-similar and scale-invariant. Such fractal-like structures and the organismic benefit that they engender has been widely noted in physiology, biology, and medicine, yet discussions of the fractal-like nature of language have remained at the level of metaphor in applied linguistics. Motivated by the lack of empirical evidence supporting this assumption, the present study examines the extent to which the use and development of complex syntax in a learner of English as a second language demonstrate the characteristics of self-similarity and scale invariance at nested timescales. Findings suggest that the use and development of syntactic complexity are governed by fractal scaling as the dynamic relationship among the subconstructs of syntax maintain their complexity and variability across multiple temporal scales. Overall, fractal analysis appears to be a fruitful analytic tool when attempting to discern the dynamic relationships among the multiple component parts of complex systems as they interact over time.

ESTIMATING THE FRACTAL DIMENSION OF PLANTS USING THE TWO-SURFACE METHOD: AN ANALYSIS BASED ON 3D-DIGITIZED TREE FOLIAGE

Fractals ◽  
2006 ◽  
Vol 14 (03) ◽  
pp. 149-163 ◽  
Author(s):  
FRÉDÉRIC BOUDON ◽  
CHRISTOPHE GODIN ◽  
CHRISTOPHE PRADAL ◽  
OLIVIER PUECH ◽  
HERVÉ SINOQUET
Keyword(s):  
Fractal Dimension ◽  
Field Measurements ◽  
Three Dimensions ◽  
Total Leaf Area ◽  
Topological Information ◽  
Surface Method ◽  
Plant Foliage ◽  
Self Similar ◽  
Branching System ◽  
Peach Trees

In this paper, we present a method to estimate the fractal dimension of plant foliage in three dimensions (3D). This method is derived from the two-surface method introduced in the 90s to estimate the fractal dimension of tree species from field measurements on collections of trees. Here we adapted the method to individual plants. The multiscale topology and geometry of the plant must first be digitized in 3D. Then leafy branching systems of different sizes are constructed from the plant database, using the topological information. 3D convex envelops are then computed for each leafy branching system. The fractal dimension of the plant is finally estimated by comparing the total leaf area and the convex envelop area of these leafy modules. The method was assessed on a set of four peach trees entirely digitized at shoot scale. Results show that the peach trees have a marked self-similar foliage with fractal dimension close to 2.4.

scholarly journals A laboratory study of sediment deformation: stress heterogeneity and grain-size evolution

1996 ◽  
Vol 22 ◽  
pp. 167-175 ◽  
Author(s):  
Neal R. Iverson ◽  
Thomas S. Hooyer ◽  
Roger Leb. Hooke
Keyword(s):  
Grain Size ◽  
Fractal Dimension ◽  
Normal Stress ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Local Stress ◽  
Large Strains ◽  
Self Similar ◽  
Deformation Stress ◽  
Stress Heterogeneity

In shearing sediment beneath glaciers, networks of grains may transiently support shear and normal stresses that are larger than spatial averages. Consistent with studies of fault-gouge genesis, we hypothesize that crushing of grains in such networks is responsible for surrounding larger grains with smaller grains. At sufficiently large strains, this should minimize stress heterogeneity, favor intergranular sliding and abrasion rather than crushing, and result in a self-similar grain-size distribution.This hypothesis is tested with a ring-shear device that slowly shears a large annular sediment sample to high strains. Shearing and comminution of weak equigranular (2.0–3.3 mm) sediment resulted in a self-similar grain-size distribution with a fractal dimension that increased with shear strain toward a steady value of 2.85. This value is significantly larger than that of gouges produced purely by crushing, 2.6, but it is comparable to values for tilts thought to be deforming beneath modern glaciers, 2.8 to nearly 3.0. At low strains, under a steady mean normal stress of 84 kPa, variations in normal stress measured locally ranged in amplitude from 50 to 300 kPa with wavelengths that were 100 times larger than the initial grain diameter. Crushing of grains, observed through the transparent walls of the device, apparently caused the failure of grain networks. At shearing displacements ranging from 0.7 to 1.0 m, the amplitude of local stress fluctuations decreased abruptly. This change is attributed to fine sediment that distributed stresses more uniformly and caused grain networks to fail primarily by intergranular sliding rather than by crushing of grains. Sliding between grains apparently produced silt by abrasion and resulted in a fractal dimension that was higher than if there had been only crushing.A size distribution with a fractal dimension greater than 2.6 is probably a necessary but not sufficient condition for determining whether a basal till has been highly deformed. Stress heterogeneity in subglacial sediment that is shearing through its full thickness should contribute to the erosion of underlying rock.

Regulatory Research for Geological Disposal of High-Level Radioactive Waste in Japan

2010 ◽  
Author(s):  
Shinichi Nakayama ◽  
Yoshio Watanabe ◽  
Masami Kato
Keyword(s):  
Radioactive Waste ◽  
Waste Management ◽  
Regional Scale ◽  
Industrial Safety ◽  
Future Research ◽  
Radioactive Waste Management ◽  
Geological Disposal ◽  
Research Activities ◽  
Research Institutes ◽  
Research Plan

The Nuclear and Industrial Safety Agency of the Ministry of Economy, Trade and Industry (NISA) has renewed its regulatory role and its need for regulatory research on radioactive waste management, with recent circumstances of radioactive waste management in Japan being taken into consideration. In response, a technical supporting organization, the Japan Nuclear Energy Safety Organization (JNES), in 2009 released the five-year research plan “Regulatory Research Plan on Radioactive Waste Management 2010–2014”, in cooperation with the research institutes of the Japan Atomic Energy Agency (JAEA) and the National Institute of Advanced Industrial Science and Technology (AIST). The geological disposal research plan and the future research activities are outlined in this paper. JNES launched safety studies on geological disposal in 2003, the year it was established. JAEA and AIST joined as regulatory support research institutes in 2005. In October 2007, all three parties signed an agreement of cooperative study on geological disposal, which facilitated joint studies and exchanges of staff, data, and results. One of the ongoing joint studies has focused on regional-scale hydrogeological modeling using JAEA’s Horonobe Underground Research Laboratory.

Application of Fractal Geometry to Fracture Forensics, Research and Production

2006 ◽  
Vol 45 ◽  
pp. 1646-1651 ◽  
Author(s):  
J.J. Mecholsky Jr.
Keyword(s):  
Fractal Analysis ◽  
Fractal Geometry ◽  
Crack Size ◽  
Structural Parameter ◽  
New Materials ◽  
Scale Invariant ◽  
Prepared Material ◽  
Reasonable Approach ◽  
Self Similar ◽  
Production Problems

The fracture surface records past events that occur during the fracture process by leaving characteristic markings. The application of fractal geometry aids in the interpretation and understanding of these events. Quantitative fractographic analysis of brittle fracture surfaces shows that these characteristic markings are self-similar and scale invariant, thus implying that fractal analysis is a reasonable approach to analyzing these surfaces. The fractal dimensional increment, D*, is directly proportional to the fracture energy, γ, during fracture for many brittle materials, i.e., γ = ½ E a0 D* where E is the elastic modulus and a0 is a structural parameter. Also, D* is equal to the crack-size-to-mirror-radius ratio. Using this information can aid in identifying toughening mechanisms in new materials, distinguishing poorly fabricated from well prepared material and identifying stress at fracture for field failures. Examples of the application of fractal analysis in research, fracture forensics and solving production problems are discussed.

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