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Journal articles on the topic 'Complexity'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Chow, Robert. "Complexity of Complexin." Biophysical Journal 106, no. 2 (2014): 11a. http://dx.doi.org/10.1016/j.bpj.2013.11.110.

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2

BLOWS, M. W. "Complexity for complexity's sake?" Journal of Evolutionary Biology 20, no. 1 (2007): 39–44. http://dx.doi.org/10.1111/j.1420-9101.2006.01241.x.

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3

Shoemaker, Jessica. "Complexity's Shadow: American Indian Property, Sovereignty, and the Future." Michigan Law Review, no. 115.4 (2017): 487. http://dx.doi.org/10.36644/mlr.115.4.complexity.

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This Article offers a new perspective on the challenges of the modern American Indian land tenure system. While some property theorists have renewed focus on isolated aspects of Indian land tenure, including the historic inequities of colonial takings of Indian lands, this Article argues that the complexity of today’s federally imposed reservation property system does much of the same colonizing work that historic Indian land policies—from allotment to removal to termination—did overtly. But now, these inequities are largely overshadowed by the daunting complexity of the whole land tenure stru

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4

Keune, Hans. "Critical complexity in environmental health practice: simplify and complexify." Environmental Health 11, Suppl 1 (2012): S19. http://dx.doi.org/10.1186/1476-069x-11-s1-s19.

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5

Pöltner, P., and T. Grechenig. "Organic Finance Framework: Aligning Financing Complexity with Organisational Complexity (for Innovative Companies)." International Journal of Trade, Economics and Finance 11, no. 6 (2020): 156–62. http://dx.doi.org/10.18178/ijtef.2020.11.6.682.

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The organic finance framework is a new tool for managing the challenges of corporate financing. This framework is especially useful for small and medium-sized enterprises in the time of a crisis, such as the COVID-19 pandemic. At its core, the framework forces a rethink of the manner in which companies initiate their financing approach. In contrast to finding potential external sources of finance, the organic finance framework starts by looking at the relevant stakeholders of the company. Alternative financing methods, such as crowdfunding and crowdinvesting, have demonstrated that companies c

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6

Read, Dwight, and Claes Andersson. "Cultural complexity and complexity evolution." Adaptive Behavior 28, no. 5 (2019): 329–58. http://dx.doi.org/10.1177/1059712318822298.

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We review issues stemming from current models regarding the drivers of cultural complexity and cultural evolution. We disagree with the implication of the treadmill model, based on dual-inheritance theory, that population size is the driver of cultural complexity. The treadmill model reduces the evolution of artifact complexity, measured by the number of parts, to the statistical fact that individuals with high skills are more likely to be found in a larger population than in a smaller population. However, for the treadmill model to operate as claimed, implausibly high skill levels must be ass

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7

Goldreich, Oded, Rafail Ostrovsky, and Erez Petrank. "Computational Complexity and Knowledge Complexity." SIAM Journal on Computing 27, no. 4 (1998): 1116–41. http://dx.doi.org/10.1137/s0097539795280524.

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8

LINIAL, NATI, and ADI SHRAIBMAN. "Learning Complexity vs Communication Complexity." Combinatorics, Probability and Computing 18, no. 1-2 (2009): 227–45. http://dx.doi.org/10.1017/s0963548308009656.

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This paper has two main focal points. We first consider an important class of machine learning algorithms: large margin classifiers, such as Support Vector Machines. The notion of margin complexity quantifies the extent to which a given class of functions can be learned by large margin classifiers. We prove that up to a small multiplicative constant, margin complexity is equal to the inverse of discrepancy. This establishes a strong tie between seemingly very different notions from two distinct areas.In the same way that matrix rigidity is related to rank, we introduce the notion of rigidity o

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9

Lachish, Oded, Ilan Newman, and Asaf Shapira. "Space Complexity Vs. Query Complexity." computational complexity 17, no. 1 (2008): 70–93. http://dx.doi.org/10.1007/s00037-008-0239-z.

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10

Iván Tarride, Mario. "The complexity of measuring complexity." Kybernetes 42, no. 2 (2013): 174–84. http://dx.doi.org/10.1108/03684921311310558.

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11

Barton, C. Michael. "Complexity, Social Complexity, and Modeling." Journal of Archaeological Method and Theory 21, no. 2 (2013): 306–24. http://dx.doi.org/10.1007/s10816-013-9187-2.

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12

Crano, Ricky D. "A Context for Complexism: Between Neoliberal Social Thought and Algorithmic Art." Open Cultural Studies 2, no. 1 (2018): 341–52. http://dx.doi.org/10.1515/culture-2018-0031.

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Abstract Among the many genres of visual art to emerge in the wake of computerisation, the subset of generative or algorithmic art known as complexism seems uniquely keyed to the social and technological mainsprings of everyday life in the twenty-first century. Complexism typically deploys computer algorithms to demonstrate how complex phenomena can emerge through the reiterative enactment of simple rulesets. The light and sound installations and the videos that complexist artists produce, alongside the discourses surrounding the works, stand out as singularly contemporary, not necessarily for

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13

Fink, B. Raymond. "Complexity." Science 231, no. 4736 (1986): 319. http://dx.doi.org/10.1126/science.231.4736.319.c.

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14

Levy, Ellen K. "Complexity." Leonardo 27, no. 1 (1994): 75. http://dx.doi.org/10.2307/1575955.

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15

Gómez-Hernández, J. Jaime. "Complexity." Ground Water 44, no. 6 Understanding (2006): 782–85. http://dx.doi.org/10.1111/j.1745-6584.2006.00222.x.

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16

SILVERT, WILLIAM. "COMPLEXITY." Journal of Biological Systems 04, no. 04 (1996): 585–91. http://dx.doi.org/10.1142/s0218339096000375.

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Complexity is a property of models, not of systems. It is shown that the complexity of a system is not a well-defined quantity, and that the complexity implicit in a model is connected to the amount of information about the system (in an information-theoretic sense) that the model is able to process.

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17

Standish, Russell K. "Complexity." International Journal of Signs and Semiotic Systems 3, no. 1 (2014): 27–45. http://dx.doi.org/10.4018/ijsss.2014010103.

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The term complexity is used informally both as a quality and as a quantity. As a quality, complexity has something to do with our ability to understand a system or object—people understand simple systems, but not complex ones. On another level, complexity is used as a quantity, when people talk about something being more complicated than another. In this article, the author explores the formalisation of both meanings of complexity, which happened during the latter half of the twentieth century.

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18

Smith, Brian D. "Complexity." Journal of Medical Marketing 9, no. 3 (2009): 185–86. http://dx.doi.org/10.1057/jmm.2009.28.

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19

Galanter, Philip, Ellen K. Levy, Manuel A. Báez, et al. "Complexity." Leonardo 36, no. 4 (2003): 259–67. http://dx.doi.org/10.1162/002409403322258583.

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20

Davie, George. "Complexity." Annals of Probability 29, no. 4 (2001): 1426–34. http://dx.doi.org/10.1214/aop/1015345756.

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21

Keil, Ode R. "Complexity." Journal of Clinical Engineering 27, no. 2 (2002): 83–84. http://dx.doi.org/10.1097/00004669-200202720-00003.

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22

Benı́tez-Bribiesca, Luis. "Complexity." Archives of Medical Research 31, no. 1 (2000): 1–2. http://dx.doi.org/10.1016/s0188-4409(99)00086-7.

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23

Trabesinger, Andreas. "Complexity." Nature Physics 8, no. 1 (2011): 13. http://dx.doi.org/10.1038/nphys2198.

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24

FINK, B. R. "Complexity." Science 231, no. 4736 (1986): 319. http://dx.doi.org/10.1126/science.231.4736.319-b.

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25

Sporns, Olaf. "Complexity." Scholarpedia 2, no. 10 (2007): 1623. http://dx.doi.org/10.4249/scholarpedia.1623.

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26

Urry, John. "Complexity." Theory, Culture & Society 23, no. 2-3 (2006): 111–15. http://dx.doi.org/10.1177/0263276406062818.

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The term ‘complexity’ has recently sprung into the physical and social sciences, humanities and semi-popular writings. ‘Complexity’ practices are constituted as something of a self-organizing global network that is spreading ‘complexity’ notions around the globe. There is a new ‘structure of feeling’ that complexity approaches both signify and enhance. Such an emergent structure of feeling involves a greater sense of contingent openness to people, corporations and societies, of the unpredictability of outcomes in time–space, of a charity towards objects and nature, of the diverse and non-linea

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27

Gough, David. "Complexity." Evidence & Policy: A Journal of Research, Debate and Practice 8, no. 4 (2012): 415–16. http://dx.doi.org/10.1332/174426412x660151.

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28

Fontana, Walter, and Susan Ballati. "Complexity." Complexity 4, no. 3 (1999): 14–16. http://dx.doi.org/10.1002/(sici)1099-0526(199901/02)4:3<14::aid-cplx3>3.0.co;2-o.

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29

Euchner, Jim. "Complexity." Research-Technology Management 67, no. 1 (2024): 12–14. http://dx.doi.org/10.1080/08956308.2023.2280480.

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30

Leabu, Mircea, and Valentin Muresan. "Preface: Life's Complexity, Complexity of Ethics." Ethics in Biology, Engineering and Medicine: An International Journal 6, no. 1-2 (2015): 45–47. http://dx.doi.org/10.1615/ethicsbiologyengmed.2015016125.

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31

Turner, Barbara J., and Leona Cuttler. "The Complexity of Measuring Clinical Complexity." Annals of Internal Medicine 155, no. 12 (2011): 851. http://dx.doi.org/10.7326/0003-4819-155-12-201112200-00009.

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32

Knor, Martin, and Riste Škrekovski. "Wiener Complexity versus the Eccentric Complexity." Mathematics 9, no. 1 (2020): 79. http://dx.doi.org/10.3390/math9010079.

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Let wG(u) be the sum of distances from u to all the other vertices of G. The Wiener complexity, CW(G), is the number of different values of wG(u) in G, and the eccentric complexity, Cec(G), is the number of different eccentricities in G. In this paper, we prove that for every integer c there are infinitely many graphs G such that CW(G)−Cec(G)=c. Moreover, we prove this statement using graphs with the smallest possible cyclomatic number. That is, if c≥0 we prove this statement using trees, and if c<0 we prove it using unicyclic graphs. Further, we prove that Cec(G)≤2CW(G)−1 if G is a unicycl

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33

Machta, J. "Natural complexity, computational complexity and depth." Chaos: An Interdisciplinary Journal of Nonlinear Science 21, no. 3 (2011): 037111. http://dx.doi.org/10.1063/1.3634009.

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34

Freeberg, Todd M. "Social Complexity Can Drive Vocal Complexity." Psychological Science 17, no. 7 (2006): 557–61. http://dx.doi.org/10.1111/j.1467-9280.2006.01743.x.

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35

Wang, M. Z. "Linear complexity profiles and jump complexity." Information Processing Letters 61, no. 3 (1997): 165–68. http://dx.doi.org/10.1016/s0020-0190(97)00004-5.

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36

Wilson, T., T. Holt, and T. Greenhalgh. "Complexity science: Complexity and clinical care." BMJ 323, no. 7314 (2001): 685–88. http://dx.doi.org/10.1136/bmj.323.7314.685.

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37

Kjos-Hanssen, Bjørn. "On the Complexity of Automatic Complexity." Theory of Computing Systems 61, no. 4 (2017): 1427–39. http://dx.doi.org/10.1007/s00224-017-9795-4.

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38

Xu, Kexiang, Aleksandar Ilić, Vesna Iršič, Sandi Klavžar, and Huimin Li. "Comparing Wiener complexity with eccentric complexity." Discrete Applied Mathematics 290 (February 2021): 7–16. http://dx.doi.org/10.1016/j.dam.2020.11.020.

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39

Frank, Kenneth A., and Kim Bernstein. "“Complexity, Complexity, Complexity”: An Introduction to the Special Issue on Adoption." Psychoanalytic Perspectives 10, no. 1 (2013): 1–9. http://dx.doi.org/10.1080/1551806x.2013.768873.

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40

BAUWENS, B., and A. SHEN. "COMPLEXITY OF COMPLEXITY AND STRINGS WITH MAXIMAL PLAIN AND PREFIX KOLMOGOROV COMPLEXITY." Journal of Symbolic Logic 79, no. 2 (2014): 620–32. http://dx.doi.org/10.1017/jsl.2014.15.

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AbstractPéter Gács showed (Gács 1974) that for every n there exists a bit string x of length n whose plain complexity C(x) has almost maximal conditional complexity relative to x, i.e., $C\left( {C\left( x \right)|x} \right) \ge {\rm{log}}n - {\rm{log}}^{\left( 2 \right)} n - O\left( 1 \right)$ (Here ${\rm{log}}^{\left( 2 \right)} i = {\rm{loglog}}i$.) Following Elena Kalinina (Kalinina 2011), we provide a simple game-based proof of this result; modifying her argument, we get a better (and tight) bound ${\rm{log}}n - O\left( 1 \right)$ We also show the same bound for prefix-free complexity.Rob

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41

Elvina, Elvina, and Oscar Karnalim. "Complexitor: An Educational Tool for Learning Algorithm Time Complexity in Practical Manner." ComTech: Computer, Mathematics and Engineering Applications 8, no. 1 (2017): 21. http://dx.doi.org/10.21512/comtech.v8i1.3783.

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Based on the informal survey, learning algorithm time complexity in a theoretical manner can be rather difficult to understand. Therefore, this research proposed Complexitor, an educational tool for learning algorithm time complexity in a practical manner. Students could learn how to determine algorithm time complexity through the actual execution of algorithm implementation. They were only required to provide algorithm implementation (i.e. source code written on a particularprogramming language) and test cases to learn time complexity. After input was given, Complexitor generated execution se

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42

Natera, Jose Miguel, and Fulvio Castellacci. "Transformational complexity, systemic complexity and economic development." Research Policy 50, no. 7 (2021): 104275. http://dx.doi.org/10.1016/j.respol.2021.104275.

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43

Papin, Marielle. "Institutional complexity is complexity with an adjective." Complexity, Governance & Networks 6, no. 1 (2021): 82. http://dx.doi.org/10.20377/cgn-101.

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A review of the studies on institutional complexity reveals that the many definitions of institutional complexity and related concepts share similarities with the understanding of complexity and complex systems of complexity science. Yet few publications on institutional complexity engage explicitly with complexity science. Most observers still confuse complicated and complex systems, for instance. Furthermore, the variety of definitions may create disarray regarding what institutional complexity and its related concepts are and what they imply. Highlighting the similarities between institutio

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44

Yang, J., R. Lusk, and W. H. Li. "Organismal complexity, protein complexity, and gene duplicability." Proceedings of the National Academy of Sciences 100, no. 26 (2003): 15661–65. http://dx.doi.org/10.1073/pnas.2536672100.

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45

Chambers, William V. "INTEGRATIVE COMPLEXITY, COGNITIVE COMPLEXITY AND IMPRESSION FORMATION." Social Behavior and Personality: an international journal 13, no. 1 (1985): 27. http://dx.doi.org/10.2224/sbp.1985.13.1.27.

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Personal construct integrative complexity (I-C) refers to the assimilation of complex information into a system of impressions. Consistent with Kelly's (1955) theory of personal constructs, Chambers (1983; 1985) found I-C subjects tended to use a credulous approach to life and were better at resolving conflicting information in forming impressions. In similar research, Crockett et al. (1975) showed a measure of cognitive complexity (C-C) interacted with a credulous cognitive set to be predictive of conflict resolution. In the present study, I-C and C-C are compared, in interaction with cogniti

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46

Rodriguez-Toro, C. A., S. J. Tate, G. E. M. Jared, and K. G. Swift. "Complexity metrics for design (simplicity + simplicity = complexity)." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 217, no. 5 (2003): 721–25. http://dx.doi.org/10.1243/095440503322011461.

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This paper presents an introduction to concepts of complexity in support of assembly-oriented design, to guide the designer in creating a product with the most effective balance of manufacturing and assembly difficulty. The goal is to provide the designer with such information throughout the design process that an efficient design is produced in the first instance. In this paper, definitions and applications of the term ‘complexity’ are reviewed, and then definitions appropriate for the situation are selected. The metrics required for comparison of different complexity variants is discussed. F

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47

Mier, Pablo, Lisanna Paladin, Stella Tamana, et al. "Disentangling the complexity of low complexity proteins." Briefings in Bioinformatics 21, no. 2 (2019): 458–72. http://dx.doi.org/10.1093/bib/bbz007.

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Abstract There are multiple definitions for low complexity regions (LCRs) in protein sequences, with all of them broadly considering LCRs as regions with fewer amino acid types compared to an average composition. Following this view, LCRs can also be defined as regions showing composition bias. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. We present statistics and methodological approaches that measure low complexity (LC) and related sequence properties. Composition bias is often associated with LC and disorder, but rep

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48

Manson, Steven M. "Simplifying complexity: a review of complexity theory." Geoforum 32, no. 3 (2001): 405–14. http://dx.doi.org/10.1016/s0016-7185(00)00035-x.

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49

Kitahara, Kazuo. "Challange to Complexity; (1) Science of Complexity." Journal of the Institute of Television Engineers of Japan 50, no. 1 (1996): 60–67. http://dx.doi.org/10.3169/itej1978.50.60.

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50

Kunneman, Harry. "General Complexity, Ethical Complexity and Normative Professionalization." Foundations of Science 21, no. 2 (2014): 449–53. http://dx.doi.org/10.1007/s10699-014-9407-6.

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