Ordered Hypotheses for Multiple Treatments: A Significance Test for Linear Ranks

Page, Ellis B.

doi:10.1080/01621459.1963.10500843

Cited by 511 publications

(25 citation statements)

References 15 publications

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“…3A. Page's test (Page, 1963) revealed that this decrease in the number of unique labels was significant (L = 1,993, m = 4, n = 11, p < .001). These results show that the languages are becoming less expressive over time.…”

Section: Loss Of Expressivitymentioning

confidence: 87%

The Cultural Evolution of Structured Languages in an Open‐Ended, Continuous World

et al. 2016

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Language maps signals onto meanings through the use of two distinct types of structure. First, the space of meanings is discretized into categories that are shared by all users of the language. Second, the signals employed by the language are compositional: The meaning of the whole is a function of its parts and the way in which those parts are combined. In three iterated learning experiments using a vast, continuous, open‐ended meaning space, we explore the conditions under which both structured categories and structured signals emerge ex nihilo. While previous experiments have been limited to either categorical structure in meanings or compositional structure in signals, these experiments demonstrate that when the meaning space lacks clear preexisting boundaries, more subtle morphological structure that lacks straightforward compositionality—as found in natural languages—may evolve as a solution to joint pressures from learning and communication.

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Section: Loss Of Expressivitymentioning

confidence: 87%

The Cultural Evolution of Structured Languages in an Open‐Ended, Continuous World

et al. 2016

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“…For all three bead sizes, we observed a monotonically decreasing trend for beads deposited and number of steps. We used Page's L tests to determine the significance and found that all bead sizes follow this trend (L 1 ¼ 10 600 with N ¼ 32, L 10 ¼ 9240 with N ¼ 27, L 45 ¼ 11 200 with N ¼ 33, all with p , 0.001) [35].…”

Section: Particles Removed During Climbingmentioning

confidence: 99%

Soiled adhesive pads shear clean by slipping: a robust self-cleaning mechanism in climbing beetles

Amador¹,

Endlein²,

Sitti³

2017

J. R. Soc. Interface.

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Animals using adhesive pads to climb smooth surfaces face the problem of keeping their pads clean and functional. Here, a self-cleaning mechanism is proposed whereby soiled feet would slip on the surface due to a lack of adhesion but shed particles in return. Our study offers an quantification of self-cleaning performance in fibrillar adhesives, using the dock beetle as a model organism. After beetles soiled their pads by stepping into patches of spherical beads, we found that their gait was significantly affected. Specifically, soiled pads slipped 10 times further than clean pads, with more particles deposited for longer slips. Like previous studies, we found that particle size affected cleaning performance. Large (45 μm) beads were removed most effectively, followed by medium (10 μm) and small (1 μm). Consistent with our results from climbing beetles, force measurements on freshly severed legs revealed larger detachment forces of medium particles from adhesive pads compared to a flat surface, possibly due to interlocking between fibres. By contrast, dock leaves showed an overall larger affinity to the beads and thus reduced the need for cleaning. Self-cleaning through slippage provides a mechanism robust to particle size and may inspire solutions for artificial adhesives.

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“…The hypothetical rankings determined through the post-hoc analysis are confirmed using Page's trend test (Page 1963). The hypothetical rankings obtained through the post-hoc analyzes and their confirmations using Page's trend test are presented in Table 7.…”

Section: Question-wise Rankings From Post-hoc Analysismentioning

confidence: 99%

Development and comparison of aerial photograph aided visualization pipelines for LiDAR datasets

Ghosh

Lohani

2014

International Journal of Digital Earth

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Light Detection and Ranging (LiDAR) technology generates dense and precise threedimensional datasets in the form of point clouds. Conventional methods of mapping with airborne LiDAR datasets deal with the process of classification or feature specific segmentation. These processes have been observed to be time-consuming and unfit to handle in scenarios where topographic information is required in a small amount of time. Thus there is a requirement of developing methods which process the data and reconstruct the scene in a small amount of time. This paper presents several pipelines for visualizing LiDAR datasets without going through classification and compares them using statistical methods to rank these processes in the order of depth and feature perception. To make the comparison more meaningful, a manually classified and computer-aided design (CAD) reconstructed dataset is also included in the list of compared methods. Results show that a heuristic-based method, previously developed by the authors perform almost equivalent to the manually classified and reconstructed dataset, for the purposes of visualization. This paper makes some distinct contributions as: (1) gives a heuristics-based visualization pipeline for LiDAR datasets, and (2) presents an experimental design supported by statistical analysis to compare different pipelines.

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Ordered Hypotheses for Multiple Treatments: A Significance Test for Linear Ranks

Cited by 511 publications

References 15 publications

The Cultural Evolution of Structured Languages in an Open‐Ended, Continuous World

The Cultural Evolution of Structured Languages in an Open‐Ended, Continuous World

Soiled adhesive pads shear clean by slipping: a robust self-cleaning mechanism in climbing beetles

Development and comparison of aerial photograph aided visualization pipelines for LiDAR datasets

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