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Space production quilts

Space production quilts

Our machines use standard voltage. A regular wall outlet is all that is needed; however, it is recommended you plug your machine into a high-quality surge protector. Length of time to complete a king-size quilt would depend on the style of quilting and complexity of the pattern i. A foot table has inches of canvas to attach to and a foot table has inches. All models come on tables that are 12 feet in length.

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Solution Quilts

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Human artefacts in general are highly structured and often display ordering principles such as translational, reflectional or rotational symmetry. In contrast, human artefacts that are intended to appear random and non symmetrical are very rare. Furthermore, many studies show that humans find it extremely difficult to recognize or reproduce truly random patterns or sequences.

Here, we attempt to model two-dimensional decorative spatial patterns produced by humans that show no obvious order. Crazy quilts are unusual because unlike most human artefacts, they are specifically intended to appear haphazard and unstructured.

We evaluate the degree to which this intention was achieved by using statistical techniques of spatial point pattern analysis to compare crazy quilts with regular quilts from the same region and era and to evaluate the fit of various random distributions to these two quilt classes. We found that the two quilt categories exhibit fundamentally different spatial characteristics: The patch areas of crazy quilts derive from a continuous random distribution, while area distributions of regular quilts consist of Gaussian mixtures.

These Gaussian mixtures derive from regular pattern motifs that are repeated and we suggest that such a mixture is a distinctive signature of human-made visual patterns. In contrast, the distribution found in crazy quilts is shared with many other naturally occurring spatial patterns. Centroids of patches in the two quilt classes are spaced differently and in general, crazy quilts but not regular quilts are well-fitted by a random Strauss process. These results indicate that, within the constraints of the quilt format, Victorian quilters indeed achieved their goal of generating random structures.

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. WG17 to W. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: W. Human ornaments and decorative art represent a class of biologically generated patterns typified by a high degree of structure and order.

Conventional decorative patterns can typically be described by their underlying symmetry [1]. Human visual artefacts very rarely intentionally violate ordering principles such as symmetry and repetition. Although randomness serves as the typical null hypothesis in the physical sciences, it has long been known that humans have great difficulty in producing random output.

Seemingly random behaviours are not uncommon in the biological world e. Apparently, humans are well equipped to detect and create ordered structures, but not random structures. One candidate class are crazy quilts: a once popular class of textile craftwork often intended for display. A crazy quilt is a blanket consisting of two fabric layers. This quilt type is unusual because it is made, unlike most other quilts, specifically to create an irregular aesthetic impression.

It is often claimed that the arrangement of the patches is random, e. In this paper, we aim to evaluate this claim by describing the properties of spatial patterns in quilts and to quantify the differences in orderedness between regular and crazy quilts see Fig.

In all images, the margins that did not contain patchwork were cropped out prior to analysis. Our analysis of real-life visual patterns follows an approach in empirical aesthetics first outlined by Gustav Fechner in the late 19th century [9] , [10]. Fechner advocated the use of three methods to investigate aesthetic proclivities in humans: studying how people produce artefacts, how artefacts are perceived and the description of properties of artefacts encountered in real life.

Research on the human production and perception processes of visual patterns in the lab [11] , [12] has shown that abstract geometrical patterns have a near universal aesthetic appeal and that the ordering principles underlying them are readily understood by a wide range of humans. Formal descriptions of real-life patterns, in particular Islamic tilings, exist that are based on classification systems derived from crystallography [1] , [13] — [15] , but very little work has been done to formally describe disorderly artefacts and patterns that do not adhere strictly to conventional symmetry classes.

Previous research applying spatial analysis tools to human artwork has focussed mainly on paintings [16] — [21] , photography [22] , [23] or on traditional patterns used in pottery and other ornamental objects [1] , [24].

Much less quantitative research has been devoted to patchwork, though see [25] , [26]. Patchwork is the stitching together of small pieces of cloth patches , into a larger unit, typically used for blankets, pillowcases or clothing. Though patchwork is best known from English-speaking cultures, in particular North America and England, it is has traditionally been produced in many countries e.

Crazy quilts are a form of patchwork that enjoyed a brief period of popularity in the late 19th and early 20th century. The oldest examples are from the s. These quilts were widely produced until the s, after which their popularity waned, although they are still occasionally produced today by patchworkers around the world. Crazy quilts typically contain many different fabric types and fabric patterns. Additionally, the edges of patches are decorated with a wide variety of embroidery stitches and centres are often embroidered with vignettes of animals and plants, although the embroidery seems to have become less elaborate as the fad progressed [25].

In combination, crazy quilts evoke an impression of lavishness and wild abundance that stands in stark contrast to the strict rules of traditional quilts and Victorian society more generally. The roots of Western crazy quilts may lie in Japanese patchwork. In Japan, the technique of yosegire reusing precious fabrics in coats and kimonos was popular in the 19th century.

Examples of yosegire patchwork appear quite unstructured, lacking the rigid repetitions of Western patterns. Japan began trading with the West in with the convention of Kanagawa, ending years of isolation policy. In , a range of textiles were displayed at the Japanese stand of the Centennial Exposition in Philadelphia, which had close to ten million visitors the population of the United States at the time was about 38 million [27].

Several historians claim this exhibition and ensuing popularity of Japanese craft was the inspiration behind American crazy patchwork [8] , [28].

Quilts in general are subject to a number of constraints that would be difficult to capture in standard random models e. Two key constraints are that patches must exceed some minimum size minimal area constraint and that, although rare exceptions exist, the overall quilt shape must be approximately rectangular edge constraint. In general, patch edges are straight for the practical reason that straight seams are easier to sew than curves if the patches are to lie flat. Unfortunately, the direct analysis of patch edges as line segments number, angle, etc is difficult, because the seams are not necessarily perfectly straight and thus vertices and corners cannot always be unambiguously classified.

In this study, we focussed instead on the properties of the patch areas and centroids, which can both be precisely calculated and serve as adequate measures of spatial organisation for our purposes.

With these constraints in mind, we adopted a Strauss process over patch centroids as our random comparison model.

A Strauss process, introduced by David Strauss in [31] , is a superset of a Poisson process which models interactions between points in the plane i. Strauss processes were further developed by Kelly and Ripley [32] and have been applied to a wide variety of biological spatial patterns, for example to model herd animal dispersion [33] , spatial distribution of tree species [34] or neuron locations in the brain [35].

Because of imprecision in manual motor control, imperfection is inherent in any handmade object. While each block is a nearly exact copy of the pattern, blocks will nonetheless show some unintentional random variation.

Minimally, we predict that crazy quilts will be significantly more random than such regular quilts. A finding that qualitatively different spatial models fit these two classes would be germane to our overall question of the hypothesised randomness of crazy quilts. Our overall goal in this study is to evaluate the degree to which crazy quilts are compatible with a random generative process, and the degree to which this differentiates them from regular quilts.

This broad question leads directly to testable hypotheses concerning patch area and patch centroid location labelled HR and HC for hypotheses about regular and crazy quilts, respectively :.

HC1: Crazy quilts are intended to create a haphazard and irregular impression. If this intention is realized, the location of patch centroids should be adequately modelled by a random spatial process. HC2: Because crazy quilts lack repeating motifs or patch types, the patch areas should come from a single overall distribution. Furthermore, as patch ensembles are constrained to fit within rectangles, we expect small patches to be more numerous than large ones.

We thus predict a positive-skewed but otherwise continuous distribution of patch sizes. HR1: Because patterns in regular quilts are intended to be periodic and symmetrical, the locations of patch centroids should not be adequately modelled by a random spatial process.

HR2: Regular quilts are made up of repeating motifs consisting of a small number of patch types. Because each element of a given type is intended to be identical in size and shape, but will include some small degree of error, we expect the overall patch size distribution of a regular quilt to be a composite of the individual distributions for each patch type as a mixture of Gaussian distributions rather than the single overall distribution predicted for crazy quilts, in HC2.

We performed a detailed spatial analysis of hand-tracings of 8 crazy quilts and 8 regular quilts from North America. Their overall properties are summarised in table 1. To ensure that the quilts had a comparable level of structural complexity and similar internal constraints, all quilts had at least one level of regular subdivision, i.

Because many quilts were made anonymously, it was not possible to date the quilts exactly, but based on the published sources, we ensured that the quilts stemmed from roughly the same geographic area USA and time ca. Additionally, we only selected images that showed the entire quilt in sufficient detail to allow an exact delineation of patches within the quilts. The analysed quilts were selected from commercially available quilt books [7] , [36] , [37]. In general, these quilts were blanket size, but one of the crazy quilts C5 , was considerably smaller than the others, roughly pillowcase size.

Digital images of the quilts were scanned from printed photographs at dots per inch CanoScan LiDe , Canon.

Despite intensive efforts, we were unable to use segmentation algorithms to derive accurate patch borders automatically, due to considerable internal complexity and heterogeneity of the quilt patches.

The tracings are shown in Fig. We converted the ROIs from pixels to cm 2 by scaling the scanned image based on the measurements of the photographs of the quilts and the dimension given in the source books. This scale was estimated twice, based on length and width measurements, and then averaged.

We excluded non-patched borders long continuous strips of fabric from the analysis, isolating the area containing patches by using the smallest possible bounding box around the patched area. For each individual patch, we computed the centroid by averaging the x and y values of the pixels within the patch and the area in FIJI.

Measurement accuracy was evaluated by remeasuring one randomly selected patch from each quilt ten times and analysing the absolute range of measurements for each quilt category.

We analysed the patch area distributions in two ways: first, by fitting multimodal distributions Gaussian mixture models and second, by fitting various standard random unimodal distributions. For unimodal distributions, we chose three plausible candidates that take only positive values: the gamma, Weibull and lognormal distribution, with no a priori reason to favour any one of these particular distributions.

The gamma distribution can take a wide variety of forms, which has led it to be widely used for modelling spatial and temporal characteristics of rainfall [39] , mutation rates in human mitochondrial DNA [40] and rate of material deterioration [41].

The Weibull distribution [42] is often used to model product failure, but also human aging and mortality for a review of recent applications see [43]. Furthermore, the distribution of two- and three-dimensional particle sizes, e. The lognormal distribution applies to variables whose logarithms have a normal distribution [46].

Finally, we also included the standard normal distribution, since we predicted this would fit regular quilts best in the form of Gaussian mixture models. We used maximum likelihood estimation to fit the distributions with the R version 2.

We used the Akaike Information Criterion AIC [51] , a measure derived from the log likelihood function, to assess which of these distributions fit the data best. To additionally evaluate the likelihood of one model over the other, we follow Burnham and Anderson [52] in converting AIC values into normalised Akaike weights which indicate the likelihood of a model given the data. This adjustment is particularly useful when comparing two models with similar AIC values.

Unlike conventional statistical tests, AIC does not allow absolute inferences about how well a model fits the data; instead it provides a relative assessment of which of the available models fits the data best, compared to the other candidates.

We constructed Gaussian mixture models for both quilt categories. For regular quilts, we classified the patches into categories i. We used the area means, standard deviations and relative frequencies of each patch category to seed the mixture models which we then used to randomly generate the same number of elements as in the quilts.

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FABRIC COLLECTIONS

Ship captains in the 19th and 20th centuries used a series of signal flags, squares of colored-blocked fabric and simple shapes, to communicate this phrase and many others night by night to other vessels passing on the water. They needed them to know: through the darkness, I am by your side. Red diamond on a white background, red and yellow square, red circle on a white background. Amy Bornman claimed that phrase more than a year ago when she began creating these signal flags herself. Looking up from the International Code of Signals dictionary sitting on her coffee table-turned-fabric-cutting space as the morning light streams into her apartment, Bornman describes them in an intimate way. Meaning: it says that which means this. The year-old fiber artist owns All Well Workshop, a virtual space where she sells signal flags, quilts, clothing and other handmade items.

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In the s, economic prospects for manufacturing quilts and duvets faltered. Quilts were a commodity, buying habits changed, and price became the main competitive focus in the industry.

Human artefacts in general are highly structured and often display ordering principles such as translational, reflectional or rotational symmetry. In contrast, human artefacts that are intended to appear random and non symmetrical are very rare. Furthermore, many studies show that humans find it extremely difficult to recognize or reproduce truly random patterns or sequences. Here, we attempt to model two-dimensional decorative spatial patterns produced by humans that show no obvious order. Crazy quilts are unusual because unlike most human artefacts, they are specifically intended to appear haphazard and unstructured. We evaluate the degree to which this intention was achieved by using statistical techniques of spatial point pattern analysis to compare crazy quilts with regular quilts from the same region and era and to evaluate the fit of various random distributions to these two quilt classes. We found that the two quilt categories exhibit fundamentally different spatial characteristics: The patch areas of crazy quilts derive from a continuous random distribution, while area distributions of regular quilts consist of Gaussian mixtures.

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Performed the experiments: GWF. Analyzed the data: GWF. Human artefacts in general are highly structured and often display ordering principles such as translational, reflectional or rotational symmetry. In contrast, human artefacts that are intended to appear random and non symmetrical are very rare. Furthermore, many studies show that humans find it extremely difficult to recognize or reproduce truly random patterns or sequences. Here, we attempt to model two-dimensional decorative spatial patterns produced by humans that show no obvious order. Crazy quilts are unusual because unlike most human artefacts, they are specifically intended to appear haphazard and unstructured. We evaluate the degree to which this intention was achieved by using statistical techniques of spatial point pattern analysis to compare crazy quilts with regular quilts from the same region and era and to evaluate the fit of various random distributions to these two quilt classes.

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Quilts have been produced for centuries, as utilitarian blankets, decorations, family heirlooms, and now treasured museum collections objects. Quilts are three-layered textile pieces with a decorated top, a back, and a filler in the middle. The composite nature of these objects creates an interesting challenge for their conservation, as the separate layers can be made of different textile materials, multiple colors, and therefore, varying degrees of wear, tear, and damage. A quilt is a multi-layered textile, traditionally composed of three layers of fiber: a woven cloth top, a layer of batting or wadding, and a woven back, combined using the technique of quilting , the process of sewing the three layers together. The pattern of stitching can be the key decorative element if a single piece of fabric is used for the top of a quilt a "wholecloth quilt" , but in many cases the top is pieced from a patchwork of smaller fabric pieces; and the pattern and color of these pieces will be important to the design. The quilts produced in Gee's Bend , Alabama are great examples of the history and use of quilts in specific space and time. Quilting is the process of sewing two or more layers of fabric together to make a thicker padded material, usually to create a quilt or quilted garment.

The Art of Quilting: Stitching Together a Community

In in his garage in Chicago, Illinois Arthur Schwarzberger developed a simple sewing concept for quilting machines that could crossover sewing lines. Arthur refined his concept and began manufacturing mechanical track quilting machines for the comforter, bedspread and mattress markets.

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John Forrest is a retired educator and administrator living in Severn Township, near Orillia, with his wife Carol. He is well known for his Christmas stories and his three books of anecdotes, spanning childhood to the present.

John Forrest is a retired educator and administrator living in Severn Township, near Orillia, with his wife Carol. He is well known for his Christmas stories and his three books of anecdotes, spanning childhood to the present.

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