Design agents and the need for high-dimensional perception

Designed artefacts may be quantified by any number of measures. This paper aims to show that in doing so, the particular measures used may matter very little, but as many as possible should be taken. A set of building plans is used to demonstrate that arbitrary measures of their shape serve to classify them into neighbourhood types, and the accuracy of classification increases as more are used, even if the dimensionality of the space in which classification occurs is held constant. It is further shown that two autonomous agents may independently choose sets of attributes by which to represent the buildings, but arrive at similar judgements as more are used. This has several implications for studying or simulating design. It suggests that quantitative studies of collections of artefacts may be made without requiring extensive knowledge of the best possible measures—often impossible in real, ill-defined, design situations. It suggests a means by which the generation of novelty can be explained in a group of agents with different ways of seeing a given event. It also suggests that communication can occur without the need for predetermined codes or protocols, introducing the possibility of alternative human-computer interfaces that may be useful in design

Inductive machine learning of optimal modular structures: Estimating solutions using support vector machines

Structural optimization is usually handled by iterative methods requiring repeated samples of a physics-based model, but this process can be computationally demanding. Given a set of previously optimized structures of the same topology, this paper uses inductive learning to replace this optimization process entirely by deriving a function that directly maps any given load to an optimal geometry. A support vector machine is trained to determine the optimal geometry of individual modules of a space frame structure given a specified load condition. Structures produced by learning are compared against those found by a standard gradient descent optimization, both as individual modules and then as a composite structure. The primary motivation for this is speed, and results show the process is highly efficient for cases in which similar optimizations must be performed repeatedly. The function learned by the algorithm can approximate the result of optimization very closely after sufficient training, and has also been found effective at generalizing the underlying optima to produce structures that perform better than those found by standard iterative methods

Spectral comparison of large urban graphs

The spectrum of an axial graph is proposed as a means for comparison between spaces, particularly for measuring between very large and complex graphs. A number of methods have been used in recent years for comparative analysis within large sets of urban areas, both to investigate properties of specific known types of street network or to propose a taxonomy of urban morphology based on an analytical technique. In many cases, a single or small range of predefined, scalar measures such as metric distance, integration, control or clustering coefficient have been used to compare the graphs. While these measures are well understood theoretically, their low dimensionality determines the range of observations that can ultimately be drawn from the data. Spectral analysis consists of a high dimensional vector representing each space, between which metric distance may be measured to indicate the overall difference between two spaces, or subspaces may be extracted to correspond to certain features. It is used for comparison of entire urban graphs, to determine similarities (and differences) in their overall structure. Results are shown of a comparison of 152 cities distributed around the world. The clustering of cities of similar properties in a high dimensional space is discussed. Principal and nonlinear components of the data set indicate significant correlations in the graph similarities between cities and their proximity to one another, suggesting that cultural features based on location are evident in the city form and that these can be quantified by the proposed method. Results of classification tests show that a city’s location can be estimated based purely on its form. The high dimensionality of the spectra is beneficial for its utility in data-mining applications that can draw correlations with other data sets such as land use information. It is shown how further processing by supervised learning allows the extraction of relevant features. A methodological comparison is also drawn with statistical studies that use a strong correlation between human genetic markers and geographical location of populations to derive detailed reconstructions of prehistoric migration. Thus, it is suggested that the method may be utilised for mapping the transfer of cultural memes by measuring comparison between cities

Where creativity comes from: the social spaces of embodied minds

This paper explores creative design, social interaction and perception. It proposes that creativity at a social level is not a result of many individuals trying to be creative at a personal level, but occurs naturally in the social interaction between comparatively simple minds embodied in a complex world. Particle swarm algorithms can model group interaction in shared spaces, but design space is not necessarily one pre-defined space of set parameters on which everyone can agree, as individual minds are very different. A computational model is proposed that allows a similar swarm to occur between spaces of different description and even dimensionality. This paper explores creative design, social interaction and perception. It proposes that creativity at a social level is not a result of many individuals trying to be creative at a personal level, but occurs naturally in the social interaction between comparatively simple minds embodied in a complex world. Particle swarm algorithms can model group interaction in shared spaces, but design space is not necessarily one pre-defined space of set parameters on which everyone can agree, as individual minds are very different. A computational model is proposed that allows a similar swarm to occur between spaces of different description and even dimensionality

Representation and generation of plans using graph spectra

Numerical comparison of spaces with one another is often achieved with set scalar measures such as global and local integration, connectivity, etc., which capture a particular quality of the space but therefore lose much of the detail of its overall structure. More detailed methods such as graph edit distance are difficult to calculate, particularly for large plans. This paper proposes the use of the graph spectrum, or the ordered eigenvalues of a graph adjacency matrix, as a means to characterise the space as a whole. The result is a vector of high dimensionality that can be easily measured against others for detailed comparison. Several graph types are investigated, including boundary and axial representations, as are several methods for deriving the spectral vector. The effectiveness of these is evaluated using a genetic algorithm optimisation to generate plans to match a given spectrum, and evolution is seen to produce plans similar to the initial targets, even in very large search spaces. Results indicate that boundary graphs alone can capture the gross topological qualities of a space, but axial graphs are needed to indicate local relationships. Methods of scaling the spectra are investigated in relation to both global local changes to plan arrangement. For all graph types, the spectra were seen to capture local patterns of spatial arrangement even as global size is varied

Representation and generation of plans using graph spectra

Numerical comparison of spaces with one another is often achieved with set scalar measures such as global and local integration, connectivity, etc., which capture a particular quality of the space but therefore lose much of the detail of its overall structure. More detailed methods such as graph edit distance are difficult to calculate, particularly for large plans. This paper proposes the use of the graph spectrum, or the ordered eigenvalues of a graph adjacency matrix, as a means to characterise the space as a whole. The result is a vector of high dimensionality that can be easily measured against others for detailed comparison. Several graph types are investigated, including boundary and axial representations, as are several methods for deriving the spectral vector. The effectiveness of these is evaluated using a genetic algorithm optimisation to generate plans to match a given spectrum, and evolution is seen to produce plans similar to the initial targets, even in very large search spaces. Results indicate that boundary graphs alone can capture the gross topological qualities of a space, but axial graphs are needed to indicate local relationships. Methods of scaling the spectra are investigated in relation to both global local changes to plan arrangement. For all graph types, the spectra were seen to capture local patterns of spatial arrangement even as global size is varied

Exploring the Effects of Caring for Congestive Heart Failure Patients on Caregiver Well-Being: A Descriptive Study

Background: As the incidence of heart failure (HF) quickly becomes the leading cause of disability among older adults, the need for non-professional, in-home caregivers increases as well. Many caregivers are family members who receive no compensation for their efforts, but all are an invaluable tool in the fight against a debilitating disease. Patients with caregivers experience an improved quality of life and lower mortality rates than patients with little social support. The caregiver of a patient with HF may be responsible for everyday activities such as housekeeping and shopping, as well as more complex disease-related necessities as managing medication regimens and fluid restrictions. The stresses associated with caring for a loved one with a progressive and life-altering disease can take a toll on the caregiver, contributing to a decrease in caregiver health and increase in mortality. Purpose: The purpose of this study was to explore how stress factors of caring for an individual with HF impact the emotional health, physical health, social activity, relationships, and lifestyle of the caregiver. Methodology: The study protocol was approved by the University of Arkansas and Washington Regional Medical Center Institutional Review Boards. Patients were accessed through a HF clinic in Northwest Arkansas, the Advanced Nurse Practitioner identifying patients that met the criteria of having an unpaid caregiver as defined in the study. The prospective cohort study was conducted September to December 2016 with 29 individuals identified as friends or family members of a patient with HF who provided care to the HF patient and received no financial compensation for their services. The Caregiver Burden Questionnaire – HF Version 3.0, consists of 26 questions regarding how the caregiver’s experience has been over the past four weeks of caregiving, and was used to measure four domains of physical, emotional/psychological, social, and lifestyle burdens. Results: Summary scores were created for all variables and descriptive statistics used. A Spearman’s rank-order correlation was used to determine the strength and direction of the association between variables. In agreement with previous research findings, physical health of the caregiver was positively correlated with emotional well-being. Discussion: Being a caregiver for a patient with HF can cause strain for the caregiver, but can also be rewarding. The benefits, such as feeling a sense of reward through helping someone else, can provide an emotional buffer that supports the caregiver through times of hospitalization or decline in the patient’s condition. Our findings suggest that interventions implemented to increase the caregiver’s perception of emotional support, perhaps through repeated contact by a healthcare professional, could improve caregiver, and therefore patient, outcomes

Invasion of transition hardwood forests by exotic Rhamnus frangula: Chronology and site requirements

The invasion chronology and site requirements of the exotic, invasive shrub, glossy buckthorn (Rhamnus frangula), were studied within intact transition hardwood---hemlock---white pine forests in Durham, NH. Data were collected from 63 plots (7 sites with 9 plots each). Within sites, plots were arranged over a topographic gradient with 3 plots in each of 3 topographic positions (upper, middle, and lower slope). From each plot, information on soil nutrients and texture, soil moisture, overstory community composition, and canopy openness was collected. Densities of R. frangula in two size classes (≥1 m in height, \u3c1 m in height) within each plot were calculated. Morphological data (height, diameter at stem base, number of live and dead stems, and age) were collected from each individual ≥1 m tall. R. frangula invaded these intact, closed-canopy forests over 30 years ago and the invasion has continued, with population density increasing over time. Nominal logistic regression suggested that site, topographic position, and overstory community type played a role in whether or not R. frangula was present in a plot. Plots on upper slopes dominated by Tsuga canadensis were less likely to become invaded than other plots. Multiple linear regression showed that density of R. frangula (≥1 m) increased with time since invasion and increasing soil quality. Density of R. frangula (\u3c1 m) was positively influenced by time since invasion, canopy openness, and density of R. frangula (≥1 m). Multiple regressions also showed that mean age and age of oldest R. frangula per plot were higher in plots with higher soil moisture content. Size of R. frangula individuals (i.e. height, diameter) generally increased with mean age of stems. The results show that successional, transition hardwood forests can be invaded by R. frangula and should not be overlooked when managing against this species. Special attention should be given to low topographic positions and areas with rich soils, while upland areas with dense hemlock canopy are much less likely to experience heavy invasion by R. frangula.

Optimising continuous microstructures: a comparison of gradient-based and stochastic methods

This work compares the use of a deterministic gradient based search with a stochastic genetic algorithm to optimise the geometry of a space frame structure. The goal is not necessarily to find a global optimum, but instead to derive a confident approximation of fitness to be used in a second optimisation of topology. The results show that although the genetic algorithm searches the space more broadly, and this space has several global optima, gradient descent achieves similar fitnesses with equal confidence. The gradient descent algorithm is advantageous however, as it is deterministic and results in a lower computational cost