Multiscalar approaches to settlement pattern analysis

This paper has emphasized the highly reflexive approach necessary for the correct identification and interpretation of the processes behind settlement patterns. In our opinion, the key challenges are: (i) to define a sample/study area and its levels of search intensity appropriately (correcting for or exploring “edge effects” statistically where necessary); (ii) to assess and sub-divide site size, function and date range (analysing comparable features only and/or arbitrating uncertain cases statistically); (iii) to account for the resource structure of the landscape (either by only considering environmental homogenous sub-regions or by factoring resource preferences into the significance-testing stage of analysis), and (iv) to use techniques of analysis that are sensitive to detecting patterns at different spatial scales. The latter in particular is an area increasingly well-explored in other disciplines, but as yet with minimal impact on archaeological practice. There remains some value in Clark and Evan’s nearest neighbour function for identifying relationships between sites at one scale of analysis, but it may fail to detect larger-scale patterning. More critically, the dichotomy it encourages between “nucleated” and “dispersed” is at best an overly simplistic model and, at worst, bears little relationship to the reality of settlement organization, which at different scales can show both nucleated and dispersed components. In our Kytheran case study, there is obviously further work to be done, but even with the existing dataset, we have shown that using a combination of Monte Carlo testing, frequency distributions, local density mappings and Ripley’s K function allows a more sensitive assessment of multiscalar patters and therefore a more critical evaluation of the processes underlying settlement distributions

Volumetric pattern analysis of airborne antennas

By blending together the roll and elevation plane high frequency solutions, a very efficient technique was developed for the volumetric pattern analysis of antennas mounted on the fuselage of a generalized aircraft. The fuselage is simulated by an infinitely long, perfectly conducting, elliptic cylinder in cross-section and a composite elliptic cylinder in profile. The wings, nose section, stabilizers, and landing gear doors may be modeled by finite flat or bent plates. Good agreement with accurate scale model measurements was obtained for a variety of airborne antenna problems

The Accumulation of Wear on Footwear Pattern Analysis

Wear is defined as the erosion of a shoe’s outsole or the loss of tread pattern, and it happens gradually over time with use. After a shoeprint is collected from a crime scene, it is questioned whether an individualization can be made if an exemplar is created after additional use of the shoe. The shoes of ten volunteers at San Jose State University were analyzed over a period of 40-45 days. Wear and Randomly Acquired Characteristics (RACs) were analyzed over time to determine if there were any observable changes or additions to the already present wear. It was hypothesized that initial wear and RACs would persist over time. The present wear retained over time throughout the study. Sixty-five percent of the shoes showed no additional wear or RACs. The remaining 35% showed at most 1 cm of additional loss of tread pattern. Therefore, it is possible for an individualization after 40-45 days between evidence collections. This study was limited by the time allotted. Future studies will need to investigate wear over many months of use

Spatial Point Pattern Analysis and Industry Concentration

Traditional measures of spatial industry concentration are restricted to given areal units. They do not make allowance for the fact that concentration may be differently pronounced at various geographical levels. Methods of spatial point pattern analysis allow to measure industry concentration at a continuum of spatial scales. While common distancebased methods are well applicable for sub-national study areas, they become inefficient in measuring concentration at various levels within industrial countries. This particularly applies in testing for conditional concentration where overall manufacturing is used as a reference population. Using Ripley’s K function approach to second-order analysis, we propose a subsample similarity test as a feasible testing approach for establishing conditional clustering or dispersion at different spatial scales. For measuring the extent of clustering and dispersion, we introduce a concentration index of the style of Besag’s (1977) L function. By contrast to Besag’s L function, the new index can be employed to measure deviations of observed from general spatial point patterns. The K function approach is illustratively applied to measuring and testing industry concentration in Germany.Spatial concentration, clustering, dispersion, spatial point pattern analysis, K function

Towards Egocentric Person Re-identification and Social Pattern Analysis

Wearable cameras capture a first-person view of the daily activities of the camera wearer, offering a visual diary of the user behaviour. Detection of the appearance of people the camera user interacts with for social interactions analysis is of high interest. Generally speaking, social events, lifestyle and health are highly correlated, but there is a lack of tools to monitor and analyse them. We consider that egocentric vision provides a tool to obtain information and understand users social interactions. We propose a model that enables us to evaluate and visualize social traits obtained by analysing social interactions appearance within egocentric photostreams. Given sets of egocentric images, we detect the appearance of faces within the days of the camera wearer, and rely on clustering algorithms to group their feature descriptors in order to re-identify persons. Recurrence of detected faces within photostreams allows us to shape an idea of the social pattern of behaviour of the user. We validated our model over several weeks recorded by different camera wearers. Our findings indicate that social profiles are potentially useful for social behaviour interpretation