A Multi-objective Optimization Approach for Disaggregating Employment Data

In many countries, including South Africa, data on employment is rarely available on a downscaled level, such as building level, and is only available on less detailed levels, such as municipal level. The aim of this research was to develop a methodology to disaggregate the employment data that is available at an aggregate level to a disaggregate, detailed building level. To achieve this, the methodology consisted of two parts. First, a method was established that could be used to prepare a base data set to be used for disaggregating the employment data. Second, a multiobjective optimization approach was used to allocate the number of employment opportunities within a municipality to building level. The algorithm was developed using an Evolutionary Algorithm framework and applied to a case study in a metropolitan municipality in South Africa. The results showed favorable use of multiobjective optimization to disaggregate employment data to building level. By enhancing the detail of employment data, planners, policy makers, modelers and other users of such data can benefit from understanding employment patterns at a much more detailed level and making improved decisions based on disaggregated data and models.     

Identifying Functional Urban Areas in Ecuador Using a Varying Travel Time Approach

Identifying integrated urban areas is an important issue for urban analysis and policy evaluation. In this article, we provide a set of FUAs suitable for monitoring urbanization in Ecuador, a less developed country without commuting data. We do so substituting such socioeconomic flows by available information on road structure, which allow us to work with accessibility based on a varying travel time. In order to build Ecuadorean FUAs, we calibrate our methodology considering Colombian data. We perform several sensitivity analysis and robustness checks to Ecuador with alternative sources of socioeconomic flows. We conclude that the use of GIS data and the calibrated thresholds provide a set of FUAs similar to the ones that would result of using commuting information.     

Residential property disparities in city districts in Prague,Czech Republic

City districts are often classified as ‘rich’ or ‘poor,’ a phenomenon that occurs within cities all over the world. While income inequality, wealth inequality, and other kinds of social inequality are frequently tracked, there is a surprising lack of research concentrating on how social inequality manifests as differences between parts of cities, especially outside of the U.S. That is mostly due to insufficient available data. In this paper, we propose a methodology for measuring the relative inequality between city districts by using the average prices of residential properties in various parts of the city, and assessing their relative difference. This approach has several advantages, as property listings are often readily available even in cities where income data is not. This methodology has potential for measuring developments in inequality in a much wider range of cities. As a proof of concept, we apply this methodology to property prices in Prague during the period 2003–2012 to identify a trend of either growing or decreasing inequality among individual parts of the city. We have found that during this period the disparity has grown only 5.97%, which means the overall growth of disparity between the city districts was negligible.     

A new method for identifying sherd refits: A case study from the Neolithic of Northumbria,U.K.

Abstract

Here we present a flexible, quantitative methodology for refitting handmade ceramics. Rather than analyzing the physical joins between sherds, we assess the likelihood that non-adjoining sherds of similar appearance are from the same vessel. The customary disregard of non-adjoining sherds in refitting experiments prompts us to address this issue. Using the Neolithic ceramic assemblage from Thirlings (Northumberland, U.K.) as a case study, we test several scoring systems for assessing the probability of two sherds pertaining to the same vessel. The utility of this approach is supported by the comparison of a set of percentage scores statistically verified using Spearman’s rank correlation coefficient. We conclude with a discussion of the contribution of the new method to post-excavation ceramic analyses, and its applicability to other assemblages.     

THE BAYESIAN APPROACH TO THE INTERPRETATION OF ARCHAEOLOGICAL DATA

Archaeologists are increasingly becoming aware of an approach to data investigation known as Bayesian statistics. In this paper we outline both the philosophical and statistical background to the approach. We show that it provides a logical and coherent framework in which to make inferences on the basis of both data and a priori expert knowledge. We note that adoption of the Bayesian framework is particularly timely since there have been recent dramatic developments in numerical methods which mean that a number of previous implementation problems have now been solved. As a result, many questions of archaeological interest, which require the use of complex statistical models, are being investigated using this methodology. We use a variety of recently published examples from a range of archaeological areas to illustrate the type of questions that can be answered and the nature of the methodologies used, and we make comparisons with the results obtained using more traditional statistical techniques.     

Measuring the Complexity of Past Social Systems: a Task Analysis Approach to the Study of Late Prehistoric Monumentality in Iberia

In this paper, we explore the heuristic potential of a set of ideas about the structural and functional complexity of systems, proposed in the 1990s by theoretical biologist Daniel McShea. In particular, we focus on the structural aspects of the complexity exhibited by social systems organized into low- and intermediate-level functional units (i.e., groups and teams). To address this subject, we describe a methodology suited for measuring the complexity in the organization of work in such systems, which is primarily based on hierarchical task analysis. With this methodology, we approach a concrete case study: the construction of megalithic monuments in late prehistoric Iberia (ca. 3800–1800 BC). On the basis of the analysis of the three best documented, most structurally, and functionally complex monuments built within each of the three periods under study (Late Neolithic, Copper Age, and Early Bronze Age), we found that there was a trend towards less complexity in work organization related to monument building from the Late Neolithic to the Early Bronze Age. We discuss the importance of these results in light of the existing models of social complexity in European Later Prehistory, concluding that a more balanced view of social processes would be obtained if we look at complexity as a property of every different social system integrated into the whole society, and not as an exclusive property of the latter.

     

A SPATIAL AND TEMPORAL AUTOREGRESSIVE LOCAL ESTIMATION FOR THE PARIS HOUSING MARKET

ABSTRACT This original study examines the potential of a spatiotemporal autoregressive Local (LSTAR) approach in modeling transaction prices for the housing market in inner Paris. We use a data set from the Paris Region notary office (Chambre des notaires d’Île‐de‐France) which consists of approximately 250,000 transactions units between the first quarter of 1990 and the end of 2005. We use the exact X–Y coordinates and transaction date to spatially and temporally sort each transaction. We first choose to use the STAR approach proposed by Pace et al., 1998 . This method incorporates a spatiotemporal filtering process into the conventional hedonic function and attempts to correct for spatial and temporal correlative effects. We find significant estimates of spatial dependence effects. Moreover, using an original methodology, we find evidence of a strong presence of both spatial and temporal heterogeneity in the model. It suggests that spatial and temporal drifts in households socio‐economic profiles and local housing market structure effects are certainly major determinants of the price level for the Paris Housing Market.     

Simulating archaeologists? Using agent-based modelling to improve battlefield excavations

The study of material culture generated by military engagements has created an emergent sub-discipline of archaeological studies centred on battlefields. This approach has developed a particular and sophisticated methodology that is able to deal with the fact that archaeologists will often not find either structures or a useful stratigraphical record on the site, as the material remains of the battle will basically be metallic objects carried by combatants. It is therefore rather complicated not only to test hypotheses about battle events based on archaeological data, but also to validate the methodology used. Here we propose the use of agent-based models to explore these issues in the case of eighteenth-century battlefield archaeology. The simulation is divided into four different steps. Firstly, a battle is simulated in order to generate realistic virtual archaeological remains left by an engagement between two armies of this era. We then simulate the loss of information that the passing of time produces in the battlefield. The third step involves simulating the archaeological survey, enabling us to explore different survey strategies and the impact on the interpretation of the event itself. Finally, we design a confidence index in order to compare the results of the different virtual excavations using spatial analysis and statistics. The results show that the methodology is fully functional in terms of understanding a battle, and it allows us to suggest new strategies to improve fieldwork and to develop new ways of exploring these particular archaeological sites. It is concluded that the described approach illustrates how simulation can be used to explore methodological issues of archaeological science.     

Geographically Weighted Discriminant Analysis

In this article, we propose a novel analysis technique for geographical data, Geographically Weighted Discriminant Analysis. This approach adapts the method of Geographically Weighted Regression (GWR), allowing the modeling and prediction of categorical response variables. As with GWR, the relationship between predictor and response variables may alter over space, and calibration is achieved using a moving kernel window approach. The methodology is outlined and is illustrated with an example analysis of voting patterns in the 2005 UK general election. The example shows that similar social conditions can lead to different voting outcomes in different parts of England and Wales. Also discussed are techniques for visualizing the results of the analysis and methods for choosing the extent of the moving kernel window.     

Direct detection of Southeast Asian smelting sites by ASTER remote sensing imagery: technical issues and future perspectives

Satellite-based multi-spectral remote sensing data were used in an attempt to identify control signatures for known prehistoric copper smelting sites in Thailand. It had been hoped that these characteristic signals could then be used as a reference for the detection of unknown Southeast Asian metal production sites, with the overall intention of strengthening the evidence base for early technological interactions with China and India. Regrettably, control signatures were not identified from the ASTER data due to issues of scale, chemistry, and vegetation, but we are able to offer reasons for this setback that might lead other scholars to develop successful applications of this methodology in more amenable (non-tropical) environments. Combined with ground truthing, intensive survey, excavation, and the technological analysis of metallurgical assemblages, this potentially useful and cost effective approach could lead to improved data density for the metal technology transmission discussions currently spanning Eurasia.     

Data scopes for digital history research

The term Macroscope has recently been introduced as an instrument to study historical big data using digital tools. In this paper we argue the need for a more elaborate set of concepts to describe and reason about the interactions to select, enrich, connect, analyse and evaluate historical data using digital tools. Interactions change the data and are essential in understanding any subsequent analysis. It makes them part of historical research methodology, but there is little consensus on how these steps can or should be performed. Moreover, they are rarely reported and discussed. We introduce the term data scope as an instrument encompassing these choices and interactions. Elaborating on these processes encourages deeper reflection on and discussion of the interactions and their consequences for research outcomes.     

上海旅游客流的B-J方法预测研究

本文在系统分析上海市2000年1月至2004年9月旅游市场动态变化时序数据的基础上,采用博克斯一詹全斯（B—J）方法预测了2004年4月至2004年9月间上海市旅游客流的发展变化趋势。通过预测结果与现实统计数据的对比表明,采用B—J方法预测旅游客流的短期趋势是可行的,因此,可运用该方法对上海市客源市场进行科学规划,但在具体运用过程中需考虑对旅游市场的突发性冲击将可能对预测精度造成的影响。     

Does Econometric Methodology Matter? An Analysis of Public Policy Using Spatial Econometric Techniques

A popular approach to examining the effects of public policy has been to rely on a spatial data sample of border counties as in Holmes (1998)—border counties from a sample of states that are used in conjunction with least‐squares estimation techniques in an attempt to isolate the policy impact while controlling for spatial dependence that often arises from latent or unobserved variables. This technique is in the spirit of control‐group methodologies from the laboratory sciences. This paper contrasts border‐county estimation results from Holmes' (1998) approach and those from a related methodology set forth in Holcombe and Lacombe (2003), with estimates from a spatial autoregressive model explicitly accounting for within‐state and between‐state public policy effects. As an illustration, the paper examines the effects of Aid to Families with Dependent Children (AFDC) and Food Stamp payments on female‐headed households and female labor force participation using the three different methods.     

From Alloy Composition to Alloying Practice: Chinese Bronzes

We propose a new methodology based on standard statistical processes for displaying and rigorously comparing the alloy composition of archaeological bronze alloys. Although traditional approaches using visual comparisons of histograms of alloying elements in an assemblage of archaeological objects are adequate for observing differences between these distributions, we argue that differences in sample size cannot be adequately accounted for without using a statistical approach. We demonstrate this methodology by comparing the alloy composition of bronzes from the sequence of Bronze Age cultures in Central China—Erlitou, Erligang (Zhengzhou, or early Shang), Anyang (late Shang) and Western Zhou. We suggest that this approach allows the identification and rigorous comparison of ‘regional alloying practices’, which in turn enables us to link the alloy composition of the objects with the intentions and skills of foundry workers.     

Statistical Network Analysis for Analyzing Policy Networks

To analyze social network data using standard statistical approaches is to risk incorrect inference. The dependencies among observations implied in a network conceptualization undermine standard assumptions of the usual general linear models. One of the most quickly expanding areas of social and policy network methodology is the development of statistical modeling approaches that can accommodate such dependent data. In this article, we review three network statistical methods commonly used in the current literature: quadratic assignment procedures, exponential random graph models (ERGMs), and stochastic actor‐oriented models. We focus most attention on ERGMs by providing an illustrative example of a model for a strategic information network within a local government. We draw inferences about the structural role played by individuals recognized as key innovators and conclude that such an approach has much to offer in analyzing the policy process.     

Painting as Agency,Style as Structure: Innovations in Mimbres Pottery Designs From Southwest New Mexico

The act of painting a design is a form of agency, and the overall style of that design in part can be conceptualized as a kind of structure. This perspective is used as a basis for analyzing chronological changes in designs on Mimbres Black-on-white pottery (ca. AD 750–1150) from Southwest New Mexico. Specific focus is on a methodology that can be used to detect innovations, that is, the introduction of novel designs that are incorporated into the design corpus and thus transform the structure. The conceptualization of a particular tradition (in this instance, pottery painting) as a form of structure analogous to general structure in Giddens' sense thus provides important insights into the recursive relationship between agency and structure.     

Urban Textural Analysis from Remote Sensor Data: Lacunarity Measurements Based on the Differential Box Counting Method

Lacunarity is related to the spatial distribution of gap or hole sizes. For low lacunarity, all gap sizes are the same and geometric objects are deemed homogeneous; conversely, for high lacunarity, gap sizes are variable and objects are therefore heterogeneous. Textures that are homogeneous at small scales can be quite heterogeneous at large scales and vice versa, and hence, lacunarity can be considered a scale-dependent measure of heterogeneity or texture. In this article, we use a lacunarity method based on a differential box counting approach to identify urban land-use and land-cover classes from satellite sensor data. Our methodology focuses on two different gliding box methods to compute lacunarity values and demonstrate a mirror extension approach for a local moving window. The extension approach overcomes, or at least minimizes, the boundary problem. The results from our study suggest that the overlapping box approach is more effective than the skipping box approach, but that there is no significant difference between window sizes. Our work represents a contribution to not only advances in textural and spatial metrics as used in remote-sensing pattern interpretation but also for broadening understanding of the computational geometry of nonlinear shape models of which lacunarity is the reciprocal of fractal theory.     

THOUGHTS ON THE UTILITY OF A BIVARIATE‐SPLITTING APPROACH TO OLMEC CERAMIC DATA INTERPRETATION*

A recently resolved debate centred on the interpretation of a major set of INAA data that was based on Olmec ceramics from Mexico. In an attempt to answer questions arising from the debate, this paper discusses the effect of numbers of samples chosen for data interpretation. It also presents interpretations of the ceramic data set based on a bivariate data‐splitting approach and compares the results of this with the multivariate analysis approaches employed by the initial publishers of the data.     

Flirting in the field: shifting positionalities and power relations in innocuous sexualisations of research encounters

In the last few decades, an engaged and sophisticated discussion about the production of data and power relations has developed within feminist methodology. Positionality, i.e. the set of relations constituting informants' and researchers' subject positions, has been widely used as an analytical tool to account for the complicated ways in which data are co-constructed in fieldwork. Based on our own experience of fieldwork conducted in the city of Zurich, however, we argue that sexuality is underrepresented in this debate. First, reflexive writing on fieldwork has been reluctant to consider sexuality as a category in the same way, for instance, as gender or race. Second, even apparently innocuous sexualisations have a considerable effect on the constitution of data and are therefore worth including in the analysis. In this article, we examine how flirtation as a part of the participant–researcher relation has re-shaped the research encounters in our respective research projects. We discuss the complex navigations between conflicting rationales that it entailed for us as researchers, depict the minor and major shifts in positionalities that emerge from the flirtation and examine the reasons why we sometimes embraced flirtation and sometimes rejected it. The objective of the article is to further enrich feminist methodological writing, and to suggest to the reader the potential for including various shades of sexual performances, such as apparently harmless flirtation, into our reflections on data collection.     

Adaptive Cell Tower Location Using Geostatistics. 基于地统计学的适应性基站发射塔选址研究

In this article, we address the problem of allocating an additional cell tower (or a set of towers) to an existing cellular network, maximizing the call completion probability. Our approach is derived from the adaptive spatial sampling problem using kriging, capitalizing on spatial correlation between cell phone signal strength data points and accounting for terrain morphology. Cell phone demand is reflected by population counts in the form of weights. The objective function, which is the weighted call completion probability, is highly nonlinear and complex (nondifferentiable and discontinuous). Sequential and simultaneous discrete optimization techniques are presented, and heuristics such as simulated annealing and Nelder–Mead are suggested to solve our problem. The adaptive spatial sampling problem is defined and related to the additional facility location problem. The approach is illustrated using data on cell phone call completion probability in a rural region of Erie County in western New York, and accounts for terrain variation using a line‐of‐sight approach. Finally, the computational results of sequential and simultaneous approaches are compared. Our model is also applicable to other facility location problems that aim to minimize the uncertainty associated with a customer visiting a new facility that has been added to an existing set of facilities.