Iron City Blues

S. N. Eisenstadt, Fundamentalism, Ectarianism, and Revolution: The Jacobin Dimension of Modernity     

Ramadan Blues: Debates in Popular Islam during Ramadan in Amman,Jordan

Within the context of the contemporary Middle East and the post‐Islamic Resurgence, avoiding music has become associated with a rise in religiosity and normative Islam. As a result, residents of Amman, Jordan actively avoid consuming music during Ramadan. A large‐scale survey and ethnographic data, including participant observation with employees in an Islamic bank, confirm that avoiding music is a public ethic of Ramadan that is temporally specific and in wide use during the month. In this article, I argue that the tensions surrounding the debates of music's compatibility with normative Islam are enacted in terms of a conflict between cultural and Islamic authenticities. These tensions are resolved temporarily during Ramadan through altered consumption in which one ethical, “Islamic” framework that regards music as haram, or “forbidden,” eclipses another, more diverse “cultural” framework, and does so largely without inducing crisis or controversy. This is because the two realms are not articulating with each other; rather, claims of a normative Islamic authenticity overwhelm the possibilities for a more diverse cultural authenticity. Outside of Ramadan, however, these two competing authenticities often spark tensions and conflicts between family members, neighbors, and coworkers. This article concludes by exploring the implications of ordering morality for religious life in this assertive, even illiberal fashion for diversity in belief and practice.     

An Evolutionary Algorithm for Site Search Problems

The goal of solving a site search problem is to allocate a contiguous set of land parcels such that the total land acquisition cost, or other objectives, are optimized. This article describes the design and implementation of an evolutionary algorithm (EA) that can be used to solve site search problems. In this article, a graph representation is used to define the spatial structure of solutions to the problem. By using this representation, the contiguity of a site is maintained during the initialization, mutation, and local search operations of the EA. The effectiveness of the EA in finding optimal or near-optimal solutions is demonstrated by testing it on a series of problems whose optimal solutions are known.     

Microartefacts' weight estimation by Genetic Algorithm minimization

The information potential of microartefacts can assist in archaeological interpretation. In this paper, a method for estimating the weight of microartefacts is presented. This method is based on Genetic Algorithms, a stochastic minimisation method that comes from Computational Intelligence techniques. It was observed that Genetic Algorithms offer a reliable estimation of microartefact weights. Experimental results are presented on archaeological data from the Neolithic site of Paliambela, in Northern Greece.     

A New Algorithm for Graph-theoretic Nodal Accessibility Measurement

Accessibility is a useful concept in the study of the spatial structure of a region, if it can be calibrated appropriately. While graph-theoretic analysis has been used widely as a measurement scheme for the nodal accessibility in various transport networks, several limitations have been pointed out in the existing graph-theoretic accessibility measurements. This study proposes a new algorithm for deriving the nodal accessibility measure, as an attempt to improve the conventional graph-theoretic accessibility measurements. Corrections are made in such a way that irrelevant loops are excluded and relevant indirect connection paths are included selectively. In particular, the new algorithm is developed for intraurban subway networks, and includes the characteristics of intraurban subway traffic behavior. The concept of inconvenience of transfer is introduced, which is one of the most influential factors in the intraurban subway traffic. Nodal differentiation is allowed, if the nodes play different roles in the travel behavior and eventually in the accessibility. For this purpose, we employ a weighting procedure, according to which the influence of transfer on a sequence of linkages is taken into account. The new accessibility measurement scheme is then applied to the Seoul subway network. Here GIS techniques are utilized to generate accessibility surfaces from the discrete nodal accessibility values, and the changes in the spatial structure of the nodal accessibility are analyzed. Finally, based on the resulting changes in the spatial structure of accessibility in the subway network, the direction of changes in the land value and the land use pattern in Seoul is discussed.     

Noninferior Bandwidth Line Simplification: Algorithm and Structural Analysis

Digital line simplification operators are an important preprocessing component of a spatial data handling system. Simplification operators are used to generalize digital line files because these files are encoded at one scale but the objects they represent can be displayed at many other scales. Most line simplification algorithms are heuristics that caricaturize lines by eliminating points representing redundant data or conversely retaining the characteristic points of a line that have a high informational content. This paper presents a noninferior simplification algorithm that produces an optimal caricature of an encoded line with respect to the bandwidth criterion that all deleted points must be within a prespecified distance of the simplified line. Results show that it is a practical alternative to existing bandwidth heuristics.     

An Improved Algorithm for Selecting Ground Motions to Match a Conditional Spectrum

This paper describes an algorithm to efficiently select ground motions from a database while matching a target mean, variance, and correlations of response spectral values at a range of periods. The approach improves an earlier algorithm by Jayaram et al. [2011]. Key steps in the process are to screen a ground motion database for suitable motions, statistically simulate response spectra from a target distribution, find motions whose spectra match each statistically simulated response spectrum, and then perform an optimization to further improve the consistency of the selected motions with the target distribution. These steps are discussed in detail, and the computational expense of the algorithm is evaluated. A brief example selection exercise is performed, to illustrate the type of results that can be obtained. Source code for the algorithm has been provided, along with metadata for several popular databases of recorded and simulated ground motions, which should facilitate a variety of exploratory and research studies.     

DEM Algorithm for Progressive Collapse Simulation of Single-Layer Reticulated Domes under Multi-Support Excitation

In this paper, the Member Discrete Element Method (MDEM) is modified and perfected for three aspects: the algorithm itself, loading and computational efficiency, and to accurately and quantitatively simulate the progressive collapse for large-span spatial steel structures. In addition, the corresponding computational programs are compiled. First, from the perspective of the method, a meshing principle for discrete element models is determined, a treatment for material nonlinearity and strain rate effect is proposed, and a damping model is established. Next, the Displacement Method is introduced to determine the multi-support excitation for the MDEM, and then motion equations of particles under multi-support excitation are derived. On this basis, the specific process of gravitational field loading is presented. Furthermore, parallel implementation strategies for the MDEM based on OpenMP are constructed. Finally, the collapse simulation of a 1/3.5-scaled single-layer reticulated dome shaking table test model under multi-support excitation is carried out. The comparison demonstrates that the ultimate load and failure mode as well as the complete collapse time of the numerical results are consistent with the experimentally measured responses, and the configuration variations from member buckling and local depression until collapse failure are fully captured. Moreover, the displacement time-history curves obtained using MDEM are almost identical to the experimental measurements, and there is a nuance only in the amplitude. It is verified that MDEM is capable of precisely addressing the collapse failure for large-span spatial steel structures. Additionally, the failure mechanism for structures of this type is naturally revealed.     

A Constructive Genetic Algorithm for Discrete Dispersion on Point Feature Cartographic Label Placement Problems

This article concerns the point feature cartographic label placement (PFCLP) problem, which is a NP‐hard (Non‐deterministic Polynomial‐time hard) combinatorial problem. It is considered that when all points must be labeled and overlaps are inevitable, the map can be more readable if overlapping labels are placed in a dispersive way, that is, overlapping labels are distant from each other. This work presents a constructive genetic algorithm (CGA) for the discrete dispersion PFCLP that utilizes the notion of masking to preserve optimal subsequences in chromosomes. We also define the discrete dispersion PFCLP as a mixed integer linear programming model, considering the problem of the minimum number of labels in conflict as well. The computational results validate our CGA approach using instances up to 5,046 points.     

Implementing Artificial Intelligence in H-BIM Using the J48 Algorithm to Manage Historic Buildings

ABSTRACT

The preservation of the architectural heritage is characterized by the intervention of different technicians, who may disagree on decision-making criteria. In recent years, the H-BIM methodology has emerged to manage these buildings, although the multidisciplinary technical personnel make the decision-taking something of a challenge. In this regard, artificial intelligence may be an opportunity to establish automatic responses, thus optimizing the process. This article proposes a methodology to implement models of classification using the J48 algorithm in a H-BIM model. The case study was focused on a tiles panel from a building which belongs to the Real Alcazar of Seville. First, a model of classification was developed to estimate the degree of intervention with an adequate degree of adjustment. Then, the model was implemented in the H-BIM software by programming using GDL. This methodology automates the decision-making and reduces times of assessments, visualizing and managing the information in the H-BIM model.     

Recursive Algorithm for Determination of Proximal (Thiessen) Polygons in Any Metric Space

A new and recursive algorithm for determining proximal polygons is based on quadtree concepts. The algorithm can use any distance metric, and produces a quadtree of the image of the proximal polygons. This can be converted to vector form, or be incorporated directly into a quadtree-based geographic information system, in order to solve a number of closest-point problems. The algorithm can also produce the Delaunay triangulation, which is the dual of the proximal polygons. Empirically, the running time of the algorithm is proportional to the number of centers raised to the 1.6 power.     

Assessing Activity Pattern Similarity with Multidimensional Sequence Alignment Based on a Multiobjective Optimization Evolutionary Algorithm

Due to the complexity and multidimensional characteristics of human activities, assessing the similarity of human activity patterns and classifying individuals with similar patterns remains highly challenging. This article presents a new and unique methodology for evaluating the similarity among individual activity patterns. It conceptualizes multidimensional sequence alignment as a multiobjective optimization problem and solves this problem with an evolutionary algorithm (EA). The study utilizes sequence alignment to code multiple facets of human activities into multidimensional sequences and to treat similarity assessment as a multiobjective optimization problem that aims to minimize the alignment cost for all dimensions simultaneously. A multiobjective optimization evolutionary algorithm is used to generate a diverse set of optimal or near‐optimal alignment solutions. Evolutionary operators are specifically designed for this problem, and a local search method is also incorporated to improve the search ability of the algorithm. We demonstrate the effectiveness of our method by comparing it with a popular existing method called ClustalG using a set of 50 sequences. The results indicate that our method outperforms the existing method for most of our selected cases. The multiobjective EA presented in this article provides an effective approach for assessing activity pattern similarity and a foundation for identifying distinctive groups of individuals with similar activity patterns. Debido a la complejidad y el carácter multidimensional de las actividades humanas, la evaluación de la similitud de los patrones de la actividad humana y la clasificación de individuos con patrones similares sigue siendo una tarea muy difícil. Este artículo presenta una metodología novedosa y única para evaluar la similitud entre los patrones de actividad individual. Se conceptualiza el método de alineación de secuencias multidimensionales (Multidimensional Sequence Alignment‐MDSA) como un problema de optimización multiobjetivo y se resuelve mediante un algoritmo evolutivo (evolutionary algorithm‐EA). El estudio utiliza la alineación de secuencias para codificar múltiples facetas de las actividades humanas en secuencias multidimensionales y para tratar la evaluación de similitud como un problema de optimización multiobjetivo que tiene como objetivo reducir al mínimo el coste de alineación para todas las dimensiones simultáneamente . Los autores utilizan algoritmo evolutivo de optimización multiobjetivo (multiobjective optimization evolutionary algorithm‐MOEA) para generar un conjunto diverso de soluciones de alineación óptimas o casi óptimas. Los operadores evolutivos del algoritmo están diseñados específicamente para este problema, al cual se le incorpora un método de búsqueda local para mejorar su desempeño. Los autores demuestran la eficacia del método propuesto mediante su comparación al método existente ClustalG haciendo uso de un conjunto de 50 secuencias. Los resultados indican que el método propuesto supera a los métodos existentes para la mayoría de casos seleccionados. La EA multiobjetivo presentado en este artículo proporciona un método eficaz para evaluar similitudes del patrón de actividad y constituye un componente fundamental para la identificación de grupos distintivos de personas con patrones de actividad similares. 由于人类活动的复杂性和多维度特性,人类活动模式的相似性评估和基于相似模式的个体分类仍具有较高的挑战性。本文提出了一种新型的、独特的方法来评估个体活动模式的相似性。该研究利用序列比对将人类活动的多个方面编码成多维序列,并将活动模式相似性评估作为一个多目标优化问题,其目的是使所有维度的比对成本同时最低。多目标最优进化算法被用于生成一组不同的最优或接近最优的比对解决方案。为此特别设计了进化算子,并集成一种局部搜索方法提高了算法的整体搜索能力。为验证该方法的有效性,本文以50对序列作为实验,并与常用的ClustalG方法进行了对比。研究结果表明,该方法在多数选取案例中性能优于ClustalG方法。因此,本文提出的多目标进化（EA）算法为个体活动模式相似性评估提供了一种有效方法,也为具有相似活动模式个体中特定群体识别奠定了基础。