The electric city newspaper: urban age electric city conference (Shoreditch Electric Light Station, London 6-7 December 2012)

In 1879 Thomas Edison invented the light bulb and built the first power station in Pearl Street in Manhattan in 1882, while the German inventor Werner von Siemens installed the first electric elevator in Mannheim in 1880. Since then, electricity has powered – directly or indirectly – the shape and dynamics of urban life. In cities of the developed world, we take for granted that electricity feeds the complex systems which sustain and sometimes spectacularly fail us. In emerging cities of the developing world, a light bulb is still embraced as a symbol of civilisation by some, while others celebrate their urbanity in a visual cacophony of neon. The Electric City is, in many ways, the crucible of patterns of production, consumption and pollution of the 21st century ‘urban age’ as cities struggle with their impact on the social and environmental well-being of the planet. After having tackled the urban economy, health and well-being, violence, security, social inclusion and design at conferences held in – amongst others – Hong Kong, Chicago, New York, São Paulo and Johannesburg, the Urban Age returns to London for its eleventh conference since 2005. We turn our attention to the challenges and responsibilities faced by cities in the digital age as Climate Change and economic pressures continue to define our everyday urban realities. Since its inception, the Urban Age has studied the spatial and social dynamics of over 30 cities in the developed and developing world, collaborated with over 40 academic institutions and municipal authorities and been attended by over 5,000 speakers and participants from urban design, policymaking, research and practice. In London we welcome over 60 speakers from 30 cities in 15 countries across four continents who take part in the two-day Urban Age Electric City conference in the aptly named Shoreditch Electric Light Station in central London – a building that in its own history reflects the connections between power and the city. It opened as an electricity generating station in 1896 to burn rubbish, giving steam for generating electricity with the waste used to heat public baths next door. The motto above the door is ‘E Pulvere Lux Et Vis, or ‘Out Of The Dust, Light And Power’, reflecting a trajectory of sustainable resilience that parallels the themes and issues debated by the protagonists of the Urban Age

Multipartite Graph Algorithms for the Analysis of Heterogeneous Data

The explosive growth in the rate of data generation in recent years threatens to outpace the growth in computer power, motivating the need for new, scalable algorithms and big data analytic techniques. No field may be more emblematic of this data deluge than the life sciences, where technologies such as high-throughput mRNA arrays and next generation genome sequencing are routinely used to generate datasets of extreme scale. Data from experiments in genomics, transcriptomics, metabolomics and proteomics are continuously being added to existing repositories. A goal of exploratory analysis of such omics data is to illuminate the functions and relationships of biomolecules within an organism. This dissertation describes the design, implementation and application of graph algorithms, with the goal of seeking dense structure in data derived from omics experiments in order to detect latent associations between often heterogeneous entities, such as genes, diseases and phenotypes. Exact combinatorial solutions are developed and implemented, rather than relying on approximations or heuristics, even when problems are exceedingly large and/or difficult. Datasets on which the algorithms are applied include time series transcriptomic data from an experiment on the developing mouse cerebellum, gene expression data measuring acute ethanol response in the prefrontal cortex, and the analysis of a predicted protein-protein interaction network. A bipartite graph model is used to integrate heterogeneous data types, such as genes with phenotypes and microbes with mouse strains. The techniques are then extended to a multipartite algorithm to enumerate dense substructure in multipartite graphs, constructed using data from three or more heterogeneous sources, with applications to functional genomics. Several new theoretical results are given regarding multipartite graphs and the multipartite enumeration algorithm. In all cases, practical implementations are demonstrated to expand the frontier of computational feasibility

ICR ANNUAL REPORT 2022 (Volume 29)[All Pages]

This Annual Report covers from 1 January to 31 December 202

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

The Maximum Clique Problem: Algorithms, Applications, and Implementations

Computationally hard problems are routinely encountered during the course of solving practical problems. This is commonly dealt with by settling for less than optimal solutions, through the use of heuristics or approximation algorithms. This dissertation examines the alternate possibility of solving such problems exactly, through a detailed study of one particular problem, the maximum clique problem. It discusses algorithms, implementations, and the application of maximum clique results to real-world problems. First, the theoretical roots of the algorithmic method employed are discussed. Then a practical approach is described, which separates out important algorithmic decisions so that the algorithm can be easily tuned for different types of input data. This general and modifiable approach is also meant as a tool for research so that different strategies can easily be tried for different situations. Next, a specific implementation is described. The program is tuned, by use of experiments, to work best for two different graph types, real-world biological data and a suite of synthetic graphs. A parallel implementation is then briefly discussed and tested. After considering implementation, an example of applying these clique-finding tools to a specific case of real-world biological data is presented. Results are analyzed using both statistical and biological metrics. Then the development of practical algorithms based on clique-finding tools is explored in greater detail. New algorithms are introduced and preliminary experiments are performed. Next, some relaxations of clique are discussed along with the possibility of developing new practical algorithms from these variations. Finally, conclusions and future research directions are given

From Smart to Green Cities: a KPI-based model for the built environment regeneration. A study of application in Bologna

Smart City (SC) emerged during the end of last century as a reference concept for shaping the city of the future. The literature review shows how SC originates from a debate questioning about the future of cities in a world continuously object of pressures: resource scarcity, economic crisis, lack of social identity, besides continuous input from technologies. The progressive permeating of innovative devices, simplifying people life or enabling them in networking and knowledge, led to relevant modification of the built environment. The word “smart” refers therefore not only to the ICT component of city but it also refers to the need of facing an increasing complexity involving all sectors of cities. The extend of approaches, applications, testing and theories coming along with the SC topic oblige the research to critically and extensively study those elements, broadening the analysis to additional experiences, and going toward the definition of SC for coming to a wider definition of Green City as an integrated, sustainable, resilient and smart urban regeneration approach. The research studies these approaches deepening the relation between Architecture Technology and Urban Planning, with a specific insight into a step-by-step project approach and a KPIs performance assessment. The main original output of the research is the proposition of the Green City Circle: a model for addressing the regeneration of districts into existing urban contexts. The thesis is Climate KIC labelled (European Institute of Technology)