Detection of Communities within the Multibody System Dynamics Network and Analysis of Their Relations

Multibody system dynamics is already a well developed branch of theoretical, computational and applied mechanics. Thousands of documents can be found in any of the well-known scientific databases. In this work it is demonstrated that multibody system dynamics is built of many thematic communities. Using the Elsevier’s abstract and citation database SCOPUS, a massive amount of data is collected and analyzed with the use of the open source visualization tool Gephi. The information is represented as a large set of nodes with connections to study their graphical distribution and explore geometry and symmetries. A randomized radial symmetry is found in the graphical representation of the collected information. Furthermore, the concept of modularity is used to demonstrate that community structures are present in the field of multibody system dynamics. In particular, twenty-four different thematic communities have been identified. The scientific production of each community is analyzed, which allows to predict its growing rate in the next years. The journals and conference proceedings mainly used by the authors belonging to the community as well as the cooperation between them by country are also analyzed

Resilient Densification: Four Studies from Johannesburg

Unlike most cities in the world, over the last 20 years Johannesburg has become more dense and more compact. This reflects the increased rates of rural-urban migration from the late 1980s as urbanisation controls collapsed, but also the relative success of Johannesburg’s economy and democratic-era policies to contain urban sprawl (such as the urban development boundary). The ending of apartheid regulations allowed a release in a pent-up demand for access to large cities with much of the movement directed to the three large metropolitan cities in Gauteng. Densification in the city has occurred in both planned and unplanned ways. In line with directions in planning internationally, post-apartheid planning has placed strong emphasis on urban densification and compaction. At the same time, however, market forces (both formal and informal) have driven densification in the city, in ways that are often unforeseen and sometimes contrary to city policies. In order to plan for further development and to respond effectively to the densification that has happened, and is occurring, research into the processes and effects of densification is clearly needed. In this work we use an “urban resilience lens” to investigate four forms of residential densification in Johannesburg, using four illustrative case-studies. We explore the effects that densification is having in the city, showing how diverse, complex and contingent it often is.The research was funded by the Department of Science and Technology and the National Research Foundation. The work does not necessarily represent their views

Analysis of the communities of an urban mobile phone network

This is the final version. Available from Public Library of Science via the DOI in this record. Data Availability: Data available at: Telecom Italia Big Data Challenge 2014, https://dandelion.eu/datamine/open-big-data/.Being able to characterise the patterns of communications between individuals across different time scales is of great importance in understanding people's social interactions. Here, we present a detailed analysis of the community structure of the network of mobile phone calls in the metropolitan area of Milan revealing temporal patterns of communications between people. We show that circadian and weekly patterns can be found in the evolution of communities, presenting evidence that these cycles arise not only at the individual level but also at that of social groups. Our findings suggest that these trends are present across a range of time scales, from hours to days and weeks, and can be used to detect socially relevant events.EPSRCEuropean Commissio

Improving Scalability of Evolutionary Robotics with Reformulation

Creating systems that can operate autonomously in complex environments is a challenge for contemporary engineering techniques. Automatic design methods offer a promising alternative, but so far they have not been able to produce agents that outperform manual designs. One such method is evolutionary robotics. It has been shown to be a robust and versatile tool for designing robots to perform simple tasks, but more challenging tasks at present remain out of reach of the method. In this thesis I discuss and attack some problems underlying the scalability issues associated with the method. I present a new technique for evolving modular networks. I show that the performance of modularity-biased evolution depends heavily on the morphology of the robot’s body and present a new method for co-evolving morphology and modular control. To be able to reason about the new technique I develop reformulation framework: a general way to describe and reason about metaoptimization approaches. Within this framework I describe a new heuristic for developing metaoptimization approaches that is based on the technique for co-evolving morphology and modularity. I validate the framework by applying it to a practical task of zero-g autonomous assembly of structures with a fleet of small robots. Although this work focuses on the evolutionary robotics, methods and approaches developed within it can be applied to optimization problems in any domain

The Essence of Software Engineering

Software Engineering; Software Development; Software Processes; Software Architectures; Software Managemen

Gender-sensitive Risks and Options Assessment for Decision making (ROAD) to support WiF2

The Gender-Sensitive Risks and Options Assessment for Decision Making (ROAD) to Support WiF-2 (ROAD migration project), a partnership coordinated by the International Food Policy Research Institute (IFPRI), Australian National University, American University Beirut, Lincoln University, and University of Dhaka, evaluated the ILO-DFID Partnership Programme on Fair Recruitment and Decent Work for Women Migrant Workers in South Asia and the Middle East (Work in Freedom, Phase 2 project [WiF-2]), which operated from 2018 to 2023. The WiF-2 project specifically aimed “to reduce vulnerability to trafficking and forced labour of women and girls across migration pathways leading to the care sector and textiles, clothing, leather and footwear industries (TCLFI) of South Asia and Arab States” (ToC WiF-2)

Language, Mind, and Cognitive Science: Remarks on Theories of the Language-Cognition Relationships in Human Minds

My dissertation establishes the basis for a systematic outlook on the role language plays in human cognition. It is an investigation based on a cognitive conception of language, as opposed to communicative conceptions, viz. those that suppose that language plays no role in cognition (its only role being to externalize thought). I focus, in Chapter 2, on three paradigmatic theories adopting this perspective, each offering different views on how language contributes to or changes cognition. In Chapter 3, I criticize current views held by dual-process theorists, and I develop a picture of the complex interaction between language and cognition that I deem more plausible by using resources from the literature on the evolution of the faculty of language. Rather than trying to find one general explanation for all cognitive processes, I take seriously the idea that our mind is composed of many subsystems, and that language can interact and modify each in different ways. There is no reason offered in the empirical literature—besides maybe parsimony—that suggest that language has to interact in the same ways with all cognitive processes. Yet, this is seemingly taken for granted, especially within dual-process approaches. On my view, it is a central requirement for a theory of the role of language in cognition to explain how language might have effects, at once, on and within various parts of cognition. In Chapter 4, I explore how this framework can modify how we think about some experiments in psychology, specifically in research on categorization. My idea is that language, once it (or any possible primitive forms) evolved, changed how some cognitive capacities worked and interacted with each other, but did so in more than one or two ways. Cognitive systems are changed in very different ways—sometimes the transformation is very subtle, such as our way of forming categories by using how similar objects are, while other times it is deep and changes the very way the system works

Computational Labeling, Partitioning, and Balancing of Molecular Networks

Recent advances in high throughput techniques enable large-scale molecular quantification with high accuracy, including mRNAs, proteins and metabolites. Differential expression of these molecules in case and control samples provides a way to select phenotype-associated molecules with statistically significant changes. However, given the significance ranking list of molecular changes, how those molecules work together to drive phenotype formation is still unclear. In particular, the changes in molecular quantities are insufficient to interpret the changes in their functional behavior. My study is aimed at answering this question by integrating molecular network data to systematically model and estimate the changes of molecular functional behaviors. We build three computational models to label, partition, and balance molecular networks using modern machine learning techniques. (1) Due to the incompleteness of protein functional annotation, we develop AptRank, an adaptive PageRank model for protein function prediction on bilayer networks. By integrating Gene Ontology (GO) hierarchy with protein-protein interaction network, our AptRank outperforms four state-of-the-art methods in a comprehensive evaluation using benchmark datasets. (2) We next extend our AptRank into a network partitioning method, BioSweeper, to identify functional network modules in which molecules share similar functions and also densely connect to each other. Compared to traditional network partitioning methods using only network connections, BioSweeper, which integrates the GO hierarchy, can automatically identify functionally enriched network modules. (3) Finally, we conduct a differential interaction analysis, namely difFBA, on protein-protein interaction networks by simulating protein fluxes using flux balance analysis (FBA). We test difFBA using quantitative proteomic data from colon cancer, and demonstrate that difFBA offers more insights into functional changes in molecular behavior than does protein quantity changes alone. We conclude that our integrative network model increases the observational dimensions of complex biological systems, and enables us to more deeply understand the causal relationships between genotypes and phenotypes