Recent Advances in Social Data and Artificial Intelligence 2019

The importance and usefulness of subjects and topics involving social data and artificial intelligence are becoming widely recognized. This book contains invited review, expository, and original research articles dealing with, and presenting state-of-the-art accounts pf, the recent advances in the subjects of social data and artificial intelligence, and potentially their links to Cyberspace

Emerging Trends in Mechatronics

Mechatronics is a multidisciplinary branch of engineering combining mechanical, electrical and electronics, control and automation, and computer engineering fields. The main research task of mechatronics is design, control, and optimization of advanced devices, products, and hybrid systems utilizing the concepts found in all these fields. The purpose of this special issue is to help better understand how mechatronics will impact on the practice and research of developing advanced techniques to model, control, and optimize complex systems. The special issue presents recent advances in mechatronics and related technologies. The selected topics give an overview of the state of the art and present new research results and prospects for the future development of the interdisciplinary field of mechatronic systems

Fuzzy adaptive emperor penguin optimizer for global optimization problems

The Emperor Penguin Optimizer (EPO) is a recently developed population-based metaheuristic algorithm that simulates the huddling behaviour of emperor penguins. Mixed results have been observed in the performance of EPO in solving general optimization problems. Within the EPO, two parameters need to be tuned (namely f and l) to ensure a good balance between exploration (i.e., roaming unknown locations) and exploitation (i.e., manipulating the current known best). Since the search contour varies depending on the optimization problem, the tuning of parameters f and l is problem-dependent, and there is no one-size-fits-all approach. To alleviate this parameter tuning problem, an adaptive mechanism can be introduced in EPO. This research work proposes a fuzzy adaptive variant of EPO, namely FAEPO, to solve this problem. As the name suggests, FAEPO can adaptively tune the parameters f and l throughout the search based on three measures (i.e., quality, success rate, and diversity of the current search) via fuzzy decisions. A test suite of twelve benchmark test functions and three global optimization problems: Team Formation Optimization (TFO), Low Autocorrelation Binary Sequence (LABS), and Modified Condition/ Decision coverage (MC/DC) test case generation problem were solved using the proposed algorithm. The respective solution results of the competing metaheuristic algorithms were compared. The experimental results demonstrate that FAEPO significantly improved the performance especially of its predecessor (EPO), an improved variant of EPO (i.e., IEPO), and a fuzzy-based variant of ChOA (i.e., FChOA) and gives superior performance against the competing metaheuristic algorithms. Moreover, the proposed FAEPO requires 50% less fitness function evaluation in each iteration than the ancestor EPO and exhibits competitive performance in terms of convergence and computational time against its predecessor (EPO) and other competing meta-heuristic algorithms with a 90% confidence level

Bio-inspired computation: where we stand and what's next

In recent years, the research community has witnessed an explosion of literature dealing with the adaptation of behavioral patterns and social phenomena observed in nature towards efficiently solving complex computational tasks. This trend has been especially dramatic in what relates to optimization problems, mainly due to the unprecedented complexity of problem instances, arising from a diverse spectrum of domains such as transportation, logistics, energy, climate, social networks, health and industry 4.0, among many others. Notwithstanding this upsurge of activity, research in this vibrant topic should be steered towards certain areas that, despite their eventual value and impact on the field of bio-inspired computation, still remain insufficiently explored to date. The main purpose of this paper is to outline the state of the art and to identify open challenges concerning the most relevant areas within bio-inspired optimization. An analysis and discussion are also carried out over the general trajectory followed in recent years by the community working in this field, thereby highlighting the need for reaching a consensus and joining forces towards achieving valuable insights into the understanding of this family of optimization techniques

Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration versus Algorithmic Behavior, Critical Analysis and Recommendations

In recent years, a great variety of nature- and bio-inspired algorithms has been reported in the literature. This algorithmic family simulates different biological processes observed in Nature in order to efficiently address complex optimization problems. In the last years the number of bio-inspired optimization approaches in literature has grown considerably, reaching unprecedented levels that dark the future prospects of this field of research. This paper addresses this problem by proposing two comprehensive, principle-based taxonomies that allow researchers to organize existing and future algorithmic developments into well-defined categories, considering two different criteria: the source of inspiration and the behavior of each algorithm. Using these taxonomies we review more than three hundred publications dealing with nature-inspired and bio-inspired algorithms, and proposals falling within each of these categories are examined, leading to a critical summary of design trends and similarities between them, and the identification of the most similar classical algorithm for each reviewed paper. From our analysis we conclude that a poor relationship is often found between the natural inspiration of an algorithm and its behavior. Furthermore, similarities in terms of behavior between different algorithms are greater than what is claimed in their public disclosure: specifically, we show that more than one-third of the reviewed bio-inspired solvers are versions of classical algorithms. Grounded on the conclusions of our critical analysis, we give several recommendations and points of improvement for better methodological practices in this active and growing research field.Comment: 76 pages, 6 figure

“just hanging out with you in my back yard”: Mark Zuckerberg and Mediated Paternalism

In a video that showcases a new Facebook feature, Mark Zuckerberg chats to his users, telling them that he’s “just hanging out with you in my backyard.” In this video-which is on his Facebook page-Zuckerberg discloses the domestic space of his backyard, revealing his interaction with family and friends. Depicted hosting a barbeque while watching the electoral debate, Zuckerberg performs an affective white postfeminist paternity (Hamad, 2014) by talking about hunting, eating meat, and being a father. This video is key in explaining how Zuckerberg affectively models patriarchal power. We argue that this PR exercise (for both him and Facebook which are portrayed as inextricably linked) functions to represent Facebook as enabling an empowered “community,” rather than being just an instrument of data accumulation. In particular, Zuckerberg’s affective paternalism is also a means to recoup and obfuscate patriarchal power structures. Zuckerberg’s Facebook page constructs an intimate paternalism in relation to his domestic sphere, but also to his followers, and this works to legitimate his corporate and global paternalism. The ways in which he is portrayed through signifiers of an emotional fatherhood work to gloss his power as the third richest man in the world

BRICS and the New American Imperialism

"BRICS is a grouping of the five major emerging economies of Brazil, Russia, India, China and South Africa. Volume five in the Democratic Marxism series, BRICS and the New American Imperialism challenges the mainstream understanding of BRICS and US dominance to situate the new global rivalries engulfing capitalism. It offers novel analyses of BRICS in the context of increasing US induced imperial chaos, deepening environmental crisis tendencies (such as climate change and water scarcity), contradictory dynamics inside BRICS countries and growing subaltern resistance. The authors revisit contemporary thinking on imperialism and anti-imperialism, drawing on the work of Rosa Luxemburg, one of the leading theorists after Marx, who attempted to understand the expansionary nature of capitalism from the heartlands to the peripheries. The richness of Luxemburg’s pioneering work inspires most of the volume’s contributors in their analyses of the dangerous contradictions of the contemporary world as well as forms of democratic agency advancing resistance. While various forms of resistance are highlighted, among them water protests, mass worker strikes, anti-corporate campaigning and forms of cultural critique, this volume grapples with the challenge of renewing anti-imperialism beyond the NGO-driven World Social Forum and considers the prospects of a new horizontal political vessel to build global convergence. It also explores the prospects of a Fifth International of Peoples and Workers.

OptPlatform: metaheuristic optimisation framework for solving complex real-world problems

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonWe optimise daily, whether that is planning a round trip that visits the most attractions within a given holiday budget or just taking a train instead of driving a car in a rush hour. Many problems, just like these, are solved by individuals as part of our daily schedule, and they are effortless and straightforward. If we now scale that to many individuals with many different schedules, like a school timetable, we get to a point where it is just not feasible or practical to solve by hand. In such instances, optimisation methods are used to obtain an optimal solution. In this thesis, a practical approach to optimisation has been taken by developing an optimisation platform with all the necessary tools to be used by practitioners who are not necessarily familiar with the subject of optimisation. First, a high-performance metaheuristic optimisation framework (MOF) called OptPlatform is implemented, and the versatility and performance are evaluated across multiple benchmarks and real-world optimisation problems. Results show that, compared to competing MOFs, the OptPlatform outperforms in both the solution quality and computation time. Second, the most suitable hardware platform for OptPlatform is determined by an in-depth analysis of Ant Colony Optimisation scaling across CPU, GPU and enterprise Xeon Phi. Contrary to the common benchmark problems used in the literature, the supply chain problem solved could not scale on GPUs. Third, a variety of metaheuristics are implemented into OptPlatform. Including, a new metaheuristic based on Imperialist Competitive Algorithm (ICA), called ICA with Independence and Constrained Assimilation (ICAwICA) is proposed. The ICAwICA was compared against two different types of benchmark problems, and results show the versatile application of the algorithm, matching and in some cases outperforming the custom-tuned approaches. Finally, essential MOF features like automatic algorithm selection and tuning, lacking on existing frameworks, are implemented in OptPlatform. Two novel approaches are proposed and compared to existing methods. Results indicate the superiority of the implemented tuning algorithms within constrained tuning budget environment

The Digital Spatial Fix

This article brings distinct strands of the political economy of communication and economic geography together in order to theorise the role digital technologies play in Marxian crisis theory. Capitalist advances into digital spaces do not make the law of value obsolete, but these spaces do offer new methods for displacing overaccumulated capital, increasing consumption, or accumulating new, cheaper labour. We build on David Harvey’s theory of the spatial fix to describe three digital spatial fixes, fixed capital projects that use the specific properties of digital spaces to increase the rate of profit, before themselves becoming obstacles to the addictive cycle of accumulation: the primitive accumulation of time in the social Web, the annihilation of time by space in high-frequency trading, and affect rent in virtual worlds. We conclude by reflecting on how these digital spatial fixes also fix the tempo of accumulation and adjust the time-scale of Marxian crisis theory