Aggregation of classifiers: a justifiable information granularity approach.

In this paper, we introduced a new approach of combining multiple classifiers in a heterogeneous ensemble system. Instead of using numerical membership values when combining, we constructed interval membership values for each class prediction from the meta-data of observation by using the concept of information granule. In the proposed method, the uncertainty (diversity) of the predictions produced by the base classifiers is quantified by the interval-based information granules. The decision model is then generated by considering both bound and length of the intervals. Extensive experimentation using the UCI datasets has demonstrated the superior performance of our algorithm over other algorithms including six fixed combining methods, one trainable combining method, AdaBoost, bagging, and random subspace

Combining heterogeneous classifiers via granular prototypes.

In this study, a novel framework to combine multiple classifiers in an ensemble system is introduced. Here we exploit the concept of information granule to construct granular prototypes for each class on the outputs of an ensemble of base classifiers. In the proposed method, uncertainty in the outputs of the base classifiers on training observations is captured by an interval-based representation. To predict the class label for a new observation, we first determine the distances between the output of the base classifiers for this observation and the class prototypes, then the predicted class label is obtained by choosing the label associated with the shortest distance. In the experimental study, we combine several learning algorithms to build the ensemble system and conduct experiments on the UCI, colon cancer, and selected CLEF2009 datasets. The experimental results demonstrate that the proposed framework outperforms several benchmarked algorithms including two trainable combining methods, i.e., Decision Template and Two Stages Ensemble System, AdaBoost, Random Forest, L2-loss Linear Support Vector Machine, and Decision Tree

State of the Art and Future Perspectives in Smart and Sustainable Urban Development

This book contributes to the conceptual and practical knowledge pools in order to improve the research and practice on smart and sustainable urban development by presenting an informed understanding of the subject to scholars, policymakers, and practitioners. This book presents contributions—in the form of research articles, literature reviews, case reports, and short communications—offering insights into the smart and sustainable urban development by conducting in-depth conceptual debates, detailed case study descriptions, thorough empirical investigations, systematic literature reviews, or forecasting analyses. This way, the book forms a repository of relevant information, material, and knowledge to support research, policymaking, practice, and the transferability of experiences to address urbanization and other planetary challenges

Human‑centred design in industry 4.0: case study review and opportunities for future research

The transition to industry 4.0 has impacted factories, but it also afects the entire value chain. In this sense, human-centred factors play a core role in transitioning to sustainable manufacturing processes and consumption. The awareness of human roles in Industry 4.0 is increasing, as evidenced by active work in developing methods, exploring infuencing factors, and proving the efectiveness of design oriented to humans. However, numerous studies have been brought into existence but then disconnected from other studies. As a consequence, these studies in industry and research alike are not regularly adopted, and the network of studies is seemingly broad and expands without forming a coherent structure. This study is a unique attempt to bridge the gap through the literature characteristics and lessons learnt derived from a collection of case studies regarding human-centred design (HCD) in the context of Industry 4.0. This objective is achieved by a well-rounded systematic literature review whose special unit of analysis is given to the case studies, delivering contributions in three ways: (1) providing an insight into how the literature has evolved through the cross-disciplinary lens; (2) identifying what research themes associated with design methods are emerging in the feld; (3) and setting the research agenda in the context of HCD in Industry 4.0, taking into account the lessons learnt, as uncovered by the in-depth review of case studies

Urban mobility and spatial justice: Prospects for non-motorized mobility in Nairobi

This research investigates the relationship between mobility and justice in the context of Nairobi. Deriving from Amartya Sen's notion that justice addresses remediable injustices, the study explores justice as a dynamic concept influenced by diverse cultures, political ideologies, and philosophical paradigms. Spatial planning is taken as a canvas for these philosophical debates, manifesting in the spatial distribution of resources. Justice in relation to mobility is invoked and performed in various ways. This is based on the premise that space not only contains resources that can be distributed but also consists of individuals who are highly mobile within that space, and whose perceptions play a pivotal role in shaping the concept of justice in relation to mobility. Mobility, as a key element, plays a pivotal role in addressing spatial inequalities, as it facilitates access to the resources that are spatially disjointed. The intersection of mobility and justice unfolds in the streets and neighbourhoods, where spatial planning decisions impact infrastructure provision and access to services and opportunities. In Nairobi, a focus on motorized mobility has subtracted from the advancement of the modes of mobility used by the majority especially the most vulnerable, with a discernible outcome of injustices. Planning for motorized mobility has historically been at a higher level of consideration although a much larger percentage of the population travels on foot. The technical engineering design that lacks integration of social aspects of mobility has presented challenges in provision of safe non-motorized infrastructure, enduringly dismissing non-motorized mobility as a valid mode of mobility. Through a four- dimensional framework that includes space, mobility, individual characteristics and time, this research explores how spatial injustices in Nairobi’s mobility landscape unfold and are made manifest. Viewed from this perspective, the organization of space and the prioritization of the mobility needs of the most vulnerable present a notable way in which spatial justice unfolds and is understood

Setting the Future of Digital and Social Media Marketing Research: Perspectives and Research Propositions

in pressThe use of the internet and social media have changed consumer behavior and the ways in which companies conduct their business. Social and digital marketing offers significant opportunities to organizations through lower costs, improved brand awareness and increased sales. However, significant challenges exist from negative electronic word-of-mouth as well as intrusive and irritating online brand presence. This article brings together the collective insight from several leading experts on issues relating to digital and social media marketing. The experts' perspectives offer a detailed narrative on key aspects of this important topic as well as perspectives on more specific issues including artificial intelligence, augmented reality marketing, digital content management, mobile marketing and advertising, B2B marketing, electronic word of mouth and ethical issues therein. This research offers a significant and timely contribution to both researchers and practitioners in the form of challenges and opportunities where we highlight the limitations within the current research, outline the research gaps and develop the questions and propositions that can help advance knowledge within the domain of digital and social marketing.Peer reviewe

Network e-Volution

Modern society is a network society permeated by information technology (IT). As a result of innovations in IT, enormous amounts of information can be communicated to a larger number of recipients faster than ever before. The evolution of networks is heavily influenced by the extensive use of IT, which has enabled co-evolving advanced quantitative and qualitative forms of networking. Although several networks have been formed with the aim to reduce or deal with uncertainty through faster and broader access to information, it is in fact IT that has created new kinds of uncertainty. For instance, although digital information integration in supply chains has made production planning more robust, it has at the same time intensified mutual dependencies, thereby actually increasing the level of uncertainty. The aim of this working paper is to investigate the aspects of evolving networks and uncertainty in networks at the cutting edges of different types of networks and from the perspective of different layers defining these networks

Intrinsic Motivation in Computational Creativity Applied to Videogames

PhD thesisComputational creativity (CC) seeks to endow artificial systems with creativity. Although human creativity is known to be substantially driven by intrinsic motivation (IM), most CC systems are extrinsically motivated. This restricts their actual and perceived creativity and autonomy, and consequently their benefit to people. In this thesis, we demonstrate, via theoretical arguments and through applications in videogame AI, that computational intrinsic reward and models of IM can advance core CC goals. We introduce a definition of IM to contextualise related work. Via two systematic reviews, we develop typologies of the benefits and applications of intrinsic reward and IM models in CC and game AI. Our reviews highlight that related work is limited to few reward types and motivations, and we thus investigate the usage of empowerment, a little studied, information-theoretic intrinsic reward, in two novel models applied to game AI. We define coupled empowerment maximisation (CEM), a social IM model, to enable general co-creative agents that support or challenge their partner through emergent behaviours. Via two qualitative, observational vignette studies on a custom-made videogame, we explore CEM’s ability to drive general and believable companion and adversary non-player characters which respond creatively to changes in their abilities and the game world. We moreover propose to leverage intrinsic reward to estimate people’s experience of interactive artefacts in an autonomous fashion. We instantiate this proposal in empowerment-based player experience prediction (EBPXP) and apply it to videogame procedural content generation. By analysing think-aloud data from an experiential vignette study on a dedicated game, we identify several experiences that EBPXP could predict. Our typologies serve as inspiration and reference for CC and game AI researchers to harness the benefits of IM in their work. Our new models can increase the generality, autonomy and creativity of next-generation videogame AI, and of CC systems in other domains