10,860 research outputs found

    Marketing in SMEs: a '4Ps' self-branding model

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    Purpose – The purpose of this paper is to explore the extent to which traditional marketing theory and practice can be applied in small- and medium-sized enterprises (SMEs) and consider how owner-managers perceive their own role in marketing within a small business setting. Design/methodology/approach – A qualitative exploratory approach using semi-structured in-depth interviews amongst owner-managers of SMEs in the UK. Findings – SME marketing is effective in that it embraces some relevant concepts of traditional marketing, tailors activities to match its customers and adds its own unique attribute of self-branding as bestowed by the SME owner-manager. Research limitations/implications – The study was limited to the UK and to a small sample of SMEs and as such the findings are not necessarily generalisable. Originality/value – A “4Ps” model for SME self-branding is proposed, which encompasses the attributes of personal branding, (co)production, perseverance and practice

    4D Multi-atlas Label Fusion using Longitudinal Images

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    Longitudinal reproducibility is an essential concern in automated medical image segmentation, yet has proven to be an elusive objective as manual brain structure tracings have shown more than 10% variability. To improve reproducibility, lon-gitudinal segmentation (4D) approaches have been investigated to reconcile tem-poral variations with traditional 3D approaches. In the past decade, multi-atlas la-bel fusion has become a state-of-the-art segmentation technique for 3D image and many efforts have been made to adapt it to a 4D longitudinal fashion. However, the previous methods were either limited by using application specified energy function (e.g., surface fusion and multi model fusion) or only considered tem-poral smoothness on two consecutive time points (t and t+1) under sparsity as-sumption. Therefore, a 4D multi-atlas label fusion theory for general label fusion purpose and simultaneously considering temporal consistency on all time points is appealing. Herein, we propose a novel longitudinal label fusion algorithm, called 4D joint label fusion (4DJLF), to incorporate the temporal consistency modeling via non-local patch-intensity covariance models. The advantages of 4DJLF include: (1) 4DJLF is under the general label fusion framework by simul-taneously incorporating the spatial and temporal covariance on all longitudinal time points. (2) The proposed algorithm is a longitudinal generalization of a lead-ing joint label fusion method (JLF) that has proven adaptable to a wide variety of applications. (3) The spatial temporal consistency of atlases is modeled in a prob-abilistic model inspired from both voting based and statistical fusion. The pro-posed approach improves the consistency of the longitudinal segmentation while retaining sensitivity compared with original JLF approach using the same set of atlases. The method is available online in open-source

    Good Dog/Bad Dog: Dogs in Medieval Religious Polemics

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    Learning Design: reflections on a snapshot of the current landscape

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    The mounting wealth of open and readily available information and the swift evolution of social, mobile and creative technologies warrant a re-conceptualisation of the role of educators: from providers of knowledge to designers of learning. This need is being addressed by a growing trend of research in Learning Design. Responding to this trend, the Art and Science of Learning Design workshop brought together leading voices in the field and provided a forum for discussing its key issues. It focused on three thematic axes: practices and methods, tools and resources, and theoretical frameworks. This paper reviews some definitions of Learning Design and then summarises the main contributions to the workshop. Drawing upon these, we identify three key challenges for Learning Design that suggest directions for future research

    Responding to class theft: Theoretical and empirical links to critical management studies

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    Redrafted submission for inclusion in Remarx Section of Rethinking MarxismThis paper suggests closer linkages between the fields of Postmodern Class Analysis (PCA) and Critical Management Studies (CMS)2 are possible. It argues that CMS might contribute to the empirical engagement with the over-determined relations between class and non-class processes in work organizations (this appears to have received relatively little attention in PCA) and that PCA's theoretical and conceptual commitments may provide one means for CMS to engage in class analysis. CMS's focus on power and symbolic relations has led to the relative neglect of exploitation and class, in surplus terms. Both fields share similar although not identical political and ethical commitments

    User evaluation of a market-based recommender system

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    Recommender systems have been developed for a wide variety of applications (ranging from books, to holidays, to web pages). These systems have used a number of different approaches, since no one technique is best for all users in all situations. Given this, we believe that to be effective, systems should incorporate a wide variety of such techniques and then some form of overarching framework should be put in place to coordinate them so that only the best recommendations (from whatever source) are presented to the user. To this end, in our previous work, we detailed a market-based approach in which various recommender agents competed with one another to present their recommendations to the user. We showed through theoretical analysis and empirical evaluation with simulated users that an appropriately designed marketplace should be able to provide effective coordination. Building on this, we now report on the development of this multi-agent system and its evaluation with real users. Specifically, we show that our system is capable of consistently giving high quality recommendations, that the best recommendations that could be put forward are actually put forward, and that the combination of recommenders performs better than any constituent recommende

    Rational Trust Modeling

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    Trust models are widely used in various computer science disciplines. The main purpose of a trust model is to continuously measure trustworthiness of a set of entities based on their behaviors. In this article, the novel notion of "rational trust modeling" is introduced by bridging trust management and game theory. Note that trust models/reputation systems have been used in game theory (e.g., repeated games) for a long time, however, game theory has not been utilized in the process of trust model construction; this is where the novelty of our approach comes from. In our proposed setting, the designer of a trust model assumes that the players who intend to utilize the model are rational/selfish, i.e., they decide to become trustworthy or untrustworthy based on the utility that they can gain. In other words, the players are incentivized (or penalized) by the model itself to act properly. The problem of trust management can be then approached by game theoretical analyses and solution concepts such as Nash equilibrium. Although rationality might be built-in in some existing trust models, we intend to formalize the notion of rational trust modeling from the designer's perspective. This approach will result in two fascinating outcomes. First of all, the designer of a trust model can incentivise trustworthiness in the first place by incorporating proper parameters into the trust function, which can be later utilized among selfish players in strategic trust-based interactions (e.g., e-commerce scenarios). Furthermore, using a rational trust model, we can prevent many well-known attacks on trust models. These two prominent properties also help us to predict behavior of the players in subsequent steps by game theoretical analyses

    Early affective changes and increased connectivity in preclinical Alzheimer's disease.

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    IntroductionAffective changes precede cognitive decline in mild Alzheimer's disease and may relate to increased connectivity in a "salience network" attuned to emotionally significant stimuli. The trajectory of affective changes in preclinical Alzheimer's disease, and its relationship to this network, is unknown.MethodsOne hundred one cognitively normal older adults received longitudinal assessments of affective symptoms, then amyloid-PET. We hypothesized amyloid-positive individuals would show enhanced emotional reactivity associated with salience network connectivity. We tested whether increased global connectivity in key regions significantly related to affective changes.ResultsIn participants later found to be amyloid positive, emotional reactivity increased with age, and interpersonal warmth declined in women. These individuals showed higher global connectivity within the right insula and superior temporal sulcus; higher superior temporal sulcus connectivity predicted increasing emotional reactivity and decreasing interpersonal warmth.ConclusionsAffective changes should be considered an early preclinical feature of Alzheimer's disease. These changes may relate to higher functional connectivity in regions critical for social-emotional processing
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