A modelling and simulation environment for self-aware and self-expressive systems

Self-awareness and self-expression are promising architectural concepts for embedded systems to be equipped with to match them with dedicated application scenarios and constraints in the avionic and space-flight industry. Typically, these systems operate in largely undefined environments and are not reachable after deployment for a long time or even never ever again. This paper introduces a reference architecture as well as a novel modelling and simulation environment for self-aware and self-expressive systems with transaction level modelling, simulation and detailed modelling capabilities for hardware aspects, precise process chronology execution as well as fine timing resolutions. Furthermore, industrial relevant system sizes with several self-aware and self-expressive nodes can be handled by the modelling and simulation environment.

The handbook of engineering self-aware and self-expressive systems

When faced with the task of designing and implementing a new self-aware and self-expressive computing system, researchers and practitioners need a set of guidelines on how to use the concepts and foundations developed in the Engineering Proprioception in Computing Systems (EPiCS) project. This report provides such guidelines on how to design self-aware and self-expressive computing systems in a principled way. We have documented different categories of self-awareness and self-expression level using architectural patterns. We have also documented common architectural primitives, their possible candidate techniques and attributes for architecting self-aware and self-expressive systems. Drawing on the knowledge obtained from the previous investigations, we proposed a pattern driven methodology for engineering self-aware and self-expressive systems to assist in utilising the patterns and primitives during design. The methodology contains detailed guidance to make decisions with respect to the possible design alternatives, providing a systematic way to build self-aware and self-expressive systems. Then, we qualitatively and quantitatively evaluated the methodology using two case studies. The results reveal that our pattern driven methodology covers the main aspects of engineering self-aware and self-expressive systems, and that the resulted systems perform significantly better than the non-self-aware systems.

A survey of self-awareness and its application in computing systems

Novel computing systems are increasingly being composed of large numbers of heterogeneous components, each with potentially different goals or local perspectives, and connected in networks which change over time. Management of such systems quickly becomes infeasible for humans. As such, future computing systems should be able to achieve advanced levels of autonomous behaviour. In this context, the system's ability to be self-aware and be able to self-express becomes important. This paper surveys definitions and current understanding of self-awareness and self-expression in biology and cognitive science. Subsequently, previous efforts to apply these concepts to computing systems are described. This has enabled the development of novel working definitions for self-awareness and self-expression within the context of computing systems.

Self-aware and self-expressive camera networks

Smart cameras perform on-board image analysis, adapt their algorithms to changes in their environment, and collaborate with other networked cameras to analyze the dynamic behavior of objects. A proposed computational framework adopts the concepts of self-awareness and self-expression to more efficiently manage the complex tradeoffs among performance, flexibility, resources, and reliability. The Web extra at http://youtu.be/NKe31-OKLz4 is a video demonstrating CamSim, a smart camera simulation tool, enables users to test self-adaptive and self-organizing smart-camera techniques without deploying a smart-camera network.

EPiCS:engineering proprioception in computing systems

Modern compute systems continue to evolve towards increasingly complex, heterogeneous and distributed architectures. At the same time, functionality and performance are no longer the only aspects when developing applications for such systems, and additional concerns such as flexibility, power efficiency, resource usage, reliability and cost are becoming increasingly important. This does not only raise the question of how to efficiently develop applications for such systems, but also how to cope with dynamic changes in the application behaviour or the system environment. The EPiCS Project aims to address these aspects through exploring self-awareness and self-expression. Self-awareness allows systems and applications to gather and maintain information about their current state and environment, and reason about their behaviour. Self-expression enables systems to adapt their behaviour autonomously to changing conditions. Innovations in EPiCS are based on systematic integration of research in concepts and foundations, customisable hardware/software platforms and operating systems, and self-aware networking and middleware infrastructure. The developed technologies are validated in three application domains: computational finance, distributed smart cameras and interactive mobile media systems. © 2012 IEEE.

Negative brand personality:the construct, its antecedents and outcome variables

By evolving brands and building on the importance of self-expression, Aaker (1997) developed the brand personality framework as a means to understand brand-consumer relationships. The brand personality framework captures the core values and characteristics described in human personality research in an attempt to humanize brands. Although influential across many streams of brand personality research, the current conceptualization of brand personality only offers a positively-framed approach. To date, no research, both conceptually and empirically, has thoroughly incorporated factors reflective of Negative Brand Personality, despite the fact that almost all researchers in personality are in agreement that factors akin to Extraversion (positive) and Neuroticism (negative) should be in a comprehensive personality scale to accommodate consumers’ expressions. As a result, the study of brand personality is only half complete since the current research trend is to position brand personality under brand image. However, with the brand personality concept being confused with brand identity at the empirical stage, factors reflective of Negative Brand Personality have been neglected. Accordingly, this thesis extends the current conceptualization of brand personality by demarcating the existing typologies of desirable brand personality and incorporating the characteristics reflective of consumers’ discrepant self-meaning to provide a more complete understanding of brand personality. However, it is not enough to interpret negative factors as the absence of positive factors. Negative factors reflect consumers’ anxious and frustrated feelings. Therefore, this thesis contributes to the current conceptualization of brand personality by, firstly, presenting a conceptual definition of Negative Brand Personality in order to provide a theoretical basis for the development of a Negative Brand Personality scale, then, secondly, identifying what constitutes Negative Brand Personality and to what extent consumers’ cognitive dissonance explains the nature of Negative Brand Personality, and, thirdly, ascertaining the impact Negative Brand Personality has on attitudinal constructs, namely: Negative Attitude, Detachment, Brand Loyalty and Satisfaction, which have proven to predict behaviors such as choice and (re-)purchasing. In order to deliver on the three main contributions, two comprehensive studies were conducted to a) develop a valid, parsimonious, yet relatively short measure of Negative Brand Personality, and b) ascertain how the Negative Brand Personality measure behaves within a network of related constructs. The mixed methods approach, grounded in theoretical and empirical development, provides evidence to suggest that there are four factors to Negative Brand Personality and, tested through use of a structural equation modeling technique, that these are influenced by Brand Confusion, Price Unfairness, Self- Incongruence and Corporate Hypocrisy. Negative Brand Personality factors mainly determined Consumers Negative Attitudes and Brand Detachment. The research contributes to the literature on brand personality by improving the consumer-brand relationship by means of engaging in a brandconsumer conversation in order to reduce consumers’ cognitive strain. The study concludes with a discussion on the theoretical and practical implications of the findings, its limitations, and potential directions for future research.

The relative advantage of marketing over technological capabilities in influencing new product performance:the moderating role of country institutions

Marketing and technological capabilities are major drivers of new product performance. Prior research has suggested that marketing capabilities outperform technological capabilities. This study shows that the relative advantage of marketing over technological capabilities for new product performance depends on the institutional context in a country. Meta-analytic data of 341 effect sizes of the relationship between capabilities and new product performance taken from 50 articles with 57 independent samples and collected in 17 different countries reveal new contingencies to the capabilities framework. Although in general, marketing capabilities have a stronger influence than technological capabilities on new product performance, this effect is moderated by institutional context factors. The relative advantage decreases and even reverses with increasing growth rates; it further decreases with increasingly stronger rules of law in a country; and it increases in societies that put emphasis on self-expression values over survival values. These findings contribute to research on the utility of different capabilities, inform the institution-based view of firms in international marketing, and provide implications for international marketing managers.

Mathematical and numerical modelling of dispersion-managed solitons, autosolitons and self-similar optical pulses

This thesis presents theoretical investigation of three topics concerned with nonlinear optical pulse propagation in optical fibres. The techniques used are mathematical analysis and numerical modelling. Firstly, dispersion-managed (DM) solitons in fibre lines employing a weak dispersion map are analysed by means of a perturbation approach. In the case of small dispersion map strengths the average pulse dynamics is described by a perturbation approach (NLS) equation. Applying a perturbation theory, based on the Inverse Scattering Transform method, an analytic expression for the envelope of the DM soliton is derived. This expression correctly predicts the power enhancement arising from the dispersion management.Secondly, autosoliton transmission in DM fibre systems with periodical in-line deployment of nonlinear optical loop mirrors (NOLMs) is investigated. The use of in-line NOLMs is addressed as a general technique for all-optical passive 2R regeneration of return-to-zero data in high speed transmission system with strong dispersion management. By system optimisation, the feasibility of ultra-long single-channel and wavelength-division multiplexed data transmission at bit-rates ³ 40 Gbit s-1 in standard fibre-based systems is demonstrated. The tolerance limits of the results are defined.Thirdly, solutions of the NLS equation with gain and normal dispersion, that describes optical pulse propagation in an amplifying medium, are examined. A self-similar parabolic solution in the energy-containing core of the pulse is matched through Painlevé functions to the linear low-amplitude tails. The analysis provides a full description of the features of high-power pulses generated in an amplifying medium.

Self-calibrated, multi-spectral photometric stereo for 3D face capture

This paper addresses the problem of obtaining 3d detailed reconstructions of human faces in real-time and with inexpensive hardware. We present an algorithm based on a monocular multi-spectral photometric-stereo setup. This system is known to capture high-detailed deforming 3d surfaces at high frame rates and without having to use any expensive hardware or synchronized light stage. However, the main challenge of such a setup is the calibration stage, which depends on the lights setup and how they interact with the specific material being captured, in this case, human faces. For this purpose we develop a self-calibration technique where the person being captured is asked to perform a rigid motion in front of the camera, maintaining a neutral expression. Rigidity constrains are then used to compute the head's motion with a structure-from-motion algorithm. Once the motion is obtained, a multi-view stereo algorithm reconstructs a coarse 3d model of the face. This coarse model is then used to estimate the lighting parameters with a stratified approach: In the first step we use a RANSAC search to identify purely diffuse points on the face and to simultaneously estimate this diffuse reflectance model. In the second step we apply non-linear optimization to fit a non-Lambertian reflectance model to the outliers of the previous step. The calibration procedure is validated with synthetic and real data.

Exploring ant-based algorithms for gene expression data analysis

Objective: Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant colony optimization (ACO) is one such algorithm based on swarm intelligence and is derived from a model inspired by the collective foraging behavior of ants. Taking advantage of the ACO in traits such as self-organization and robustness, this paper investigates ant-based algorithms for gene expression data clustering and associative classification. Methods and material: An ant-based clustering (Ant-C) and an ant-based association rule mining (Ant-ARM) algorithms are proposed for gene expression data analysis. The proposed algorithms make use of the natural behavior of ants such as cooperation and adaptation to allow for a flexible robust search for a good candidate solution. Results: Ant-C has been tested on the three datasets selected from the Stanford Genomic Resource Database and achieved relatively high accuracy compared to other classical clustering methods. Ant-ARM has been tested on the acute lymphoblastic leukemia (ALL)/acute myeloid leukemia (AML) dataset and generated about 30 classification rules with high accuracy. Conclusions: Ant-C can generate optimal number of clusters without incorporating any other algorithms such as K-means or agglomerative hierarchical clustering. For associative classification, while a few of the well-known algorithms such as Apriori, FP-growth and Magnum Opus are unable to mine any association rules from the ALL/AML dataset within a reasonable period of time, Ant-ARM is able to extract associative classification rules.

On the compatibility of benevolence and self-interest:philanthropy and entrepreneurial orientation

This article explores the philanthropy of owner–managers of small- and medium-sized enterprises (SMEs) investigating whether and why more entrepreneurially oriented SMEs are also more likely to engage in philanthropic activities. We find support for a positive link between entrepreneurial orientation (EO) and philanthropy in a representative sample of 270 Lithuanian SMEs controlling for alternative explanations. We highlight that philanthropy is relatively common among SME owner–managers and thus complement existing research which views philanthropy as sequentially following wealth generation. In line with our theorizing, further qualitative findings point to drivers of philanthropy beyond those considered in the dominant strategic-instrumental perspective. Building on social-psychological theories of motivation, we argue and confirm that philanthropy can also be an expression of owner–managers’ altruistic values; these values can be compatible and even mutually reinforcing with entrepreneurship. Our study is set in a transition economy, Lithuania, facilitating the analysis of heterogeneity in attitudes toward philanthropy.