4,041 research outputs found

    Tipping the scales: ambidexterity practices on e-HRM projects

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    Purpose: We examine and conceptualise the ways in which a balance can be achieved between optimising the efficiency and effectiveness of electronic HRM (e-HRM) systems for human resource management (HRM) and enabling innovation to occur during the system implementation. Design/methodology/approach: An intepretive case study of a UK local authority e-HRM system implementation is examined using the notion of ambidexterity as an analytical device. Ambidexterity relates to how an organisation develops the ability to operate efficiently in the now, while at the same time being able to adapt to environmental changes around and ahead of them in order to grow into the future. Findings: As an intra-organisational capability, ambidexterity is found to derive from the simultaneous interplay and balancing of dual capabilities: exploitation and exploration.. E-HRM exploitation concerned the capability to generate new knowledge with innovatory effects, created through the everyday practices performed by practitioners at all levels in the organisation. E-HRM exploration, rather than being a purposeful act, was found to be an accidental consequence of engaging in exploitation to maintain the status quo. Originality/value: There is a lack of detailed investigation of how organisations actually achieve ambidexterity, particularly in three under-researched areas: ambidexterity in the public sector, at HR functional level and e-HRM systems implementation. Bundling these three areas into an integrated examination allows us to both identify how exploitation and exploration play out in the ambidextrous practices of an e-HRM project and also to identify the dimensions of ambidexterity in balancing e-HRM work

    Catgame: A Tool For Problem Solving In Complex Dynamic Systems Using Game Theoretic Knowledge Distribution In Cultural Algorithms, And Its Application (catneuro) To The Deep Learning Of Game Controller

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    Cultural Algorithms (CA) are knowledge-intensive, population-based stochastic optimization methods that are modeled after human cultures and are suited to solving problems in complex environments. The CA Belief Space stores knowledge harvested from prior generations and re-distributes it to future generations via a knowledge distribution (KD) mechanism. Each of the population individuals is then guided through the search space via the associated knowledge. Previously, CA implementations have used only competitive KD mechanisms that have performed well for problems embedded in static environments. Relatively recently, CA research has evolved to encompass dynamic problem environments. Given increasing environmental complexity, a natural question arises about whether KD mechanisms that also incorporate cooperation can perform better in such environments than purely competitive ones? Borrowing from game theory, game-based KD mechanisms are implemented and tested against the default competitive mechanism – Weighted Majority (WTD). Two different concepts of complexity are addressed – numerical optimization under dynamic environments and hierarchal, multi-objective optimization for evolving deep learning models. The former is addressed with the CATGame software system and the later with CATNeuro. CATGame implements three types of games that span both cooperation and competition for knowledge distribution, namely: Iterated Prisoner\u27s Dilemma (IPD), Stag-Hunt and Stackelberg. The performance of the three game mechanisms is compared with the aid of a dynamic problem generator called Cones World. Weighted Majority, aka “wisdom of the crowd”, the default CA competitive KD mechanism is used as the benchmark. It is shown that games that support both cooperation and competition do indeed perform better but not in all cases. The results shed light on what kinds of games are suited to problem solving in complex, dynamic environments. Specifically, games that balance exploration and exploitation using the local signal of ‘social’ rank – Stag-Hunt and IPD – perform better. Stag-Hunt which is also the most cooperative of the games tested, performed the best overall. Dynamic analysis of the ‘social’ aspects of the CA test runs shows that Stag-Hunt allocates compute resources more consistently than the others in response to environmental complexity changes. Stackelberg where the allocation decisions are centralized, like in a centrally planned economic system, is found to be the least adaptive. CATNeuro is for solving neural architecture search (NAS) problems. Contemporary ‘deep learning’ neural network models are proven effective. However, the network topologies may be complex and not immediately obvious for the problem at hand. This has given rise to the secondary field of neural architecture search. It is still nascent with many frameworks and approaches now becoming available. This paper describes a NAS method based on graph evolution pioneered by NEAT (Neuroevolution of Augmenting Topologies) but driven by the evolutionary mechanisms under Cultural Algorithms. Here CATNeuro is applied to find optimal network topologies to play a 2D fighting game called FightingICE (derived from “The Rumble Fish” video game). A policy-based, reinforcement learning method is used to create the training data for network optimization. CATNeuro is still evolving. To inform the development of CATNeuro, in this primary foray into NAS, we contrast the performance of CATNeuro with two different knowledge distribution mechanisms – the stalwart Weighted Majority and a new one based on the Stag-Hunt game from evolutionary game theory that performed the best in CATGame. The research shows that Stag-Hunt has a distinct edge over WTD in terms of game performance, model accuracy, and model size. It is therefore deemed to be the preferred mechanism for complex, hierarchical optimization tasks such as NAS and is planned to be used as the default KD mechanism in CATNeuro going forward

    Boundary Management in Projects: Antecedents, Activities and Performance

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    Despite increasing interest among practitioners and the recent scientific explo-rations on the dynamics of boundary management in project and team contexts, the existing studies seems to lack empirical understanding on the factors that explain the boundary management behavior of project managers. The purpose of this study is to analyze how the three antecedent factors - cross-functional participation, embeddedness and top management control - are related to four different types of boundary management activities practiced by project managers, namely coordinating, enabling, reporting and guarding. Based on the sample of 236 projects, the results show that embeddedness and top-management control have positive influence on boundary-management activities and cross-functional participation has both positive and negative contribution to boundary management activities. Furthermore, the results reveal that boundary management activities have both positive and negative influence on project performance. Contributions of the research are discussed, as well as practical implications, limitations, and directions for future research.Boundary management, project team, embeddedness, cross-functional participation, top-management control

    Design and semantics of form and movement (DeSForM 2006)

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    Design and Semantics of Form and Movement (DeSForM) grew from applied research exploring emerging design methods and practices to support new generation product and interface design. The products and interfaces are concerned with: the context of ubiquitous computing and ambient technologies and the need for greater empathy in the pre-programmed behaviour of the ‘machines’ that populate our lives. Such explorative research in the CfDR has been led by Young, supported by Kyffin, Visiting Professor from Philips Design and sponsored by Philips Design over a period of four years (research funding £87k). DeSForM1 was the first of a series of three conferences that enable the presentation and debate of international work within this field: • 1st European conference on Design and Semantics of Form and Movement (DeSForM1), Baltic, Gateshead, 2005, Feijs L., Kyffin S. & Young R.A. eds. • 2nd European conference on Design and Semantics of Form and Movement (DeSForM2), Evoluon, Eindhoven, 2006, Feijs L., Kyffin S. & Young R.A. eds. • 3rd European conference on Design and Semantics of Form and Movement (DeSForM3), New Design School Building, Newcastle, 2007, Feijs L., Kyffin S. & Young R.A. eds. Philips sponsorship of practice-based enquiry led to research by three teams of research students over three years and on-going sponsorship of research through the Northumbria University Design and Innovation Laboratory (nuDIL). Young has been invited on the steering panel of the UK Thinking Digital Conference concerning the latest developments in digital and media technologies. Informed by this research is the work of PhD student Yukie Nakano who examines new technologies in relation to eco-design textiles

    Data-driven control of a Pendulum Wave Energy Converter: A Gaussian Process Regression approach

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    The energy coming from the motion of the waves of seas and oceans could be an important component in the solution of the energy problem related to the pursuit of alternatives to fossil fuels. However, wave energy is still technologically immature and it has not reached the economic feasibility required for economy of scale. One of the major technological challenges for the achievement of this goal is the development of control strategies capable of maximizing the extracted energy, adapting to the conditions of the seas and oceans that surround the Wave Energy Converter (WEC) devices. To perform this task, control systems often adopt explicitly control-oriented models, that are by nature affected by uncertainties. On the contrary, to address the problem a data-driven solution is proposed here. The presented strategy applies an optimization approach based on a Gaussian Process Regression (GPR) metamodel to learn the control strategy to be applied. In order to accelerate the learning process, we present a novel method that exploits in the initial phase a previous knowledge given by simulations with the system model and based on the co-kriging concept. To test this approach the Pendulum Wave Energy Converter has been adopted as a case study. To differentiate the previous knowledge and the real system behaviour, a simplified linear model is used to obtain the prior knowledge, while a complex nonlinear one acts as the environment in which simulate the behaviour of the real system. A month-long simulation is used to validate the effectiveness of the proposed strategy, showing the ability of adapting to a real system different from the simplified model on the basis only of data, and overcoming the model-based strategy in terms of performance

    Joining Entities Across Relation and Graph with a Unified Model

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    This paper introduces RG (Relational Genetic) model, a revised relational model to represent graph-structured data in RDBMS while preserving its topology, for efficiently and effectively extracting data in different formats from disparate sources. Along with: (a) SQLδ_\delta, an SQL dialect augmented with graph pattern queries and tuple-vertex joins, such that one can extract graph properties via graph pattern matching, and "semantically" match entities across relations and graphs; (b) a logical representation of graphs in RDBMS, which introduces an exploration operator for efficient pattern querying, supports also browsing and updating graph-structured data; and (c) a strategy to uniformly evaluate SQL, pattern and hybrid queries that join tuples and vertices, all inside an RDBMS by leveraging its optimizer without performance degradation on switching different execution engines. A lightweight system, WhiteDB, is developed as an implementation to evaluate the benefits it can actually bring on real-life data. We empirically verified that the RG model enables the graph pattern queries to be answered as efficiently as in native graph engines; can consider the access on graph and relation in any order for optimal plan; and supports effective data enrichment.Comment: 24 pages, 16 figures, 5 table

    Quantitative analysis of computer interaction movements

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    Understanding user experience of mobile video: Framework, measurement, and optimization

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    Since users have become the focus of product/service design in last decade, the term User eXperience (UX) has been frequently used in the field of Human-Computer-Interaction (HCI). Research on UX facilitates a better understanding of the various aspects of the user’s interaction with the product or service. Mobile video, as a new and promising service and research field, has attracted great attention. Due to the significance of UX in the success of mobile video (Jordan, 2002), many researchers have centered on this area, examining users’ expectations, motivations, requirements, and usage context. As a result, many influencing factors have been explored (Buchinger, Kriglstein, Brandt & Hlavacs, 2011; Buchinger, Kriglstein & Hlavacs, 2009). However, a general framework for specific mobile video service is lacking for structuring such a great number of factors. To measure user experience of multimedia services such as mobile video, quality of experience (QoE) has recently become a prominent concept. In contrast to the traditionally used concept quality of service (QoS), QoE not only involves objectively measuring the delivered service but also takes into account user’s needs and desires when using the service, emphasizing the user’s overall acceptability on the service. Many QoE metrics are able to estimate the user perceived quality or acceptability of mobile video, but may be not enough accurate for the overall UX prediction due to the complexity of UX. Only a few frameworks of QoE have addressed more aspects of UX for mobile multimedia applications but need be transformed into practical measures. The challenge of optimizing UX remains adaptations to the resource constrains (e.g., network conditions, mobile device capabilities, and heterogeneous usage contexts) as well as meeting complicated user requirements (e.g., usage purposes and personal preferences). In this chapter, we investigate the existing important UX frameworks, compare their similarities and discuss some important features that fit in the mobile video service. Based on the previous research, we propose a simple UX framework for mobile video application by mapping a variety of influencing factors of UX upon a typical mobile video delivery system. Each component and its factors are explored with comprehensive literature reviews. The proposed framework may benefit in user-centred design of mobile video through taking a complete consideration of UX influences and in improvement of mobile videoservice quality by adjusting the values of certain factors to produce a positive user experience. It may also facilitate relative research in the way of locating important issues to study, clarifying research scopes, and setting up proper study procedures. We then review a great deal of research on UX measurement, including QoE metrics and QoE frameworks of mobile multimedia. Finally, we discuss how to achieve an optimal quality of user experience by focusing on the issues of various aspects of UX of mobile video. In the conclusion, we suggest some open issues for future study
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