919 resultados para Intelligence artificielle


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This paper focuses on the processes by which firms, particularly knowledge intensive firms, can augment their overall knowledge stock by tapping into external sources of knowledge. It is argued that Top Management Teams' (TMTs') social intelligence is a critical learning capability in acquiring external knowledge that leads to strategic change. Social intelligence involves social awareness, social understanding and social skills. The study draws from the experience of 11 of the largest Information Technology Service Providers (ITSPs) in India and based on in-depth interviews. The findings show that TMTs' learning capability in the context of social intelligence to interact with external stakeholders is important to ITSPs in facilitating external knowledge acquisition and allowing new knowledge emerge within and across networks. The findings provide significant insights into ITSPs emerging in other developing countries such as in China. Research limitation and future research direction are also provided.

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Numerous authors have expressed concerns that the introduction of the Personally Controlled Electronic Health Record (PCEHR) will lead to an escalation of disputes. Some disputes will concern the accuracy of the record whereas others will arise simply due to greater access to health care records. Online dispute resolution (ODR) programs have been successfully applied to cost-effectively help disputants resolve commercial, insurance and other legal disputes, and can also facilitate the resolution of health care related disputes. However, we expect that health differs from other application domains in ODR because of the emotional engagement patients have with their health and those of loved ones. In this study we will be looking at whether the success of an online negotiation is related to how people recognise and manage emotions, and in particular, their Emotional intelligence score.

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Business intelligence (BI) architecture based on service-oriented architecture (SOA) concept enables enterprises to deploy agile and reliable BI applications. However, the key factors for implementing a SOA-based BI architecture from technical perspectives have not yet been systematically investigated. Most of the prior studies focus on organisational and managerial perspectives rather than technical factors. Therefore, this study explores the key technical factors that are most likely to have an impact on the implementation of a SOA-based BI architecture. This paper presents a conceptual model of BI architecture built on SOA concept. Drawing on academic and practitioner literature related to SOA and software architectural design, we propose fourteen key factors that may influence the implementation of a SOA-based BI architecture. This study bridges the gap between academic and practitioners.

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This chapter presents an introduction to computational intelligence (CI) paradigms. A number of CI definitions are first presented to provide a general concept of this new, innovative computing field. The main constituents of CI, which include artificial neural networks, fuzzy systems, and evolutionary algorithms, are explained. In addition, different hybrid CI models arisen from synergy of neural, fuzzy, and evolutionary computational paradigms are discussed.

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The authors of this paper argue that human intuition alone cannot be relied upon for strategic decision making in today’s business environment and that quality data intelligence is an imperative. The proposed project described in this paper is research-in-progress, action design research (ADR), to implement an appropriate information systems (IS) enabling enhanced organisational decision making. ADR is a new research method that draws on action research and design research in an organisational setting. In phase 1 of the project, a sociotechnical ‘sense-making’ approach is used to gather and analyse information and decision needs in a not-for-profit (NFP) association, Connections ACT. In phase 2, requirements are designed and modelled to build a conceptual framework that guides NFPs in improving business performance and reporting capability. Phase 3 is the evaluative stage when the framework is reflected upon and refined, with intervention in the organisation’s processes as a promising outcome.

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Social media data are becoming increasingly critical for businesses to capture, analyse, and utilise in a timely manner. However, the unstructured and distributed nature and volume of this information makes the task of extracting useful and practical information challenging. Given the dynamic evolution of social media and social media monitoring, our current understanding of how social media monitoring can help organisations to create business value is inadequate. As a result, there is a need to study how organisations can (a) extract and analyse social media data related to their business (Sensing), and (b) utilise external intelligence gained from social media monitoring for specific business initiatives (Seizing). This study uses a qualitative approach with a multiple embedded case study design to understand the phenomenon of social media monitoring and its outcome for organisations. Anticipated contributions are presented.

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In many respects, A History of Intelligence and Intellectual 'Disability' is a confronting work. At a literal level, it comprises eighteen chapters verging on a total of quarter of a million words, apart from twenty-two pages of primary and secondary sources. Many of its chapters are drawn from Chris Goodey's articles since the early 'nineties in such journals as Ancient Philosophy, Archiv für Geschichte der Philosophie, History of the Human Sciences, and Political Theory. However, he immediately warns us that such articles exist as a "more primitive form" (vii) of the current volume.

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Computational Intelligence (CI) models comprise robust computing methodologies with a high level of machine learning quotient. CI models, in general, are useful for designing computerized intelligent systems/machines that possess useful characteristics mimicking human behaviors and capabilities in solving complex tasks, e.g., learning, adaptation, and evolution. Examples of some popular CI models include fuzzy systems, artificial neural networks, evolutionary algorithms, multi-agent systems, decision trees, rough set theory, knowledge-based systems, and hybrid of these models. This special issue highlights how different computational intelligence models, coupled with other complementary techniques, can be used to handle problems encountered in image processing and information reasoning.

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Objective: 
Clinical reasoning studies have acknowledged tacit aspects of practice, and recent research 
suggests that clinical reasoning contains intuition informed by tacit knowledge. Intuition also appears to be influenced by awareness and understanding of emotions. This study investigated the relationship between intuition and emotional intelligence among occupational therapists in mental health practice.

Method: 
We mailed a survey containing measures of cognitive style and of use of emotional competencies at work and demographic questions to 400 members of the national occupational therapy association; 134 occupational therapists responded.
Results: 
A moderate relationship was found between intuitive cognitive style and emotional intelligence. Experienced therapists scored higher on the use of emotional competencies at work and reported a preference for an intuitive cognitive style to a greater extent than novices.
Conclusion: 
This study represents the first attempt to explore occupational therapists’ preferred cognitive style and self-reported emotional intelligence. Findings suggest that exploring emotions through reflective practice could enhance intuitive aspects of clinical reasoning.

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Due to ubiquitous information requirements, market interest in mobile business intelligence (BI) has grown markedly. However, mobile BI market is a relatively new area that has been driven primarily by the IT industry. Yet, there is a lack of systematic study on the critical success factors for mobile BI. This research reviews the state-of-the-art of mobile BI, and explores the critical success factors based on a rigorous examination of the academic and practitioner literature. The study reveals that critical success factors of mobile BI generally fall into four key dimensions, namely security, mobile technology, system content and quality, and organisational support perspectives. The various research findings will be useful to organisations which are considering or undertaking mobile business intelligence initiatives.

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Computational Intelligence (CI) holds the key to the development of smart grid to overcome the challenges of planning and optimization through accurate prediction of Renewable Energy Sources (RES). This paper presents an architectural framework for the construction of hybrid intelligent predictor for solar power. This research investigates the applicabil- ity of heterogeneous regression algorithms for 6 hour ahead solar power availability forecasting using historical data from Rockhampton, Australia. Real life solar radiation data is collected across six years with hourly resolution from 2005 to 2010. We observe that the hybrid prediction method is suitable for a reliable smart grid energy management. Prediction reliability of the proposed hybrid prediction method is carried out in terms of prediction error performance based on statistical and graphical methods. The experimental results show that the proposed hybrid method achieved acceptable prediction accuracy. This potential hybrid model is applicable as a local predictor for any proposed hybrid method in real life application for 6 hours in advance prediction to ensure constant solar power supply in the smart grid operation.