999 resultados para event log


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Demonstrating socially responsible behaviour has become increasingly important for corporations. Using the Psychological Continuum Model (PCM) as its theoretical framework, this paper examines the meditational role of corporate social responsibility (CSR) on the relationship between sport participation motivation, event attachment and purchase intent of a sport event’s sponsors’ products. A questionnaire was distributed to a sample of sport event participants (N=689) to measure sport participation motivation (recreation and charity), attachment to the event, CSR, and purchase intent of sponsors’ products. Results reveal that CSR fully mediates the link between purchase intent and sport participation motivation and partially mediates the influence of attachment on purchase intent. The authors propose that corporations strategically align with sport events in which participants are attached to allow for CSR and the meaning elicited by the event to work jointly.

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The research presented in this thesis addresses inherent problems in signaturebased intrusion detection systems (IDSs) operating in heterogeneous environments. The research proposes a solution to address the difficulties associated with multistep attack scenario specification and detection for such environments. The research has focused on two distinct problems: the representation of events derived from heterogeneous sources and multi-step attack specification and detection. The first part of the research investigates the application of an event abstraction model to event logs collected from a heterogeneous environment. The event abstraction model comprises a hierarchy of events derived from different log sources such as system audit data, application logs, captured network traffic, and intrusion detection system alerts. Unlike existing event abstraction models where low-level information may be discarded during the abstraction process, the event abstraction model presented in this work preserves all low-level information as well as providing high-level information in the form of abstract events. The event abstraction model presented in this work was designed independently of any particular IDS and thus may be used by any IDS, intrusion forensic tools, or monitoring tools. The second part of the research investigates the use of unification for multi-step attack scenario specification and detection. Multi-step attack scenarios are hard to specify and detect as they often involve the correlation of events from multiple sources which may be affected by time uncertainty. The unification algorithm provides a simple and straightforward scenario matching mechanism by using variable instantiation where variables represent events as defined in the event abstraction model. The third part of the research looks into the solution to address time uncertainty. Clock synchronisation is crucial for detecting multi-step attack scenarios which involve logs from multiple hosts. Issues involving time uncertainty have been largely neglected by intrusion detection research. The system presented in this research introduces two techniques for addressing time uncertainty issues: clock skew compensation and clock drift modelling using linear regression. An off-line IDS prototype for detecting multi-step attacks has been implemented. The prototype comprises two modules: implementation of the abstract event system architecture (AESA) and of the scenario detection module. The scenario detection module implements our signature language developed based on the Python programming language syntax and the unification-based scenario detection engine. The prototype has been evaluated using a publicly available dataset of real attack traffic and event logs and a synthetic dataset. The distinct features of the public dataset are the fact that it contains multi-step attacks which involve multiple hosts with clock skew and clock drift. These features allow us to demonstrate the application and the advantages of the contributions of this research. All instances of multi-step attacks in the dataset have been correctly identified even though there exists a significant clock skew and drift in the dataset. Future work identified by this research would be to develop a refined unification algorithm suitable for processing streams of events to enable an on-line detection. In terms of time uncertainty, identified future work would be to develop mechanisms which allows automatic clock skew and clock drift identification and correction. The immediate application of the research presented in this thesis is the framework of an off-line IDS which processes events from heterogeneous sources using abstraction and which can detect multi-step attack scenarios which may involve time uncertainty.

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There is consensus among community and road safety agencies that driver fatigue is a major road safety issue and it is well known that excessive fatigue is linked with an increased risk of a motor vehicle crash. Previous research has implicated a wide variety of factors involved in fatigue-related crashes and the effects of these various factors in regard to crash risk can be interpreted as causal (i.e. alcohol and/or drugs may induce fatigue states) or additive (e.g. where a lack of sleep is combined with alcohol). As such, the purpose of this investigation was to examine self-report data to determine whether there are any differences in the prevalence, crash characteristics, and travel patterns of males and females involved in a fatigue-related crash or close call event. Such research is important to understand how fatigue related incidents occur within the typical driving patterns of men and women and it provides a starting point in order to explore if males and females experience and understand the risk of diving when tired in the same way. A representative sample of (N = 1,600) residents living in the Australian Capital Territory (ACT) and New South Wales (NSW), Australia, were surveyed regarding their experience of fatigue and their involvement in fatigue-related crashes and close call incidents. Results revealed that over 35% of participants reported having had a close call or crash due to driving when tired in the five years prior to the study being conducted. In addition, the results obtained revealed a number of interesting characteristics that provide preliminary evidence that gender differences do exist when examining the prevalence, crash characteristics, and travel patterns of males and females involved in a fatigue-related crash or close call event. It is argued that the results obtained can provide particularly useful information for the refinement and further development of appropriate countermeasures that better target this complex issue.

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In this paper, we use time series analysis to evaluate predictive scenarios using search engine transactional logs. Our goal is to develop models for the analysis of searchers’ behaviors over time and investigate if time series analysis is a valid method for predicting relationships between searcher actions. Time series analysis is a method often used to understand the underlying characteristics of temporal data in order to make forecasts. In this study, we used a Web search engine transactional log and time series analysis to investigate users’ actions. We conducted our analysis in two phases. In the initial phase, we employed a basic analysis and found that 10% of searchers clicked on sponsored links. However, from 22:00 to 24:00, searchers almost exclusively clicked on the organic links, with almost no clicks on sponsored links. In the second and more extensive phase, we used a one-step prediction time series analysis method along with a transfer function method. The period rarely affects navigational and transactional queries, while rates for transactional queries vary during different periods. Our results show that the average length of a searcher session is approximately 2.9 interactions and that this average is consistent across time periods. Most importantly, our findings shows that searchers who submit the shortest queries (i.e., in number of terms) click on highest ranked results. We discuss implications, including predictive value, and future research.

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Previous studies have reported that patients with schizophrenia demonstrate impaired performance during working memory (WM) tasks. The current study aimed to determine whether WM impairments in schizophrenia are accompanied by reduced slow wave (SW) activity during on-line maintenance of mnemonic information. Event-related potentials were obtained from patients with schizophrenia and well controls as they performed a visuospatial delayed response task. On 50% of trials, a distractor stimulus was introduced during the delay. Compared with controls, patients with schizophrenia produced less SW memory negativity, particularly over the right hemisphere, together with reduced frontal enhancement of SW memory negativity in response to distraction. The results indicate that patients with schizophrenia generate less maintenance phase neuronal activity during WM performance, especially under conditions of distraction.

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With the increasing growth of cultural events both in Australia and internationally, there has also been an increase in event management studies; in theory and in practice. Although a series of related knowledge and skills required specifically by event managers has already been identified by many researchers (Perry et al., 1996; Getz, 2002 & Silvers et al., 2006) and generic event management models proposed, including ‘project management’ strategies in an event context (Getz, 2007), knowledge gaps still exist in relation to identifying specific types of events, especially for not-for-profit arts events. For events of a largely voluntary nature, insufficient resources are recognised as the most challenging; including finance, human resources and infrastructure. Therefore, the concepts and principles which are adopted by large scale commercial events may not be suitable for not-for-profit arts events aiming at providing professional network opportunities for artists. Building partnerships are identified as a key strategy in developing an effective event management model for this type of event. Using the 2008 World Dance Alliance Global Summit (WDAGS) in Brisbane 13-18 July, as a case study, the level, nature and relationship of key partners are investigated. Data is triangulated from interviews with organisers of the 2008 WDAGS, on-line and email surveys of delegates, participant observation and analysis of formal and informal documents, to produce a management model suited to this kind of event.

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Research has lead to a proliferation of multi-attribute scales to understand the motives for sport event attendance. The large number of potential motives, coupled with the long questionnaires needed to measure them, creates challenges for sport marketing research in natural populations. This research brings parsimony to the study of sport consumer behaviour by developing and testing a core set of five SportWay facets of motivation. Results provide guidance to sport marketing professionals and academics in survey development decisions related to selecting the most appropriate motives and items.