928 resultados para service level management
Resumo:
Modern IT infrastructures are constructed by large scale computing systems and administered by IT service providers. Manually maintaining such large computing systems is costly and inefficient. Service providers often seek automatic or semi-automatic methodologies of detecting and resolving system issues to improve their service quality and efficiency. This dissertation investigates several data-driven approaches for assisting service providers in achieving this goal. The detailed problems studied by these approaches can be categorized into the three aspects in the service workflow: 1) preprocessing raw textual system logs to structural events; 2) refining monitoring configurations for eliminating false positives and false negatives; 3) improving the efficiency of system diagnosis on detected alerts. Solving these problems usually requires a huge amount of domain knowledge about the particular computing systems. The approaches investigated by this dissertation are developed based on event mining algorithms, which are able to automatically derive part of that knowledge from the historical system logs, events and tickets. ^ In particular, two textual clustering algorithms are developed for converting raw textual logs into system events. For refining the monitoring configuration, a rule based alert prediction algorithm is proposed for eliminating false alerts (false positives) without losing any real alert and a textual classification method is applied to identify the missing alerts (false negatives) from manual incident tickets. For system diagnosis, this dissertation presents an efficient algorithm for discovering the temporal dependencies between system events with corresponding time lags, which can help the administrators to determine the redundancies of deployed monitoring situations and dependencies of system components. To improve the efficiency of incident ticket resolving, several KNN-based algorithms that recommend relevant historical tickets with resolutions for incoming tickets are investigated. Finally, this dissertation offers a novel algorithm for searching similar textual event segments over large system logs that assists administrators to locate similar system behaviors in the logs. Extensive empirical evaluation on system logs, events and tickets from real IT infrastructures demonstrates the effectiveness and efficiency of the proposed approaches.^
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Background: The management of childhood obesity is challenging. Aims: Thesis, i) reviews the evidence for lifestyle treatment of obesity, ii) explores cardiometabolic burden in childhood obesity, iii) explores whether changes in body composition predicts change in insulin sensitivity (IS), iv) develops and evaluates a lifestyle obesity intervention; v) develops a mobile health application for obesity treatment and vi) tests the application in a clinical trial. Methods: In Study 1, systematic reviews and meta-analyses of the 12‐month effects of lifestyle and mHealth interventions were conducted. In Study 2, the prevalence of cardiometabolic burden was estimated in a consecutive series of 267 children. In Study 3, body composition was estimated with bioelectrical impedance analysis (BIA) and dual x-ray absorptiometry (DXA) and linear regression analyses were used to estimate the extent to which each methods predicted change in IS. Study 4 describes the development of the Temple Street W82GO Healthy Lifestyle intervention for clinical obesity in children and a controlled study of treatment effect in 276 children is reported. Study 5 describes the development and testing of the Reactivate Mobile Obesity Application. Study 6 outlines the development and preliminary report from a clinical effectiveness trial of Reactivate. Results: In Study 1, meta--‐analyses BMI SDS changed by -0.16 (-0.24,‐0.07, p<0.01) and -0.03 (-0.13, 0.06, p=0.48). In study 2, cardiometabolic comorbidities were common (e.g. hypertension in 49%) and prevalence increased as obesity level increased. In Study 3, BC changes significantly predicted changes in IS. In Study 4, BMI SDS was significantly reduced in W82GO compared to controls (p<0.001). In Study 5, the Reactivate application had good usability indices and preliminary 6‐month process report data from Study 6, revealed a promising effect for Reactivate. Conclusions: W82GO and Reactivate are promising forms of treatment.
Resumo:
Coastal zones with their natural and societal subsystems are exposed to rapid changes and pressures on resources. Scarcity of space and impacts of climate change are prominent drivers of land use and adaptation management today. Necessary modifications to present land use management strategies and schemes influence both the structures of coastal communities and the ecosystems involved. Approaches to identify the impacts and account for (i) the linkages between social references and needs and (ii) ecosystem services in coastal zones have been largely absent. The presented method focuses on improving the inclusion of ecosystem services in planning processes and clarifies the linkages with social impacts. In this study, fourteen stakeholders in decisionmaking on land use planning in the region of Krummhörn (northwestern Germany, southern North Sea coastal region) conducted a regional participative and informal process for local planning capable to adapt to climate driven changes. It is argued that scientific and practical implications of this integrated assessment focus on multifunctional options and contribute to more sustainable practices in future land use planning. The method operationalizes the ecosystem service approach and social impact analysis and demonstrates that social demands and provision of ecosystem services are inherently connected.
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Recent debate on the quality of arts events has concentrated on the requirement to deliver against a complex range of political, social, and cultural criteria with an emphasis on the external partnerships that are forged. Yet those aspects of quality over which event organizers have more direct control have been accorded minor examination. The authors believe that operational effectiveness is key to service quality in the cultural context, and seek to demonstrate that a balanced consideration of both process and product is vital to fully deliver quality arts events. This article identifies areas of emergent research and practice and focuses on issues in the front-of-house environment where the breakdown of service quality is a real concern, using the experience of one UK not-for-profit arts organization as a case study to illustrate potential management responses.
Resumo:
BACKGROUND: Persistently elevated natriuretic peptide (NP) levels in heart failure (HF) patients are associated with impaired prognosis. Recent work suggests that NP-guided therapy can improve outcome, but the mechanisms behind an elevated BNP remain unclear. Among the potential stimuli for NP in clinically stable patients are persistent occult fluid overload, wall stress, inflammation, fibrosis, and ischemia. The purpose of this study was to identify associates of B-type natriuretic peptide (BNP) in a stable HF population.
METHODS: In a prospective observational study of 179 stable HF patients, the association between BNP and markers of collagen metabolism, inflammation, and Doppler-echocardiographic parameters including left ventricular ejection fraction (LVEF), left atrial volume index (LAVI), and E/e prime (E/e') was measured.
RESULTS: Univariable associates of elevated BNP were age, LVEF, LAVI, E/e', creatinine, and markers of collagen turnover. In a multiple linear regression model, age, creatinine, and LVEF remained significant associates of BNP. E/e' and markers of collagen turnover had a persistent impact on BNP independent of these covariates.
CONCLUSION: Multiple variables are associated with persistently elevated BNP levels in stable HF patients. Clarification of the relative importance of NP stimuli may help refine NP-guided therapy, potentially improving outcome for this at-risk population.
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Background: Concerns exist about the end of life care
that people with intellectual disabilities receive. This population
are seldom referred to palliative care services and
inadequate data sets exist about their place of death.
Aim: To scope the extent of service provision to people
with intellectual disabilities at the end of life by specialist
palliative care and intellectual disability services in one
region of the United Kingdom.
Methods: As part of a larger doctoral study a regional survey
took place of a total sample (n=66) of specialist palliative
care and intellectual disability services using a postal
questionnaire containing forty items. The questionnaire
was informed by the literature and consultation with an
expert reference group. Data were analysed using SPSS to
obtain descriptive statistics.
Results: A total response rate from services of 71.2%
(n=47) was generated. Findings showed a range of experience
among services in providing end of life care to people
with intellectual disabilities in the previous five years, but
general hospitals were reported the most common place of
death. A lack of accessible information on end of life care
for people with learning disabilities was apparent. A few
services (n=14) had a policy to support this population to
make decisions about their care or had used adapted Breaking
Bad News guidelines (n=5) to meet their additional
needs. Both services recognised the value of partnership
working in assessing and meeting the holistic needs of
people with intellectual disabilities at end of life.
Conclusions: A range of experience in caring for people
with intellectual disabilities was present across services,
but more emphasis is required on adapting communication
for this population to facilitate them to participate in their
care. These findings could have international significance
given that studies in other countries have highlighted a
need to widen access to palliative care for this group of
people.
Resumo:
The level of demand for healthcare services can fluctuate widely and this can place pressure on the capacity of service providers. This article examines some of the approaches used to influence the level of available capacity in the healthcare services sector. A number of strategies designed to flex capacity are discussed, including the development of flexible approaches to human resources; rapid responses to changes in demand; the use of self-service technology and self-care; and the use of temporary additional facilities.
Resumo:
This paper describes an audit of prevention and management of violence and aggression care plans and incident reporting forms which aimed to: (i) report the compliance rate of completion of care plans; (ii) identify the extent to which patients contribute to and agree with their care plan; (iii) describe de-escalation methods documented in care plans; and (iv) ascertain the extent to which the de-escalation methods described in the care plan are recorded as having been attempted in the event of an incident. Care plans and incident report forms were examined for all patients in men's and women's mental health care pathways who were involved in aggressive incidents between May and October 2012. In total, 539 incidents were examined, involving 147 patients and 121 care plans. There was no care plan in place at the time of 151 incidents giving a compliance rate of 72%. It was documented that 40% of patients had contributed to their care plans. Thematic analysis of de-escalation methods documented in the care plans revealed five de-escalation themes: staff interventions, interactions, space/quiet, activities and patient strategies/skills. A sixth category, coercive strategies, was also documented. Evidence of adherence to de-escalation elements of the care plan was documented in 58% of incidents. The reasons for the low compliance rate and very low documentation of patient involvement need further investigation. The inclusion of coercive strategies within de-escalation documentation suggests that some staff fundamentally misunderstand de-escalation.
Resumo:
In today’s big data world, data is being produced in massive volumes, at great velocity and from a variety of different sources such as mobile devices, sensors, a plethora of small devices hooked to the internet (Internet of Things), social networks, communication networks and many others. Interactive querying and large-scale analytics are being increasingly used to derive value out of this big data. A large portion of this data is being stored and processed in the Cloud due the several advantages provided by the Cloud such as scalability, elasticity, availability, low cost of ownership and the overall economies of scale. There is thus, a growing need for large-scale cloud-based data management systems that can support real-time ingest, storage and processing of large volumes of heterogeneous data. However, in the pay-as-you-go Cloud environment, the cost of analytics can grow linearly with the time and resources required. Reducing the cost of data analytics in the Cloud thus remains a primary challenge. In my dissertation research, I have focused on building efficient and cost-effective cloud-based data management systems for different application domains that are predominant in cloud computing environments. In the first part of my dissertation, I address the problem of reducing the cost of transactional workloads on relational databases to support database-as-a-service in the Cloud. The primary challenges in supporting such workloads include choosing how to partition the data across a large number of machines, minimizing the number of distributed transactions, providing high data availability, and tolerating failures gracefully. I have designed, built and evaluated SWORD, an end-to-end scalable online transaction processing system, that utilizes workload-aware data placement and replication to minimize the number of distributed transactions that incorporates a suite of novel techniques to significantly reduce the overheads incurred both during the initial placement of data, and during query execution at runtime. In the second part of my dissertation, I focus on sampling-based progressive analytics as a means to reduce the cost of data analytics in the relational domain. Sampling has been traditionally used by data scientists to get progressive answers to complex analytical tasks over large volumes of data. Typically, this involves manually extracting samples of increasing data size (progressive samples) for exploratory querying. This provides the data scientists with user control, repeatable semantics, and result provenance. However, such solutions result in tedious workflows that preclude the reuse of work across samples. On the other hand, existing approximate query processing systems report early results, but do not offer the above benefits for complex ad-hoc queries. I propose a new progressive data-parallel computation framework, NOW!, that provides support for progressive analytics over big data. In particular, NOW! enables progressive relational (SQL) query support in the Cloud using unique progress semantics that allow efficient and deterministic query processing over samples providing meaningful early results and provenance to data scientists. NOW! enables the provision of early results using significantly fewer resources thereby enabling a substantial reduction in the cost incurred during such analytics. Finally, I propose NSCALE, a system for efficient and cost-effective complex analytics on large-scale graph-structured data in the Cloud. The system is based on the key observation that a wide range of complex analysis tasks over graph data require processing and reasoning about a large number of multi-hop neighborhoods or subgraphs in the graph; examples include ego network analysis, motif counting in biological networks, finding social circles in social networks, personalized recommendations, link prediction, etc. These tasks are not well served by existing vertex-centric graph processing frameworks whose computation and execution models limit the user program to directly access the state of a single vertex, resulting in high execution overheads. Further, the lack of support for extracting the relevant portions of the graph that are of interest to an analysis task and loading it onto distributed memory leads to poor scalability. NSCALE allows users to write programs at the level of neighborhoods or subgraphs rather than at the level of vertices, and to declaratively specify the subgraphs of interest. It enables the efficient distributed execution of these neighborhood-centric complex analysis tasks over largescale graphs, while minimizing resource consumption and communication cost, thereby substantially reducing the overall cost of graph data analytics in the Cloud. The results of our extensive experimental evaluation of these prototypes with several real-world data sets and applications validate the effectiveness of our techniques which provide orders-of-magnitude reductions in the overheads of distributed data querying and analysis in the Cloud.
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In order to address the increasing stakeholder requirements for environmentally sustainable products and processes, firms often need the participation of their supply chain partners. Green supply chain management has emerged as a set of managerial practices that integrate environmental issues into supply chain management. If implemented successfully, green supply chain management can be a way to achieve competitive advantage while enhancing the environmental sustainability of the firm. The overall purpose of this dissertation is to contribute to the discussion on green supply chain management practices from the perspective of their drivers and performance implications. The theoretical background arises from the literature on competitive strategy, firm performance and green supply chain management. The research questions are addressed by analysing firm-level data from manufacturing, trading and logistics firms operating in Finland. The empirical data comes from two consecutive Finland State of Logistics surveys in 2012 and 2014, combined with financial reporting data from external databases. The data is analysed with multiple statistical methods. First, the thesis contributes to the discussion of the drivers of GSCM practices. To enhance the understanding of the relationship between competitive strategy and GSCM practices, a conceptual tool to describe generic competitive strategy approaches was developed. The findings suggest that firms pursuing marketing differentiation are more likely to be able to compete by having only small environmental effects and by adopting a more advanced form of external green supply chain management, such as a combination of strong environmental collaboration and the increased environmental monitoring of suppliers. Furthermore, customer requirements for environmental sustainability are found to be an important driver in the implementation of internal GSCM practices. Firms can respond to this customer pressure by passing environmental requirements on to their suppliers, either through environmental collaboration or environmental monitoring. Second, this thesis adds value to the existing literature on the effects of green supply chain management practices on firm performance. The thesis provides support for the idea that there is a positive relationship between GSCM practices and firm performance and enhances the understanding of how different types of GSCM practices are related to 1) financial, 2) operational and 3) environmental performance in manufacturing and logistics. The empirical results suggest that while internal GSCM practices have the strongest effect on environmentalperformance, environmental collaboration with customers seems to be the most effective way to improve financial performance. In terms of operational performance, the findings were more mixed, suggesting that the operational performance of firms is more likely to be affected by firm characteristics than by the choices they make regarding their environmental collaboration. This thesis is also one of the first attempts to empirically analyse the relationship between GSCM practices and performance among logistics service providers. The findings also have managerial relevance. Management, especially in manufacturing and logistics industries, may benefit by gaining knowledge about which types of GSCM practice could provide the largest benefits in terms of different performance dimensions. This thesis also has implications for policy-makers and regulators regarding how to promote environmentally friendly activities among 1) manufacturing; 2) trading; and 3) logistics firms.
Resumo:
Public participation in health-service management is an increasingly prominent policy internationally. Frequently, though, academic studies have found it marginalized by health professionals who, keen to retain control over decision-making, undermine the legitimacy of involved members of the public, in particular by questioning their representativeness. This paper examines this negotiation of representative legitimacy between staff and involved users by drawing on a qualitative study of service-user involvement in pilot cancer-genetics services recently introduced in England, using interviews, participant observation and documentary analysis. In contrast to the findings of much of the literature, health professionals identified some degree of representative legitimacy in the contributions made by users. However, the ways in which staff and users constructed representativeness diverged significantly. Where staff valued the identities of users as biomedical and lay subjects, users themselves described the legitimacy of their contribution in more expansive terms of knowledge and citizenship. My analysis seeks to show how disputes over representativeness relate not just to a struggle for power according to contrasting group interests, but also to a substantive divergence in understanding of the nature of representativeness in the context of state-orchestrated efforts to increase public participation. This divergence might suggest problems with the enactment of such aspirations in practice; alternatively, however, contestation of representative legitimacy might be understood as reflecting ambiguities in policy-level objectives for participation, which secure implementation by accommodating the divergent constructions of those charged with putting initiatives into practice.
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Part 21: Mobility and Logistics
Resumo:
Studies of strategic HRM have dominated HRM research over the last three decades. Focusing on the HRM-organisation performance relationship, researchers take various themes and perspectives in their approach to strategic HRM. Among these themes, two contrasting approaches of strategic HRM continue to flourish: first, the best practice approach suggests that certain HRM practices will have the same effect irrespective of context and, second, the best fit approach suggests that the choice of HRM practices should be designed in accordance with an organisations’ specific context. While there is little consensus on what constitutes strategic HRM, the most common feature agreed in this field is the notion of the strategic integration; aligning HRM practices with organisations’ overall strategic objectives (vertical fit) and with each other (horizontal fit). Utilising the best fit approach as its theoretical framework, this study examines how vertical and horizontal fit is practised in the Indonesian civil service and what factors likely influence the prevalence of vertical and horizontal fit in the Indonesian civil service context. This study is significant for two important reasons. Firstly, the literature suggests that there are limited studies examining the best fit concept in the civil sector despite its implementation in the private sector positively contributing to organisational performance improvement. Secondly, the study provides enlightenment on how the best fit approach could contribute to performance improvement in the Indonesian civil service. This is in line with the fact that negative images of the Indonesian civil service are continuously highlighted although various HRM reform initiatives have been put in place. To achieve the objectives of the study, the qualitative case study approach accompanied by semi-structured interviews was employed involving 53 senior officials and one focus group discussion from eight Indonesian government agencies, consisting of three central agencies mandated to manage human resources, the National Bureaucratic Reform Team and four line agencies from both central and local governments. Thematic analysis was employed for data analyses and NVIVO software was used to manage the data. The study suggests three main findings. First, various HRM initiatives in relation to the HRM reform have been introduced in the Indonesian civil service differentiating them from the old HRM practices. However, the findings indicate that some HRM policies are still contradicting and hinder vertical and horizontal fit. Second, despite the contradictory policies, vertical and horizontal fit can be seen in the line agencies which have been acknowledged as ‘reformed agencies’. This demonstrates that the line agencies play an important role in aligning HRM practices with the line agencies’ goals and objectives and with one another although they are bounded by HRM policies that are unlikely to support the vertical and horizontal fit concept. Third, factors influencing the prevalence of vertical and horizontal fit include knowledge of contemporary HRM in both central agencies and line agencies, commitment from the line agencies’ leaders, devolvement of HRM to the line agencies and the socio-political and economic environments of the Indonesian civil service. The findings of the study raise policy, practical and theoretical implications. In terms of policy implications, the study highlights the importance of fit in HRM policies to support the achievement of the line agencies’ goals. Therefore, when formulating an HRM policy, the central agencies need to ensure that the HRM policy is linked to line agencies’ goals and to other HRM policies. This is to ensure synchronisation among the policies and thus maximising the achievement of the line agencies’ goals. From the practical perspectives, the study highlights important points which can be learned by the central agencies in carrying out their strategic role with regard to the formulation of HRM policies; by the line agencies in maximising the contribution of HRM to the achievement of the goals and objectives of the agencies through the implementation of the best fit concept, and by the leaders of the agencies in providing continuous support to each of the involved parties in the line agencies and involving the HRM department in all agency’s strategic decision-making. In relation to the theoretical implication, it is clear that the best fit approach is not thoroughly applied due to factors discussed previously. However, this does not mean that the best fit concept cannot be implemented. As argued by McCourt & Ramgutty-Wong (2003), instead of adopting the whole concept of best fit, a modulated approach reflecting the best fit concept, such as selecting individual HRM practices and experimenting with devolution, is possible for civil service organisations which still embrace centralised HRM systems. As demonstrated in the findings, some of the line agencies being studied seem to be ready to adopt the best fit approach given that they have knowledge of the best fit concept, strong support from the top leader, less political intervention and less corruption, collusion, and nepotism practices in their HRM practices.