948 resultados para management tools


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Early water resources modeling efforts were aimed mostly at representing hydrologic processes, but the need for interdisciplinary studies has led to increasing complexity and integration of environmental, social, and economic functions. The gradual shift from merely employing engineering-based simulation models to applying more holistic frameworks is an indicator of promising changes in the traditional paradigm for the application of water resources models, supporting more sustainable management decisions. This dissertation contributes to application of a quantitative-qualitative framework for sustainable water resources management using system dynamics simulation, as well as environmental systems analysis techniques to provide insights for water quality management in the Great Lakes basin. The traditional linear thinking paradigm lacks the mental and organizational framework for sustainable development trajectories, and may lead to quick-fix solutions that fail to address key drivers of water resources problems. To facilitate holistic analysis of water resources systems, systems thinking seeks to understand interactions among the subsystems. System dynamics provides a suitable framework for operationalizing systems thinking and its application to water resources problems by offering useful qualitative tools such as causal loop diagrams (CLD), stock-and-flow diagrams (SFD), and system archetypes. The approach provides a high-level quantitative-qualitative modeling framework for "big-picture" understanding of water resources systems, stakeholder participation, policy analysis, and strategic decision making. While quantitative modeling using extensive computer simulations and optimization is still very important and needed for policy screening, qualitative system dynamics models can improve understanding of general trends and the root causes of problems, and thus promote sustainable water resources decision making. Within the system dynamics framework, a growth and underinvestment (G&U) system archetype governing Lake Allegan's eutrophication problem was hypothesized to explain the system's problematic behavior and identify policy leverage points for mitigation. A system dynamics simulation model was developed to characterize the lake's recovery from its hypereutrophic state and assess a number of proposed total maximum daily load (TMDL) reduction policies, including phosphorus load reductions from point sources (PS) and non-point sources (NPS). It was shown that, for a TMDL plan to be effective, it should be considered a component of a continuous sustainability process, which considers the functionality of dynamic feedback relationships between socio-economic growth, land use change, and environmental conditions. Furthermore, a high-level simulation-optimization framework was developed to guide watershed scale BMP implementation in the Kalamazoo watershed. Agricultural BMPs should be given priority in the watershed in order to facilitate cost-efficient attainment of the Lake Allegan's TP concentration target. However, without adequate support policies, agricultural BMP implementation may adversely affect the agricultural producers. Results from a case study of the Maumee River basin show that coordinated BMP implementation across upstream and downstream watersheds can significantly improve cost efficiency of TP load abatement.

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A knowledge management tool developed by the GIS Center for to support project reporting tools, project publications, and a project data portal for materials related to the WAWASH Program.

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The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity. We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.

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This paper summarizes the literature on hedge funds (HFs) developed over the last two decades, particularly that which relates to risk management characteristics (a companion piece investigates the managerial characteristics of HFs). It discusses the successes and the shortfalls to date in developing more sophisticated risk management frameworks and tools to measure and monitor HF risks, and the empirical evidence on the role of the HFs and their investment behaviour and risk management practices on the stability of the financial system. It also classifies the HF literature considering the most recent contributions and, particularly, the regulatory developments after the 2007 financial crisis.

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The goal of FOCUS, which stands for Frailty Management Optimization through EIPAHA Commitments and Utilization of Stakeholders’ Input, is to reduce the burden of frailty in Europe. The partners are working on advancing knowledge of frailty detection, assessment, and management, including biological, clinical, cognitive and psychosocial markers, in order to change the paradigm of frailty care from acute intervention to prevention. FOCUS partners are working on ways to integrate the best available evidence from frailty-related screening tools, epidemiological and interventional studies into the care of frail people and their quality of life. Frail citizens in Italy, Poland and the UK and their caregivers are being called to express their views and their experiences with treatments and interventions aimed at improving quality of life. The FOCUS Consortium is developing pathways to leverage the knowledge available and to put it in the service of frail citizens. In order to reach out to the broadest audience possible, the FOCUS Platform for Knowledge Exchange and the platform for Scaling Up are being developed with the collaboration of stakeholders. The FOCUS project is a development of the work being done by the European Innovation Partnership on Active and Healthy Ageing (EIPAHA), which aims to increase the average healthy lifespan in Europe by 2020 while fostering sustainability of health/social care systems and innovation in Europe. The knowledge and tools developed by the FOCUS project, with input from stakeholders, will be deployed to all EIPAHA participants dealing with frail older citizens to support activities and optimize performance.

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Softeam has over 20 years of experience providing UML-based modelling solutions, such as its Modelio modelling tool, and its Constellation enterprise model management and collaboration environment. Due to the increasing number and size of the models used by Softeam’s clients, Softeam joined the MONDO FP7 EU research project, which worked on solutions for these scalability challenges and produced the Hawk model indexer among other results. This paper presents the technical details and several case studies on the integration of Hawk into Softeam’s toolset. The first case study measured the performance of Hawk’s Modelio support using varying amounts of memory for the Neo4j backend. In another case study, Hawk was integrated into Constellation to provide scalable global querying of model repositories. Finally, the combination of Hawk and the Epsilon Generation Language was compared against Modelio for document generation: for the largest model, Hawk was two orders of magnitude faster.

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This thesis presents a cloud-based software platform for sharing publicly available scientific datasets. The proposed platform leverages the potential of NoSQL databases and asynchronous IO technologies, such as Node.JS, in order to achieve high performances and flexible solutions. This solution will serve two main groups of users. The dataset providers, which are the researchers responsible for sharing and maintaining datasets, and the dataset users, that are those who desire to access the public data. To the former are given tools to easily publish and maintain large volumes of data, whereas the later are given tools to enable the preview and creation of subsets of the original data through the introduction of filter and aggregation operations. The choice of NoSQL over more traditional RDDMS emerged from and extended benchmark between relational databases (MySQL) and NoSQL (MongoDB) that is also presented in this thesis. The obtained results come to confirm the theoretical guarantees that NoSQL databases are more suitable for the kind of data that our system users will be handling, i. e., non-homogeneous data structures that can grow really fast. It is envisioned that a platform like this can lead the way to a new era of scientific data sharing where researchers are able to easily share and access all kinds of datasets, and even in more advanced scenarios be presented with recommended datasets and already existing research results on top of those recommendations.

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This document presents an Enterprise Application Integration based proposal for research outcomes and technological information management. The proposal addresses national and international science and research outcomes information management, and corresponding information systems. Information systems interoperability problems, approaches, technologies and integration tools are presented and applied to the research outcomes information management case. A business and technological perspective is provided, including the conceptual analysis and modelling, an integration solution based in a Domain-Specific Language (DSL) and the integration platform to execute the proposed solution. For illustrative purposes, the role and information system needs of a research unit is assumed as the representative case.

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Demands for mechanisms to pay for adaptation to climate risks have multiplied rapidly as concern has shifted from greenhouse gas mitigation alone to also coping with the now-inevitable impacts. A number of viable approaches to how to pay for those adjustments to roads, drainage systems, lifeline utilities and other basic infrastructure are emerging, though untested at the scale required across the nation, which already has a trillion-dollar deferred maintenance and replacement problem. There are growing efforts to find new ways to harness private financial resources via new market arrangements to meet needs that clearly outstrip public resources alone, as well as to utilize and combine public resources more effectively. To date, mechanisms are often seen through a specific lens of scale, time, and method, for example national versus local and public versus market-based means. The purpose here is to integrate a number of those perspectives and also to highlight the following in particular. Current experience with seemingly more pedestrian needs like stormwater management funding is in fact a learning step towards new approaches for broader adaptation needs, using re-purposed but existing fiscal tools. The resources raised from new large-scale market approaches for using catastrophe- and resiliency-bond-derived funds will have their use embodied and operationalized in many separate local and state projects. The invention and packaging of innovative projects—the pre-development phase—will be pivotal to better using fiscal resources of many types. Those efforts can be greatly aided or hindered by larger national and especially state government policy, regulatory and capital market arrangements. Understanding the path to integration of effort across these scales deserves much more attention. Examples are given of how federal, state and local roles are each dimensions of that frontier, how existing tools can apply in new ways and how smart project creation plays a role.

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This thesis presents a cloud-based software platform for sharing publicly available scientific datasets. The proposed platform leverages the potential of NoSQL databases and asynchronous IO technologies, such as Node.JS, in order to achieve high performances and flexible solutions. This solution will serve two main groups of users. The dataset providers, which are the researchers responsible for sharing and maintaining datasets, and the dataset users, that are those who desire to access the public data. To the former are given tools to easily publish and maintain large volumes of data, whereas the later are given tools to enable the preview and creation of subsets of the original data through the introduction of filter and aggregation operations. The choice of NoSQL over more traditional RDDMS emerged from and extended benchmark between relational databases (MySQL) and NoSQL (MongoDB) that is also presented in this thesis. The obtained results come to confirm the theoretical guarantees that NoSQL databases are more suitable for the kind of data that our system users will be handling, i. e., non-homogeneous data structures that can grow really fast. It is envisioned that a platform like this can lead the way to a new era of scientific data sharing where researchers are able to easily share and access all kinds of datasets, and even in more advanced scenarios be presented with recommended datasets and already existing research results on top of those recommendations.

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Quality management provides to companies a framework to improve quality in overall systems, reduction of costs, reallocation of resources efficiently, correct planning of strategies, prevent or correct errors in the right time and increase the performance of companies. In this text, we discuss the different theories in this field, their obligatory or non-obligatory compliance, the importance of quality management for exporting companies and a case study of a Colombian firm that its main objective is to manage quality. In conclusion, we find out that there is different types of quality management systems such as Juran’s trilogy, Deming 14 points, Six sigma, HACCP, and so on; also that companies have to manage suppliers and that quality has a positive influence on exports volume; in the case of Colombian small and medium enterprises, it can be mentioned that the majority has implemented tools regarding quality management but is not enough.

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The present study deals with the development of systematic conservation planning as management instrument in small oceanic islands, ensuring open systems of governance, and able to integrate an informed and involved participation of the stakeholders. Marxan software was used to define management areas according a set of alternative land use scenarios considering different conservation and management paradigms. Modeled conservation zones were interpreted and compared with the existing protected areas allowing more fused information for future trade-outs and stakeholder's involvement. The results, allowing the identification of Target Management Units (TMU) based on the consideration of different development scenarios proved to be consistent with a feasible development of evaluation approaches able to support sound governance systems. Moreover, the detailed geographic identification of TMU seems to be able to support participated policies towards a more sustainable management of the entire island

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The purpose of the air traffic management system is to ensure the safe and efficient flow of air traffic. Therefore, while augmenting efficiency, throughput and capacity in airport operations, attention has rightly been placed on doing it in a safe manner. In the control tower, many advances in operational safety have come in the form of visualization tools for tower controllers. However, there is a paradox in developing such systems to increase controllers' situational awareness: by creating additional computer displays, the controller's vision is pulled away from the outside view and the time spent looking down at the monitors is increased. This reduces their situational awareness by forcing them to mentally and physically switch between the head-down equipment and the outside view. This research is based on the idea that augmented reality may be able to address this issue. The augmented reality concept has become increasingly popular over the past decade and is being proficiently used in many fields, such as entertainment, cultural heritage, aviation, military & defense. This know-how could be transferred to air traffic control with a relatively low effort and substantial benefits for controllers’ situation awareness. Research on this topic is consistent with SESAR objectives of increasing air traffic controllers’ situation awareness and enable up to 10 % of additional flights at congested airports while still increasing safety and efficiency. During the Ph.D., a research framework for prototyping augmented reality tools was set up. This framework consists of methodological tools for designing the augmented reality overlays, as well as of hardware and software equipment to test them. Several overlays have been designed and implemented in a simulated tower environment, which is a virtual reconstruction of Bologna airport control tower. The positive impact of such tools was preliminary assessed by means of the proposed methodology.

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School websites are not only sources of information and documentation, but also means of communication that are increasingly being accessed by members of society, especially by the different educational communities, thanks to the democratisation of Internet access. This paper deals with a qualitative research project in which information and communication technology coordinators of infant and primary publicly funded private schools (concertados) and state schools in urban, rural and semi-urban/rural areas within the Region of Cantabria (Spain) were interviewed in order to understand how school websites are managed. The findings show a range of views and practices in the schools’ management of their websites, some positive developments in their uses and functions, and numerous opportunities for improvement. School websites are essential communication tools, which need to be continuously improved/updated by their managers, with the support of the education authorities.

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From its domestication until nowadays, the horse has assumed multiple roles in human society. Over time, this condition and the lack of specific regulation have led to the development of different kinds of management systems for this species. This Ph.D. research project aims to investigate horses' welfare in different management practices and housing systems, considering a multidisciplinary approach, taking into account biological function, naturalness, and affective dimension. The results are presented in five articles that evidence risk factors that can mine horse welfare, and examine tools and parameters that can be employed for its assessment. Our research shows the importance of considering the evolutionary history and the species-specific and behavioural needs of horses in their management and housing. Sociality, free movement, diet composition and foraging routine, and the workload that these animals undergo are important factors that should be taken into account. Furthermore, this research has evidenced the importance of employing different parameters (e.g., behaviour, endocrinological parameters, and immune activity) in welfare assessment and proposes the use of horsehair DHEA (dehydroepiandrosterone) as a possible useful additional non-invasive measure for the investigation of long-term stress conditions. Finally, our results underline the importance of considering the affective dimension in welfare research. Recently, Judgement Bias Tests (JBT), which are based on the influence of affective states on the decision-making process, have been widely employed in animal welfare research. However, our studies show that the use of spatial JBT in horses can have some limitations. Still today several management systems do not fulfill species-specific needs of horses, thus the implementation of specific regulations could ameliorate horse welfare. A multidisciplinary approach to welfare assessment is fundamental, but it should be always remembered the individual and its own characteristics, which can influence not only physiological, immunological, and behavioural responses but also emotional and cognitive dimensions.