13 resultados para Total quality management in government

em Digital Commons at Florida International University


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This research document is motivated by the need for a systemic, efficient quality improvement methodology at universities. There exists no methodology designed for a total quality management (TQM) program in a university. The main objective of this study is to develop a TQM Methodology that enables a university to efficiently develop an integral total quality improvement (TQM) Plan. ^ Current research focuses on the need of improving the quality of universities, the study of the perceived best quality universities, and the measurement of the quality of universities through rankings. There is no evidence of research on how to plan for an integral quality improvement initiative for the university as a whole, which is the main contribution of this study. ^ This research is built on various reference TQM models and criteria provided by ISO 9000, Baldrige and Six Sigma; and educational accreditation criteria found in ABET and SACS. The TQM methodology is proposed by following a seven-step metamethodology. The proposed methodology guides the user to develop a TQM plan in five sequential phases: initiation, assessment, analysis, preparation and acceptance. Each phase defines for the user its purpose, key activities, input requirements, controls, deliverables, and tools to use. The application of quality concepts in education and higher education is particular; since there are unique factors in education which ought to be considered. These factors shape the quality dimensions in a university and are the main inputs to the methodology. ^ The proposed TQM Methodology is used to guide the user to collect and transform appropriate inputs to a holistic TQM Plan, ready to be implemented by the university. Different input data will lead to a unique TQM plan for the specific university at the time. It may not necessarily transform the university into a world-class institution, but aims to strive for stakeholder-oriented improvements, leading to a better alignment with its mission and total quality advancement. ^ The proposed TQM methodology is validated in three steps. First, it is verified by going through a test activity as part of the meta-methodology. Secondly, the methodology is applied to a case university to develop a TQM plan. Lastly, the methodology and the TQM plan both are verified by an expert group consisting of TQM specialists and university administrators. The proposed TQM methodology is applicable to any university at all levels of advancement, regardless of changes in its long-term vision and short-term needs. It helps to assure the quality of a TQM plan, while making the process more systemic, efficient, and cost effective. This research establishes a framework with a solid foundation for extending the proposed TQM methodology into other industries. ^

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In the early 1980s many hotels in the United States adopted quality assurance as a business strategy. By the late 1980s independent and chain hotels realized that total quality management (TQM) was a more powerful process and they began utilizing many of its components. For over 10 years, hotels have flirted with a variety of tools, processes, and theories to improve service to the guest

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This research presents several components encompassing the scope of the objective of Data Partitioning and Replication Management in Distributed GIS Database. Modern Geographic Information Systems (GIS) databases are often large and complicated. Therefore data partitioning and replication management problems need to be addresses in development of an efficient and scalable solution. ^ Part of the research is to study the patterns of geographical raster data processing and to propose the algorithms to improve availability of such data. These algorithms and approaches are targeting granularity of geographic data objects as well as data partitioning in geographic databases to achieve high data availability and Quality of Service(QoS) considering distributed data delivery and processing. To achieve this goal a dynamic, real-time approach for mosaicking digital images of different temporal and spatial characteristics into tiles is proposed. This dynamic approach reuses digital images upon demand and generates mosaicked tiles only for the required region according to user's requirements such as resolution, temporal range, and target bands to reduce redundancy in storage and to utilize available computing and storage resources more efficiently. ^ Another part of the research pursued methods for efficient acquiring of GIS data from external heterogeneous databases and Web services as well as end-user GIS data delivery enhancements, automation and 3D virtual reality presentation. ^ There are vast numbers of computing, network, and storage resources idling or not fully utilized available on the Internet. Proposed "Crawling Distributed Operating System "(CDOS) approach employs such resources and creates benefits for the hosts that lend their CPU, network, and storage resources to be used in GIS database context. ^ The results of this dissertation demonstrate effective ways to develop a highly scalable GIS database. The approach developed in this dissertation has resulted in creation of TerraFly GIS database that is used by US government, researchers, and general public to facilitate Web access to remotely-sensed imagery and GIS vector information. ^

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Next-generation integrated wireless local area network (WLAN) and 3G cellular networks aim to take advantage of the roaming ability in a cellular network and the high data rate services of a WLAN. To ensure successful implementation of an integrated network, many issues must be carefully addressed, including network architecture design, resource management, quality-of-service (QoS), call admission control (CAC) and mobility management. ^ This dissertation focuses on QoS provisioning, CAC, and the network architecture design in the integration of WLANs and cellular networks. First, a new scheduling algorithm and a call admission control mechanism in IEEE 802.11 WLAN are presented to support multimedia services with QoS provisioning. The proposed scheduling algorithms make use of the idle system time to reduce the average packet loss of realtime (RT) services. The admission control mechanism provides long-term transmission quality for both RT and NRT services by ensuring the packet loss ratio for RT services and the throughput for non-real-time (NRT) services. ^ A joint CAC scheme is proposed to efficiently balance traffic load in the integrated environment. A channel searching and replacement algorithm (CSR) is developed to relieve traffic congestion in the cellular network by using idle channels in the WLAN. The CSR is optimized to minimize the system cost in terms of the blocking probability in the interworking environment. Specifically, it is proved that there exists an optimal admission probability for passive handoffs that minimizes the total system cost. Also, a method of searching the probability is designed based on linear-programming techniques. ^ Finally, a new integration architecture, Hybrid Coupling with Radio Access System (HCRAS), is proposed for lowering the average cost of intersystem communication (IC) and the vertical handoff latency. An analytical model is presented to evaluate the system performance of the HCRAS in terms of the intersystem communication cost function and the handoff cost function. Based on this model, an algorithm is designed to determine the optimal route for each intersystem communication. Additionally, a fast handoff algorithm is developed to reduce the vertical handoff latency.^

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The integration of automation (specifically Global Positioning Systems (GPS)) and Information and Communications Technology (ICT) through the creation of a Total Jobsite Management Tool (TJMT) in construction contractor companies can revolutionize the way contractors do business. The key to this integration is the collection and processing of real-time GPS data that is produced on the jobsite for use in project management applications. This research study established the need for an effective planning and implementation framework to assist construction contractor companies in navigating the terrain of GPS and ICT use. An Implementation Framework was developed using the Action Research approach. The framework consists of three components, as follows: (i) ICT Infrastructure Model, (ii) Organizational Restructuring Model, and (iii) Cost/Benefit Analysis. The conceptual ICT infrastructure model was developed for the purpose of showing decision makers within highway construction companies how to collect, process, and use GPS data for project management applications. The organizational restructuring model was developed to assist companies in the analysis and redesign of business processes, data flows, core job responsibilities, and their organizational structure in order to obtain the maximum benefit at the least cost in implementing GPS as a TJMT. A cost-benefit analysis which identifies and quantifies the cost and benefits (both direct and indirect) was performed in the study to clearly demonstrate the advantages of using GPS as a TJMT. Finally, the study revealed that in order to successfully implement a program to utilize GPS data as a TJMT, it is important for construction companies to understand the various implementation and transitioning issues that arise when implementing this new technology and business strategy. In the study, Factors for Success were identified and ranked to allow a construction company to understand the factors that may contribute to or detract from the prospect for success during implementation. The Implementation Framework developed as a result of this study will serve to guide highway construction companies in the successful integration of GPS and ICT technologies for use as a TJMT.

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This research, conducted in 2006-2008, examines the ways in which various groups involved with the marine resources of Seward, Alaska construct attitudes towards the environment. Participant observation and semi-structured interviews are used to assess how commercial halibut fishers, tour boat operators, local residents and government officials understand the marine environment based on their previous experiences. This study also explores how ideologies relate to the current practices of each group. Two theories orient the analyses: The first, cultural modeling provided a theoretical and methodological framework for pursuing a more comprehensive analysis of resource management. The second, Theory of Reasoned Action (Ajzen and Fishbein 1980), guided the analysis of the ways in which each participant’s ideology towards the marine environment relates to their practice. Aside from contributing to a better understanding of a coastal community’s ideologies and practices, this dissertation sought to better understand the role of ecological ideologies and behaviors in fisheries management. The research illustrates certain domains where ideologies and practices concerning Pacific halibut and the marine environment differ among commercial fishers, government, and management officials, tour boat operators and residents of Seward, AK. These differences offer insights into how future collaborative efforts between government officials, managers and local marine resource users might better incorporate local ideology into management, and provide ecological information to local marine resource users in culturally appropriate ways.

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The service-producing industries have experienced problems in quality in the 1980s because of intense competition. The author discusses how these problems have been compounded in the fast food industry and how quality control can lead to success.

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Now that baby boomers are older and pursuing more career-oriented jobs, managers of the hospitality industry are experiencing the effects of the pre- sent labor crisis; they now know that those vacant hourly jobs are going to be tough to fill with quality personnel. The companies able to attract quality personnel by offering employees what they need and want will be the successful ones in the next decade. The authors explain how the labor crisis is currently affecting the hospitality industry and make suggestions about how firms may survive the "labor crash” of the 1990s with the application of marketing technology to human resource management.

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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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In this paper, a heterogeneous network composed of femtocells deployed within a macrocell network is considered, and a quality-of-service (QoS)-oriented fairness metric which captures important characteristics of tiered network architectures is proposed. Using homogeneous Poisson processes, the sum capacities in such networks are expressed in closed form for co-channel, dedicated channel, and hybrid resource allocation methods. Then a resource splitting strategy that simultaneously considers capacity maximization, fairness constraints, and QoS constraints is proposed. Detailed computer simulations utilizing 3GPP simulation assumptions show that a hybrid allocation strategy with a well-designed resource split ratio enjoys the best cell-edge user performance, with minimal degradation in the sum throughput of macrocell users when compared with that of co-channel operation.

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South Florida continues to become increasingly developed and urbanized. My exploratory study examines connections between land use and water quality. The main objectives of the project were to develop an understanding of how land use has affected water quality in Miami-Dade canals, and an economic optimization model to estimate the costs of best management practices necessary to improve water quality. Results indicate Miami-Dade County land use and water quality are correlated. Through statistical factor and cluster analysis, it is apparent that agricultural areas are associated with higher concentrations of nitrogen, while urban areas commonly have higher levels of phosphorous than agricultural areas. The economic optimization model shows that urban areas can improve water quality by lowering fertilizer inputs. Agricultural areas can also implement methods to improve water quality although it may be more expensive than urban areas. It is important to keep solutions in mind when looking towards future water quality improvements in South Florida.

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This research, conducted in 2006-2008, examines the ways in which various groups involved with the marine resources of Seward, Alaska construct attitudes towards the environment. Participant observation and semi-structured interviews are used to assess how commercial halibut fishers, tour boat operators, local residents and government officials understand the marine environment based on their previous experiences. This study also explores how ideologies relate to the current practices of each group. Two theories orient the analyses: The first, cultural modeling provided a theoretical and methodological framework for pursuing a more comprehensive analysis of resource management. The second, Theory of Reasoned Action (Ajzen and Fishbein 1980), guided the analysis of the ways in which each participant’s ideology towards the marine environment relates to their practice. Aside from contributing to a better understanding of a coastal community’s ideologies and practices, this dissertation sought to better understand the role of ecological ideologies and behaviors in fisheries management. The research illustrates certain domains where ideologies and practices concerning Pacific halibut and the marine environment differ among commercial fishers, government, and management officials, tour boat operators and residents of Seward, AK. These differences offer insights into how future collaborative efforts between government officials, managers and local marine resource users might better incorporate local ideology into management, and provide ecological information to local marine resource users in culturally appropriate ways.

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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.