10 resultados para TOTAL ANALYSIS SYSTEMS

em Digital Commons at Florida International University


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This dissertation examines the sociological process of conflict resolution and consensus building in South Florida Everglades Ecosystem Restoration through what I define as a Network Management Coordinative Interstitial Group (NetMIG). The process of conflict resolution can be summarized as the participation of interested and affected parties (stakeholders) in a forum of negotiation. I study the case of the Governor's Commission for a Sustainable South Florida (GCSSF) that was established to reduce social conflict. Such conflict originated from environmental disputes about the Everglades and was manifested in the form of gridlock among regulatory (government) agencies, Indian tribes, as well as agricultural, environmental conservationist and urban development interests. The purpose of the participatory forum is to reduce conflicts of interest and to achieve consensus, with the ultimate goal of restoration of the original Everglades ecosystem, while cultivating the economic and cultural bases of the communities in the area. Further, the forum aim to formulate consensus through envisioning a common sustainable community by providing means to achieve a balance between human and natural systems. ^ Data were gathered using participant observation and document analysis techniques to conduct a theoretically based analysis of the role of the Network Management Coordinative Interstitial Group (NetMIG). I use conflict resolution theory, environmental conflict theory, stakeholder analysis, systems theory, differentiation and social change theory, and strategic management and planning theory. ^ The purpose of this study is to substantiate the role of the Governor's Commission for a Sustainable South Florida (GCSSF) as a consortium of organizations in an effort to resolve conflict rather than an ethnographic study of this organization. Environmental restoration of the Everglades is a vehicle for recognizing the significance of a Network Management Coordinative Interstitial Group (NetMIG), namely the Governor's Commission for a Sustainable South Florida (GCSSF), as a structural mechanism for stakeholder participation in the process of social conflict resolution through the creation of new cultural paradigms for a sustainable community. ^

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Geographic Information Systems (GIS) is an emerging information technology (IT) which promises to have large scale influences in how spatially distributed resources are managed. It has had applications in the management of issues as diverse as recovering from the disaster of Hurricane Andrew to aiding military operations in Desert Storm. Implementation of GIS systems is an important issue because there are high cost and time involvement in setting them up. An important component of the implementation problem is the "meaning" different groups of people who are influencing the implementation give to the technology. The research was based on the theory of (theoretical stance to the problem was based on the) "Social Construction of Knowledge" systems which assumes knowledge systems are subject to sociological analysis both in usage and in content. An interpretive research approach was adopted to inductively derive a model which explains how the "meanings" of a GIS are socially constructed. The research design entailed a comparative case analysis over two county sites which were using the same GIS for a variety of purposes. A total of 75 in-depth interviews were conducted to elicit interpretations of GIS. Results indicate that differences in how geographers and data-processors view the technology lead to different implementation patterns in the two sites.

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With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.

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The total time a customer spends in the business process system, called the customer cycle-time, is a major contributor to overall customer satisfaction. Business process analysts and designers are frequently asked to design process solutions with optimal performance. Simulation models have been very popular to quantitatively evaluate the business processes; however, simulation is time-consuming and it also requires extensive modeling experiences to develop simulation models. Moreover, simulation models neither provide recommendations nor yield optimal solutions for business process design. A queueing network model is a good analytical approach toward business process analysis and design, and can provide a useful abstraction of a business process. However, the existing queueing network models were developed based on telephone systems or applied to manufacturing processes in which machine servers dominate the system. In a business process, the servers are usually people. The characteristics of human servers should be taken into account by the queueing model, i.e. specialization and coordination. ^ The research described in this dissertation develops an open queueing network model to do a quick analysis of business processes. Additionally, optimization models are developed to provide optimal business process designs. The queueing network model extends and improves upon existing multi-class open-queueing network models (MOQN) so that the customer flow in the human-server oriented processes can be modeled. The optimization models help business process designers to find the optimal design of a business process with consideration of specialization and coordination. ^ The main findings of the research are, first, parallelization can reduce the cycle-time for those customer classes that require more than one parallel activity; however, the coordination time due to the parallelization overwhelms the savings from parallelization under the high utilization servers since the waiting time significantly increases, thus the cycle-time increases. Third, the level of industrial technology employed by a company and coordination time to mange the tasks have strongest impact on the business process design; as the level of industrial technology employed by the company is high; more division is required to improve the cycle-time; as the coordination time required is high; consolidation is required to improve the cycle-time. ^

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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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The Unified Modeling Language (UML) has quickly become the industry standard for object-oriented software development. It is being widely used in organizations and institutions around the world. However, UML is often found to be too complex for novice systems analysts. Although prior research has identified difficulties novice analysts encounter in learning UML, no viable solution has been proposed to address these difficulties. Sequence-diagram modeling, in particular, has largely been overlooked. The sequence diagram models the behavioral aspects of an object-oriented software system in terms of interactions among its building blocks, i.e. objects and classes. It is one of the most commonly-used UML diagrams in practice. However, there has been little research on sequence-diagram modeling. The current literature scarcely provides effective guidelines for developing a sequence diagram. Such guidelines will be greatly beneficial to novice analysts who, unlike experienced systems analysts, do not possess relevant prior experience to easily learn how to develop a sequence diagram. There is the need for an effective sequence-diagram modeling technique for novices. This dissertation reports a research study that identified novice difficulties in modeling a sequence diagram and proposed a technique called CHOP (CHunking, Ordering, Patterning), which was designed to reduce the cognitive load by addressing the cognitive complexity of sequence-diagram modeling. The CHOP technique was evaluated in a controlled experiment against a technique recommended in a well-known textbook, which was found to be representative of approaches provided in many textbooks as well as practitioner literatures. The results indicated that novice analysts were able to perform better using the CHOP technique. This outcome seems have been enabled by pattern-based heuristics provided by the technique. Meanwhile, novice analysts rated the CHOP technique more useful although not significantly easier to use than the control technique. The study established that the CHOP technique is an effective sequence-diagram modeling technique for novice analysts.

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Existing instrumental techniques must be adaptable to the analysis of novel explosives if science is to keep up with the practices of terrorists and criminals. The focus of this work has been the development of analytical techniques for the analysis of two types of novel explosives: ascorbic acid-based propellants, and improvised mixtures of concentrated hydrogen peroxide/fuel. In recent years, the use of these explosives in improvised explosive devices (IEDs) has increased. It is therefore important to develop methods which permit the identification of the nature of the original explosive from post-blast residues. Ascorbic acid-based propellants are low explosives which employ an ascorbic acid fuel source with a nitrate/perchlorate oxidizer. A method which utilized ion chromatography with indirect photometric detection was optimized for the analysis of intact propellants. Post-burn and post-blast residues if these propellants were analyzed. It was determined that the ascorbic acid fuel and nitrate oxidizer could be detected in intact propellants, as well as in the post-burn and post-blast residues. Degradation products of the nitrate and perchlorate oxidizers were also detected. With a quadrupole time-of-flight mass spectrometer (QToFMS), exact mass measurements are possible. When an HPLC instrument is coupled to a QToFMS, the combination of retention time with accurate mass measurements, mass spectral fragmentation information, and isotopic abundance patterns allows for the unequivocal identification of a target analyte. An optimized HPLC-ESI-QToFMS method was applied to the analysis of ascorbic acid-based propellants. Exact mass measurements were collected for the fuel and oxidizer anions, and their degradation products. Ascorbic acid was detected in the intact samples and half of the propellants subjected to open burning; the intact fuel molecule was not detected in any of the post-blast residue. Two methods were optimized for the analysis of trace levels of hydrogen peroxide: HPLC with fluorescence detection (HPLC-FD), and HPLC with electrochemical detection (HPLC-ED). Both techniques were extremely selective for hydrogen peroxide. Both methods were applied to the analysis of post-blast debris from improvised mixtures of concentrated hydrogen peroxide/fuel; hydrogen peroxide was detected on variety of substrates. Hydrogen peroxide was detected in the post-blast residues of the improvised explosives TATP and HMTD.

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This research analyzed the spatial relationship between a mega-scale fracture network and the occurrence of vegetation in an arid region. High-resolution aerial photographs of Arches National Park, Utah were used for digital image processing. Four sets of large-scale joints were digitized from the rectified color photograph in order to characterize the geospatial properties of the fracture network with the aid of a Geographic Information System. An unsupervised landcover classification was carried out to identify the spatial distribution of vegetation on the fractured outcrop. Results of this study confirm that the WNW-ESE alignment of vegetation is dominantly controlled by the spatial distribution of the systematic joint set, which in turn parallels the regional fold axis. This research provides insight into the spatial heterogeneity inherent to fracture networks, as well as the effects of jointing on the distribution of surface vegetation in desert environments.

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The Unified Modeling Language (UML) has quickly become the industry standard for object-oriented software development. It is being widely used in organizations and institutions around the world. However, UML is often found to be too complex for novice systems analysts. Although prior research has identified difficulties novice analysts encounter in learning UML, no viable solution has been proposed to address these difficulties. Sequence-diagram modeling, in particular, has largely been overlooked. The sequence diagram models the behavioral aspects of an object-oriented software system in terms of interactions among its building blocks, i.e. objects and classes. It is one of the most commonly-used UML diagrams in practice. However, there has been little research on sequence-diagram modeling. The current literature scarcely provides effective guidelines for developing a sequence diagram. Such guidelines will be greatly beneficial to novice analysts who, unlike experienced systems analysts, do not possess relevant prior experience to easily learn how to develop a sequence diagram. There is the need for an effective sequence-diagram modeling technique for novices. This dissertation reports a research study that identified novice difficulties in modeling a sequence diagram and proposed a technique called CHOP (CHunking, Ordering, Patterning), which was designed to reduce the cognitive load by addressing the cognitive complexity of sequence-diagram modeling. The CHOP technique was evaluated in a controlled experiment against a technique recommended in a well-known textbook, which was found to be representative of approaches provided in many textbooks as well as practitioner literatures. The results indicated that novice analysts were able to perform better using the CHOP technique. This outcome seems have been enabled by pattern-based heuristics provided by the technique. Meanwhile, novice analysts rated the CHOP technique more useful although not significantly easier to use than the control technique. The study established that the CHOP technique is an effective sequence-diagram modeling technique for novice analysts.

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Existing instrumental techniques must be adaptable to the analysis of novel explosives if science is to keep up with the practices of terrorists and criminals. The focus of this work has been the development of analytical techniques for the analysis of two types of novel explosives: ascorbic acid-based propellants, and improvised mixtures of concentrated hydrogen peroxide/fuel. In recent years, the use of these explosives in improvised explosive devices (IEDs) has increased. It is therefore important to develop methods which permit the identification of the nature of the original explosive from post-blast residues. Ascorbic acid-based propellants are low explosives which employ an ascorbic acid fuel source with a nitrate/perchlorate oxidizer. A method which utilized ion chromatography with indirect photometric detection was optimized for the analysis of intact propellants. Post-burn and post-blast residues if these propellants were analyzed. It was determined that the ascorbic acid fuel and nitrate oxidizer could be detected in intact propellants, as well as in the post-burn and post-blast residues. Degradation products of the nitrate and perchlorate oxidizers were also detected. With a quadrupole time-of-flight mass spectrometer (QToFMS), exact mass measurements are possible. When an HPLC instrument is coupled to a QToFMS, the combination of retention time with accurate mass measurements, mass spectral fragmentation information, and isotopic abundance patterns allows for the unequivocal identification of a target analyte. An optimized HPLC-ESI-QToFMS method was applied to the analysis of ascorbic acid-based propellants. Exact mass measurements were collected for the fuel and oxidizer anions, and their degradation products. Ascorbic acid was detected in the intact samples and half of the propellants subjected to open burning; the intact fuel molecule was not detected in any of the post-blast residue. Two methods were optimized for the analysis of trace levels of hydrogen peroxide: HPLC with fluorescence detection (HPLC-FD), and HPLC with electrochemical detection (HPLC-ED). Both techniques were extremely selective for hydrogen peroxide. Both methods were applied to the analysis of post-blast debris from improvised mixtures of concentrated hydrogen peroxide/fuel; hydrogen peroxide was detected on variety of substrates. Hydrogen peroxide was detected in the post-blast residues of the improvised explosives TATP and HMTD.