6 resultados para Real Root Isolation Methods

em Digital Commons - Michigan Tech


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This research is a study of the use of capital budgeting methods for investment decisions. It uses both the traditional methods and the newly introduced approach called the real options analysis to make a decision. The research elucidates how capital budgeting can be done when analysts encounter projects with high uncertainty and are capital intensive, for example oil and gas production. It then uses the oil and gas find in Ghana as a case study to support its argument. For a clear understanding a thorough literature review was done, which highlights the advantages and disadvantages of both methods. The revenue that the project will generate and the costs of production were obtained from the predictions by analysts from GNPC and compared to others experts’ opinion. It then applied both the traditional and real option valuation on the oil and gas find in Ghana to determine the project’s feasibility. Although, there are some short falls in real option analysis that are presented in this research, it is still helpful in valuing projects that are capital intensive with high volatility due to the strategic flexibility management possess in their decision making. It also suggests that traditional methods of evaluation should still be maintained and be used to value projects that have no options or those with options yet the options do not have significant impact on the project. The research points out the economic ripples the production of oil and gas will have on Ghana’s economy should the project be undertaken. These ripples include economic growth, massive job creation and reduction of the balance of trade deficit for the country. The long run effect is an eventually improvement of life of the citizens. It is also belief that the production of gas specifically can be used to generate electricity in Ghana which would enable the country to have a more stable and reliable power source necessary to attract more foreign direct investment.

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In this study, we isolated eight copper-resistant bacteria from Torch Lake sediment contaminated by copper mine tailings (stamp sand). Sequence analysis of gyrB and rpoD genes revealed that these organisms are closer to various Pseudomonas species. These eight bacterial isolates were also resistant to zinc, cesium, lead, arsenate and mercury. Further characterization showed that all the strains produced plant growth promoting indole-3-acetic acid (IAA), iron chelating siderophore and solubilized mineral phosphate and metals. The effect of bacterial inoculation on plant growth and copper uptake by maize (Zea mays) and sunflower (Helianthus annuus) was investigated using one of the isolates (Pseudomonas sp. TLC 6-6.5-4) with higher IAA production and phosphate and metal soubilization, which resulted in a significant increase in copper accumulation in maize and sunflower, and an increase in the total biomass of maize. Genes involved in copper resistance of Pseudomonas sp. TLC 6-6.5-4 was analyzed by transposon mutational analysis. Two copper sensitive mutants with significant reduction in copper resistance were identified: CSM1, a mutant disrupted in trp A gene (tryptophan synthase alpha subunit); CSM2, a mutant disrupted in clpA gene (ATP-dependent Clp protease). Proteomic and metabolomic analysis were performed to identify biochemical and molecular mechanisms involved in copper resistance using CSM2 due to its lower minimum inhibitory concentration compared with CSM1 and the wild type. The effect of different bacterial inoculation methods on plant growth, copper uptake and soil enzyme activities was investigated. Four different delivery methods were used including soil inoculation (before or after plant emergence), seed coating and root dipping. Soil inoculation before sowing seeds and coating seeds with PGPB led to better growth of maize, higher copper uptake and an increase in soil invertase and dehydrogenase activities. Proteomic and metabolomic analyses were performed to investigate the effect of bacterial inoculation on maize grown in normal soil and stamp sand. Our results revealed that bacterial inoculation led to environment-dependent effects on maize proteome and metabolome.

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This study investigated the use of real-world contexts during instruction in a high school physics class - through building file folder bridges- and the resulting effect upon student interest in the subject matter, level of understanding, and degree of retention. In particular, the study focused upon whether increases in student interest were attained through the use of real-world contexts, and if the elevated interest level led to a higher degree of subject matter understanding than would be achieved using more traditional teaching methods. The study also determined whether using real-world contexts ultimately resulted in achievement of greater levels of knowledge retention by students. Class observations during traditionally taught units and during units that incorporated real-world contexts, along with a post-graduation questionnaire, were used to assess differences in student interest levels. Student pre- and post-unit test scores were evaluated and compared to determine if statistical differences existed in levels of understanding resulting from the different teaching methods. The post-graduation questionnaire results provided evidence of retention that could be related back to teaching methods. The results of this study revealed the importance of incorporating real-world contexts into science and mathematics courses. Students better understood the relevance of the lessons, which led to higher levels of interest and greater understanding than was achieved through more traditional teaching methods. The use of real-world contexts improved knowledge retention.

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As the development of genotyping and next-generation sequencing technologies, multi-marker testing in genome-wide association study and rare variant association study became active research areas in statistical genetics. This dissertation contains three methodologies for association study by exploring different genetic data features and demonstrates how to use those methods to test genetic association hypothesis. The methods can be categorized into in three scenarios: 1) multi-marker testing for strong Linkage Disequilibrium regions, 2) multi-marker testing for family-based association studies, 3) multi-marker testing for rare variant association study. I also discussed the advantage of using these methods and demonstrated its power by simulation studies and applications to real genetic data.

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This thesis develops high performance real-time signal processing modules for direction of arrival (DOA) estimation for localization systems. It proposes highly parallel algorithms for performing subspace decomposition and polynomial rooting, which are otherwise traditionally implemented using sequential algorithms. The proposed algorithms address the emerging need for real-time localization for a wide range of applications. As the antenna array size increases, the complexity of signal processing algorithms increases, making it increasingly difficult to satisfy the real-time constraints. This thesis addresses real-time implementation by proposing parallel algorithms, that maintain considerable improvement over traditional algorithms, especially for systems with larger number of antenna array elements. Singular value decomposition (SVD) and polynomial rooting are two computationally complex steps and act as the bottleneck to achieving real-time performance. The proposed algorithms are suitable for implementation on field programmable gated arrays (FPGAs), single instruction multiple data (SIMD) hardware or application specific integrated chips (ASICs), which offer large number of processing elements that can be exploited for parallel processing. The designs proposed in this thesis are modular, easily expandable and easy to implement. Firstly, this thesis proposes a fast converging SVD algorithm. The proposed method reduces the number of iterations it takes to converge to correct singular values, thus achieving closer to real-time performance. A general algorithm and a modular system design are provided making it easy for designers to replicate and extend the design to larger matrix sizes. Moreover, the method is highly parallel, which can be exploited in various hardware platforms mentioned earlier. A fixed point implementation of proposed SVD algorithm is presented. The FPGA design is pipelined to the maximum extent to increase the maximum achievable frequency of operation. The system was developed with the objective of achieving high throughput. Various modern cores available in FPGAs were used to maximize the performance and details of these modules are presented in detail. Finally, a parallel polynomial rooting technique based on Newton’s method applicable exclusively to root-MUSIC polynomials is proposed. Unique characteristics of root-MUSIC polynomial’s complex dynamics were exploited to derive this polynomial rooting method. The technique exhibits parallelism and converges to the desired root within fixed number of iterations, making this suitable for polynomial rooting of large degree polynomials. We believe this is the first time that complex dynamics of root-MUSIC polynomial were analyzed to propose an algorithm. In all, the thesis addresses two major bottlenecks in a direction of arrival estimation system, by providing simple, high throughput, parallel algorithms.

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In this report, we attempt to define the capabilities of the infrared satellite remote sensor, Multifunctional Transport Satellite-2 (MTSAT-2) (i.e. a geosynchronous instrument), in characterizing volcanic eruptive behavior in the highly active region of Indonesia. Sulfur dioxide data from NASA's Ozone Monitoring Instrument (OMI) (i.e. a polar orbiting instrument) are presented here for validation of the processes interpreted using the thermal infrared datasets. Data provided from two case studies are analyzed specifically for eruptive products producing large thermal anomalies (i.e. lava flows, lava domes, etc.), volcanic ash and SO2 clouds; three distinctly characteristic and abundant volcanic emissions. Two primary methods used for detection of heat signatures are used and compared in this report including, single-channel thermal radiance (4-µm) and the normalized thermal index (NTI) algorithm. For automated purposes, fixed thresholds must be determined for these methods. A base minimum detection limit (MDL) for single-channel thermal radiance of 2.30E+05 Wm- 2sr-1m-1 and -0.925 for NTI generate false alarm rates of 35.78% and 34.16%, respectively. A spatial comparison method, developed here specifically for use in Indonesia and used as a second parameter for detection, is implemented to address the high false alarm rate. For the single-channel thermal radiance method, the utilization of the spatial comparison method eliminated 100% of the false alarms while maintaining every true anomaly. The NTI algorithm showed similar results with only 2 false alarms remaining. No definitive difference is observed between the two thermal detection methods for automated use; however, the single-channel thermal radiance method coupled with the SO2 mass abundance data can be used to interpret volcanic processes including the identification of lava dome activity at Sinabung as well as the mechanism for the dome emplacement (i.e. endogenous or exogenous). Only one technique, the brightness temperature difference (BTD) method, is used for the detection of ash. Trends of ash area, water/ice area, and their respective concentrations yield interpretations of increased ice formation, aggregation, and sedimentation processes that only a high-temporal resolution instrument like the MTSAT-2 can analyze. A conceptual model of a secondary zone of aggregation occurring in the migrating Kelut ash cloud, which decreases the distal fine-ash component and hazards to flight paths, is presented in this report. Unfortunately, SO2 data was unable to definitively reinforce the concept of a secondary zone of aggregation due to the lack of a sufficient temporal resolution. However, a detailed study of the Kelut SO2 cloud is used to determine that there was no climatic impacts generated from this eruption due to the atmospheric residence times and e-folding rate of ~14 days for the SO2. This report applies the complementary assets offered by utilizing a high-temporal and a high-spatial resolution satellite, and it demonstrates that these two instruments can provide unparalleled observations of dynamic volcanic processes.