How do Small Players Deduce Beliefs about Uncertainty? A Look at Texas Shale Oil Investments

Thesis (Ph.D.)--University of Washington, 2016-08

Cross-sensors analysis of multispectral Earth observation data for environmental monitoring

Time Series Analysis of multispectral satellite data offers an innovative way to extract valuable information of our changing planet. This is now a real option for scientists thanks to data availability as well as innovative cloud-computing platforms, such as Google Earth Engine. The integration of different missions would mitigate known issues in multispectral time series construction, such as gaps due to clouds or other atmospheric effects. With this purpose, harmonization among Landsat-like missions is possible through statistical analysis. This research offers an overview of the different instruments from Landsat and Sentinel missions (TM, ETM, OLI, OLI-2 and MSI sensors) and products levels (Collection-2 Level-1 and Surface Reflectance for Landsat and Level-1C and Level-2A for Sentinel-2). Moreover, a cross-sensors comparison was performed to assess the interoperability of the sensors on-board Landsat and Sentinel-2 constellations, having in mind a possible combined use for time series analysis. Firstly, more than 20,000 pairs of images almost simultaneously acquired all over Europe were selected over a period of several years. The study performed a cross-comparison analysis on these data, and provided an assessment of the calibration coefficients that can be used to minimize differences in the combined use. Four of the most popular vegetation indexes were selected for the study: NDVI, EVI, SAVI and NDMI. As a result, it is possible to reconstruct a longer and denser harmonized time series since 1984, useful for vegetation monitoring purposes. Secondly, the spectral characteristics of the recent Landsat-9 mission were assessed for a combined use with Landsat-8 and Sentinel-2. A cross-sensor analysis of common bands of more than 3,000 almost simultaneous acquisitions verified a high consistency between datasets. The most relevant discrepancy has been observed in the blue and SWIRS bands, often used in vegetation and water related studies. This analysis was supported with spectroradiometer ground measurements.

Extrapolation theory for the real interpolation method

We develop an abstract extrapolation theory for the real interpolation method that covers and improves the most recent versions of the celebrated theorems of Yano and Zygmund. As a consequence of our method, we give new endpoint estimates of the embedding Sobolev theorem for an arbitrary domain Omega

Strategic investment appraisal; extended real options approach

Tutkielma keskittyy lisäämään investointiarviointiprosessien rationaalisuutta strategisten investointien arvioinnissa duopoli- / oligopolimarkkinoilla. Tutkielman päätavoitteena on selvittää kuinka peliteorialla laajennettu reaalioptioperusteinen investointien arviointimenetelmä, laajennettu reaalioptiokehikko, voisi mahdollisesti parantaa analyysien tarkkuutta. Tutkimus lähestyy ongelmaa investoinnin ajoituksen sekä todellisten investoinnin arvoattribuuttien riippuvuuksien kautta. Laajennettu reaalioptiokehikko on investointien analysointi- ja johtamistyökalu, joka tarjoaa osittain rajoitetun (sisältää tällä hetkellä ainoastaan parametrisen ja peliteoreettisen epävarmuuden) optimaalisen arvovälin investoinnin todellisesta arvosta. Kehikossa, ROA kartoittaa mahdolliset strategiset hyödyt tunnistamalla investointiinliittyvät eri optiot ja epävarmuudet, peliteoria korostaa ympäristön luomia paineita investointiin liittyvän epävarmuuden hallitsemisessa. Laajennettu reaalioptiokehikko tarjoaa rationaalisemman arvion strategisen investoinnin arvosta, koska se yhdistää johdonmukaisemmin option toteutuksen ja siten myös optioiden aika-arvon, yrityksen todellisiin rajoitettuihin (rajoituksena muiden markkinatoimijoiden toimet) polkuriippuvaisiin kyvykkyyksiin.

Protein Microarray: "Theory" to "Real Practice"

Fueled by ever-growing genomic information and rapid developments of proteomics–the large scale analysis of proteins and mapping its functional role has become one of the most important disciplines for characterizing complex cell function. For building functional linkages between the biomolecules, and for providing insight into the mechanisms of biological processes, last decade witnessed the exploration of combinatorial and chip technology for the detection of bimolecules in a high throughput and spatially addressable fashion. Among the various techniques developed, the protein chip technology has been rapid. Recently we demonstrated a new platform called “Spacially addressable protein array” (SAPA) to profile the ligand receptor interactions. To optimize the platform, the present study investigated various parameters such as the surface chemistry and role of additives for achieving high density and high-throughput detection with minimal nonspecific protein adsorption. In summary the present poster will address some of the critical challenges in protein micro array technology and the process of fine tuning to achieve the optimum system for solving real biological problems.

Decision theory and real estate development: a note on uncertainty

Real estate development appraisal is a quantification of future expectations. The appraisal model relies upon the valuer/developer having an understanding of the future in terms of the future marketability of the completed development and the future cost of development. In some cases the developer has some degree of control over the possible variation in the variables, as with the cost of construction through the choice of specification. However, other variables, such as the sale price of the final product, are totally dependent upon the vagaries of the market at the completion date. To try to address the risk of a different outcome to the one expected (modelled) the developer will often carry out a sensitivity analysis on the development. However, traditional sensitivity analysis has generally only looked at the best and worst scenarios and has focused on the anticipated or expected outcomes. This does not take into account uncertainty and the range of outcomes that can happen. A fuller analysis should include examination of the uncertainties in each of the components of the appraisal and account for the appropriate distributions of the variables. Similarly, as many of the variables in the model are not independent, the variables need to be correlated. This requires a standardised approach and we suggest that the use of a generic forecasting software package, in this case Crystal Ball, allows the analyst to work with an existing development appraisal model set up in Excel (or other spreadsheet) and to work with a predetermined set of probability distributions. Without a full knowledge of risk, developers are unable to determine the anticipated level of return that should be sought to compensate for the risk. This model allows the user a better understanding of the possible outcomes for the development. Ultimately the final decision will be made relative to current expectations and current business constraints, but by assessing the upside and downside risks more appropriately, the decision maker should be better placed to make a more informed and “better”.

Stochastic quantization of real-time thermal field theory

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Real-time estimation of transmission line impedance based on modal analysis theory

The objective of this paper is to show a methodology to estimate the longitudinal parameters of transmission lines. The method is based on the modal analysis theory and developed from the currents and voltages measured at the sending and receiving ends of the line. Another proposal is to estimate the line impedance in function of the real-time load apparent power and power factor. The procedure is applied for a non-transposed 440 kV three-phase line. © 2011 IEEE.

The economics of demand-led growth: theory and evidence for Brazil

Includes bibliography

A Comparative Analysis of In-Medium Spectral Functions for N(940) and N (au)(1535) in Real-Time Thermal Field Theory

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Generalizing the dynamic field theory of spatial cognition across real and developmental time scales

Within cognitive neuroscience, computational models are designed to provide insights into the organization of behavior while adhering to neural principles. These models should provide sufficient specificity to generate novel predictions while maintaining the generality needed to capture behavior across tasks and/or time scales. This paper presents one such model, the Dynamic Field Theory (DFT) of spatial cognition, showing new simulations that provide a demonstration proof that the theory generalizes across developmental changes in performance in four tasks—the Piagetian A-not-B task, a sandbox version of the A-not-B task, a canonical spatial recall task, and a position discrimination task. Model simulations demonstrate that the DFT can accomplish both specificity—generating novel, testable predictions—and generality—spanning multiple tasks across development with a relatively simple developmental hypothesis. Critically, the DFT achieves generality across tasks and time scales with no modification to its basic structure and with a strong commitment to neural principles. The only change necessary to capture development in the model was an increase in the precision of the tuning of receptive fields as well as an increase in the precision of local excitatory interactions among neurons in the model. These small quantitative changes were sufficient to move the model through a set of quantitative and qualitative behavioral changes that span the age range from 8 months to 6 years and into adulthood. We conclude by considering how the DFT is positioned in the literature, the challenges on the horizon for our framework, and how a dynamic field approach can yield new insights into development from a computational cognitive neuroscience perspective.

Valuation of a new entrant in an oligopolistic market, including its option to abandon: A real-life case

The purpose of this paper is to increase current empirical evidence on the relevance of real options for explaining firm investment decisions in oligopolistic markets. We study an actual investment case in the Spanish mobile telephony industry, the entrant in the market of a new operator, Yoigo. We analyze the option to abandon in order to show the relevance of the possibility of selling the company in an oligopolistic market where competitors are not allowed free entrance. The NPV (net present value) of the new entrant is calculated as a starting point. Then, based on the general approach proposed by Copeland and Antikarov (2001), a binomial tree is used to model managerial flexibility in discrete time periods, and value the option to abandon. The strike price of the option is calculated based on incremental EBITDA margins due to selling customers or merging with a competitor.