Public-Private-Partnership (P3) is gaining momentum as the delivery method for the development of public infrastructure. These projects, however, are exposed to economic risks. If the private parties are not comfortable with the level of the risks, they would not participate in the project and, as a result, the infrastructure will most likely not be realized. As an incentive for participation in the P3 project, private parties are sometimes offered guarantees against unfavorable economic risks. Therefore, the valuation of these guarantees is essential for deciding whether or not to participate in the project. While previous works focused on the valuation of guarantees, the incorporation of credit risk in the value of the P3 projects and the guarantees has been neglected. The effect of credit risk can be taken into account by using the rigorous Credit Value Adjustment method (CVA). CVA is a computationally demanding method that the valuation methods currently in the literature are not capable of handling. This research offers a novel approach for the valuation of guarantees and P3 projects which is computationally superior to the existing methods. Because of this computational efficiency, CVA can be implemented to account for credit risk. For the development of this method, a continuous stochastic differential equation (SDE) is derived from the forecasted curve of an economic risk. Using the SDE, the partial differential equation (PDE) governing the value of the guarantees will be derived. Then, the PDE will be solved using Finite Difference Method (FDM). A new feature for this method is that it obtains exercise strategies for the Australian guarantees. The present work extends the literature by providing a valuation method for the cases that multiple risks affect P3 projects. It also presents an approach for the valuation of the Asian style guarantee, a contract which reimburses the private party based on the average of risk factor. Finally, a hypothetical case study illustrates the implementation of the FDM-based valuation method and CVA to obtain the value of the P3 project and the guarantees adjusted for the counterparty credit risk.

Hospital Acquired Infections (HAI) are a global patient safety challenge, costly to treat, and affect hundreds of millions of patients annually worldwide. It has been shown that the majority of HAI are transferred to patients by caregivers' hands and therefore, can be prevented by proper hand hygiene (HH). However, many factors including cognitive load, cause caregivers to forget to cleanse their hands. Hand hygiene compliance among caregivers remains low around the world. In this thesis I showed that it is possible to build a wearable accelerometer-based HH reminder system to identify ongoing nursing activities with the patient, indicate the high-risk activities, and prompt the caregivers to clean their hands. Eight subjects participated in this study, each wearing five wireless accelerometer sensors on the wrist, upper arms and the back. A pattern recognition approach was used to classify six nursing activities offline. Time-domain features that included mean, standard deviation, energy, and correlation among accelerometer axes were found to be suitable features. On average, 1-Nearest Neighbour classifier was able to classify the activities with 84% accuracy. A novel algorithm was developed to adaptively segment the accelerometer signals to identify the start and stop time of each nursing activity. The overall accuracy of the algorithm for a total of 96 events performed by 8 subjects was approximately 87%. The accuracy was higher than 91% for 5 out of 8 subjects. The sequence of nursing activities was modelled by an 18-state Markov Chain. The model was evaluated by recently published data. The simulation results showed that the high-risk of cross-contamination decreases exponentially by frequency of HH and this happens more rapidly up to 50%-60% hand hygiene rate. It was also found that if the caregiver enters the room with high-risk of transferring infection to the current patient, given the assumptions in this study, only 55% HH is capable of reducing the risk of infection transfer to the lowest level. This may help to prevent the next patient from acquiring infection, preventing an infection outbreak. The model is also capable of simulating the effects of the imperfect HH on the risk of cross-contamination.

Public-Private-Partnership (P3) is gaining momentum as the delivery method for the development of public infrastructure. These projects, however, are exposed to economic risks. If the private parties are not comfortable with the level of the risks, they would not participate in the project and, as a result, the infrastructure will most likely not be realized. As an incentive for participation in the P3 project, private parties are sometimes offered guarantees against unfavorable economic risks. Therefore, the valuation of these guarantees is essential for deciding whether or not to participate in the project. While previous works focused on the valuation of guarantees, the incorporation of credit risk in the value of the P3 projects and the guarantees has been neglected. The effect of credit risk can be taken into account by using the rigorous Credit Value Adjustment method (CVA). CVA is a computationally demanding method that the valuation methods currently in the literature are not capable of handling. This research offers a novel approach for the valuation of guarantees and P3 projects which is computationally superior to the existing methods. Because of this computational efficiency, CVA can be implemented to account for credit risk. For the development of this method, a continuous stochastic differential equation (SDE) is derived from the forecasted curve of an economic risk. Using the SDE, the partial differential equation (PDE) governing the value of the guarantees will be derived. Then, the PDE will be solved using Finite Difference Method (FDM). A new feature for this method is that it obtains exercise strategies for the Australian guarantees. The present work extends the literature by providing a valuation method for the cases that multiple risks affect P3 projects. It also presents an approach for the valuation of the Asian style guarantee, a contract which reimburses the private party based on the average of risk factor. Finally, a hypothetical case study illustrates the implementation of the FDM-based valuation method and CVA to obtain the value of the P3 project and the guarantees adjusted for the counterparty credit risk.

Call-response surveys were conducted to better delineate and estimate the population of the nationally threatened least bittern and their habitat requirements in southern Manitoba, Canada. Other marsh bird species whose populations are believed to be declining due to wetland loss throughout, or in parts of, their range were also surveyed including the American bittern, pied-billed grebe, sora, Virginia rail and yellow rail. Surveys were conducted during the 2003 and 2004 breeding seasons within 46 different wetlands. Least bitterns were encountered on 26 occasions at 15 sites within 5 wetlands. The sora was the most abundant and widely distributed target species and was encountered on 330 occasions in 39 of the 46 surveyed wetlands. Yellow rails were not detected during either survey year due to survey methodology. Use of the call-response survey protocol led to an increase in the numbers of all target species detected. This increase was more significant for the least bittern, sora and Virginia rail. Habitat was assessed as percent vegetation cover within a 50-m radius around the calling sites, and forest resource inventory data were used in a Geographic Information System to determine the landscape composition within a 500-m radius around the sites and within a 5-km radius around the wetlands surveyed. Logistic regression analyses were used to evaluate the relationship between the presence of the target species and the site and landscape characteristics. The target species responded differently to different site and landscape characteristics. Least bittern and pied-billed grebe selected areas with higher proportions of Typha spp. and tall shrubs; American bittern also selected areas with higher proportions of tall shrubs. At the 5-km scale, the American bittern responded positively to the amount of wetland and some positive trends were also detected for the pied-billed grebe. Sora and Virginia rail were not associated with any of the measured landscape characteristics. One of the most important steps towards the conservation of marsh bird species in Manitoba and elsewhere is the development, adoption, and implementation of a standardized survey protocol. Based on the results of the present study, I recommend that future surveys include both a passive and call-broadcast period for marsh bird species. Future surveys should be conducted in both the morning and evening and sites should be visited 3 times each during the breeding season. In southern Manitoba, call-response surveys should begin as early as the beginning of May to ensure the survey incorporates the period of peak vocalization. I recommend that future yellow rail surveys be conducted after dark. In this study many of the target species selected sites that had a greater area of wetland habitat surrounding them. Future wetland conservation efforts should focus on the protection and/or restoration of wetland complexes to ensure that remaining wetlands do not become smaller and increasingly isolated from one another. In addition, the Rat River Swamp was found to be the most productive marsh complex for least bittern in southern Manitoba. Measures should be taken to protect this area from future development and alteration.

A software GPS receiver is a functional GPS receiver in software. It has several advantages compared to its hardware counterparts. For instance, improvements in receiver architecture as well as GPS system structure can be easily adapted to it. Furthermore, interaction between nearby sensors can be coordinated easily. In this thesis, a SGR (software GPS receiver) is presented from a practical point of view. Major components of the SGR are implemented in Matlab environment. Furthermore, some alternative algorithms are implemented. SGR implementation is considered in two main sections namely a signal processing section and a navigation section. Signal processing section is driven by the raw GPS signal samples obtained from a GPS front-end of NordNavTM R-25 instrument. The conventional and the block adjustment of synchronizing signal (BAAS) processing methods are implemented and their performances are compared in terms of their speed and outputs. Signal processing section outputs raw GPS measurements and navigation data bits. Since the output data length is insufficient in our case, navigation section input is fed from AshtechTM GPS receiver for a moving platform and TrimbleTM GPS Receiver for a stationary platform. Satellite position computation, pseudorange corrections, Kalman filter and LSE (least squares estimation) are implemented in the navigation section. Kalman filter and LSE methods are compared in terms of positioning accuracy for a moving as well as a stationary platform. Results are compared with the commercial GPS outputs. This comparison shows that the software navigation section is equivalent to the commercial GPS in terms of positioning accuracy.

國內結構債市場業已蓬勃發展，市場模型亦相當適合結構債評價。本文在市場模型下，因市場模型不具馬可夫性質，運用最小平方蒙地卡羅法針對三連結標的為LIBOR的結構債進行評價。 / The market of the structured notes has been blossoming. The lognormal forward LIBOR model is more suitable for the valuation of structured notes than do the traditional interest rate models. In this article, we perform three case studies of the valuation of the structured notes linked to LIBOR in lognormal forward LIOBR model. It is easier to implement the lognormal forward LIBOR model by Monte Carlo simulation due to the non-Markovian property. Therefore, the least-squares Monte Carlo approach is used to deal with the callable feature of the structured notes in our case studies.

This thesis, which consists of five papers, is concerned with various aspects of confirmatory factor analysis (CFA) of ordinal variables and the generation of non-normal data. The first paper studies the performances of different estimation methods used in CFA when ordinal data are encountered.  To take ordinality into account the four estimation methods, i.e., maximum likelihood (ML), unweighted least squares, diagonally weighted least squares, and weighted least squares (WLS), are used in combination with polychoric correlations. The effect of model sizes and number of categories on the parameter estimates, their standard errors, and the common chi-square measure of fit when the models are both correct and misspecified are examined. The second paper focuses on the appropriate estimator of the polychoric correlation when fitting a CFA model. A non-parametric polychoric correlation coefficient based on the discrete version of Spearman's rank correlation is proposed to contend with the situation of non-normal underlying distributions. The simulation study shows the benefits of using the non-parametric polychoric correlation under conditions of non-normality. The third paper raises the issue of simultaneous factor analysis. We study the effect of pooling multi-group data on the estimation of factor loadings. Given the same factor loadings but different factor means and correlations, we investigate how much information is lost by pooling the groups together and only estimating the combined data set using the WLS method. The parameter estimates and their standard errors are compared with results obtained by multi-group analysis using ML. The fourth paper uses a Monte Carlo simulation to assess the reliability of the Fleishman's power method under various conditions of skewness, kurtosis, and sample size. Based on the generated non-normal samples, the power of D'Agostino's (1986) normality test is studied. The fifth paper extends the evaluation of algorithms to the generation of multivariate non-normal data.  Apart from the requirement of generating reliable skewness and kurtosis, the generated data also need to possess the desired correlation matrices.  Four algorithms are investigated in terms of simplicity, generality, and reliability of the technique.

Mi tesis se basa en los resultados de least squares learning, que modela agentes individuales como econometricos: los agentes funcionan como regresiones, usan datos disponibles para formar sus expectativas. En el primer capítulo de mi tesis demuestro que la presencia de principiantes de learning en una economía se puede racionalizar incluso en coexistencia con los agentes racionales. En el segundo capítulo, examino cuál es la implicación en la política monetaria óptima cuando los agentes privados siguen aprendiendo con least squares learning. Este capítulo demuestra que la política monetaria óptima bajo learning introduce unas nuevas características del comportamiento de la política que no son presentes cuando los agentes privados tienen expectativas racionales. / My thesis builds on the results of the least squares learning literature, which models individual agents as econometricians: agents are running least squares regressions using available data in order to form their expectations. I the ¯first chapter of my thesis I show that the presence of learners in an economy can be rationalized even in coexistence with rational agents. In the second chapter, I examine what is the implication on optimal policy when private agents follow learning. This chapter shows that optimal monetary policy under learning introduces new features of policy behavior that are not present under rational expectations.

Les motivacions entorn al programari lliure han estat sempre un tema de gran interès, sent la pregunta més obvia, "perquè les persones treballen de forma gratuïta?". Les motivacions dels desenvolupadors han estat establertes (per exemple, von Hippel (2001), Lerner and Tirole (2002)). De la mateixa manera que ho han estat per a les empreses grans i petites que adopten programari lliure basat en models de negoci (per exemple, Lakhani and von Hippel, 2003; Fitzgerald, 2006; Krishnamurthy, 2004). No obstant això, un nombre cada vegada més elevat de les PIMES amb estratègies que no estan directament relacionades amb aquest model de negoci estan contribuint a les comunitats de programari lliure. En aquest estudi s'investiga les motivacions d'aquestes empreses des d'un punt de vista de comportament mitjançant un model d'investigació basat en TPB (Theory of Planned Behavior). Hem demostrat que factors com la "obertura" d'una PIME, la importància percebuda del programari lliure, els desenvolupadors (empleats) d'una PIME, juntament amb l'ambient extern, podrien influir en la decisió d'una PIME a participar en comunitats de programari lliure. A més, hem demostrat que es poden identificar algunes diferències entre empreses d'alta base tecnològica i empreses amb poca base tecnològica. Aquestes conclusions poden ajudar governs nacionals o regionals per millorar el disseny de polítiques per tal d'incentivar l'ús i la participació de les empreses en les comunitats de programari lliure. Especialment ara, degut a la forta crisi econòmica que pateix Europa, el programari lliure pot ser una solució adequada per a fomentar la innovació. / Motivations in FLOSS have always been a subject of great interest, by starting with the most obvious question, “why people work for free?”. The motivations of developers have been well established (eg von Hippel (2001), Lerner and Tirole 2002). The same exists also for big and small companies adopting FLOSS based Business Models (eg Lakhani and von Hippel, 2003; Fitzgerald 2006; Krishnamurthy, 2004). However an increasing number of SMEs with strategies not directly related to the Business Model are contributing to FLOSS communities. In this study we try to investigate these motivations under a behavioral perspective by using a research model based on TPB (Theory of Planned Behavior). We demonstrated that factors like the “openness” of a SME, the perceived importance of FLOSS, the developers (employees) of a SME along with the external environment of a SME, could influence the decision of a SME to participate in FLOSS communities. Also, we have demonstrated that some differences can be identified between high tech firms and non high tech firms. These findings can help national or regional governments to design better policies in order to better promote the use and the participation of firms to FLOSS communities. Especially now, in times of heavy economical crisis in Europe, FLOSS can be an adequate solution to foster innovation.

Kath. Universiẗat, Diss.--Eichstätt-Ingolstadt, 2007.