This study evaluated how well energy savings persisted over time in ten university buildings that had undergone retro-commissioning in 1996. The savings achieved immediately following retro-commissioning and in three subsequent years were documented in a previous study (Cho 2002). The current study expanded on this previous study by evaluating the performance of each building over nine additional years. Follow up retro-commissioning work performed in each building during that time was documented, as well as changes to the energy management control system. Savings were determined in accordance with the methodology outlined in the International Performance Measurement and Verification Protocol (IPMVP 2007), with ASHRAE Guideline 14 also serving as a reference. Total annualized savings for all buildings in 1997 (the year just after retro-commissioning) were 45(plus or minus 2)% for chilled water, 67(plus or minue 2)% for hot water, and 12% for electricity. Combining consumption from the most recent year for each building with valid energy consumption data showed a total savings of 39(plus or minus 1)% for chilled water, 64(plus or minus 2)% for heating water, and 22% for electricity. Uncertainty values were calculated in accordance with methodology in the IPMVP and ASHRAE Guideline 14, and were reported at the 90% confidence interval. The most recent year of data for most of the buildings was 2008-2009, although a few of the buildings did not have valid consumption data for that year. Follow up work performed in the buildings, lighting retrofits, and building metering changes beginning in 2005 were the major issues believed to have contributed to the high level of savings persistence in later years. When persistence trends were evaluated with adjustment for these factors, average savings for the buildings studied were found to degrade over time, and exponential models were developed to describe this degradation. The study concluded that on average energy savings after retro-commissioning will degrade over time in a way that can be modeled exponentially. It was also concluded that high levels of savings persistence can be achieved through performing retro-commissioning follow up, particularly when significant increases are observed in metered energy consumption data, but also at other times as retro-commissioning procedures and technology continually improve.

Background: We have reason to believe that in fear of doing wrong; most PPM investors are crippled to stay passive. Hence, they are not using the full potential of the PPM systems. Some are lured in to use professional pension saving steward by promises of abnormal return. According to efficient market hypothesis this would be impossible, however, studies have shown that their might exist inherent financial anomalies that by the utilization of historic information can open the window for abnormal return. Purpose: The purpose of the study is to draw attention to the problem of using ex ante data to predict ex post returns. Thus, we would have evaluated the practical implication of using ex ante data as a determinant in relation to optimal PPM funds selection, and if possible to provide some simplistic guidelines for the average PPM investor. Results: We found a handful of portfolios that gave significant results against their own index; however, when tested against Sverige, rena and Global, Mix bolag the evidence of abnormal return were thin.  From our results, we conclude that their seems to be a persistence effect, as top achievers continued to perform above average in almost all cases, however, one could not profitize on abnormal return other than by chance.  Consequently, historic return can give the investor an aid in optimal portfolio selection. Historic figures concerning standard deviation, expense ratios, and load fees all significantly correlated with return, however, neither seem to give the investor an edge in optimal PPM portfolio selection.

One of the main problems in statistical climatology is to construct a parsimonious model of natural climate variability. Such a model serves for instance as a null hypothesis for detection of human induced climate changes and of periodic climate signals. Fitting thismodel to various climatic time series also helps to infer the origins of underlying temporal variability and to cross validate it between different data sets. We consider the use of a spectral power-law model in this role for the surface temperature, for the free atmospheric air temperature of the troposphere and stratosphere, and for the total ozone. First, we lay down a methodological foundation for our work. We compare two variants of five different power-law fitting methods by means of Monte-Carlo simulations and their application to observed air temperature. Then using the best two methods we fit the power-law model to several observational products and climate model simulations. We make use of specialized atmospheric general circulation model simulations and of the simulations of the Coupled Model Intercomparison Project 3 (CMIP3). The specialized simulations allow us to explain the power-law exponent spatial distribution and to account for discrepancies in scaling behaviour between different observational products. We find that most of the pre-industrial control and 20th century model simulations capture many aspects of the observed horizontal and vertical distribution of the power-law exponents. At the surface, regions with robust power-law exponents—the North Atlantic, the North Pacific, and the Southern Ocean — coincide with regions with strong inter-decadal variability. In the free atmosphere, the large power-law exponents are detected on annual to decadal time scales in the tropical and subtropical troposphere and stratosphere. The spectral steepness in the former is explained by its strong coupling to the surface and in the latter by its sensitivity to volcanic aerosols. However power-law behaviour in the tropics and in the free atmosphere saturates on multi-decadal timescales. We propose a novel diagnostic to evaluate the relative goodness-of-fit of the autoregressive model of the first order (AR1) and the power-law model. The collective behaviour of CMIP3 simulations appears to fall between the two statistical models. Our results suggest that the power-law model should serve as an upper bound and the AR1 model should serve as a lower bound for climate persistence on monthly to decadal time scales. On the applied side we find that the presence of power-law like natural variability increases the uncertainty on the long-term total ozone trend in the Northern Hemisphere high latitudes attributable to anthropogenic chlorine by about a factor of 1.5, and lengthens the expected time to detect ozone recovery by a similar amount.

Why do some first year students continue and others leave before their second year? This has been a pressing question for a number of years. Consequently, there has been a growing interest in examining the experiences of first-year post-secondary students and identifying the factors that are associated with their attrition and persistence. In Canada, there is a specific need to understand the experiences of the Aboriginal people. This group of individuals has shown significantly lower post-secondary completion rates than the non-Aboriginal population, and many view their participation in higher education as being the key to a better future. The purpose of this research was to explore factors associated with the adjustment and anticipated persistence of first year Aboriginal and non-Aboriginal students. To this end, the connections between adjustment, person-environment fit, anticipated persistence and a number of psychosocial and background variables were investigated using a quantitative-descriptive mixed method design. In the first part of the study, Aboriginal and non-Aboriginal participants within a university context and Aboriginal participants alone within a college environment were followed from the fall of their first year (N=316) to the spring of their first year (N=159) in order to examine the first year transition experience. In the second portion of the study, a subset of Aboriginal students (N=11) was interviewed about their post-secondary experiences in order to obtain a more comprehensive understanding of the transition experience. Full or partial support was found for the majority of the hypotheses related to adjustment, fit, and anticipated persistence. In the present study, academic, social and personal-emotional adjustment were each associated with subjective fit, beliefs about the transition experience, social support, and academic self-efficacy. Furthermore, each type of adjustment was also associated with additional unique correlates. This research also highlights that anticipated persistence is complex, with a number of background factors (e.g., high school preparation), psychosocial factors (e.g., beliefs about the transition experience, social support, academic self-efficacy) as well as adjustment and person-environment fit being relevant to this decision. In addition, this research highlights that Aboriginal students do not have poorer adjustment or fit compared to their non-Aboriginal peers but that they do have lower levels of anticipated persistence. A discussion of these and other findings as well as the implications and limitations of the present study is provided.

One of the main problems in statistical climatology is to construct a parsimonious model of natural climate variability. Such a model serves for instance as a null hypothesis for detection of human induced climate changes and of periodic climate signals. Fitting thismodel to various climatic time series also helps to infer the origins of underlying temporal variability and to cross validate it between different data sets. We consider the use of a spectral power-law model in this role for the surface temperature, for the free atmospheric air temperature of the troposphere and stratosphere, and for the total ozone. First, we lay down a methodological foundation for our work. We compare two variants of five different power-law fitting methods by means of Monte-Carlo simulations and their application to observed air temperature. Then using the best two methods we fit the power-law model to several observational products and climate model simulations. We make use of specialized atmospheric general circulation model simulations and of the simulations of the Coupled Model Intercomparison Project 3 (CMIP3). The specialized simulations allow us to explain the power-law exponent spatial distribution and to account for discrepancies in scaling behaviour between different observational products. We find that most of the pre-industrial control and 20th century model simulations capture many aspects of the observed horizontal and vertical distribution of the power-law exponents. At the surface, regions with robust power-law exponents—the North Atlantic, the North Pacific, and the Southern Ocean — coincide with regions with strong inter-decadal variability. In the free atmosphere, the large power-law exponents are detected on annual to decadal time scales in the tropical and subtropical troposphere and stratosphere. The spectral steepness in the former is explained by its strong coupling to the surface and in the latter by its sensitivity to volcanic aerosols. However power-law behaviour in the tropics and in the free atmosphere saturates on multi-decadal timescales. We propose a novel diagnostic to evaluate the relative goodness-of-fit of the autoregressive model of the first order (AR1) and the power-law model. The collective behaviour of CMIP3 simulations appears to fall between the two statistical models. Our results suggest that the power-law model should serve as an upper bound and the AR1 model should serve as a lower bound for climate persistence on monthly to decadal time scales. On the applied side we find that the presence of power-law like natural variability increases the uncertainty on the long-term total ozone trend in the Northern Hemisphere high latitudes attributable to anthropogenic chlorine by about a factor of 1.5, and lengthens the expected time to detect ozone recovery by a similar amount.

Why do some first year students continue and others leave before their second year? This has been a pressing question for a number of years. Consequently, there has been a growing interest in examining the experiences of first-year post-secondary students and identifying the factors that are associated with their attrition and persistence. In Canada, there is a specific need to understand the experiences of the Aboriginal people. This group of individuals has shown significantly lower post-secondary completion rates than the non-Aboriginal population, and many view their participation in higher education as being the key to a better future. The purpose of this research was to explore factors associated with the adjustment and anticipated persistence of first year Aboriginal and non-Aboriginal students. To this end, the connections between adjustment, person-environment fit, anticipated persistence and a number of psychosocial and background variables were investigated using a quantitative-descriptive mixed method design. In the first part of the study, Aboriginal and non-Aboriginal participants within a university context and Aboriginal participants alone within a college environment were followed from the fall of their first year (N=316) to the spring of their first year (N=159) in order to examine the first year transition experience. In the second portion of the study, a subset of Aboriginal students (N=11) was interviewed about their post-secondary experiences in order to obtain a more comprehensive understanding of the transition experience. Full or partial support was found for the majority of the hypotheses related to adjustment, fit, and anticipated persistence. In the present study, academic, social and personal-emotional adjustment were each associated with subjective fit, beliefs about the transition experience, social support, and academic self-efficacy. Furthermore, each type of adjustment was also associated with additional unique correlates. This research also highlights that anticipated persistence is complex, with a number of background factors (e.g., high school preparation), psychosocial factors (e.g., beliefs about the transition experience, social support, academic self-efficacy) as well as adjustment and person-environment fit being relevant to this decision. In addition, this research highlights that Aboriginal students do not have poorer adjustment or fit compared to their non-Aboriginal peers but that they do have lower levels of anticipated persistence. A discussion of these and other findings as well as the implications and limitations of the present study is provided.

<p>This dissertation places intersection homology and local homology within the framework of persistence, which was originally developed for ordinary homology by Edelsbrunner, Letscher, and Zomorodian. The eventual goal, begun but not completed here, is to provide analytical tools for the study of embedded stratified spaces, as well as for high-dimensional and possibly noisy datasets for which the number of degrees of freedom may vary across the parameter space. Specifically, we create a theory of persistent intersection homology for a filtered stratified space and prove several structural theorems about the pair groups asso- ciated to such a filtration. We prove the correctness of a cubic algorithm which computes these pair groups in a simplicial setting. We also define a series of intersec- tion homology elevation functions for an embedded stratified space and characterize their local maxima in dimension one. In addition, we develop a theory of persistence for a multi-scale analogue of the local homology groups of a stratified space at a point. This takes the form of a series of local homology vineyards which allow one to assess the homological structure within a one-parameter family of neighborhoods of the point. Under the assumption of dense sampling, we prove the correctness of this assessment at a variety of radius scales.</p> / Dissertation

<p>We study how the preimages of a mapping f : X &rarr Y between manifolds vary under perturbations. First, we consider the preimage of a single point and track the history of its connected component as this point varies in Y. This information is compactly represented in a structure that is the generalization of the Reeb graph we call the Reeb space. We study its local and global properties and provide an algorithm for its construction. Using homology, we then consider higher dimensional connectivity of the preimage. We develop a theory quantifying the stability of each homology class under perturbations of the mapping f . This number called robustness is given to each homology class in the preimage. The robustness of a class is the magnitude of the perturbation necessary to remove it from the preimage. The generality of this theory allows for many applications. We apply this theory to quantify the stability of contours, fixed points, periodic orbits, and more.</p> / Dissertation

How to evaluate mutual fund performance correctly and determine the investment targets of mutual funds are the important issues to investors. In this study, we apply an innovative bootstrap statistical technique, to solve the small sample size problem and the distribution assumption disturbance in previous research. We examine the performance of domestic open-end mutual funds over the period from 1998 to 2003 using five performance measurement models. We further test the persistence of mutual fund performance. This study shows that¡G 1. On average, mutual fund managers do not own superior ability in stock selection. Most funds experiencing abnormal performance may simply result from good luck, since random selection also creates abnormal performance. 2. Mutual fund managers do not own market-timing ability. Classified further by investment objectives, the sample indicates that only the group of small-scale stocks shows significant market-timing ability. 3. Performance persistence does not exist no matter in long-term or short-term period.

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