This research attempts to establish that landscapes can support and enhance a business identity program. Previous environmental perception research has investigated affective and cognitive responses to natural landscapes, but little, if any, research has explored the area of meaning in a business landscape. Consequently, this study develops a theoretical framework from which to demonstrate a business identity in the landscape. In an effort to structure a framework for both affective and cognitive meanings in business environments, this study draws on past environmental perception research that focuses on affective responses to molar environments. From out of this research design, affective and cognitive dimensions are identified that allow testing of business identities in the environment. Findings show that landscapes can support and enhance an overall business identity program. The study concludes with a discussion of future research that might further the benefits of landscapes to the business community.

No description available.

Experimental verification of a novel system identification technique that can detect defects at the element level is successfully accomplished. The method can be used for in-service health assessment of real structures without disrupting normal operations. This study conclusively verifies the method.Analytical verification of the proposed algorithm has been successfully completed by the research team at the University of Arizona. Vo and Haldar (2004) experimentally verified the method by conducting tests on fixed-ended and simply supported defect-free and defective beams. The purpose of this research was to validate the method by conducting experiments with more realistic structures. A three-story one-bay steel frame, built to 1/3 scale to fit the experimental facility, was considered. The frame was excited by harmonic or impulsive excitation forces. The transverse acceleration responses were collected using capacitive accelerometers. The angular displacement responses were measured using an autocollimator. The dynamic responses of the frames were collected by a data acquisition system with simultaneous sampling capability. Using only experimentally collected response information and completely ignoring the excitation information, the stiffness of all the structural elements were identified. The method identified the defect-free frame very accurately. Defects, in terms of removing a beam, reducing cross sectional area over a small segment of a beam, and cutting notches in a beam, were introduced. The method correctly identified the defect location in all cases. Additional sensors were placed around the location of the defect in an effort to identify the defect spot more accurately. The proposed method also successfully identified defect with improved accuracy. To increase the implementation potential of the proposed method, the defect-free and defective frames are then identified using limited response information. A two-stage Kalman filter-based approach is used. It is denoted as Generalized Iterative Least Square Extended Kalman Filter with Unknown Input (GILS-EKF-UI) method. A sub-structure approach is used for this purpose. The GILS-EKF-UI method also identified the state of the structure using only limited response information. As expected, in this case the error in the identification goes up as less information is used. However, the error is much smaller than other methods currently available in the literature, even when input excitation was used for the identification purpose. The method is very robust and can identify defects caused by different types of loadings. The method can be used as a nondestructive defect assessment technique for structures.

An important aspect of sustainable development is the social impacts from the consumption of goods and services. A recently developed method for social life cycle assessment (S-LCA) assesses the potential positive and negative social impacts along a product’s life cycle, while avoiding shifting negative impacts from one part of the supply chain to another. This thesis evaluated the applicability of S-LCA in three case studies, as well as a way of introducing an ethical perspective on the distribution of social impacts among stakeholders. The case study of laptop computers identified workers and the local community as the stakeholders at greatest risk of negative social impacts, with China, Russia, Saudi Arabia, Thailand and Brazil being most prone to these impacts. A case study of vehicle fuels identified some fossil and some renewable fuels with high or very high risks of negative impacts, suggesting a need for strict procurement requirements on social performance for all types of vehicle fuels. A study of e-waste recycling in Pakistan revealed negative social impacts on workers and the community, while decreasing poverty by providing employment. By performing a social hotspot assessment using S-LCA methodology, much can be learned about the potential social impacts associated with a product’s life cycle, and potentially important aspects that would otherwise have been neglected can be identified. Some methodological issues of S-LCA requiring further attention are: Indicator relevance. Impact pathways between indicators and performance assessment on social issues must be examined and improved. Aggregation and weighting of impacts and indicators. With major uncertainties still present, results must be transparent, but also aggregated for the purposes of interpretation and communication. Assessment of the use phase. To be more complete, S-LCA methodology needs to be complemented with an assessment of the use phase. Introduction of context. Identifying the context of relevant stakeholders in different parts of the life cycle would allow identification of the greatest leverage in improvement of social conditions. / En viktig del av hållbar utveckling är att hantera social påverkan från konsumtionen av varor och tjänster. Social livscykelanalys (S - LCA) är en metod som syftar till att bedöma positiv och negativ social påverkan av produkter under hela deras livscykel och samtidigt undvika att bara flytta negativ påverkan från en del av livscykeln till en annan. Denna avhandling utvärderar S - LCA i tre fallstudier, samt undersöker hur fördelningen av den sociala påverkan på olika intressentgrupper kan bedömas ur ett etiskt perspektiv. I en fallstudie som utfördes på en laptop identifierades arbetstagare och lokalsamhället som de intressenter, som löper störst risk för negativ social påverkan. Länder som Kina, Ryssland, Saudiarabien, Thailand och Brasilien var de som var mest kopplade till denna påverkan. En fallstudie kring fordonsbränslen visade att av de bränslen som bedömts uppvisade både en del fossila och en del förnybara bränslen höga eller mycket höga risker för negativ social påverkan, vilket tyder på att strikta upphandlingskrav gällande social prestanda behövs för alla typer av drivmedel. En studie av återvinning av elektroniskt avfall i Pakistan uppvisade påtaglig negativ social påverkan på arbetstagarna och lokalsamhället, samtidigt som återvinningen gav sysselsättning som minskar fattigdomen. Genom att använda S-LCA vid bedömningen av en produkt finns det mycket att lära om potentiell social påverkan från produktens livscykel. Viktiga aspekter, som annars riskerar att missas, kan nu identifieras med S-LCA. Metoden är dock inte färdigutvecklad, och metodfrågor som behöver ytterligare uppmärksamhet är: Relevanta indikatorer. Kopplingen mellan indikatorerna och den påverkan man försöker mäta måste undersökas närmare och förbättras. Sätt att aggregera och väga ihop påverkan. Med tanke på de osäkerheter som ännu så länge finns kring metoden måste resultaten hållas transparenta, samtidigt som sammanfattande resultat behövs för tolkning och kommunikation. Påverkan i användningsfasen. För att bli mer komplett, måste metoden kompletteras med en bedömning av social påverkan i användningsfasen. Sätta resultaten i sitt sammanhang. Utgångsläget för dem, som berörs av en produkts sociala påverkan avgör vilken hävstångseffekt en förbättring av de sociala förhållandena kan ha, och kan därmed påverka vilka åtgärder som bör prioriteras. / <p>QC 20131217</p>

This study is a narrative self-study that reflects on the relationship between knowledge of assessment practice and theory and factors that lead to a change in practice. There are a variety of ways to use assessment as a teacher in school settings, and this paper explores how the researcher-subject developed and changed assessment practices to inform her teaching, to assist her students in attaining mastery of curricular outcomes, and to report student achievement to parents and school administrators. While tackling this complex topic, one discovers there is not one best way to assess student learning. Deciding to learn more about assessment demonstrating a willingness to try new assessment methods, to grow from successes and failures, and to look introspectively and critically current assessment practices, the result can be a more valid assessment of what a student knows and can do, and a more informed understanding of good teaching and assessment practices.

Many infrastructure networks rely on each other to deliver utilities and services to the community. In the event of a disaster, these networks can sustain significant damage. It is therefore important to identify interdependencies among networks to mitigate the disaster consequences. In 2003, Public Safety Canada (PSC) and NSERC initiated the Joint Infrastructure Interdependencies Research Program (JIIRP) for this purpose. The research was carried out at six Universities across Canada including the University of British Columbia (UBC). The aim of JIIRP at UBC was to study infrastructure interdependencies during disasters in order to aid in decision making. This involved the development disaster simulation methodology and tool, and the implementation of a case study. UBC's Point Grey campus was used as case study. The campus is located in southwestern British Columbia, a known seismic zone, therefore earthquake disaster scenario was chosen. Reasonable estimations of the expected seismic damage and losses are required in order to simulate a realistic disaster scenario. For this reason, in this thesis, seismic risk assessment was carried out for the buildings at UBC. This involved the development of a building database, the assessment of the expected level of damage to the structural and nonstructural building components, and the estimation of monetary, human and functionality losses. Buildings in the database were classified into prototypes and the damage was estimated for several levels ofintensity using damage probability matrices. As expected, the most vulnerable buildings on campus were those containing unreinforced masonry. These buildings make up 7% of the buildings on campus. The least vulnerable buildings were multi-family residential woodbuildings which account for 27% of the buildings on campus. Losses were estimated following the damage assessments. Casualties were estimated for three times of day. 2PM was determined to be the critical time of day as the campus population is the greatest at this time. Monetary loss and functionality trends were examined with respect to earthquake intensity and it was shown that for moderate intensity earthquakes, the losses depend primarily on nonstructural damage, while structural damage plays the most important role for higher intensities.

Cross validation (CV) is widely used for model assessment and comparison. In this thesis, we first review and compare three v-fold CV strategies: best single CV, repeated and averaged CV and double CV. The mean squared errors of the CV strategies in estimating the best predictive performance are illustrated by using simulated and real data examples. The results show that repeated and averaged CV is a good strategy and outperforms the other two CV strategies for finite samples in terms of the mean squared error in estimating prediction accuracy and the probability of choosing an optimal model. In practice, when we need to compare many models, conducting repeated and averaged CV strategy is not computational feasible. We develop an efficient sequential methodology for model comparison based on CV. It also takes into account the randomness in CV. The number of models is reduced via an adaptive, multiplicity-adjusted sequential algorithm, where poor performers are quickly eliminated. By exploiting matching of individual observations, it is sometimes even possible to establish the statistically significant inferiority of some models with just one execution of CV. This adaptive and computationally efficient methodology is demonstrated on a large cheminformatics data set from PubChem. Cross validated mean squared error (CVMSE) is widely used to estimate the prediction mean squared error (MSE) of statistical methods. For linear models, we show how CVMSE depends on the number of folds, v, used in cross validation, the number of observations, and the number of model parameters. We establish that the bias of CVMSE in estimating the true MSE decreases with v and increases with model complexity. In particular, the bias may be very substantial for models with many parameters relative to the number of observations, even if v is large. These results are used to correct CVMSE for its bias. We compare our proposed bias correction with that of Burman (1989), through simulated and real examples. We also illustrate that our method of correcting for the bias of CVMSE may change the results of model selection.

No description available.

No description available.

Stroke is a condition that arises from partial or complete blockage of blood flow to parts of the brain. Upper limb impairments (sensorimotor deficits) usually occur as a result of stroke. Assessment and diagnosis of the resulting upper limb impairments is important for effective rehabilitation and proper recovery. In terms of assessment, current ordinal scale systems used are inherently subjective and incorporate coarse rating scores (Chedoke McMaster, Fugel Meyer test, etc.). These scores do not provide clinicians with information regarding the underlying impairments which is important for effective rehabilitation therapy. We investigated the use of a reaching task on a bi-lateral upper limb robotic device (KINARM), developed by one of our team members (Stephen Scott), to assess upper limb impairments due to stroke. Control and stroke subjects were instructed to reach with both arms on the robotic device to illuminating spatial targets as quickly and as accurately as possible. We first developed a tool that would aid in locating targets where reaching impairments are visible for stroke subjects. From the Kinematic data collected, we then selected reaction time and first peak velocity of the hand and investigated their potential for separating control and stroke subjects. Results of our analysis showed the potential of both parameters as good quantitative assessment measures. In particular results for reaction time presented symmetrical differences between both arms were of main interest in this thesis. Such differences presented the potential of sensitivity in showing subtle impairments. / Thesis (Master, Computing) -- Queen's University, 2007-09-25 11:54:00.694