We study and analyze the performance of iterative equalization and decoding (IED) using an M-BCJR equalizer. We use bit error rate (BER), frame error rate simulations and extrinsic information transfer (EXIT) charts to study and compare the performances of M-BCJR and BCJR equalizers on precoded and non-precoded channels. Using EXIT charts, the achievable channel capacities with IED using the BCJR, M-BCJR and MMSE LE equalizers are also compared. We predict the BER performance of IED using the M-BCJR equalizer from EXIT charts and explain the discrepancy between the observed and predicted performances by showing that the extrinsic outputs of the $M$-BCJR algorithm are not true logarithmic-likelihood ratios (LLR's). We show that the true LLR's can be estimated if the conditional distributions of the extrinsic outputs are known and finally we design a practical estimator for computing the true LLR's from the extrinsic outputs of the M-BCJR equalizer.

Complexity theory studies the workings of complex adaptive systems (CAS). A complex adaptive system can adapt and change in response to information it gathers from its environment. It responds to feedback by changing its actions, and develops new activities, learning capacity and ability to innovate. Complex adaptive systems depend on information flow through linked networks of individuals and groups, such as those present in cities or communities. Hornby Island, a small northern gulf island in British Columbia, Canada, possesses the characteristics of a complex adaptive system and is used to provide examples of how complexity theory can be applied and used by a community. Observations from Hornby Island and the use of SWOT analysis (strengths, weaknesses, opportunities and threats) have provided insight to the applicability and usefulness of complexity theory in the theoretical and local action contexts of community development. Misunderstandings between the scientific and humanitarian backgrounds of complexity and community development theories represent weaknesses and pose some threats to the field of community development. However, complexity theory also possesses strengths that have the potential to provide community development practitioners and communities with opportunities, such as tools and ideas, to better adapt to change. The following opportunities for learning and action within communities are suggested and expanded upon in this thesis: human led creative adaptation; location of mal-adaptive schemata; education for adaptive schemata; reducing and changing mal-adaptive schemata; guidelines and generalizations; and intangibles and legitimization of actions. This thesis concludes that complexity theory is applicable and useful to community development because it strengthens other theories and concepts related to community development; helps frame what goes on in the community; and locates focuses for change. It also provides new tools and ideas for action, to communities and practitioners, to better deal with change and create resilient communities.

Darbe tiriamas kėlinių, derinių, poaibių ir Grėjaus kodų generavimo algoritmų sudėtingumas. Atliekama algoritmų analizė. Tyrimo tikslams sukurta programa realizuojanti minėtus algoritmus. / The complexity research of permutations, combinations, subsets and Gray codes generating algorithms is provided in this paper. Algorithms are analyzed and implemented in the application developed for research purposes.

Drawing on social movement literature, my thesis examines if news media, NGO, business and government engagement of the BP Oil Spill in the Gulf of Mexico is affected by issue or event complexity, visuality, or issue build-up. To engage this, data from English language newspaper articles in the US, Canada, and the UK, press releases by Greenpeace and Sierra Club, press releases by BP, ExxonMobil, and Shell as well as press releases by the White House are analyzed using both quantitative and qualitative methods. I find that as an issue or event’s casual narrative becomes less complicated and as it becomes easier to portray visually its engagement by social and political actors increases. I also find that issue engagement is influenced by whether or not social and political actors signal an issue or an event’s importance to others.

Despite rapidly burgeoning diversity in the Canadian workforce, and demonstrable gains to be made as a result of increasing inclusion, organizations still struggle to create meaningfully inclusive workplaces. The traditional diversity management model has largely failed to fix this longstanding problem. A variety of research has identified successful strategies for increasing inclusion across disciplines such as social psychology, critical management studies, systems theory, and universal design. However, these overlapping strategies, as well as the commonalities of underlying structure, go unseen due to ideological and disciplinary siloing. Working from a foundation of theoretical pluralism, I present two linked ideas in this paper. First, I propose and justify a shift in language from the counter-productive <italic>diversity management</italic> towards <italic>meaningful inclusion</italic>. Second, using multi-disciplinary research I identify successful, broadly-applicable strategies for enhancing meaningful inclusion in the workplace, and describe an <italic>inclusion matrix</italic> of best practices that creates a practical road map organizations can use to enhance meaningful inclusion.

Knapsack problem has been widely studied in computer science for years. There exist several variants of the problem, with zero-one maximum knapsack in one dimension being the simplest one. In this thesis we study several existing approximation algorithms for the minimization version of the problem and propose a scaling based fully polynomial time approximation scheme for the minimum knapsack problem. We compare the performance of this algorithm with existing algorithms. Our experiments show that, the proposed algorithm runs fast and has a good performance ratio in practice. We also conduct extensive experiments on the data provided by Canadian Pacific Logistics Solutions during the MITACS internship program. We propose a scaling based e-approximation scheme for the multidimensional (d-dimensional) minimum knapsack problem and compare its performance with a generalization of a greedy algorithm for minimum knapsack in d dimensions. Our experiments show that the e- approximation scheme exhibits good performance ratio in practice. / x, 85 leaves ; 29 cm

Due to the exponential growth of the dimension of the space of tensors V_(1)⊗• • •⊗V_(n), any naive method of representing these tensors is intractable on a computer. In practice, we consider feasible subspaces (subvarieties) which are defined to reduce the storage cost and the computational complexity. In this thesis, we study two such types of subvarieties: the third secant variety of the product of n projective spaces, and tensor network states. For the third secant variety of the product of n projective spaces, we determine set-theoretic defining equations, and give an upper bound of the degrees of these equations. For tensor network states, we answer a question of L. Grasedyck that arose in quantum information theory, showing that the limit of tensors in a space of tensor network states need not be a tensor network state. We also give geometric descriptions of spaces of tensor networks states corresponding to trees and loops.

Complexity theory investigates complex systems and how parts of a system give rise to collective behaviours. My thesis focuses upon the nature of the complex systems emerging within the classrooms of three award-winning high school physics teachers in Ontario. Using vignettes for each teacher and their classroom system, I have highlighted themes related to the emergence of collective behaviours. My interpretations found the first classroom collective agreeing to work towards academic excellence with the intention of achieving success in university. The second classroom collective was invested in relationship-building and used the resulting emphasis on teamwork and group-oriented learning to further physics understanding. The final classroom system was in the process of learning to grapple with discovering physics through following and contending with the results of their instincts. From a complex systems perspective, differences amongst teachers and students and different sets of interactions result in unique systems. Therefore, a single prescription for the emergence of certain collective behaviours is unlikely. The journal/commentary format traces my changing understandings of complexity thinking in education and how those understandings made an impact on the way I approached and reflected upon the observations of the study. As such, the thesis also documents shifts in perspectives highlighting the tensions felt between reductionist and complexivist thinking. Ultimately, complexity thinking illuminated how important it was to consider the teacher as part of the system instead of separated from it. Further issues relating to complex emergence and physics education that lead to greater pedagogical awareness are discussed. / Thesis (Master, Education) -- Queen's University, 2007-07-18 13:48:42.481

Comparing protein structures based on their contact maps is an important problem in structural proteomics. Building a system for reconstructing protein tertiary structures from their contact maps is one of the motivations for devising novel contact map comparison algorithms. Several methods that address the contact map comparison problem have been designed which are briefly discussed in this thesis. However, they suggest scoring schemes that do not satisfy the two characteristics of “metricity” and “universality”. In this research we investigate the applicability of the Universal Similarity Metric (USM) to the contact map comparison problem. The USM is an information theoretical measure which is based on the concept of Kolmogorov complexity. The ultimate goal of this research is to use the USM in case-based reasoning system to predict protein structures from their predicted contact maps. The fact that the contact maps that will be used in such a system are the ones which are predicted from the protein sequences and are not noise-free, implies that we should investigate the noise-sensitivity of the USM. This is the first attempt to study the noise-tolerance of the USM. In this research, as the first implementation of the USM we converted the two-dimensional data structures (contact maps) to one-dimensional data structures (strings). The results of this implementation motivated us to circumvent the dimension reduction in our second attempt to implement the USM. Our suggested method in this thesis has the advantage of obtaining a measure which is noise tolerant. We assess the effectiveness of this noise tolerance by testing different USM implementation schemes against noise-contaminated versions of distinguished data-sets. / Thesis (Master, Computing) -- Queen's University, 2008-09-27 05:53:31.988

Software security failures are common and the problem is growing. A vulnerability is a weakness in the software that, when exploited, causes a security failure. It is difficult to detect vulnerabilities until they manifest themselves as security failures in the operational stage of the software, because security concerns are often not addressed or known sufficiently early during the Software Development Life Cycle (SDLC). Complexity, coupling, and cohesion (CCC) related software metrics can be measured during the early phases of software development such as design or coding. Although these metrics have been successfully employed to indicate software faults in general, the relationships between CCC metrics and vulnerabilities have not been extensively investigated yet. If empirical relationships can be discovered between CCC metrics and vulnerabilities, these metrics could aid software developers to take proactive actions against potential vulnerabilities in software. In this thesis, we investigate whether CCC metrics can be utilized as early indicators of software vulnerabilities. We conduct an extensive case study on several releases of Mozilla Firefox to provide empirical evidence on how vulnerabilities are related to complexity, coupling, and cohesion. We mine the vulnerability databases, bug databases, and version archives of Mozilla Firefox to map vulnerabilities to software entities. It is found that some of the CCC metrics are correlated to vulnerabilities at a statistically significant level. Since different metrics are available at different development phases, we further examine the correlations to determine which level (design or code) of CCC metrics are better indicators of vulnerabilities. We also observe that the correlation patterns are stable across multiple releases. These observations imply that the metrics can be dependably used as early indicators of vulnerabilities in software. We then present a framework to automatically predict vulnerabilities based on CCC metrics. To build vulnerability predictors, we consider four alternative data mining and statistical techniques – C4.5 Decision Tree, Random Forests, Logistic Regression, and Naïve-Bayes – and compare their prediction performances. We are able to predict majority of the vulnerability-prone files in Mozilla Firefox, with tolerable false positive rates. Moreover, the predictors built from the past releases can reliably predict the likelihood of having vulnerabilities in future releases. The experimental results indicate that structural information from the non-security realm such as complexity, coupling, and cohesion are useful in vulnerability prediction. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2009-09-24 17:31:36.581