identifier: Salimi, Shide  (2019) Simulation-Based Optimization of Energy Consumption and Occupants Comfort in Open-Plan Office Buildings Using Probabilistic Occupancy Prediction Model.  PhD thesis, Concordia University.

abstract:
Considering the ever-growing increase in the world energy consumption and the fact that buildings contribute a large portion of the global energy consumption arises a need for detailed investigation towards more effective energy performance of buildings. Thus, monitoring, estimating, and reducing buildings’ energy consumption have always been important concerns for researchers and practitioners in the field of energy management. Since more than 80% of energy consumption happens during the operation phase of a building’s life cycle, efficient management of building operation is a promising way to reduce energy usage in buildings. Among the parameters influencing the total building energy consumption, building occupants’ presence and preferences could have high impacts on the energy usage of a building. To consider the effect of occupancy on building energy performance, different occupancy models, which aim to estimate the space utilization patterns, have been developed by researches. However, providing a comprehensive occupancy model, which could capture all important occupancy features, is still under development. Moreover, researchers investigated the effect of the application of occupancy-centered control strategies on the efficiency of the energy-consuming systems. However, there are still many challenges in this area of research mainly related to collecting, processing, and analyzing the occupancy data and the application of intelligent control strategies. In addition, generally, there is an inverse relationship between the energy consumption of operational systems and the comfort level of occupants using these systems. As a result, finding a balance between these two important concepts is crucial to improve the building operation. The optimal operation of building energy-consuming systems is a complex procedure for decision-makers, especially in terms of minimizing the energy cost and the occupants’ discomfort.
On this premise, this research aims to develop a new simulation-based multi-objective optimization model of the energy consumption in open-plan offices based on occupancy dynamic profiles and occupants’ preferences and has the following objectives: (1) developing a method for extracting detailed occupancy information with varying time-steps from collected Real-Time Locating System (RTLS) occupancy data. This method captures different resolution levels required for the application of intelligent, occupancy-centered local control strategies of different building systems; (2) developing a new time-dependent inhomogeneous Markov chain occupancy prediction model based on the derived occupancy information, which distinguishes the temporal behavior of different occupants within an open-plan office; (3) improving the performance of the developed occupancy prediction model by determining the near-optimum length of the data collection period, selecting the near-optimum training dataset, and finding the most satisfying temporal resolution level for analyzing the occupancy data; (4) developing local control algorithms for building energy-consuming systems; and (5) integrating the energy simulation model of an open-plan office with an optimization algorithm to optimally control the building energy-consuming systems and to analyze the trade-off between building energy consumption and occupants’ comfort. It is found that the occupancy perdition model is able to estimate occupancy patterns of the open-plan office with 92% and 86% accuracy at occupant and zone levels, respectively. Also, the proposed integrated model improves the thermal condition by 50% along with 2% savings in energy consumption by developing intelligent, optimal, and occupancy-centered local control strategies.


identifier: Narayana, Manasvini  (2019) The Spatial Turn in History: Implications for Curriculum in Higher Education.  PhD thesis, Concordia University.

type: Thesis NonPeerReviewed

abstract:
The emergence of visualization and spatialization technologies, such as digital maps, Geographic Information Systems (GIS), and data visualization is generating new ways of knowing within academic disciplines. This epistemological shift, or “spatial turn,” like the Quantitative or Cultural Turns before it, impacts the ways in which knowledge is created, consumed, and communicated. New jobs that require spatial skills are coming into being. It is reasonable to expect, therefore, that education in general, and curricula in particular, would respond to this shift. This thesis explores the curricular responses to spatial ways of knowing in higher education, using the case of one academic discipline–History. The dissertation investigates through a case study, five inter-related aspects of the spatial turn in History: The creation and communication of History knowledge through spatial means, work and employment of History graduates with spatial skills, teaching and learning in higher education with respect to spatial ways of knowing, tools and technologies that drive the spatial turn, and the perspectives of History professors and students with respect to spatial ways of knowing. I explore each aspect separately and use them to triangulate my findings, before synthesizing them into conclusions.

The findings indicate spatial ways of knowing are still a niche area in History as far as creating History knowledge is concerned. In addition, spatial History is decidedly interdisciplinary, and scholars and the professional community take a variety of approaches to navigate this interdisciplinarity. Several career opportunities exist both within and outside academia for the spatially oriented Historian, but this is not a factor that traditional History departments consider when determining curricula. However, a wide range of online learning resources are available with respect to spatial ways of knowing, should students wish to pursue this line of learning in addition to their regular History education. Geo-spatial and visual-spatial tools present their own set of challenges to Historians, and I analyze how they contribute to the complexity of teaching spatial ways of knowing. I conclude that although spatial ways of knowing offer History some unique possibilities for generating knowledge, the curricular response to them is mixed. I offer some recommendations for possible ways in which History higher education curricula may respond to the spatial turn.


identifier: Dhanvantari, Sujaya  (2019) Beauvoir, Fanon, and the Existential Ethics of Liberation: An Anticolonial Inheritance for New Revolutions.  PhD thesis, Concordia University.

abstract:
Beauvoir, Fanon, and the Existential Ethics of Liberation investigates existential theories of liberation to provide an ethics for contemporary revolutionary movements. Existential humanism must now be mobilized for its politico-ethical critique, despite the many posthumanist critiques. Post-WWII liberation struggles, which were oriented by existential humanism and ethics, offer important guidelines for the conduct of today’s liberation struggles. Yet, Beauvoir’s ethics and its linkage to Fanon’s anticolonial philosophy remain undertheorized. I argue that examining Beauvoir’s understanding of liberation in terms of her ethics and putting Fanon’s view of anticolonial liberation into the context of Beauvoir’s ethics can help to rethink liberation for today.
My account traces the concept of liberation via existential humanism across their works. I draw out a dialogical relation between Beauvoir and Fanon to show their critical intersections vis-à-vis liberation. I argue that Fanon redeploys Beauvoir’s concept of authoritarian seriousness to critique colonial power; mobilizes Beauvoir’s legitimation of revolutionary violence to argue for violent action against the colonizer; and, finally, advances Beauvoir’s concept of intersubjectivity to open up the question of the human beyond colonization. Yet, I claim, Fanon implicitly critiques Beauvoir for neglecting the colonized other’s agency. Fanon offers another concept of liberation, in which the colonized becomes instrumental to the goal of resisting the colonial permutations of oppressive power.
Following both existentialist thinkers, who account for concrete realities to substantiate ethical action, I develop an ethics attentive to the lived experience of the oppressed. In so doing, I demonstrate that their concepts of oppression, revolution, and freedom provide possible historical and critical resources for interpreting contemporary social and political crises. In order to address violent ontologies, liberation must today be thought in relation to the resurgence of violence, the recurrence of oppressive power, and the longue durée of colonial racism. Drawing attention to the urgency of ethics, Beauvoir, Fanon, and the Existential Ethics of Liberation shows that existential humanism comprises an anticolonial inheritance for radical black and anti-racist politics, feminism, environmental justice, and anti-fascist and anti-capitalist movements.


identifier: Ma, Li  (2019) Optimization of Passive Solar Design and Integration of Building Integrated Photovoltaic/Thermal (BIPV/T) System in Northern Housing.  Masters thesis, Concordia University.

abstract: With the growing concerns about climate change, Northern Canada is aiming to adopt a “net-zero ready” model building code by 2030. Northern Canada has its unique environmental loads and challenges – namely, the extremely cold climate and the high expense, as the north imports most of its materials and fuel from the south. Significant energy savings could be achieved by optimizing the design of building envelopes and integrating solar design strategies, with a little added construction cost. This thesis focuses on optimizing the passive solar design parameters and the use of thermal and electrical energy from building integrated photovoltaic/thermal (BIPV/T) system as moves toward net-zero energy housing in northern Canada. A reference house representing the typical residential building in northern regions is modeled in EnergyPlus software to study the building design parameters, including thermal resistance of the building envelope, thermal mass, window-wall ratio, shading schedule and ventilation rate. The optimization is carried out by coupling EnergyPlus and Matlab using a multi-objective genetic algorithm. The optimal house under a 25-year life cycle in Yellowknife, NWT, could achieve a 46% energy savings with an initial construction cost increase of 10%. Based on this optimized house, the optimal use of thermal energy produced by a BIPV/T system is evaluated by integration with the space heating system, heat recovery ventilation (HRV) and air-source heat pump (ASHP). Simulation results show that a BIPV/T system with a space heating system can reduce total energy consumption by 15.5%, a BIPV/T system with a HRV could decrease the frost risk time by 8.8% and defrost time by 7.8%, and a BIPV/T system with an ASHP could extend the ASHP working period by 128 hours and increase the annual COP about 2.5%.


identifier: Merino Gordo, Felipe  (2019) Evaluating the Effect of Wind-induced Exfiltration on the Hygrothermal Performance of Walls of Low-rise Buildings.  Masters thesis, Concordia University.

abstract:
With the increasing levels of insulation employed for energy saving purposes, building envelopes require a reliable hygrothermal analysis to avoid mould and other moisture-related problems. Air leakage has long been identified as one of the primary drivers of moisture transport through building envelopes. Wind is always mentioned as one of the three driving forces of air leakage, but seldom is wind explicitly considered for hygrothermal analysis. In other words, under current practice, hygrothermal analysis will yield exactly the same result regardless of whether the building is in a windy or a windless area.

This study focused on identifying the wind speed and wall orientation that would increase the risk of developing mould in the wall assemblies for a low-rise building. Wind pressure coefficients were used to calculate wind-induced pressure differentials acting across the walls which were then integrated into the Air Infiltration Model. Design variables were structured into a parametric study. The wall performance was evaluated in a heat, air, and moisture (HAM) simulation program.

Through a parametric study this thesis has qualitatively illustrated that wind-induced exfiltration can have a significant effect on the hygrothermal performance of walls of low-rise buildings, and that under some conditions, if wind is ignored mould risk can be underestimated. Based on the limited work of this study, wind speeds under which mould is more likely to be underestimated
were quantified, the corresponding wind speed values are not meant to be definitive but rather a demonstration that a similar guideline is worthwhile to be developed.


identifier: Cen, Yusheng  (2019) Institutional Ownership and Firm Performance: A Global Analysis.  Masters thesis, Concordia University.

abstract: In this thesis, I analyze the roles of different institutional investors and how they affect firm performance based on a global dataset of 31 countries (regions) from 2007 to 2016. Breaking down institutions by geographic information (domestic or foreign) and type (such as mutual fund or pension funds), I first find that all institutions share preference for large firms, firms that experienced negative stock returns, and firms with lower leverage and high liquidity. I also find that various types of institutional investors affect firms’ operating performance differently. The relation is convex for foreign institutions, while the opposite is true for domestic institutions. This indicates that foreign institutional investors exert better corporate governance when ownership is high, while domestic institutions are subject to business ties with firms when they hold substantial amounts of voting rights. Further analysis reveals a U-shaped relationship between firms’ operating performance and the ownership level of investment advisors/bank trusts/pension funds, indicating a monitoring effect with high levels of ownership. However, mutual funds exhibit a concave influence on firm value, signifying negative impact of business ties when ownership is high. The findings for other types of institutions (hedge fund and insurance companies) are inconclusive.


identifier: Mohseni, Vahid  (2019) A Comparative Study of Greenhouse Gases Produced by Membrane Bioreactors, Submerged Membrane Electro Bioreactors and Lagoons During Wastewater Treatment Process.  Masters thesis, Concordia University.

abstract: Climate change is without a doubt the most important environmental issues of our age. Numerous studies have indicated the climate change and its effects are attributed to anthropogenic activities emitting CO2, CH4, N2O and other greenhouse gases. Wastewater treatment plants and their discharge account for 7.6% of the total emissions. The main objective of this study was to investigate greenhouse gases generated by two advanced wastewater treatment methods: conventional membrane bioreactor (MBR) and novel submerged membrane electro bioreactor (SMEBR). Subsequently, outcomes from both systems in lab scale were compared to the most popular wastewater treatment method, the lagoon systems, which account for 80% in Canada. This study comprises four phases. In phase 1, the 7 L MBR system was set up and run based on synthetic wastewater, simulating discharge to lagoons in in a municipality in Quebec. Subsequently, gas emissions were collected and analyzed. In phase 2, a submerged membrane electro-bioreactor, with identical technological parameters as MBR in phase 1, was submitted to investigations, where its emitted gases were also analyzed. In phase 3, a larger MBR was exposed to biogas measurements. Then, it was transformed to SMEBR while gas measurements continued. In phase 4, gas emissions from lagoons were estimated and compared to the outcomes from phases 1, 2 and 3. Results showed that the MBR produced around 22 g of CO2 equivalent per litre of wastewater per day, while the SMEBR generated around 12 g CO2 eq/L per day. In phase 3, the MBR transformation to SMEBR permitted to decrease the gas production while improving the ammonia removal efficiency. Phase 4 showed that the SMEBR reactor generated less N2O when compared to other investigated systems. It was concluded that the SMEBR system produced the lowest amounts of N2O per litre of wastewater, while showing superiority in nutrient removal. It is an important information from the point of view of sustainability and climate change prevention.


identifier: Rozsa, Irene  (2019) On the Edge of the Screen: Film Culture and Practices of Noncommercial Cinema in Cuba (1948-1966).  PhD thesis, Concordia University.

abstract:
The place of Cuban cinema in the film-historical canon is limited to the history of the Cuban film institute (ICAIC) founded in the early days of the Cuban Revolution, in 1959. This dissertation investigates the island’s film culture in the years prior, commonly referred to as the republican period, to establish its contributions to post-revolutionary developments. I examine the practices of film culture and noncommercial cinema in Cuba, tracing their evolution from 1948 to 1966. I research the development of the film course offered at the University of Havana and explain the formative impact of film education on future film promoters, film critics, and filmmakers. I also document the distinct cine club communities constituted around non-theatrical film exhibition, elucidating their role in the diversification of the 1950s film public and on the configuration of an identifiable art cinema audience. In addition, I provide background on the history of amateur filmmaking on the island. Furthermore, I analyze the elements that contributed to ICAIC’s hegemonic position within the country’s cultural landscape, including their acquisition of material assets, their privileged access to mediated forms of public discourse, and their concerted strategies for transforming popular taste. I argue that post-revolutionary institutionalized film culture was built upon its pre-revolutionary antecedents, and that the process of audience diversification that started in the 1950s persisted despite the policies implemented in the 1960s to centralize film exhibition and programming, to emphasize ideological interpretation in film criticism, and to restrict amateur filmmaking. My investigation demonstrates the gradual formation of a new two-tier system in which both elite and unsophisticated inclinations continued to coexist, and that resourceful amateurs found clandestine ways to make films outside of institutional channels.

This study contributes to Cuban film historiography by restoring continuity to the island’s cinematic past. I challenge perspectives that ignore the transnational exchanges and the modernizing forces at play during the late republican period. In adopting a more expansive conception of film history –one that is not strictly concerned with film production and the filmic text, but integrates exhibition, distribution, promotion, and knowledge dissemination–  I establish multiple threads that connect pre-revolutionary and post-revolutionary developments.


identifier: Elderhalli, Yassmeen  (2019) Dynamic Dependability Analysis using HOL Theorem Proving with Application in Multiprocessor Systems.  PhD thesis, Concordia University.

abstract:
Dynamic dependability analysis has become an essential step in the design process of safety-critical systems to ensure the delivery of a trusted service without failures. Dependability usually encompasses several attributes, such as reliability and availability. A dynamic dependability model is created using one of the dependability modeling techniques, such as Dynamic Fault Trees (DFTs) and Dynamic Reliability Block Diagrams (DRBDs). Several analysis methods, including paper-and-pencil or simulation, exist for analyzing these models to ascertain various dependability related parameters. However, their results cannot be always trusted since they may involve some approximations, truncations or even errors. Formal methods, such as model checking and theorem proving, can be used to overcome these inaccuracy limitations due to their inherent soundness and completeness. However, model checking suffers from state-space explosion if the state space is large. While, theorem proving was used  only for the static dependability analysis without considering the system dynamics.

In order to conduct the formal dependability analysis of systems that exhibit dynamic failure behaviors within a theorem prover, these models need to be captured formally, where their structures, operators and properties are properly formalized. In this thesis, we provide a complete framework for the formal dependability analysis of systems modeled as DFTs and DRBDs in the HOL4 higher-order logic theorem prover. We provide the formalization of DFT gates and verify important simplification theorems based on well-known DFT algebra. In addition, our framework allows both qualitative and quantitative DFT analyses to be conducted using theorem proving. We use this formalization to formally verify the DFT rewrite rules, that are used by automated DFT analysis tools, to ascertain their correctness. Due to the lack of a DRBD algebra that allows the analysis using a theorem prover, in this thesis, we develop and formalize a novel  algebra that includes operators and simplification theorems to formalize traditional RBD structures, such as the series and parallel, besides the DRBD spare construct. We formally verify their reliability expressions, which allows conducting both the qualitative and quantitative analyses of a given system. Leveraging upon the complementary nature of DFTs and DRBDs, our proposed framework provides the possibility of formally converting one model to the other, which allows reasoning about both the success and failure of a given system. Our framework provides generic expressions of probability of failure and reliability that are independent of the failure distribution of an arbitrary number of system components, which cannot be obtained using other formal tools, such as model checking. In order to demonstrate the usefulness of the proposed framework, we formally model and analyze the dependability of the terminal, broadcast and network reliability of shuffle-exchange networks, which are multistage interconnections networks that are used to connect the elements of multiprocessor systems. Conducting a sound analysis with generic expressions is essential in these systems, where it is required to accurately capture and analyze the failure behavior.


identifier: El-Hamamsy, Ahmed  (2019) Connectivity Preservation in Multi-Agent Systems using Model Predictive Control.  Masters thesis, Concordia University.

abstract: Flocking of multiagent systems is one of the basic behaviors in the field of control of multiagent systems and it is an essential element of many real-life applications. Such systems under various network structures and environment modes have been extensively studied in the past decades. Navigation of agents in a leader-follower structure while operating in environments with obstacles is particularly challenging. One of the main challenges in flocking of multiagent systems is to preserve connectivity. Gradient descent method is widely utilized to achieve this goal. But the main shortcoming of applying this method for the leader-follower structure is the need for continuous data transmission between agents and/or the preservation of a fixed connection topology. In this research, we propose an innovative model predictive controller based on a potential field that maintains the connectivity of a flock of agents in a leader-follower structure with dynamic topology. The agents navigate through an environment with obstacles that form a path leading to a certain target. Such a control technique avoids collisions of followers with each other  without using any communication links while following their leader which navigates in the environment through potential functions for modelling the neighbors and obstacles. The potential field is dynamically updated by introducing weight variables in order to preserve connectivity among the followers as we assume  only the leader knows the target position. The values of these weights are changed in real-time according to trajectories of the agents when the critical neighbors of each agent is determined. We compare the performance of our predictive-control based algorithm with other approaches. The results show that our algorithm causes the agents to reach the target in less time. However, our algorithm faces more deadlock cases when the agents go through relatively narrow paths. Due to the consideration of the input costs in our controller, the group of agents reaching the target faster does not necessarily result in the followers consuming more energy than the leader.


identifier: Pelly, Amelie  (2019) “Mother and wife — genius — governess:” Anna Freud and the Analytic Environment.  Masters thesis, Concordia University.

abstract: This thesis considers Anna Freud’s (1895-1982) early analytic environment (the combined space of her waiting room, bedroom and consulting room), at Berggasse 19 in Vienna, Austria. It explores the interrelation of space, psychoanalysis and biography, within a framework where interiority and interiors are considered agential tools. Built upon primary documents such as familial correspondence, photographs and relevant psychoanalytic theories, the following is, by necessity, a reconstruction of the child psychoanalyst’s analytic environment. The text progresses spatially through the rooms and examines what Anna considered as societal expectations directed towards her: “Mother and wife — genius — governess”. Beginning with the waiting room which Anna shared with her illustrious father and psychoanalyst, Sigmund Freud (1856-1939), the physical decorative manifestations of the highly gendered term ‘genius’ are explored. The bedroom, the next room in the analytic environment, opens with a discussion of Anna’s relation to the roles of mother and wife, making way for a discussion of asceticism and altruism, two factors which inform the arrangement of the bedroom’s furnishing. The consulting room marks a professional space as we observe Anna’s move from governess to child psychoanalyst. Likewise, the consulting room’s décor leads to a discussion of interiors at the threshold of fin-de-siècle and modern rapport to belongings. Ultimately, this thesis will argue that Anna’s negotiation of gendered social expectations offered an opportunity to redefine not only psychoanalytic techniques and models, but the very environment in which it belonged.


identifier: Chatterjee, Debdeep  (2019) Improving Sustainability Performance in a Two-Tier Supply Network: An Agency Perspective.  Masters thesis, Concordia University.

abstract: Equity owners are often blamed for the unsustainable behaviors of other supply chain members. Recent events show that focal firms may face reputational and financial damages when such misconducts are exposed. However, controlling sub-suppliers can be challenging due to the high supply chain complexity, lack of contractual relation, and the large distance between the supply chain members. Focal firms adopt different governance strategies to improve sustainability performance, but it is unclear how the behavioral and contextual contingencies affect the sustainability performance of sub-suppliers. To explore this issue, the current study employs agent-based modeling and uses agency theory as an interpretive lens. The results shed light on how sustainability performance of sub-suppliers is impacted by (1) risk-aversion of supply chain members, (2) the cost of monitoring and the cost of undertaking sustainability practices, (3) varying information asymmetry between the focal buyer, intermediary supplier, and focal supplier, (4) stakeholder pressure, (5) and supply chain power.


identifier: Hadadian, Armin  (2019) Finite Element Analysis and Design Optimization of Deep Cold Rolling of Titanium Alloy at Room and Elevated Temperatures.  PhD thesis, Concordia University.

abstract:
High strength-to-density ratio, high corrosion resistance and superior biocompatibility are the main advantages of Ti-6Al-4V (Ti64), making it a long been favored titanium alloy for aerospace and biomedical applications. Designing titanium components to last longer and refurbishing of aged ones using surface treatments have become a desirable endeavor considering high environmental damage, difficulty in casting, scarcity and high cost associated with this metal.
Among mechanical surface treatments, Deep Cold Rolling (DCR) has been shown to be a very promising process to improve fatigue life by introducing a deep compressive residual stress and work-hardening in the surface layer of components. This process has shown to be superior compared with other surface treatment methods as it yields a better surface quality and induces a deeper residual stress profile which can effectively be controlled through the process parameters (i.e. ball diameter, rolling pressure and feed). However, residual stresses induced through this process at room temperature are generally relaxed upon exposure of the components to elevated operating temperatures.
In this work, high-fidelity Finite Element (FE) models have been developed to simulate the DCR process in order to predict the induced residual stresses at room temperature and their subsequent relaxation following exposure to temperature increase. Accuracy of the developed models has been validated using experimental measurements available in the literature. A design optimization strategy has also been proposed to identify the optimal process parameters to maximize the induced beneficial compressive residual stress on and under the surface layer and thus prolong the fatigue life. Conducting optimization directly on the developed high-fidelity FE model is not practical due to high computational cost associated with nonlinear dynamic models. Moreover, responses from the FE models are typically noisy and thus cannot be utilized in gradient based optimization algorithms. In this research study, well-established machine learning principles are employed to develop and validate surrogate analytical models based on the response variables obtained from FE simulations. The developed analytical functions are smooth and can efficiently approximate the residual stress profiles with respect to the process parameters. Moreover the developed surrogate models can be effectively and efficiently utilized as explicit functions for the optimization process.
Using the developed surrogate models, conventional (one-sided) DCR process is optimized for a thin Ti64 plate considering the material fatigue properties, operating temperature and external load. It is shown that the DCR process can lead to a tensile balancing residual stress on the untreated side of the component which can have a detrimental effect on the fatigue life. Additionally, application of conventional DCR on thin geometries such as compressor blades can cause manufacturing defects due to unilateral application of the rolling force and can also lead to thermal distortion of the part due to asymmetric profile of the induced residual stresses.
Double-sided deep rolling has been shown as a viable alternative to address those issues since both sides of the component are treated simultaneously. The process induces a symmetric residual stress which can be further optimized to achieve a compressive residual stress on both sides of the component. For this case, a design optimization problem is formulated to improve fatigue life in high stress locations on a generic compressor blade.
All the optimization problems are formulated for multi-objective functions to achieve most optimal residual stress profiles both at room temperature as well as elevated temperature of 450℃. A hybrid optimization algorithm based on combination of sequential quadratic programming (SQP) technique with stochastic based genetic algorithm (GA) has been developed to accurately catch the global optimum solutions. It has been shown that the optimal solution depends on the stress distribution in the component due to the external load as well as the operating temperature.


identifier: Dehghani, Akbar  (2019) A quantitative comparison of Overlapping and Non-overlapping sliding windows effects for human activity recognition using inertial sensors.  Masters thesis, Concordia University.

abstract:
The sliding window technique is widely used to segment inertial sensor signals, i.e., accelerometers and gyroscopes, for activity recognition. In this technique, the sensor signals are partitioned into fix-sized time windows which can be of two types: (1) non-overlapping windows, in which time windows do not intersect, and (2) overlapping windows, in which they do. There is a generalized idea about the positive impact of using overlapping sliding windows on the performance of recognition systems in Human Activity Recognition.
In this thesis, we analyze the impact of overlapping sliding windows on the performance of Human Activity Recognition systems with different evaluation techniques, namely subject-dependent cross validation and subject-independent cross validation. Our results show that the performance improvements regarding to overlapping windowing reported in the literature seem to be associated with the underlying limitations of subject-dependent cross validation. Furthermore, we do not observe any performance gain from the use of such technique in conjunction with subject-independent cross validation. We conclude that when using subject-independent cross validation,
non-overlapping sliding windows reach the same performance as sliding windows. This result has significant implications on the resource usage for training the human activity recognition systems.


identifier: Minooie, Miaad  (2019) Visual Style in early works of Douglas Fairbanks.  Masters thesis, Concordia University.

abstract: Douglas Fairbanks, the actor, the star, and the artist, has been the subject of many scholarly articles and books. However, little has been written about Fairbanks as an auteur. While some scholars have referred to him as an auteur, the designation is generally reserved for directors rather than actors and producers. The present thesis, through a systematic analysis of the visual style in Fairbanks’ films from 1915 to 1918, demonstrates how some unique characteristics of his films—such as the Average Shot Length and use of Camera Movements, Intertitles, etc.—follow a systematic trend over time and with various directors at the helm, while at the same time deviating from its contemporary industry trends. The only common denominator among the 18 films studies in this sample is Fairbanks, as opposed to a director, writer, cinematographer, or even studio. The findings of this study, coupled with historical accounts painting Fairbanks as the man in charge, suggest that the term auteur is an appropriate designation for this silent-era star.


identifier: Kalra, Meeta  (2019) A Study on Online Variational learning : Medical Applications.  Masters thesis, Concordia University.

abstract:
Data mining is an extensive area of research which is applied in various critical domains. In clinical aspect, data mining has emerged to assist clinicians in early detection, diagnosis and prevention of diseases. On the other hand, advances in computational methods have led to the implementation of machine learning in multi-modal clinical image analysis such as in CT, X-ray, MRI, microscopy among others. A challenge to these applications is the high variability, inconsistent regions with missing edges, absence of texture contrast and high noise in the background of biomedical images. To overcome this limitation various segmentation approaches have been investigated to address these shortcomings and to transform medical images into meaningful information. It is of utmost importance to have the right match between the bio-medical data and the applied algorithm.

During the past decade, ﬁnite mixture models have been revealed to be one of the most ﬂexible and popular approaches in data clustering. Here, we propose a statistical framework for online variational learning of ﬁnite mixture models for clustering medical images. The online variational learning framework is used to estimate the parameters and the number of mixture components simultaneously in a uniﬁed framework, thus decreasing the computational complexity of the model and the over ﬁtting problems experienced with maximum likelihood approaches guaranteeing convergence. In online learning, the data becomes available in a sequential order, thus sequentially updating the best predictor for the future data at each step, as opposed to batch learning techniques which generate the best predictor by learning the entire data set at once. The choice of distributions remains the core concern of mixture models in recent research. The efﬁciency of Dirichlet family of distributions for this purpose has been proved in latest studies especially for non-Gaussian data. This led us to analyze online variational learning approach for ﬁnite mixture models based on different distributions.

iii To this end, our contribution is the application of online variational learning approach to design ﬁnite mixture models based on inverted Dirichlet, generalized inverted Dirichlet with feature selection and inverted Beta-Liouville distributions in medical domain. We evaluated our proposed models on different biomedical image data sets. Furthermore, in each case we compared the proposed algorithm with other popular algorithms. The models detect the disease patterns with high conﬁdence. Computational and statistical approaches like the ones presented in our work hold a signiﬁcant impact on medical image analysis and interpretation in both clinical applications and scientiﬁc research. We believe that the proposed models have the capacity to address multi modal biomedical image data sets and can be further applied by researchers to analyse correct disease patterns.


identifier: Koochekian Sabor, Korosh  (2019) Automatic bug triaging techniques using machine learning and stack traces.  PhD thesis, Concordia University.

abstract:
When a software system crashes, users have the option to report the crash using automated bug tracking systems. These tools capture software crash and failure data (e.g., stack traces, memory dumps, etc.) from end-users. These data are sent in the form of bug (crash) reports to the software development teams to uncover the causes of the crash and provide adequate fixes. The reports are first assessed (usually in a semi-automatic way) by a group of software analysts, known as triagers. Triagers assign priority to the bugs and redirect them to the software development teams in order to provide fixes.
The triaging process, however, is usually very challenging. The problem is that many of these reports are caused by similar faults. Studies have shown that one way to improve the bug triaging process is to detect automatically duplicate (or similar) reports. This way, triagers would not need to spend time on reports caused by faults that have already been handled. Another issue is related to the prioritization of bug reports. Triagers often rely on the information provided by the customers (the report submitters) to prioritize bug reports. However, this task can be quite tedious and requires tool support. Next, triagers route the bug report to the responsible development team based on the subsystem, which caused the crash. Since having knowledge of all the subsystems of an ever-evolving industrial system is impractical, having a tool to automatically identify defective subsystems can significantly reduce the manual bug triaging effort.
The main goal of this research is to investigate techniques and tools to help triagers process bug reports. We start by studying the effect of the presence of stack traces in analyzing bug reports. Next, we present a framework to help triagers in each step of the bug triaging process. We propose a new and scalable method to automatically detect duplicate bug reports using stack traces and bug report categorical features. We then propose a novel approach for predicting bug severity using stack traces and categorical features, and finally, we discuss a new method for predicting faulty product and component fields of bug reports.
We evaluate the effectiveness of our techniques using bug reports from two large open-source systems. Our results show that stack traces and machine learning methods can be used to automate the bug triaging process, and hence increase the productivity of bug triagers, while reducing costs and efforts associated with manual triaging of bug reports.


identifier: Millet-Boureima, Cassandra ORCID: https://orcid.org/0000-0002-1521-0778 <https://orcid.org/0000-0002-1521-0778>  (2019) Cyst reduction in a first-in-kind Drosophila model of polycystic kidney disease.  Masters thesis, Concordia University.

abstract:
Polycystic kidney disease (PKD) is an incurable degenerative disease affecting 12.5 million people worldwide. Numerous cysts form in the renal tubules, which progressively enlarge and damage the surrounding kidney tissues, severely reducing quality of life and leading most patients to kidney failure with the need for dialysis or transplant. Partly due to lack of knowledge of the precise PKD pathological mechanisms, therapeutic options are limited. The complex anatomy of the human and vertebrate kidney makes it difficult to define the PKD mechanisms and perform drug discovery. In contrast, the fruit fly Drosophila melanogaster shares high genetic conservation with humans and features anatomically isolated Malpighian (renal) tubules with physiologically diversified regions, making it an ideal model for studying renal cystogenesis and performing rapid drug discovery in vivo. One mimic of the second
mitochondria-derived activator of caspases (Smac), a class of pro-apoptotic molecules being developed for cancer therapy, was found to reduce renal cysts in a murine ADPKD model. Here, we used our first-in-kind Drosophila PKD model, the Bicaudal C mutant, to test the cyst-reducing properties of four novel Smac mimics. Smac mimicry was found to decrease the overall incidence of tubular cysts. Intriguingly, cysts were reduced at different rates along the Malpighian tubules, underscoring functional differences in the tubular regions. Thus, this study suggests novel hypotheses on the conservation of renal cystic mechanisms and the function of RNA-binding protein Bicaudal C in the renal tubule.


identifier: Aly, Nader Essam ORCID: https://orcid.org/0000-0001-8156-5799 <https://orcid.org/0000-0001-8156-5799>  (2019) Seismic Performance and Building Height Limits of Ductile Reinforced Concrete Masonry Shear Walls with Boundary Elements.  PhD thesis, Concordia University.

abstract:
The National Building Code of Canada, NBCC-15, has recently added a new Seismic Force Resisting System (SFRS) category, ductile shear walls, for Reinforced Concrete Masonry (RCM) buildings. Although it is given a higher ductility-related force modification factor, Rd=3.0, compared to that of moderately ductile walls Rd=2.0, NBCC-15 assigned the same building height limits for the ductile and moderately ductile RCM walls. The research work outlined herein contributes to the understanding of the seismic performance and collapse capacity of ductile RCM shear wall buildings with boundary elements. The main objective is to develop component and system levels, solutions and design recommendations to enhance the overall seismic performance of RCM buildings.
At the component (structural element) level, it is proposed to utilize RCM shear walls with boundary elements built using C-shaped masonry blocks. To quantify the component’s seismic performance, six half-scale high-rise RCM shear walls were constructed and tested under high constant axial compressive load, along with in-plane fully reversed cyclic loading synchronized with top moment. The tested walls represented the plastic hinge region of prototype 6- and 12-storey RCM structural walls. The studied parameters are the boundary element’s length, the boundary element’s vertical reinforcement ratio, the wall’s shear span-to-depth ratio, the type of masonry blocks used in constructing the boundary elements (stretcher or C-shaped), and the lap splicing of vertical rebars in the plastic hinge region.
At the system (building) level, a hybrid structural system composed of ductile and gravity walls is proposed. The ductile walls are RCM shear walls with boundary elements, whereas the gravity walls are conventional rectangular RCM walls with no special seismic detailing. Several archetype buildings were designed according to NBCC-15 and the Canadian masonry design standard CSA S304-14 with varying heights, location’s seismicity, ductile shear wall ratios and cross-sectional configurations. Validated macro-modelling approaches were utilized to simulate the nonlinear response of the buildings. A series of linear and nonlinear, pseudo-static and dynamic time-history analyses were performed to quantify the influence of the studied parameters on the seismic response and collapse capacity. Besides, the possibility of increasing the height limits of ductile RCM shear walls was evaluated. Finally, the potential for reducing and terminating the specially detailed boundary elements over the building’s height was investigated.
The results of the experimental testing confirmed that the presence of the well-detailed and confined boundary elements is capable of mitigating the impacts of the high axial compression load. Using the C-shaped masonry blocks instead of the regular stretcher blocks in constructing the boundary elements enhanced the construction and performance of the walls. Lap splicing of vertical rebars increased the initial lateral stiffness, the rate of stiffness and strength degradation, and slightly limited the displacement ductility. However, with proper detailing of the splice and confinement of the end zones, the premature tensile bond failure was prevented.
Based on the findings of the numerical simulations, it was suggested to increase the height limits of RCM buildings with ductile shear walls with boundary elements. In addition, the results emphasized that utilizing the ductile walls with boundary elements, instead of the traditional rectangular walls, in the proposed hybrid structural system enhanced the structural response and optimized the design. Furthermore, the results demonstrated the possibility of vertically reducing and terminating the specially detailed boundary elements. Therefore, the experimental and numerical results of this research form a step forward in presenting RCM shear walls with boundary elements as a practical and competitive SFRS.


identifier: agah, mohammadkazem  (2019) Relocation Strategies for Mobile Sensor Networks in Emergency Coverage Situations.  Masters thesis, Concordia University.

abstract: The focus of this thesis is directed towards developing distributed coordination protocols for a group of agents (mobile sensors) deployed to cover an area of interest. It is assumed that sensors are subject to an alert message at any point in time, which is issued in an emergency situation. Such an emergency event is formulated as an abrupt change in the coverage priority of specific regions in the field. In the normal situation, a protocol is used to move the mobile sensors in the plane in such a way that the overall sensing coverage is increased. Then, as soon as an alert message is issued, sensors that receive the information communicate with their neighbors to inform them of the message. An appropriate number of sensors are subsequently tasked to further improve the coverage of the specified area by adjusting their positions iteratively to increase the coverage of the alert area. Two types of algorithms are developed, where the first one is mainly focused on the alert area coverage, and the second one aims to also cover the rest of the field as much as possible. The algorithms are Voronoi-based, and are guaranteed to increase the desired sensing coverage at each iteration. Some examples and comparative results are provided to demonstrate the effectiveness of the proposed algorithms.


identifier: Kiani, Shayesteh  (2019) Exploring factors affecting the distribution of Saccharomyces cerevisiae tRNA nucleotidyltransferase.  Masters thesis, Concordia University.

abstract:
The enzyme ATP(CTP): tRNA-specific tRNA nucleotidyltransferase (also known as Cca1, the CCA-adding enzyme) adds to all tRNAs the 3’-cytidine, cytidine, and adenosine (CCA) tail required for aminoacylation. A single essential nuclear gene, CCA1, in Saccharomyces cerevisiae codes for versions of this protein found in the cytosol, nucleus and mitochondrion (Chen et al., 1992). Here, we use mass spectrometry to explore factors involved in the distribution and activity of this enzyme. These factors may be cis-acting, e.g., post-translational modifications (PTMs) of Cca1, or trans-acting, e.g., accessory proteins involved in Cca1 activity or which serve to direct Cca1 to specific locations in the cell.
Specific PTMs, i.e., phosphorylation and/or acetylation, were identified on amino acids S4, T5, T7, S12, T17, T19, and S21 at the N-terminus of Cca1 and also on K57, K118, K150, K328, T407, and K507. Most of these PTMs are reported for the first time in this study. These PTMs might impact enzyme localization (as the N-terminal cluster of PTMs is near the known mitochondrial targeting signal) or activity as some post-translationally modified amino acids (e.g., K118, K150) are in important functional domains of the protein. Differences between the PTMs detected at specific positions in different cellular fractions, suggest the role of these modifications in Cca1 localization. Moreover, some conserved PTMs (e.g., K150, T407, and K507) across different conditions and fraction might implicate these specific modifications in enzyme activity.
As Cca1 is an essential enzyme present in different parts of the cell (mitochondria, nucleus and cytosol), we identified proteins interacting with it that might mediate its function or localization. Among the proteins identified were the karyopherins Kap95, Kap104 and Kap123, which allowed us to predict a nuclear localization signal in a eukaryotic CCA-adding enzyme for the first time. Additionally, Cca1 was shown to interact with other enzymes required for tRNA maturation and repair.


identifier: Qiu, Dong ORCID: https://orcid.org/0000-0001-6255-2618 <https://orcid.org/0000-0001-6255-2618>  (2019) Individual Claims Reserving: Using Machine Learning Methods.  Masters thesis, Concordia University.

abstract: To date, most methods for loss reserving are still used on aggregate data arranged in a triangular form such as the Chain-Ladder (CL) method and the over-dispersed Poisson (ODP) method. With the booming of machine learning methods and the significant increment of computing power, the loss of information resulting from the aggregation of the individual claims data into accident and development year buckets is no longer justifiable. Machine learning methods like Neural Networks (NN) and Random Forest (RF) are then applied and the results are compared with the traditional methods on both simulated data and real data (aggregate at company level).


identifier: Park, Serim  (2019) Comparison of Lift Path Planning Algorithms for Mobile Crane Operations in Heavy Industrial Projects.  Masters thesis, Concordia University.

abstract:
Heavy industrial projects, especially oil refineries, are constructed by modules
prefabricated in factories, transported to sites and installed by mobile cranes. Due to a large number
of lifts on the congested and dynamic site layouts in heavy industrial projects, the lift path planning
has been attention for not only safe and efficient mobile crane operation but also better project
productivity and safety. Although the path planning algorithms have been introduced over the
years, they have not been used actively in practice since the comparison of these algorithms has
not been examined yet based on the realistic mobility of mobile cranes and real site environment.
Therefore, this thesis compares the path planning algorithms including A* search, rapidly
exploring random tree (RRT), genetic algorithms (GA) and 3D visualization-based mathematical
algorithm (3DVMA) under the same site environment in order to find a competent method using
measurement metrics considering collision-free and optimal lift paths with the lower crane
operation cost and less computation time. The proposed comparison is implemented in a case study
that includes a series of modules lifted by a mobile crane on various site conditions. This
comparison shows the advantages and disadvantages of each algorithm for the crane path planning
in heavy industrial projects and suggests the direction of further research in this field.


identifier: Stanga, Daniela  (2019) Elucidation of the cellular functions of TrappC11.  PhD thesis, Concordia University.

abstract:
Transport protein particle complex component 11 (TRAPPC11) is a subunit of TRAPP III, a protein complex which is involved in membrane traffic, autophagy and maintenance of Golgi structure. The mechanisms by which it functions in these processes are not fully understood. Mutations in human TRAPPC11 have been linked to a wide spectrum of phenotypes including developmental delays, muscular dystrophies, intellectual disabilities, dystroglycanopathies and fatty liver. Here, we show that TRAPPC11 has a role upstream of autophagosome formation in macroautophagy. This contrasts with other TRAPP III proteins that function earlier (TRAPPC8) or later (TRAPPC12) than TRAPPC11 in the pathway. Upon TRAPPC11 depletion, LC3-positive membranes fail to become sealed autophagosomes and are not cleared during starvation conditions. ATG2B and its binding partner WIPI4/WDR45 are thought to be TRAPPC11 interactors, and TRAPPC11 depletion phenocopies the one of either ATG2 or WIPI4, which act in isolation membrane expansion. In the absence of TRAPPC11, recruitment of both these proteins to membranes is defective and fibroblasts from an individual with an altered carboxy-terminus of TRAPPC11 failed to recruit ATG2B-WIPI4, suggesting that this interaction is physiologically relevant. We propose a model whereby the TRAPP III complex coordinates growth and expansion of the isolation membrane through multiple interactions.

TRAPPC11 can also function independent of the complex in the formation of lipid-linked oligosaccharides in N-glycosylation, so further research is needed to tease apart the roles of TRAPPC11 independently and within the complex. Collectively, all these dysregulated functions could potentially explain the spectrum of phenotypes seen in individuals having variants of TRAPPC11. The region around the highly-conserved Gly980 appears to be critical for membrane trafficking and N-linked glycosylation, causing the muscular weakness phenotype, whereas the extreme carboxy-terminus seems to be involved in autophagy, being linked to some of the same neurological phenotypes shared with TRAPPC12 variants.


identifier: Aghababaei Tafreshi, Omid  (2019) Heat Transfer Study of the In-situ Automated Fiber Placement (AFP) for Thermoplastic Composites.  Masters thesis, Concordia University.

abstract:
With more and more use of composites in engineering applications, the need for automated composites manufacturing is evident. The use of automated fiber placement (AFP) machine for the manufacturing of thermoplastic composites is under rapid development. In this technique, a moving heat source (hot gas torch, laser, or heat lamp) is melting the thermoplastic composite tape and consolidation occurs in situ. Due to the rapid heating and cooling of the material, there are many issues to be addressed. First is the development of the temperature distribution in different directions which gives rise to temperature gradients. Second is the quality of the bond between different layers, and third is the rate of material deposition to satisfy industrial demand. This thesis addresses the first issue. The temperature distribution affects the variation in crystallinity, and residual stresses throughout the structure as it is being built. The end result is the distortion of the composite laminate even during the process. In order to address this problem, first the temperature distribution due to a moving heat source needs to be determined. From the temperature distribution, the development and distribution of crystallinity, residual stresses and deformation of the structure can then be determined.
As the first phase of the work, this thesis investigates the temperature distribution due to a moving heat source for thermoplastic composites, without considering the material deposition. A finite difference (FD) code based on the energy balance approach is developed to predict the temperature distribution during the process. Unidirectional composite strips are manufactured using AFP and fast-response K-type thermocouples are used to determine the thermal profiles in various locations through the thickness of the composite laminate subjected to a moving heat source. It is shown that temperature variations measured experimentally during the heating pass, using thermocouples embedded into the composite substrate, underneath layers of the composite material, are consistent with the generated thermal profiles from the numerical model. The temperature distribution, both in the direction of the tape and through-thickness direction can be predicted numerically.
It should be noted that the convective heat transfer coefficient employed in the thermal analysis of the process plays an important role in the heat transfer mechanism. Information from the literature shows values of h that vary from 80 W⁄(m^2.K) to 2500 W⁄(m^2.K). This large range can provide a great degree of uncertainty in the determination of important quantities such as temperature distributions and residual stresses. The reason for these large differences can be due to the differences in the process parameters in each of the studies. The process parameters can include the flow rate of the hot gas, the gas temperature, the distance between the nozzle exit and the surface of the composite substrate, the angle of the torch with respect to the surface of the substrate etc. The purpose of the final part of this thesis is to investigate the effect of different AFP process parameters on the convective heat transfer coefficient and to propose a procedure for the determination of the h value according to the particular experimental setup.


identifier: Leonczuk Minetto, Robert Alexis  (2019) Simulation and Analysis of Morphing Blades applied to a Vertical Axis Wind Turbine.  Masters thesis, Concordia University.

abstract: This study compares the performance of a Vertical Axis Wind Turbine with and without using morphing capabilities applied to its blades. It also explores the feasibility of applying moving mesh to model the morphing capability inside the software package STAR CCM+© in order to use Computational Fluid Dynamics (CFD) to analyze the flow’s behavior. Particularly it is important to capture the presence of dynamic stall and vortex shedding at certain regions over the blade’s path, which are associated with a decreased in the overall power coefficient. This work developed a methodology to analyze these morphing capabilities when applied over airfoils in 2D simulations, by using a combination of overset meshes and the morphing approach. The accuracy is verified by creating a baseline scenario and compare it against a benchmark case, while also testing for grid and time step sensitivity. The use of Reynold Averaged Navier Stokes equations was chosen, with Menter’s SST k-omega as the turbulence model. Afterward, a maximum power coefficient curve was plotted by testing three airfoil’s shapes as references, one forming the baseline case, while the other two delimiting the maximum deformation, marked as outward and inward cases. A final optimized case was tested, where the morphing was applied to strategic regions where the dynamic stall was highest, and where the shapes could ensure the maximum possible power output.This resulted in an improvement of 46.2% of the overall power coefficient.


identifier: Plamadeala, Cristina  (2019) Methods and motivations behind the collaboration and resistance of secret informers with the Securitate in Communist Romania (1945-89).  PhD thesis, Concordia University.

abstract:
Working primarily with Securitate files, currently stored at the National Council for the Study of Securitate Archives (CNSAS), located in Bucharest and Popesti-Leordeni, Romania, this thesis explains the various terror mechanisms the Securitate, Romania’s secret police during the country’s communist period, employed in order to gain recruits and employ them as part of its surveillance network.  Although the thesis discusses the entire communist period in Romania, it places significant emphasis on the last two decades of communism (1965-89), when Nicolae Ceauşescu was in power. This thesis introduces and discusses the following two concepts— psuchegraphy and dossierveillance—described herein as two terror methods applied by the Securitate to obtain informers and compel them to collaborate.
 	The former mentioned concept entailed collecting biographical data Securitate’s targets that would give one sufficient clues about a person’s core beliefs, personality, character, and identity, all with the scope of getting to know that which Securitate referred to in its files as a person’s vulnerable points. This thesis shows that this kind of analysis was a precursor to recruitment of the members of the Securitate’s surveillance network. The latter aforemetioed method of terror stresses the role of technology and documentation in surveillance practices and their use for recruitment of informers and management of the population by maintaining it in a sense of dread and fear. The ‘dossier in dossierveillance, loosely defined in this thesis as the technology that the Securitate employed to place its targets under surveillance, represented one of the Securitate’s most effective “disciplinary” tools (Foucault 1975) through which it managed to instill fear in people. This thesis also describes the outcome of enforcing such mechanisms on a nation, amassing to a phenomenon described here as the banalization of evil, a term that builds on the work of Hannah Arendt on the banality of evil. Lastly, this thesis revists the subject of lustration and transitional justice and explores how the new scholarship discussed in the thesis may further contribute to understanding and treating the subject of collaboration in a post-communist context in Romania.


identifier: Zandi Karimi, Alireza  (2019) Development of Glass Ionomer Cements with Improved Mechanical and Remineralizing Properties by Incorporation of 45S5 Bioglass®-Ceramic.  PhD thesis, Concordia University.

abstract:
Despite significant efforts to improve the clinical performance (e.g. mechanical and remineralizing properties) of glass ionomer cements (GICs), their essential characteristics such as proper translucency, adhesion to enamel and dentine, and fluoride-releasing capability cannot yet be fully exploited in load-bearing areas in restorative dentistry. The aim of this study is to introduce a functional approach to improve not only the mechanical properties of GICs, but also to enhance their biomineralizing capacity.
In the first stage of this study, a series of versatile heat treatment profiles are used to tailor the crystallinity of 45S5 Bioglass® within a wide range of 5% to 100% via the formation of solely combeite as a mechanically competent yet bioactive phase. The resulting 45S5 glass-ceramics containing combeite not only are expected to retain beneficial levels of bioactivity, but also show improved mechanical properties compared to those of the amorphous 45S5 Bioglass®. By choosing the proper heat treatment from the proposed profiles in this study, different levels of mechanical properties and bioactivity in Bioglass® can be achieved according to the target application(s).
In the second stage of this study, hybrid GICs with enhanced mechanical and remineralizing properties were developed via incorporation of an optimum amount (5 wt%) of 45S5 Bioglass®-ceramic particles with a certain degree of crystallinity. The effect of the degree of crystallinity of additives, which is completely overlooked in the current literature, was also addressed in this study. Mechanical properties testing, in vitro studies and microstructural analysis revealed that the Bioglass®-ceramic particles with 74% crystallinity best act as both remineralizing and reinforcing agents. Enhanced remineralizing and mechanical properties may not only broaden the hybrid GICs’ clinical applications but also can potentially enhance their in vivo performance.
In the last stage of this study, a novel aluminum-free, 45S5 Bioglass®-based GIC with standard mechanical properties was produced. For the first time, 45S5 Bioglass® and its Bioglass®-ceramic were used as the GIC solid component. The Bioglass®-ceramic particles with 74% crystallinity was used as they favorably act as both remineralizing and reinforcing agents. The early stage progression of setting reaction was monitored. Bimodal particle size distribution was shown to improve the packing density and integrity of the set cement. In such GICs, not only the neurotoxicity of Al is eliminated, but chemical bond formation at cement/hard tissue(s) interface through interfacial biomineralization and adhesion is expected.


identifier: Ding, Kejia  (2019) Innovative Butler Matrix Concepts Based on Novel Components For 2-D Beamforming.  PhD thesis, Concordia University.

abstract:
Several innovative concepts and schemes to enrich the features of Butler matrices (BMs) to enhance their suitability over the conventional schemes are discussed, demonstrated, and analyzed. Mobile communication and radar systems require compact and versatile multibeam-forming networks (MBFNs). Therefore, the study is aimed to provide feasible and practical solutions with more flexible beam numbers of BMs, more concise configurations of the two-dimensional (2-D) beamforming, and broadband characteristics while maintaining the intrinsic merits of conventional BMs (such as theoretically lossless, spatially orthogonal beams, and relatively simple structure). In addition, the study implements some of the concepts to millimeter-wave (mm-wave) frequencies applications.
Concretely, the effects of some components, such as T-junctions and crossovers, on the bandwidth of parallel-feeding networks and MBFNs, are investigated and analyzed. The corresponding solutions to broaden the bandwidth are suggested and verified by the measurements. Further, for the 2-D beamforming based on BMs, a generalized scheme to build 2-D MBFN with any 2M+N beams based on traditional 2M× 2M- and 2N× 2N BMs is elaborated and experimentally verified. Especially as the key component of 2-D BMs, an innovative eight-port coupler with a very compact structure is proposed. The applications of the coupler for 2-D monopulse arrays, dual-polarized monopulse arrays, and mm-wave 2-D beamforming are also demonstrated. Besides, two solutions to extend the numbers of beams of BMs from traditional 2N × 2N to almost arbitrary number, such as 2M×3N or M × 2N, are introduced by using a three-way coupler and electrically switchable coupler, respectively (M and N are arbitrary integers greater than 0).
Though the majority of ideas and examples presented is exemplified by planar circuits and transverse-electro-magnetic (TEM) transmission lines, they can also be transferred to and applied on other circuit forms, such as ridge-gap waveguide (RGW), printed RGW (PRGW), substrate-integrated waveguide (SIW), and packaged microstrip line (PMSL) for mm-wave applications.
Keywords: Butler matrices, two-dimensional Butler matrices, directional couplers, reconfigurable couplers, phase shifters, crossovers, eight-port couplers, packaged microstrip line.


identifier: de la Cruz, Vladimir  (2019) Human motion convolutional autoencoders using different rotation representations.  Masters thesis, Concordia University.

abstract:
This research proposes the application of four different techniques of animation storage
(Axis Angle, Quaternions, Rotation Matrices and Euler Angles), in order to determine the advantages
and disadvantages of each method through the training and evaluation of autoencoders for
reconstructing and denoising parsed data, when passing through a convolutional neural network.
The designed autoencoders provide a novel insight into the comparative performance of these animation
representation methods in an analog architecture, making them measurable in the same
conditions, and thus possible to evaluate with quantitative metrics such as Minimum Square Error
(MSE), and Root Mean Square Error (RMSE), as well as qualitatively through close observation of
the naturality, its real-time performance after being decoded in full output sequences.
My results show that the most accurate method for this purpose qualitatively is Quaternions, followed
by Rotation Matrices, Euler Angles and finally with the least accurate results:e Axis Angles.
These results persist in decoding and in simple encoding-decoding. Consistent denoising results
were achieved in the representations, up until sequences with 25% of added gaussian noise.


identifier: Tan, Zhejun  (2019) The Impact of Supervisor’s Leadership Style on Followers’ Leadership Self-Efficacy and Motivation to Lead: Differential Effects for Men and Women.  Masters thesis, Concordia University.

abstract: There is an abundance of evidence that women are underrepresented in managerial positions. Drawing on self-determination and social role theory, this study examines the effects of three distinct supervisor leadership styles (transformational, servant and directive) on followers’ leadership self-efficacy and motivation to lead, while accounting for followers’ gender. I propose that supervisors’ transformational and servant leadership positively contribute to followers’ leadership self-efficacy while directive leadership is negatively related to this variable, and that these relationships are stronger among women followers. I further propose that followers’ leadership self-efficacy is positively related to their motivation to lead, but that this effect is weaker among women followers. Data were collected using an online questionnaire and a time-lagged design in a sample of employees (N = 117 at T2) from various firms in the United States. As expected, supervisor transformational and servant leadership were positively related to followers’ leadership self-efficacy, and these effects were stronger among women followers. Contrary to expectations, supervisor directive leadership was not significantly related to follower leadership self-efficacy. In turn, leadership self-efficacy was positively associated with follower motivation to lead, but this relationship was weaker among women followers. The findings of this study are relevant for both supervisors and followers, as leaders who adopt a transformational or servant leadership style will be more likely to develop their followers’ – and especially women followers – leadership self-efficacy, and ultimately motivate them to take on leading roles in their careers. I discuss implications for future research and for practice.


identifier: Raina, Prashant ORCID: https://orcid.org/0000-0002-1039-3472 <https://orcid.org/0000-0002-1039-3472>  (2019) Fine Feature Reconstruction in Point Set Surfaces Using Deep Learning.  PhD thesis, Concordia University.

abstract:
Point clouds are typically captured from surfaces of real-world objects using scanning devices. This scanning process invariably results in the loss of sharp edges as well as other geometric features of the original surface, which we collectively refer to as "fine features". This thesis explores leveraging recent advances in deep learning in order to recover fine features of surfaces which were lost when acquiring the point cloud. We first focus on reconstructing sharp edges of the original surface. We define a new concept – a sharpness field – over the underlying surface of a point cloud, whose ridges give the locations of sharp edges even at points not originally sampled from the surface. We then demonstrate that with appropriate training data, deep neural networks can be trained to compute the sharpness field for a point cloud. We evaluate several different local neighborhood representations and deep learning models to improve the accuracy of sharpness field computation across different neighborhood scales. Some applications of the sharpness field are then described. The most important such application is feature-aware smoothing: using the computed sharpness field to preserve sharp edges while removing noise from point clouds. Our novel smoothing algorithm shows superior performance in reconstructing sharp edges and corners compared to the state-of-the-art RIMLS algorithm, while also yielding points lying on sharp edges. Other applications of the sharpness field are also presented:  generating a graphical representation of sharp edges and segementing a point cloud into smooth surface patches. We then expand the scope of the problem from sharp edges to undersampled fine features in general. We tackle this by developing a unique deep learning approach to point cloud super-resolution using an innovative application of generative adversarial networks (GANs). The novelty of our super-resolution method lies in framing point cloud super-resolution as a domain translation task between heightmaps obtained from point clouds and heightmaps obtained from triangular meshes. By using recent developments in domain translation using GANs, we obtain results qualitatively and quantitatively superior to state-of-the-art point cloud super-resolution methods, all while using a radically different deep learning approach which is also more computationally efficient.

The main contributions of this thesis are:
    1. Establishing sharpness field computation as a novel method for localizing sharp edges in 3D point clouds.
    2. Several new data-driven methods to compute the sharpness field for a point cloud using different local neighborhood representations and machine learning models.
    3. A novel feature-aware smoothing algorithm for denoising point clouds while preserving sharp edges, using the aforementioned sharpness field. This method produces denoising results superior to the state-of-the-art RIMLS smoothing method.
    4. An innovative application of GAN-based domain translation, in order to transform sparse heightmaps obtained from point cloud neighborhoods into dense heightmaps obtained from triangular meshes.
    5. A unique method for reconstrucing fine features in point clouds, by using heightmap domain translation to perform point cloud super-resolution. The reconstructed surfaces are qualitatively and quantitatively superior to those produced by state-of-the-art point cloud super-resolution methods.

Other contributions include:
    1. An algorithm for extracting an explicit graphical representation of the sharp edges of a point cloud, using the sharpness field.
    2. An algorithm for segmenting a point cloud into smooth patches, using the sharpness field.
    3. Feature-aware smoothing algorithms which incorporate the aforementioned edge graph and patch segmentation.


identifier: Farshidy, Mohammad  (2019) Application of Enhanced Desorption-Sorption as a New Process for Remediation of the Sediments.  PhD thesis, Concordia University.

abstract:
Contamination of the sediments by organics and inorganics is a rising concern. However, remediation of contaminated sediments is complex and challenging.
As yet, the application of the enhanced desorption combined with the sorption for remediation of the contaminated solid media has not been investigated. In environmental research, few studies have focused on closed-loop remediation methods. This study was to evaluate a desorption-sorption process and the influential parameters for remediation of hydrocarbon-contaminated sediments. Also, it aimed to investigate the adsorption capacity of the sorbent (silica aerogel), adsorption isotherms and adsorption kinetics, as well as the fate of heavy metals, phosphorus and nitrogen, and regeneration of aerogels by solvents and heat in the desorption-sorption process.
A laboratory-scale system was designed and built for fast remediation of sediments. A strong turbulence vessel was used to increase the desorption of contaminants from sediments. A packed column containing hydrophobic silica aerogel granules was used to remove the contaminants from the effluent slurry.
The results showed 29.5% total petroleum hydrocarbon (TPH) removal from sediment after 45 minutes of vigorous agitation at 15900 rpm. The processed sediment and effluent water met Canadian governmental and provincial quality criteria. Higher agitation speeds (22100 rpm) increased the leaching of hydrocarbons from sediments by 31%.
In a warm environment (35oC), the desorption of TPH from sediments was 28.9% higher than at ambient temperature (22oC), but in a cold environment (10oC), it was 16.3% lower than at ambient temperature. The sorption capacity of aerogels was increased from 9.6 mg/g at 22 oC to 10.5 mg/g at 10oC but decreased to 6.7 mg/g at 35oC. pH (5, 7 and 9), salinity (3.5%), solid load (5, 10 and 15 g/l) and retention time (11.5 and 26 seconds) did not show a significant effect on the efficiency of the process. Adsorption data suggested a pseudo-second-order kinetics and a Freundlich adsorption model were the most appropriate.
The sediment quality including the content of investigated heavy metals (Cr, As, Cd, Pb, Cu, Zn, Ni, Mn, Co, Mo), nitrogen, and phosphorus did not change significantly after the desorption-sorption process. The concentration of heavy metals in the effluent water was significantly lower than the drinking and freshwater standards. Aerogels showed a low affinity towards the heavy metals but decreased the concentration of total phosphorus and total Kjeldahl nitrogen in water by 65% and more than 95%, respectively. Regeneration of the aerogels by organic solvents was not feasible. Repetitive regeneration by heat reduced the sorption capacity of aerogels. This research introduces a new environmentally-friendly methodology for remediation of sediments and other solid environmental media.


identifier: Golnaraghi, Sasan  (2019) Quantifying the Impact of Change Orders on Construction Labor Productivity Using System Dynamics.  PhD thesis, Concordia University.

abstract:
Researchers and industry practitioners agree that changes are unavoidable in construction projects and may become troublesome if poorly managed. One of the root causes of sub-optimal productivity in construction projects is the number and impact of changes introduced to the initial scope of work during the course of project execution. In labor-intensive construction projects, labor costs represent a substantial percentage of the total project budget. Understanding labor productivity is essential to project success. If productivity is impacted by any reasons such as extensive changes or poor managerial policies, labor costs will increase over and above planned cost. The true challenge of change management is having a comprehensive understanding of change impacts and how these impacts can be reduced or prevented before they cascade forming serious problems. This thesis proposes a change management framework that project teams can use to quantify labor productivity losses due to change orders and managerial policies across all phases of construction projects. The proposed framework has three models; fuzzy risk-based change management, AI baseline-productivity estimating, and system dynamics to illustrate cause-impact relationships. These models were developed in five stages.
In the first stage, the fuzzy risk-based change management (FRCM) model was developed to prioritize change orders in a way that only essential change orders can be targeted. In this stage, Fuzzy Analytic Hierarchy Process (F-AHP) and Hierarchical Fuzzy Inference System are utilized to calculate relative weights of the factors considered and generate a score for each contemplated change. In the second stage, baseline productivity model was developed considering a set of environmental and operational variables. In this step, various techniques were used including Stepwise, Best Subset, Evolutionary Polynomial Regression (EPR), General Regression Neural Network (GRNN), Artificial Neural Network (ANN), Radial Basis Function Neural Network (RBFNN), and Adaptive Neuro Fuzzy Inference System (ANFIS) in order to compare results and choose the best method for producing that estimate. The selected method was then used in the development of a novel AI model for estimating labor productivity. The developed AI model is based on Radial Basis Function Neural Network (RBFNN) after enhancing it by raw dataset preprocessing and Particle Swarm Optimization (PSO) to extract significant dataset features for better generalization. The model, named PSO-RBFNN, was selected over other techniques based on its statistical performance and was used to estimate the baseline productivity values used as the initial value in the developed system dynamics (SD) model.
In the fourth stage, a novel SD model was developed to examine the impact of change orders and different managerial decisions in response to imposed change orders on the expected productivity during the lifecycle of a project. In other words, the SD model is used to quantify the impact of change orders and related managerial decisions on excepted productivity. The SD model boundary was defined by clustering key variables into three categories: exogenous, endogenous, and excluded. The relationships among these key variables were extracted from the literature and experts in this domain. A holistic causal loop diagram was then developed to illustrate the interaction among various variables.
In the final stage, the developed computational framework and its models were verified and validated through a real case study and the results show that the developed SD model addresses various consequences derived from a change in combination with the major environmental and operational variables of the project. It allows for the identification and quantification of the cumulative impact of change orders on labor productivity in a timely manner to facilitate the decision-making process. The developed framework can be used during the development and execution phases of a project. The findings are expected to enhance the assessment of change orders, facilitate the quantification of productivity losses in construction projects, and help to perform critical analysis of the impact of various scope change internal and external variables on project time and cost.


identifier: Sparapani, Samantha  (2019) Elucidating the Regulation of the Metaphase-to-Anaphase Transition During Mitosis in Candida albicans.  PhD thesis, Concordia University.

abstract:
Candida albicans is an important fungal pathogen of humans. Understanding the regulation of its cell cycle and mechanisms governing the metaphase-to-anaphase transition may reveal new targets for therapeutic development. This process is dependent on several factors including; separase, a conserved cohesin protease, the separase regulator securin, the Anaphase Promoting Complex/Cyclosome (APC/C) and its cofactors Cdc20p and Cdh1p, as well as the cohesin complex. Although Cdc20p and Cdh1p have been previously characterized in C. albicans, a detailed framework of metaphase-to-anaphase progression remains elusive. We provide the first characterization of separase in C. albicans, and demonstrate its putative interactors, collectively implying conserved and novel functions. We hypothesized one putative interactor; a divergent securin called Eip1p (Esp1-Interacting Protein 1). Subsequent characterization demonstrated that Eip1p is Candida-specific, important for chromosome segregation, and exhibited conserved securin-like features including stabilization in the presence of DNA damage/stress agents. Moreover, Eip1p depletion partially suppressed a metaphase block induced by these agents. Eip1p was reduced upon Cdc5p depletion, suggesting regulation via degradation, a diagnostic feature of securins. A proportion of Eip1p-depleted cells also exhibited novel phenotypes including misoriented spindles and maintenance of elongated spindles. However, Eip1p was not consistently or strongly enriched in the absence of Cdc20p unlike other securins, and its mechanisms of action remained unclear.
 Since Eip1p is functioning like a securin, we hypothesized that its regulation includes degradation mediated by the APC/C Cdc20p, and inconsistent modulation in Cdc20p-depleted cells may be due to an incomplete Cdc20p-arrest phenotype. To test this, we investigated the APC/C subunit Cdc16p and provide the first characterization of an APC/C subunit in C. albicans. Bioinformatic analyses revealed sequence conservation of Cdc16p. Its depletion caused an early mitotic arrest, and showed enrichment of the mitotic cyclin Clb2p. Eip1p was strongly enriched upon Cdc16p depletion, suggesting conserved function of Cdc16p in C. albicans. Mechanisms of action of Eip1p were addressed through affinity purification of Eip1p and mass spectrometry, revealing some unique putative protein interactors. Overall, we present evidence of a new securin, a potential drug target, and novel insights on mitotic regulation in C. albicans.


identifier: Mkhallalati, Mouafak  (2019) A Qualitative Study of Vulnerability-Fixing Commits.  Masters thesis, Concordia University.

abstract: Security issues are a major concern in software development since the impact of exploiting security issues can be detrimental. Much of the prior work has proposed techniques that scan for and predict security vulnerabilities. However, in-depth, qualitative studies on software vulnerabilities are limited. Such studies can help the community better understand the types of vulnerabilities that exist and their potential impact in order to avoid them in the future. Therefore, in this thesis, we present the results of studying security issues faced by developers. Our study leverages data provided by the SAP research team, which contains security fixing commits related to open source Java projects used by SAP and manually curated and validated by their researchers. We study a statistically significant sample of those commits. In particular, we collect information from the related repositories, issue trackers, documentation and advisories with the aim to comprehend and categorize such security issues. Also, we provide the context required to understand the issue along with code examples extracted from each of the categories in our study. Our findings show that the vulnerabilities commonly facing developers are related to deserialization of untrusted data, zip slip, xml external entity processing, validation, authorization, race conditions, and information exposure. The fixes required to fix those vulnerabilities range from providing proper configuration of the used parser in the case of XML related issues to requiring in-depth knowledge of the code and the security issue as in vulnerabilities related to thread synchronization.


identifier: Dwyer, Meredyth  (2019) Educational Benefits from Immersion into Fiction and Nonfiction Literary Worlds.  Masters thesis, Concordia University.

abstract: Reading fiction is positively correlated with many educational and social benefits. The current study explored a comparison of historical fiction and nonfiction read alouds to determine if differences were observed in student’s transportation, content learning and socio-emotional development. The participants consisted of 40 students with ages ranging from 9- to 12-years-old. Over the period of one week, four classrooms were visited by a researcher for three sessions where excerpts from a fiction novel or nonfiction book were read aloud. The participants were then assessed on their content knowledge of the Great Depression, and their self-reports of transportation, perspective taking, fantasy, empathetic concern and helping behaviours. Through quantitative and qualitative data analysis, it was discovered that both fiction and nonfiction groups learned the same amount of content; however, fiction allowed for more positive relationships between transportation and socio-emotional development self-reports. Therefore, fiction novels can provide opportunities for the learning of historical information, while enabling a child’s growth in socio-emotional development.


identifier: Buzorgnia, David  (2019) Fast Convergence in Consensus Control of Leader-Follower Multi-Agent Systems.  Masters thesis, Concordia University.

abstract: In this thesis, different distributed consensus control strategies are introduced for a multi-agent network with a leader-follower structure. The proposed strategies are based on the nearest neighbor rule, and are shown to reach consensus faster than conventional methods. Matrix equations are given to obtain equilibrium state of the network based on which the average-based control input is defined accordingly. Two network control rules are subsequently developed, where in one of them the control input is only applied to the leader, and in the other one it is applied to the leader and its neighbors. The results are then extended to the case of a time-varying network with switching topology and a relatively large number of agents. The convergence performance under the proposed strategies in the case of a time-invariant network with fixed topology is evaluated based on the location of the dominant eigenvalue of the closed-loop system. For the case of a time-varying network with switching topology, on the other hand, the state transition matrix of the system is investigated to analyze the stability of the proposed strategies. Finally, the input saturation in agents' dynamics is considered and the stability of the network under the proposed methods in the presence of saturation is studied.


identifier: Bourbonniere, Mathieu  (2019) Playing With Culture: Reframing Video Game Localization Discourse and Issues of Censorship.  Masters thesis, Concordia University.

abstract: This thesis sets out to explore the adaptation, or alteration, of unique elements in video games and their localization, questioning their relation and relevance to censorship. While translation studies has addressed issues of censorship within literary works, little attention has been devoted to this topic within localization, and less within video game localization. Due to and industry shift from America to Japan,  localization became essential to the industry’s survival, and a kind culture clash often arises when a Japanese video game gets localized for the Western market. This thesis analyzes elements that go beyond the textual or narratological aspects of video games, to include the domain of the ludologi-cal. Some concepts utilized here are from the  field of video game studies and are used to elucidate how video game localization works within video game culture. Most importantly, video games are con-sidered cultural products, as exemplified through the dynamic of gameplay, which can be extracted, analysed, and adapted to different locales One controversial issue often brought up by users and critics through video game journalism is the belief that some alterations constitute a form a censorship. A broader video game history and game studies perspective offers localization studies a more nuanced picture of the stated aim of cultural adaptation in localization, while a more complete depiction of standard localization offers an explanatory rationale to video game studies as to how and why certain decisions are made. A useful notion of “social censorship” emerges when analyzing video game locali-zation in the domain of translation studies.


identifier: Ammar, Marwan ORCID: https://orcid.org/0000-0003-2949-4924 <https://orcid.org/0000-0003-2949-4924>  (2019) High-Level Analysis of the Impact of Soft-Faults in Cyberphysical Systems.  PhD thesis, Concordia University.

abstract:
As digital systems grow in complexity and are used in a broader variety of safety-critical applications, there is an ever-increasing demand for assessing the dependability and safety of such systems, especially when subjected to hazardous environments. As a result, it is important to identify and correct any functional abnormalities and component faults as early as possible in order to minimize performance degradation and to avoid potential perilous situations. Existing techniques often lack the capacity to perform a comprehensive
and exhaustive analysis on complex redundant architectures, leading to less than optimal risk evaluation. Hence, an early analysis of dependability of such safety-critical applications enables designers to develop systems that meets high dependability requirements. Existing techniques in the field often lack the capacity to perform full system analyses due to state-explosion limitations (such as transistor and gate-level analyses), or due to the time and monetary costs attached to them (such as simulation, emulation, and physical testing).

In this work we develop a system-level methodology to model and analyze the effects of Single Event Upsets (SEUs) in cyberphysical system designs. The proposed methodology investigates the impacts of SEUs in the entire system model (fault tree level), including SEU propagation paths, logical masking of errors, vulnerability to specific events, and critical nodes. The methodology also provides insights on a system's weaknesses, such as the impact of each component to the system's vulnerability, as well as hidden sources of failure, such as latent faults. Moreover, the proposed methodology is able to identify and categorize the system's components in order of criticality, and to evaluate different approaches to the mitigation of such criticality (in the form of different configurations of TMR) in order to obtain the most efficient mitigation solution available.

The proposed methodology is also able to model and analyze system components individually (system component level), in order to more accurately estimate the component's vulnerability to SEUs. In this case, a more refined analysis of the component is conducted, which enables us to identify the source of the component's criticality. Thereafter, a second mitigation mechanic (internal to the component) takes place, in order to evaluate the gains and costs of applying different configurations of TMR to the component internally. Finally, our approach will draw a comparison between the results obtained at both levels of analysis in order to evaluate the most efficient way of improving the targeted system design.


identifier: Qin, Mengfei  (2019) The effect of institutional distance on the choice of ownership among Chinese cross-border acquisitions.  Masters thesis, Concordia University.

abstract: This paper explores the relationship between the acquired proportions of equity, Chinese multinational enterprises’ choice and various institutional distances namely, the government and the judicial system distance, economic distance and management distance. This paper uses 554 cases of Chinese companies' cross-border acquisitions from 2010-2019.These cases were collected by Zephyr database. This paper concludes that when Chinese companies enter an unfamiliar market, as the government and the judicial system difference expands, the Chinese companies choose to acquire a higher proportion of the targets; However, as the difference in economic system expands, Chinese multinational companies reduce the proportion of equity; The management distance effect for Chinese companies' cross-border acquisitions on share ownership is not obvious.


identifier: Chen, Fei  (2019) Applications of Sulfinate Salts – Pyridine as a Removable Directing Group for Facile Access to ortho-Functionalized Sulfinate Salts.  PhD thesis, Concordia University.

abstract: Palladium catalysis is a salient synthetic methodology for carbon-carbon bond formation for which the classical procedures have been powerful tools in chemistry for decades. Due to certain limitations, alternative methods for palladium catalyzed cross couplings have been developed, rendering the approach more environmentally sustainable. Notably, the desulfinative cross coupling reaction avoids stoichiometric organometallic waste production. Furthermore, sulfinate salts are functionally versatile as they can act both as an electrophilic or nucleophilic cross coupling partner, and at the same time they are also bench stable and easy to handle. However, as sulfinate salts can undergo self-disproportionation in solution, it limits their further synthetic applications. To overcome the issue, we propose to introduce a removable multiuse moiety to maintain the sulfinic acid. We explore pyridine as a multi-purpose option, due to its directing impact on palladium catalyzed ortho-halogenation. The methodology also translates to ortho-deuteration for the synthesis of useful isotopic compounds with potential value for pharmaceutical research. After ortho-functionalization, the pyridine group can be removed to regain the sulfinic acid moiety for subsequent cross couplings. Combined, these approaches complement existing methodologies in accessing multi-functionalized arene systems.