identifier: Ghodrati Asbfroushani, Hamed  (2017) Deep Shape Representations for 3D Object Recognition.  PhD thesis, Concordia University.

abstract:
Deep learning is a rapidly growing discipline that models high-level features in data as multilayered
neural networks. The recent trend toward deep neural networks has been driven, in large part, by
a combination of affordable computing hardware, open source software, and the availability of
pre-trained networks on large-scale datasets.
In this thesis, we propose deep learning approaches to 3D shape recognition using a multilevel
feature learning paradigm. We start by comprehensively reviewing recent shape descriptors,
including hand-crafted descriptors that are mostly developed in the spectral geometry setting and
also the ones obtained via learning-based methods. Then, we introduce novel multi-level feature
learning approaches using spectral graph wavelets, bag-of-features and deep learning. Low-level
features are first extracted from a 3D shape using spectral graph wavelets. Mid-level features are
then generated via the bag-of-features model by employing locality-constrained linear coding as a
feature coding method, in conjunction with the biharmonic distance and intrinsic spatial pyramid
matching in a bid to effectively measure the spatial relationship between each pair of the bag-offeature
descriptors.
For the task of 3D shape retrieval, high-level shape features are learned via a deep auto-encoder
on mid-level features. Then, we compare the deep learned descriptor of a query shape to the
descriptors of all shapes in the dataset using a dissimilarity measure for 3D shape retrieval. For the
task of 3D shape classification, mid-level features are represented as 2D images in order to be fed
into a pre-trained convolutional neural network to learn high-level features from the penultimate
fully-connected layer of the network. Finally, a multiclass support vector machine classifier is
trained on these deep learned descriptors, and the classification accuracy is subsequently computed.
The proposed 3D shape retrieval and classification approaches are evaluated on three standard 3D
shape benchmarks through extensive experiments, and the results show compelling superiority of
our approaches over state-of-the-art methods.


identifier: Hemmatian, Masoud  (2017) Sound Transmission Analysis of Circular Sandwich Panels Fully and Partially Treated with MR Fluid Core Layer.  PhD thesis, Concordia University.

type: Thesis NonPeerReviewed

abstract:
Magnetorheological (MR) fluid is categorized as smart material whose rheological properties can be varied instantaneously under the application of an external magnetic field. Utilization of these smart multifunctional materials into the devices and structures provides a unique opportunity to develop adaptive devices/structures capable of changing their dynamic characteristics in response to wide range of external disturbances. MR fluid have been recently utilized in sandwich panels to provide variable stiffness and damping to effectively control vibrations. The main objective of the present dissertation is to investigate the sound transmission loss (STL) capability of sandwich panels treated with MR fluids at low frequencies. This dissertation contributes in three major parts. First the effect of applied magnetic field on the structural and acoustical behavior of MR fluid sandwich panels is experimentally investigated. An experimental test setup including two anechoic chambers and an electro-magnet has been designed and fabricated to experimentally investigate the effect of applied magnetic field on the STL and natural frequency of sandwich panels having different thicknesses of MR core layer. The magnetic flux density generated inside the electromagnet is simulated using magneto-static finite element analysis and validated with the measured magnetic flux density using Gaussmeter. The results from the magneto-static analysis is used to derive approximate polynomial functions to evaluate the magnetic flux density as a function of the plate’s radius and applied current.
In the second part, the sound transmission behavior of MR based-circular sandwich panels is investigated through development of efficient numerical models. The forced vibration equations of motion of the circular sandwich panel fully treated with MR fluid core layer is first derived utilizing Ritz and finite element (FE) methods using circular and annular elements. The transverse velocity in the transmitted side of the panel is then calculated and utilized to obtain the sound radiated from the panel and subsequently the STL. The theoretical models are validated comparing the simulation results with those obtained experimentally. The developed models have been subsequently used to conduct parametric studies in order to investigate the effect of the applied magnetic field, the thickness of the face sheets and the thickness of the MR core layer on the first axisymmetric natural frequency and STL of the MR based-clamped circular panels.
The last part of the present study is devoted to the topology optimization of sandwich panels partially treated with MR fluid and silicone rubber core layer. The FE model of the sandwich panel partially treated with MR fluid and silicone rubber has been developed using circular and 4-node quadrilateral elements. The developed model is then utilized to investigate the vibroacoustic behavior of MR-based sandwich panels and to obtain their natural frequencies, loss factors and STL. Subsequently, systematic parametric studies on the effect of the position of the MR fluid and silicone rubber segments on the first axisymmetric natural frequency, corresponding loss factor and also STL are presented. It has been shown that the vibrational and acoustical behavior of the sandwich panel considerably changes by varying the location of the MR fluid treatment segments. A formal constrained and unconstrained design optimization strategy have been subsequently formulated to identify the optimal location of the MR fluid segments. Due to high computational cost associated with the FE model and considering that in each optimization iteration, FE model requires to be executed several times, approximate meta-models have been developed using random and D-optimal design points to conduct optimization problems efficiently without using the full FE model. The developed meta-models are then utilized to solve the topology optimization problems using the genetic algorithm (GA) and integer programing (IP) problems. The suitability of the identified optimal candidates are further evaluated using the developed finite element model to determine the true optimized topologies for the constrained and unconstrained problems.


identifier: Krishan, Kabir  (2017) Occupant-Seat Contact Pressure Characteristics of Polyurethane Foam Seats Using Explicit Finite-Element Analyses.  Masters thesis, Concordia University.

abstract: The occupant-seat contact properties are investigated through analyses of interface pressure using explicit dynamic finite element (FE) simulations. A finite-element analysis model of a seat is developed in the LS-DYNA platform, where the material model is formulated on the basis of reported stress-strain properties of different polyurethane materials. The seat model is coupled with the finite-element models of the occupant based on the well-established frontal crash anthropomorphic test devices (ATD). The validity of the seat model is initially illustrated through simulation of a compression test model, which suggested that the hyperelastic stress-strain responses of the PUF materials can be reliably estimated using the explicit dynamic finite element platform, LS-DYNA®. The validity of the coupled seat-ATD model is also illustrated through comparisons of the contact pressure and contact area responses with the reported measured data. It is shown that the coupled occupant-seat finite element model can provide reasonable good predictions of the interface pressure and contact area, which have been correlated with occupant’s sensation of comfort. This suggested that FE models of ATD can be effectively used for predicting occupant-seat contact pressure and thus the comfort performance of seats for different body sizes, ranging from 5th percentile female to 50th and 95th percentile male population. The simulation results are obtained to illustrate significance of various factors affecting the contact pressure distribution, namely the material property, material thickness, dimensions of ATD, occupant load distribution, seat geometry and design of side wings. The contact pressure distribution and contact area responses of different design configurations of the seat are subsequently obtained and discussed so as to build guidance towards designs of seats with reduced contact pressure distributions. It is shown that the side wings constitute an additional load path and can contribute significantly in distributing the occupant load over a wider contact area and thereby limit the peak contact pressure.


identifier: Hunt, Chris  (2017) Understanding the Effects of Brand Label Attributes on Consumer Preference and Purchase Intentions: An Exploratory Study of Multinational Food Brands.  Masters thesis, Concordia University.

abstract: The Canadian consumer packaged goods industry is rife with competition and brand managers are faced with limited marketing resources.  This makes it essential for brands to stand out where it matters most: the store shelf.  This research aims to understand the effect of a foreign brand’s attributes—as represented on a product label—on Canadian consumers’ preferences and purchase intentions.  The results of this study suggest that brands must carefully select the language(s) which appear on the label when competing in a foreign market.  This research helps brand managers as they form a strategy to either change an existing brand or introduce a new packaged goods brand to the Canadian market.


identifier: Dilimulati, Aierken  (2017) Augmenting Urban Wind Energy: Shrouded Diffuser Casing for Roof-mounted Wind Turbines.  Masters thesis, Concordia University.

abstract: The increased demand for renewable energy and the development of energy independent building designs have motivated significant research into the improvement of wind power technologies that target urban environments. However, the implementation of wind turbines in urban environments still faces many challenges. The complexity of wind profile and high turbulence due to the topographical characteristics of urban environments severely limit the performance of urban wind turbines. To explore possible solutions to such challenges and better understand them, the current state of urban wind energy is thoroughly reviewed and the urban flow characteristics are investigated using computational fluid dynamics (CFD). Promising directions that can improve urban wind turbine performance are identified. A flanged shrouded diffuser mechanism - a fluid machine, mounted on rooftop of buildings used as a casing for small wind turbines can significantly improve turbine performance. The fluid machine can increase the wind energy potential by up to a factor of four, by guiding and accelerating the airflow over the building roofs utilizing its geometric features such as, cycloidal curve surface at the inlet and a vortex generating flange at the outlet. The performance of the fluid machine is tested using CFD and wind tunnel tests are also performed. To provide further evidence for its performance, the diffuser mechanism is modeled on the rooftop of an existing building in a test site in Montreal, Canada using CFD and the topographical map including the geometrical data of the buildings in the test site. The CFD analysis performed on the diffuser mechanism in the test site used real statistical wind data of the city of Montreal. CFD investigation of the test site found close agreement with the initially predicted performance of the mechanism. As a power-augmenting device, the fluid machine can mitigate the challenges faced by the urban wind energy systems and it opens new ways to improving energy efficiency of urban wind turbines.


identifier: Aggarwal, Deepak Kumar  (2017) A Platform as a Service for Concurrency-based Applications Provisioning in Internet of Things.  Masters thesis, Concordia University.

abstract:
The Internet of Things (IoT) is becoming ubiquitous with sensor nodes getting more intelligent and capable of transmitting their processed data to a cloud. Concurrency-based applications play a vital role in the rise of the IoT. A concurrency-based application has multiple processes running independently and interacting with each other. An example of the concurrency-based application in IoT is wildfire management application. In a forest, various sensor devices are deployed in the different areas. The processes of the wildfire management application are running on the sensor devices of different areas independently. The process of a particular area monitors the temperature and interacts with the processes in the neighboring areas. This interaction is based on the fire contour algorithm, which allows the application to provide the real-time direction and evolution of the fire in case of the fire incident.
Cloud computing is a paradigm for swiftly provisioning a shared pool of configurable resources (e.g., services, applications, network, and storage) on demand. Cloud computing can help to tackle the challenges of IoT-based applications provisioning by offering the Platform as a Service (PaaS). Therefore, developers of such concurrency-based applications can use cloud's PaaS for faster development as well as cost efficiency. However, the PaaS faces several challenges at the time of provisioning of concurrency-based application (i.e., development, deployment, and management). For the concurrency-based application development phase, PaaS should support the various API and frameworks for the development of multiple processes of the concurrency-based application, which helps to start development quickly. For the deployment of the concurrency-based application, the PaaS must offer the facility of hosting of different processes in an isolated environment and enable process's edges to allow inter-process communication. In management phase of the concurrency-based application, PaaS should be able to orchestrate the chain of processes defined during the development phase.
The main intent of this dissertation is to provide a PaaS solution for concurrency-based applications provisioning in IoT to solve the challenges as mentioned above. The major contributions of the thesis are in twofold. First, we propose a PaaS architecture for concurrency-based applications provisioning in IoT. Second, we provide a proof of concept in which a prototype is built using as basis Cloud Foundry, an existing PaaS platform, and TelosB as the IoT Infrastructure devices. The performance measurements have also been made to validate the results claimed.


identifier: Quach, Kha Gia ORCID: https://orcid.org/0000-0001-6952-306X <https://orcid.org/0000-0001-6952-306X>  (2017) Overcomplete Dictionary and Deep Learning Approaches to Image and Video Analysis.  PhD thesis, Concordia University.

abstract:
Extracting useful information while ignoring others (e.g. noise, occlusion, lighting) is an essential and challenging data analyzing step for many computer vision tasks such as facial recognition, scene reconstruction, event detection, image restoration, etc. Data analyzing of those tasks can be formulated as a form of matrix decomposition or factorization to separate useful and/or fill in missing information based on sparsity and/or low-rankness of the data. There has been an increasing number of non-convex approaches including conventional matrix norm optimizing and emerging deep learning models. However, it is hard to optimize the ideal l0-norm or learn the deep models directly and efficiently. Motivated from this challenging process, this thesis proposes two sets of approaches: conventional and deep learning based.
For conventional approaches, this thesis proposes a novel online non-convex lp-norm based Robust PCA (OLP-RPCA) approach for matrix decomposition, where 0 < p < 1. OLP-RPCA is developed from the offline version LP-RPCA. A robust face recognition framework is also developed from Robust PCA and sparse coding approaches. More importantly, OLP-RPCA method can achieve real-time performance on large-scale data without parallelizing or implementing on a graphics processing unit. We mathematically and empirically show that our OLP-RPCA algorithm is linear in both the sample dimension and the number of samples. The proposed OLP-RPCA and LP-RPCA approaches are evaluated in various applications including Gaussian/non-Gaussian image denoising, face modeling, real-time background subtraction and video inpainting and compared against numerous state-of-the-art methods to demonstrate the robustness of the algorithms. In addition, this thesis proposes a novel Robust lp-norm Singular Value Decomposition (RP-SVD) method for analyzing two-way functional data. The proposed RP-SVD is formulated as an lp-norm based penalized loss minimization problem. The proposed RP-SVD method is evaluated in four applications, i.e. noise and outlier removal, estimation of missing values, structure from motion reconstruction and facial image reconstruction.
For deep learning based approaches, this thesis explores the idea of matrix decomposition via Robust Deep Boltzmann Machines (RDBM), an alternative form of Robust Boltzmann Machines, which aiming at dealing with noise and occlusion for face-related applications, particularly. This thesis proposes an extension to texture modeling in the Deep Appearance Models (DAMs) by using RDBM to enhance its robustness against noise and occlusion. The extended model can cope with occlusion and extreme poses when modeling human faces in 2D image reconstruction. This thesis also introduces new fitting algorithms with occlusion awareness through the mask obtained from the RDBM reconstruction. The proposed approach is evaluated in various applications by using challenging face datasets, i.e. Labeled Face Parts in the Wild (LFPW), Helen, EURECOM and AR databases, to demonstrate its robustness and capabilities.


identifier: Vallianos, Charalampos ORCID: https://orcid.org/0000-0003-4208-5842 <https://orcid.org/0000-0003-4208-5842>  (2017) A study of hybrid ventilation in an institutional building: Modeling and predictive control.  Masters thesis, Concordia University.

abstract:
This thesis presents a numerical and experimental study of a hybrid ventilation system of an institutional building with emphasis on thermal comfort. Hybrid ventilation can improve thermal comfort and at the same time reduce energy consumption and peak power demand. By precooling the thermal mass of the building the energy consumption of the following day can also be reduced. A 17–story high institutional building is used as a case study to test different control strategies and to define the temperature low limit for admitting exterior air into the building through a transition space (a corridor), in order to ensure thermal comfort. A developed model, calibrated from full–scale tests, estimates the heat removed from the concrete and the impact on thermal comfort. It is used to test and compare the existing
control strategy to different ones of both reactive and predictive nature. 12 typical days are used to compare different control strategies. The system is currently operating based on heuristic control, with an exterior air temperature setpoint above which the air is allowed into the corridors. A control strategy based on data of the previous hour (reactive) is expected to triple the energy savings potential, but not guarantee satisfactory thermal comfort. A predictive control strategy provides thermal comfort, but also energy savings potential of the same magnitude as the reactive. Energy savings potential is increased even more if it is weighted more against discomfort when the building is unoccupied. In general the predictive control strategy opens the motorized dampers as much as possible during the cold days – without compromising thermal comfort – to precool the concrete floor so that it can reduce the cooling load of the next day.


identifier: Alsaieq, Hadia  (2017) The process of identity formation for youth growing up in multicultural familial contexts.  Masters thesis, Concordia University.

abstract: The present research examines the process of identity formation for young people who grew up in multicultural contexts. While identity development has been studied by many researchers, there is little research examining how young people who are simultaneously growing up in multiple cultures experience the process of identity formation. In the present research, ten young people (20-24 years old) who have parents from two different cultures that are different than the Euro-Canadian culture, and at least one parent is considered part of visible minority, were interviewed. Two of the participants took part in a focus group to enrich and validate the findings. The overarching category that emerged was processing being different. The first aspect of processing being different was exploring one’s belonging and one’s personal choices. The other aspect was managing relationships with family members and friends; and managing conflicts that arise in these relationships. While exploring different possibilities in how to belong to different cultural contexts and what choices to make, young people find themselves always trying to balance relationships and conflicts with significant people in their lives. The process of identity formation for multicultural youth is complex and dynamic. It requires them to exercise agency in exploring and making decisions. An appropriate support system that allows young people to express themselves and feel heard may facilitate the process of navigating between different cultural contexts and building resilience.


identifier: Li, Jiaye  (2017) How to trigger employees’ proactivity in competitive climates? A test of competing hypotheses.  Masters thesis, Concordia University.

abstract: Employees’ proactive behaviors are increasingly important for organizational development and they are highly influenced by the employees’ working atmosphere, such as its level of competitiveness. However, the implications of competitive climates for employees’ proactive behaviors remain unclear to date. This study aims to examine whether employees will engage in more or less proactive behaviors in a competitive working environment. To add more nuance to this investigation, I (a) differentiate the outcome of employees’ proactive behavior as self-beneficial (e.g., self-development) or organizational-beneficial; and (b) explore whether the relationship between competitive climates and proactive behavior is moderated by individual (learning goal orientation) and organizational factors (procedural justice). The results of this research show that competitive climates can indeed increase employees’ proactivity, for the benefit of both the organization and the individuals themselves. As expected, employees with high perceptions of procedural justice engaged in more organizational beneficial proactivity under high competitive climate, instead of more proactive behaviors targeting their own development. Contrary to expectations, the results indicate that employees with a high learning goal orientation become less motivated to engage in proactive behavior aimed at both the organization and themselves under competitive climates compared to employees with a low learning orientation. These results and their implications are discussed to encourage more research as well as supportive organizational practices for increased proactivity.


identifier: Khan, Mohd Jawad Ur Rehman  (2017) Predicting road transport GHG emissions with application for Canada.  Masters thesis, Concordia University.

abstract:
Prediction of greenhouse gas (GHG) emissions is vital to minimize their negative impact on climate change and global warming. In this thesis, we propose new models based on data mining and supervised machine learning algorithms (Regression and classification) for predicting GHG emissions arising from passenger and freight road transport in Canada. Four categories of models are investigated namely artificial neural network multilayer perceptron, multiple linear regression, multinomial logistic regression and decision tree models. From the application results, it was found that artificial neural network multilayer perceptron model showed better predictive performance over other models. Ensemble technique (Bagging & Boosting) was applied on the developed Multilayer Perceptron model which significantly improved the model's predictive performance.
The independent variable importance analysis conducted on multilayer perceptron model disclosed that among the input attributes Light truck emissions, Car emissions, GDP transportation, Heavy truck emission, Light duty truck fuel efficiency, Interest rate (overnight), Medium Trucks Emission, Passenger car fuel efficiency and Gasoline Price have higher sensitivity on the output of the predictive model of GHG emissions by Canadian road transport.
Scenario analysis is conducted using widely available socioeconomic, emission and fuel efficiency attributes as inputs in multilayer perceptron (with bagging) model. The results show that in all Canadian road transport GHG emission projection scenarios, all the way through 2030, emissions from Light trucks will hold a major share of GHG emissions. Thereby, rigorous efforts should be made in mitigating GHG emissions from these trucks (freight transport) to meet the ambitious GHG emission target for Canadian road transport.


identifier: Rezaei, Hamidreza  (2017) Modelling and Solving Decentralized and Dynamic Aircraft Landing Scheduling Problems.  Masters thesis, Concordia University.

abstract:
Aircraft landing problem (ALP) is considered as a scheduling problem where aircrafts are sequenced and allocated with appropriate time slots. In this thesis ALP problem is investigated where several constraints such as aircraft’s landing time windows, minimum separation time and position shifting constraints are taken into consideration.  Existing approaches such as optimized solution based methods and heuristic methods to tackle different aspects of the problem are reviewed, and a static mathematical model is studied. The mathematical model is solved and verified using random data generated from simulation. The data are generated based on Pierre Elliott Trudeau International Airport (YUL) in Montreal, Quebec, Canada as well as from relevant data base library. AnyLogictm software was used to simulate aircraft landing operations in a runway environment. An agent based simulation was designed to include the dynamic event of aircrafts arrivals to the runway system.
In the agent based system, an iterative bidding framework is used to generate flight landing schedule in a decentralized environment. In the decentralized environment, we consider each flight as a self-interest agent competing with other flights to get the most appropriate landing time. The efficiency of the decentralized approach is also studied. The results of the decentralized approach are compared with the centralized ALP solution. The results show that the agent based solution approach is able to generate reasonable landing comparing to optimal aircraft landing schedule from the centralized ALP model.


identifier: valeh, moayeri  (2017) Design Change Management in Construction Projects Using Building Information Modeling (BIM).  PhD thesis, Concordia University.

abstract: Scope changes in construction can vary, and among all types of changes, design change by owner is the type that most often threatens a project with failure. Design changes requested by owners include additions, deletions and/or modifications to the original scope of the work. Design changes frequently impact project cost and time and have the potential to increase the possibility of conflicts between owners and contractors. Project time and cost change impact can become severe if owners do not consider the fact that a change in one part of the project may cause a series of changes in other parts of the project, which is known as the “change ripple effect.” Therefore, for the well-organized delivery of construction projects, it is essential to have an efficient design change management system. The fundamental objective of any change management system is to eliminate any unnecessary extra costs and time delays to the original contract. Therefore, there are two main factors to effectively manage design change: first, identifying the ripple effect of the design change on other project components, and second, quantifying the ripple effect of a change on project cost and time. Limited work has been conducted in this area and no integrated model has been developed that would be able to visualize, identifies and quantifies the above-mentioned factors. This thesis presents an automated model named BIM-Change for design professionals and owners that make it possible to visualize the ripple effects of owners’ design changes. The developed model calculates the impact of design changes and their ripple effect on a project’s total duration and updates the project schedule accordingly. It then estimates the impact of design changes, and their ripple effect, on project cost. The cost data provided by the developed model would be the updated project total cost including direct cost, indirect cost and impact cost. As result of the proposed model, the computer program called BIM-Change was developed using the “Visual C#. Net” programming language. This program consists of six add-ins: Check Change, Ripple Effect, Room Grouping, Time Impact, and Cost Impact, Data Filtering. The model has been applied to a case study to demonstrate its usefulness, illustrate its essential features, and facilitate its evaluation. The result validated the advantages of the BIM-Change over the available software such as Vico, Innovaya, Autodesk Navisworks, Synchro and Assemble.


identifier: Elnashar, Gamaleddine A. M. ORCID: https://orcid.org/0000-0003-3868-9168 <https://orcid.org/0000-0003-3868-9168>  (2017) Modeling and Analysis of Pavement-Vehicle Interaction Dynamics for Pavement Distress Prediction.  PhD thesis, Concordia University.

abstract:
Increased road traffic combined with heavy vehicle loads lead to deterioration and distress of pavements and consequently reduces the life span of the paved roads. As a result, large amounts of financial and labor resources are spent every year to improve and maintain road infrastructures around the world. Traditionally, vehicle and pavement dynamics are treated as two separate areas of research. However, they are strongly coupled together through their contact points. Thus, one of the major concerns is to develop a more reliable dynamic pavement-vehicle interaction model to investigate and evaluate accurately both vehicle and pavement responses, and also to examine the pavement distress due to the severity of traffic loads. One of the most important distress modes in pavements is fatigue cracking. Despite the fact that there have been considerable efforts in recent years in fatigue performance evaluation and the design of flexible pavements, there is still a need for further studies in predicting fatigue cracking in terms of damage distribution considering the uncertainty and variability associated with the input parameters of pavement-vehicle interaction and traffic load repetitions.

The main objective of this research study is to carry out an in-depth investigation of the dynamics of the pavement-vehicle interaction and the effect of coupling action on system response, as well as fatigue study of the pavement due to repeated traffic loads. The response of the pavement-vehicle coupled system supported by a linear visco-elastic foundation has been investigated. The vehicle is modeled as a two-degree-of-freedom quarter-vehicle model, and the pavement-foundation system is described by a simply supported Euler-Bernoulli beam resting on Pasternak foundation, while the tire is coupled to the flexible pavement with a single point contact. Galerkin method has been utilized to develop the governing differential equations of motion. Direct numerical integration approach based on implicit Newmark linear average acceleration technique has been used to solve the governing differential equations in order to evaluate the response of the coupled system. Results have been validated with previous research work and also compared with those of conventional uncoupled system. The effects of different parameters such as vehicle speed, road roughness, soil stiffness and suspension damping on the responses are then investigated. For the fatigue study of flexible pavements, a methodology, for modeling pavement damage and predicting fatigue cracking of flexible pavements is presented. The methodology is based on the combination of deterministic method and stochastic approach using Palmgren-Miner’s hypothesis in which Poisson process is employed to characterize the actual repetitions of traffic load. Different models are then presented to estimate the fatigue life of the pavement surface layer. The results are compared and discussed.


identifier: Graham, M. Dean  (2017) Neuropharmacological mechanisms underlying the effect of medial preoptic area dopamine in the sexual behaviour of female rats.  PhD thesis, Concordia University.

abstract: Dopamine (DA) in the medial preoptic area (mPOA) mediates the display of solicitational behaviours in the female rat.  Previous work from my Masters’ thesis demonstrated that a DA D1 receptor (D1R)-mediated excitatory state appears to occur in females hormonally-primed with both estradiol benzoate (EB) and progesterone (P).  Conversely, a DA D2 receptor (D2R)-mediated inhibitory state appears to occur in females primed only with EB.  The goals of the current thesis were to understand the mechanisms by which this control occurs, and to incorporate this understanding into the bigger framework of neural control underlying female sexual behaviour.  To accomplish this, a variety of techniques were utilized.  First, the same behavioural results observed previously were replicated through an endogenous alteration of DA release.  It was found that administration of ascorbic acid produced an increase in solicitational, but not consummatory behaviours, in females in both hormonal conditions.  Three techniques were then employed to study changes in DA receptors (DAR) in the mPOA under three hormonal profiles.  Immunohistochemistry determined the number of neurons in the mPOA containing D1R or D2R, DAR protein levels were analyzed using Western blotting, and DAR functional binding levels were examined using autoradiography.  The results from all three techniques supported the previous behavioural findings that EB+P females have a higher D1R/D2R ratio, and thus a D1R-mediated system, and EB-alone females have a lower D1R/D2R ratio, and thus a D2R-mediated system.  Finally, fluorescence immunohistochemistry was used to map connections from the mPOA to areas known to regulate female sexual behaviour.  These pathways were investigated for neuronal type and presence of DAR under different hormonal conditions.  Modifications were found, demonstrating that ovarian steroids alter the mechanisms underlying solicitational behaviour via projections to other areas implicated in female sexual behaviour.  A conceptual model is presented here that integrates the data in this thesis along with other known networks that control female sexual behaviour.  This model has important implications for the treatment of female sexual desire disorders, and places a central role of DA terminals in the mPOA in the regulation of motivated behaviours in general.


identifier: Rader, Aubyn  (2017) Thetis.  Masters thesis, Concordia University.

title: Thetis

abstract:
Thetis is a Nereid, a minor female deity, living a quiet existence in her villa on the island of Lemnos. When a strange, wretched creature crash lands onto her shores, Thetis has a prophetic vision that the wretch’s life is inextricably connected to the fate of her prophesied son. Complicating matters, the Olympian gods Zeus and Hera have taken a strange interest in the creature, commanding her to kill it. Thetis must make a choice: trust her visions and care for the creature, or go against the will of the gods and decide to kill it. Throughout her journey, Thetis will discover the nature of the creature, how it has earned the animosity of the gods, and what the creature has to do with her unborn son.

Drawing on the myths of Homer, Ovid, and Apollonius Rhodius, "Thetis" brings the life of a background character into the foreground, and connects the seemingly disparate mentions of her life into a unified narrative.


identifier: Yin, Yuming  (2017) Enhancement of Ride and Directional Performances of Articulated Vehicles via Optimal Frame Steering and Hydro-Pneumatic Suspension.  PhD thesis, Concordia University.

abstract:
Off-road vehicles employed in agriculture, construction, forestry and mining sectors are known to exhibit comprehensive levels of terrain-induced ride vibration and relatively lower directional stability limits, especially for the articulated frame-steered vehicles (AFSV). The transmitted whole-body vibration (WBV) exposure levels to the human operators generally exceed the safety limits defined in ISO-2631-1 and the European Community guidelines. Moreover, the directional stability limits are generally assessed neglecting the contributions due to terrain roughness and kineto-dynamics of the articulated frame steering (AFS) system. Increasing demand for high load capacity and high-speed off-road vehicles raises greater concerns for both the directional stability limits and WBV exposure. The criterion for acceptable handling and stability limits of such vehicles do not yet exist and need to be established. Furthermore, both directional stability performance and ride vibration characteristics are coupled and pose conflicting vehicle suspension design requirements. This dissertation research focuses on enhancement of ride, and roll- and yaw-plane stability performance measures of frame-steered vehicle via analysis of kineto-dynamics of the AFS system and hydro-pneumatic suspensions.
A roll stability performance measure is initially proposed for off-road vehicles considering magnitude and spectral contents of the terrain elevations. The roll dynamics of an off-road vehicle operating on random rough terrains were investigated, where the two terrain-track profiles were synthesized considering coherency between them. It is shown that a measure based on steady-turning root-mean-square lateral acceleration corresponding to the sustained period of unity lateral-load-transfer-ratio prior to the absolute-rollover, could serve as a reliable measure of roll stability of vehicles operating on random rough terrains. The simulation results revealed adverse effects of terrain elevation magnitude on the roll stability, while a relatively higher coherency resulted in lower terrain roll-excitation and thereby higher roll stability. The yaw-plane stability limits of an AFSV are investigated in terms of free yaw-oscillations as well as transient steering characteristics through field measurements and simulations of kineto-dynamics of the AFS system. It was shown that employing hydraulic fluid with higher bulk modulus and increasing the steering arm lengths would yield higher yaw stiffness of the AFS system and thereby higher frequency of yaw-oscillations. Greater leakage flows and viscous seal friction within the AFS system struts caused higher yaw damping coefficient but worsened the steering gain and articulation rate. A design guidance of the AFS system is subsequently proposed. The essential objective measures are further identified considering the AFSV’s yaw oscillation/stability and steering performances, so as to seek an optimal design of the AFS system.
For enhancing the ride performance of AFSV, a simple and low cost design of a hydro-pneumatic suspension (HPS) is proposed. The nonlinear stiffness and damping properties of the HPS strut that permits entrapment of gas into the hydraulic oil were characterized experimentally and analytically. The formation of the gas-oil emulsion was studied in the laboratory, and variations in the bulk modulus and mass density of the emulsion were formulated as a function of the gas volume fraction. The model results obtained under different excitations in the 0.1 to 8 Hz frequency range showed reasonably good agreements with the measured stiffness and damping properties of the HPS strut. The results showed that increasing the fluid compressibility causes increase in effective stiffness but considerable reduction in the damping in a highly nonlinear manner. Increasing the gas volume fraction resulted in substantial hysteresis in the force-deflection and force-velocity characteristics of the strut.
A three-dimensional AFSV model is subsequently formulated integrating the hydro-mechanical AFS system and a hydro-pneumatic suspension. The HPS is implemented only at the front axle, which supports the driver cabin in order to preserve the roll stability of the vehicle. The validity of the model is illustrated through field measurements on a prototype vehicle. The suspension parameters are selected through design sensitivity analyses and optimization, considering integrated ride vibration, and roll- and yaw-plane stability performance measures. The results suggested that implementation of HPS to the front unit alone could help preserve the directional stability limits compared to the unsuspended prototype vehicle and reduce the ride vibration exposure by nearly 30%. The results of sensitivity analyses revealed that the directional stability performance limits are only slightly affected by the HPS parameters. Further reduction in the ride vibration exposure was attained with the optimal design, irrespective of the payload variations.


identifier: Mamani, Sara  (2017) Residual Stresses in Thick Thermoset Composite Laminates due to Manufacturing Process.  Masters thesis, Concordia University.

abstract:
The relevance of fiber-reinforced polymer composite materials to aerospace has increased to the point that they are used for high-load-bearing applications. For example, thick flex beam composite parts could be used in rotorcraft industries to manufacture helicopter’s main rotor yoke. Manufacturing thick thermosetting laminates inside an autoclave is usually accompanied with an exothermic reaction and temperature overshoot during the curing process. This can cause process-induced stresses to build-up. To measure these internal stresses, the numerical and experimental approaches were studied. 80 layer unidirectional and cross-ply glass/epoxy laminates were manufactured by hand lay-up. The temperature distribution during curing process inside the autoclave was measured through placing five thermocouples at every 20 layers inside the laminate. The finite difference formulation of the one-dimensional transient heat transfer including internal heat generation was developed to simulate the temperatures and degrees of cure. The calculated temperature profile was compared with the experimental result and it was found that the numerical values agreed well with the measured temperatures through the thickness. Afterwards, the evolution of residual stresses as the direct consequence of the complex gradients of temperature and degree of cure across the thickness were calculated incrementally.
To experimentally quantify the residual stresses in thick composite laminates, deep hole drilling technique was proposed. This method relies on the measurement of strain relaxation resulting from material removal. First, a small hole was drilled in a plate consisting of 80 layer glass/epoxy laminate. The diameters of the hole were measured. Then, the changes in the hole diameters due to the stress relaxation by trepanning a core from around the hole were re-measured. Finite element analyses were then carried out to provide distortion coefficients for far field applied stresses. Residual stresses were be determined through the combination of numerical and experimental approach.


identifier: Anyan, Jeffrey, J.C.  (2017) Investigating individual differences in circadian locomotor parameters, depression- and anxiety-like behaviors and comorbidity in healthy Lewis rats.  PhD thesis, Concordia University.

abstract:
Disrupted circadian rhythms are a core feature of various psychiatric disorders, including, but not limited to depression and anxiety. At this point, it remains uncertain whether disrupted circadian rhythms are implicated in the pathophysiology of mental disorders or whether the disrupted circadian rhythms are simply a byproduct of the disorder.  The objective of this thesis is to explore the relationship between circadian rhythms and mood.  The first study examines individual differences in circadian locomotor behavior and mood-related behaviors in rats.  The circadian phenotype of male Lewis rats was characterized by analyzing daily wheel running activity under multiple lighting conditions: standard 12h:12h LD conditions, constant dark, constant light, and rate of re-entrainment to a phase advance. Rats were then tested on a battery of behavioral tests: activity box, elevated plus maze (EPM), forced swim test (FST), and fear conditioning.

We found an interesting relationship between entrainment parameters and mood-related behaviors.  Under 12h:12h LD conditions, percent of daily activity in the light phase and variability in activity onset were associated with latency to immobility in the FST.  Variability in onset was also associated with anxiety-like behavior in the EPM.  Rate of re-entrainment correlated with anxiety-like behaviors in the activity box and EPM.  Our findings suggest that Lewis rats may be a suitable strain for studying the relationship between circadian rhythms and mood-related behaviors in rodents.

In human clinical populations, comorbidity rates between depression and anxiety are very high.  Surprisingly, little attention has been given to the question of comorbidity in animal models.  To further examine the utility of Lewis rats for the study of mood-related behaviors we then assessed for comorbidity between depression- and anxiety-like behaviors. Interestingly, our findings indicate suggest that Lewis rats do not exhibit comorbid depression- and anxiety-like behaviors. While the absence of a comorbid relationship between depression- and anxiety-like behaviors may come as a surprise, we present an alternative interpretation of escape-directed behaviors in the FST.


identifier: Duong, Chi Nhan ORCID: https://orcid.org/0000-0002-5177-0393 <https://orcid.org/0000-0002-5177-0393>  (2017) Beyond PCA: Deep Learning Approaches for Face Modeling and Aging.  PhD thesis, Concordia University.

abstract: Modeling faces with large variations has been a challenging task in computer vision. These variations such as expressions, poses and occlusions are usually complex and non-linear. Moreover, new facial images also come with their own characteristic artifacts greatly diverse. Therefore, a good face modeling approach needs to be carefully designed for flexibly adapting to these challenging issues. Recently, Deep Learning approach has gained significant attention as one of the emerging research topics in both higher-level representation of data and the distribution of observations. Thanks to the nonlinear structure of deep learning models and the strength of latent variables organized in hidden layers, it can efficiently capture variations and structures in complex data. Inspired by this motivation, we present two novel approaches, i.e. Deep Appearance Models (DAM) and Robust Deep Appearance Models (RDAM), to accurately capture both shape and texture of face images under large variations. In DAM, three crucial components represented in hierarchical layers are modeled using Deep Boltzmann Machines (DBM) to robustly capture the variations of facial shapes and appearances. DAM has shown its potential in inferencing a representation for new face images under various challenging conditions. An improved version of DAM, named Robust DAM (RDAM), is also introduced to better handle the occluded face areas and, therefore, produces more plausible reconstruction results. These proposed approaches are evaluated in various applications to demonstrate their robustness and capabilities, e.g. facial super-resolution reconstruction, facial off-angle reconstruction, facial occlusion removal and age estimation using challenging face databases: Labeled Face Parts in the Wild (LFPW), Helen and FG-NET. Comparing to classical and other deep learning based approaches, the proposed DAM and RDAM achieve competitive results in those applications, thus this showed their advantages in handling occlusions, facial representation, and reconstruction. In addition to DAM and RDAM that are mainly used for modeling single facial image, the second part of the thesis focuses on novel deep models, i.e. Temporal Restricted Boltzmann Machines (TRBM) and tractable Temporal Non-volume Preserving  (TNVP) approaches, to further model face sequences. By exploiting the additional temporal relationships presented in sequence data, the proposed models have their advantages in predicting the future of a sequence from its past. In the application of face age progression, age regression, and age-invariant face recognition, these models have shown their potential not only in efficiently capturing the non-linear age related variance but also producing a smooth synthesis in age progression across faces. Moreover, the structure of TNVP can be transformed into a deep convolutional network while keeping the advantages of probabilistic models with tractable log-likelihood density estimation. The proposed approach is evaluated in terms of synthesizing age-progressed faces and cross-age face verification. It consistently shows the state-of-the-art results in various face aging databases, i.e. FG-NET, MORPH, our collected large-scale aging database named AginG Faces in the Wild (AGFW), and Cross-Age Celebrity Dataset (CACD). A large-scale face verification on Megaface challenge 1 is also performed to further show the advantages of our proposed approach.


identifier: Zhang, Ziyang  (2017) Development of an Integrated Risk Analysis System (ARCTRA) for Runoff Related Heavy Metal Contaminant in Unsaturated Zone.  Masters thesis, Concordia University.

abstract:
An integrated analytical runoff and contaminant transport risk analysis system (ARCTRA) is developed for assessing the environmental risks associated with heavy metal transport in the unsaturated zone. The ARCTRA system considers three processes: rainfall runoff, soil erosion and solute transport in soil. A corresponding analytical solution is applied for each process. Particularly, a Monte Carlo simulation is integrated to quantify the uncertainties associated with key model parameters after model sensitivity analysis. Moreover, the Fuzzy Set risk assessment method is employed to quantify incomplete-type uncertainties associated with the site conditions, environmental quality guidelines and health impact criteria based on the Monte Carlo Probability Simulation. Fuzzy membership functions are established considering the environmental-guideline-based risk (ER) and health risk (HR) to obtain a generalized risk level through a fuzzy rule base. An integrated risk value can be then obtained to
evaluate and rank the risk level of a contaminated site. Finally, a user interface was developed for the ARCTRA system based on the VB program code in Excel to facilitate technology transfer and to provide a user-friendly system to assist in the processing of input and calculation of results. The ARCTRA system developed in this study can be used to systematically assess the heavy metal in the unsaturated zone caused by rainfall-runoff process and support effective management of the contaminated site.

The developed ARCTRA system was verified through compassion analysis against existing models. Specifically, the rainfall-runoff section was compared with the PCSWMM model which simulates the runoff formation under given rainfall conditions. In the soil erosion part, an analytic solution from the Hairsine-Rose model
was studied to conduct a comparative analysis of the concentration of heavy metal dissolved in the surface runoff. And, the ARCTRA module for analyzing transport of contaminants in the soil is examined against the STANMOD and the HYDRUS model. Two real cases were studied in this thesis. Pb and Zn were studied in the case studies. The results of the ARCTRA and other existing models were obtained based on the real case data and compared with monitoring data The model verification and validation indicates the developed ARCTRA system is useful in assessing the risks of heavy metals in the soil caused by the rainfall-runoff process.


identifier: Melgar, Mindy  (2017) Screening of a library of putative maleate isomerases for the engineering of a synthetic maleic acid-producing Escherichia coli strain.  Masters thesis, Concordia University.

abstract: Efforts to stimulate economic independence while remaining environmentally conscious have motivated researchers to replace non-renewable resources through the engineering of suitable microbes. The efficient generation of polymer precursors, such as maleic acid, through engineered microbial strains will contribute to this aim. This work proposed an engineered strain of Escherichia coli to produce the non-native dicarboxylic acid, maleic acid. The strategy included the design of a synthetic metabolic pathway to overproduce fumaric acid, which would serve as a substrate for the heterologously expressed maleate isomerase. The modifications to the E. coli strain included 6 knockouts, that resulted in a 10-fold increase in fumaric acid production (7.46mg/l vs. 0.78mg/l). The kinetic characteristics of maleate isomerases had not previously been explored in great detail, which prompted the inclusion of a screening of putative isomerases for optimal activity in the synthetic pathway. A library of 55 maleate isomerase candidates was generated from published literature and bioinformatics databases. Activity of the candidates was screened; the favoured forward reaction (maleic acid to fumaric acid) was observed in 23 variants, and the desired reverse reaction was observed in 13 variants. Maleic acid was successfully produced in vivo at a titre of about 100μg/l, which will require significant improvement before industrial implementation is possible. This is however, to our knowledge, the first time a host has been engineered to produce maleic acid using maleate isomerases. Future optimization of this production strain will contribute to a reduced dependence on petroleum as a resource for the polymer precursor, maleic acid.


identifier: Saleh, Muftah  (2017) Analysis, Design Optimization, and Semi-Active Control of Skid Landing Gear Featuring Bi-Fold Magnetorheological Dampers.  PhD thesis, Concordia University.

abstract:
Providing safer environment and minimizing the fatalities during helicopter harsh impacts and crashes have been a concern to scientists, engineers, and the regulating agencies since the dawn of helicopter industry. Tremendous efforts have been devoted to enhance the crashworthiness capabilities of helicopter’s skid landing gear (SLG) system. These efforts have been aiming to improve the energy absorption capabilities of the conventional SLG designs while maintaining minimum weight and adequate strength to comply with the airworthiness requirements. The emerging of smart materials and the advances in control engineering have provided a new horizon to design lightweight landing gears with enhanced energy absorption capacity.
In this context, the main objectives of the present dissertation research are to investigate the crashworthiness performance of the conventional SLG; to formulate a design optimization strategy to design light-weight SLG with enhanced energy absorption capacity and finally to propose an adaptive SLG utilizing bi-fold magnetorheological dampers in an attempt to  exceed the requirements of the crashworthiness specifications for skid landing gear systems while minimizing the level of sudden acceleration experienced by the aircraft occupants in the event of impact. The present research consists of four synergistically related phases. In the first phase, the dynamic response analysis has been conducted on the baseline conventional skid landing gear system in order to assess its capabilities and to establish a reference benchmark for the subsequent work. In the second phase, a design optimization strategy has been formulated to identify the optimal cross sectional dimensions of the round shaped crosstubes in the SLG system to maximize their energy absorption at sink rate of 2.44 m/s and to minimize the crosstubes mass. The optimization results showed that the specific energy absorption of the design optimized SLG could be substantially increased by 35% compared to that of baseline design and the crosstubes mass was decreased by 24.5%. Deign curves and guidelines have also been presented to directly determine the required effective mass of the helicopter and the corresponding desired maximum deflection of the helicopter under given sink rate and different values of rotor lift factor.
In the third phase, governing equations to predict the damping force and dynamic range of a bi-fold magnetorheological energy absorber (MREA) under impact have been presented. To predict the behavior of the MREA more accurately under high impact velocities, the Bingham plastic model with minor loss factors (BPM) has been incorporated in the problem formulation.  The optimal geometrical parameters of the candidate bi-fold magnetorheological energy absorber (MREA) under volume constraint to maximize the damping force at piston velocity of 5 m/s have then been presented. Results showed a dynamic range of around two has been attained at this design speed. The proposed optimization problem has been solved using combined stochastic based (Genetic Algorithm) and nonlinear mathematical programming (Sequential Quadratic Programming Algorithm) techniques.
In the fourth phase, the MREA device model has been incorporated in a single degree of freedom helicopter model to assess the performance of the adaptive SLG system. The comparison of the responses revealed that the proposed adaptive SLG equipped with the MREA could minimize the induced acceleration while utilizing the full energy absorption stroke without encountering end-stop impact. The MREA performance was evaluated in terms of Bingham numbers for compression and rebound strokes. New optimum Bingham numbers-rotor lift factor chart has been introduced to control the generation of the required damping force based on the activated rotor lift force. Finally, to investigate the closed-loop performance of the tuneable MREA in the SLG system, a simple semi-active control strategy has been presented. The semi-active controller was designed based on the optimum Bingham numbers identified previously. Using the values of the velocity at the impact instant and the mass of the helicopter, the controller evaluates the required current for the MREA to generate desired yield force.


identifier: Okoye, Mildred Chidinma  (2017) New applications of blockchain technology to voting and lending.  Masters thesis, Concordia University.

abstract:
With a lot of attention (even hype) given to blockchain technology, it is not startling that many researchers, developers, journalists, and start-ups have posited blockchain technology as the missing link for solving several problems with major interest within the
financial sector.

Motivated by the current burst of interest around blockchains, we examine the feasibility of a few decentralized blockchain applications: specifically, voting and lending. The spiked interest in blockchain is the result of its perceived benefits, ranging from the removal of trusted parties and bureaucracy, lower costs, transparency, among others. In this thesis, we explore how the blockchain mechanism works, how it can be integrated with the
concept of smart contracts (scripts that exist on the blockchain enabling the automation of processes), and how to create applications that operate on this decentralized platform.

We start by considering the viability of voting on a blockchain. Then, the bulk of thisthesis focuses on a lending infrastructure for cryptocurrencies deployed on the Ethereum Virtual Machine. We present a cognitive walk-through for the deployment of a loan (peer
to peer lending and bonds) on the blockchain by utilizing the transparency offered. A performance evaluation is given in terms of transparency, cost, security and reliability of the system. Limitations encountered as well as future work are discussed in the later part
of this thesis.


identifier: Lyu, Di  (2017) The Role of Brand Relationship Quality and Cultural Values in Building Brand Loyalty in Social Commerce Environments.  Masters thesis, Concordia University.

abstract: Rapid development of social commerce environments has made marketers and managers sense enormous business values in that, they hope to gain customer’s loyalty by utilizing social media platforms. This research aims to investigate the mediating role of brand relationship quality in influencing the effect of characteristics of brand pages on brand loyalty. Besides, this research covers the gap of investigating the role of cultural values in influencing brand relationship quality and brand loyalty, since no research focuses on how cultural values influence customer’s loyalty towards brands and their relationships with brands in social commerce environments. Results indicate that cultural values like individualism, and power distance positively influence the effect of brand relationship quality on brand loyalty, while indulgence negatively influences the relationship between brand relationship quality and brand loyalty. When it comes to managerial implications, the research suggests that brand marketers and managers need to maintain friendly relationships with their customers in order to attract their loyalty. Another implication for marketers and managers is that cultural values are so crucial in building up brand loyalty that it should not be ignored, they should consider how to retain customers with lower individualism scores and lower power distance scores, since they are less attractive in gaining brand loyalty in social commerce environments.


identifier: Kane, Aminata  (2017) Efficient and Scalable Techniques for Multivariate Time Series Analysis and Search.  PhD thesis, Concordia University.

abstract:
Innovation and advances in technology have led to the growth of time series data at a phenomenal rate in many applications. Query processing and the analysis of time series data have been studied and, numerous solutions have been proposed. In this research, we focus on multivariate time series (MTS) and devise techniques for high dimensional and voluminous MTS data.
The success of such solution techniques relies on effective dimensionality reduction in a preprocessing step. Feature selection has often been used as a dimensionality reduction technique. It helps identify a subset of features that capture most characteristics from the data. We propose a more effective feature subset selection technique, termed Weighted Scores (WS), based on statistics drawn from the Principal Component Analysis (PCA) of the input MTS data matrix. The technique allows reducing the dimensionality of the data, while retaining and ranking its most influential features. We then consider feature grouping and develop a technique termed FRG (Feature Ranking and Grouping) to improve the effectiveness of our technique in sparse vector frameworks. We also developed a PCA based MTS representation technique M2U (Multivariate to Univariate transformation) which allows to transform the MTS with large number of variables to a univariate signal prior to performing downstream pattern recognition tasks such as seeking correlations within the set.
In related research, we study the similarity search problem for MTS, and developed a novel correlation based method for standard MTS, ESTMSS (Efficient and Scalable Technique for MTS Similarity Search). For this, we uses randomized dimensionality reduction, and a threshold based correlation computation. The results of our numerous experiments on real benchmark data indicate the effectiveness of our methods.
The technique improves computation time by at least an order of magnitude compared to other techniques, and affords a large reduction in memory requirement while providing comparable accuracy and precision results in large scale frameworks.


identifier: Oum, Nathalie  (2017) Modeling socio-economic impacts of infrastructure works.  PhD thesis, Concordia University.

abstract: One-third of Canadian municipal infrastructure is in fair, poor or very poor condition, thus increasing the risk of service disruption (FCM, 2016). This represents a call for major construction works, which cause considerable business closures and increased travel delays. Therefore, the quantification of socio-economic impacts on businesses, residents, and road users due to construction works, has become important for municipalities. However, there is a lack of research on the quantification of socio-economic impacts at macro-level. In previous research efforts, developed quantification models were mostly site-specific, at micro-level, with no clear distinction between proposed categories of impacts. The main objective of this research is to model social costs of municipal infrastructure interventions at macro-level. First, the indicators that constitute tangible and intangible social costs of infrastructure works were identified and studied. Second, models were developed for each indicator to predict social cost variables. Third, non-linear regression models were built on the relationship between social cost variables and predictor variables, using the method of least squares. The following infrastructure assets are included in this research: potable water, wastewater and storm water pipes and roads. This research demonstrates that social cost indicators related to infrastructure works can be modeled by non-linear regression functions, thus enabling to assess social costs at a large scale. Then the social costs were incorporated in a Decision support system to compare three scenarios of renewal policies. The first scenario that is avoiding open-cut road reconstruction until the buried pipe replacement, results in the highest total costs and the best levels of service (LOS). The second scenario that is avoiding pipe replacement until the road reconstruction, results in the lowest total costs and the lowest LOS. This is because of the increase of pipe failures. Finally, the third scenario that is mixing both of the aforementioned strategies, results in the in-between solution with lower total costs and acceptable LOS.


identifier: Alagesan, Vignesh  (2017) Investigating congestion mitigation scenarios to reduce truck turn time at Port of Montreal using Discrete Event Simulation.  Masters thesis, Concordia University.

abstract:
Container ports are facing the growing problem of congestion due to the high volume of container trucks entering the terminal. Globalization, growth of trade and increasing consumer demand have further added to this complexity which has resulted in increased greenhouse gas emissions at the ports. Several measures are being undertaken by the ports to reduce this problem and improve port sustainability. Examples of these measures are implementing advanced technology equipment, implementing extended gate hours, changing the arrival patterns of trucks, and implementing variable gate lane policies.
The objective of the thesis is to develop a discrete event simulation (DES) model to investigate the congestion mitigation scenarios to improve terminal productivity and reduce truck turn times at the Port of Montreal. A case study with the Montreal Port Authority is conducted. The results of our simulation study yield upgrade of technology at the terminals as the best solution followed by managing the arrival patterns, changing gate lanes and extended gating hours. The proposed work is novel and one of the very few to be conducted in the context of Port of Montreal. The generated results can be used by decision makers at Port of Montreal in developing strategies to mitigate congestion and reduce truck turn times at terminals.


identifier: Ahmed, Marwa Hussein  (2017) Integrated NDE Methods Using Data Fusion-For Bridge Condition Assessment.  PhD thesis, Concordia University.

abstract:
Bridge management system (BMS) is an effective mean for managing bridges throughout their design life. BMS requires accurate collection of data pertinent to bridge conditions. Non Destructive Evaluation methods (NDE) are automated accurate tools used in BMS to supplement visual inspection. This research provides overview of current practices in bridge inspection and in-depth study of thirteen NDE methods for condition assessment of concrete bridges and eleven for structural steel bridges. The unique characteristics, advantages and limitations of each method are identified along with feedback on their use in practice. Comparative study of current practices in bridge condition rating, with emphasis on the United States and Canada is also performed. The study includes 4 main criteria: inspection levels, inspection principles, inspection frequencies and numerical ratings for 4 provinces and states in North America and 5 countries outside North America. Considerable work has been carried out using a number of sensing technologies for condition assessment of civil infrastructure. Fewer efforts, however, have been directed for integrating the use of these technologies. This research presents a newly developed method for automated condition assessment and rating of concrete bridge decks. The method integrates the use of ground penetrating radar (GPR) and infrared thermography (IR) technologies. It utilizes data fusion at pixel and feature levels to improve the accuracy of detecting defects and, accordingly, that of condition assessment. Dynamic Bayesian Network (DBN) is utilized at the decision level of data fusion to overcome cited limitations of Markov chain type models in predicting bridge conditions based on prior inspection results. Pixel level image fusion is applied to assess the condition of a bridge deck in Montreal, Canada using GPR and IR inspection results.  GPR data are displayed as 3D from 24 scans equally spaced by 0.33m to interpret a section of the bridge deck surface. The GPR data is fused with IR images using wavelet transform technique. Four scenarios based on image processing are studied and their application before and after data fusion is assessed in relation to accuracy of the employed fusion process. Analysis of the results showed that bridge condition assessment can be improved with image fusion and, accordingly, support inspectors in interpretation of the results obtained. The results also indicate that predicted bridge deck condition using the developed method is very close to the actual condition assessment and rating reported by independent inspection.
The developed method was also applied and validated using three case studies of reinforced concrete bridge decks. Data and measurements of multiple NDE methods are extracted from Iowa, Highway research board project, 2011. The method utilizes data collected from ground penetrating radar (GPR), impact echo (IE), Half-cell potential (HCP) and electrical resistivity (ER). The analysis results of the three cases indicate that each level of data fusion has its unique advantage. The power of pixel level fusion lies in combining the location of bridge deck deterioration in one map as it appears in the fused image. While, feature fusion works in identification of specific types of defects, such as corrosion, delamination and deterioration. The main findings of this research recommend utilization of data fusion within two levels as a new method to facilitate and enhance the capabilities of inspectors in interpretation of the results obtained.  To demonstrate the use of the developed method and its model at the decision level of data fusion an additional case study of a bridge deck in New Jersey, USA is selected. Measurements of NDE methods for years 2008 and 2013 for that bridge deck are used as input to the developed method. The developed method is expected to improve current practice in forecasting bridge deck deterioration and in estimating the frequency of inspection. The results generated from the developed method demonstrate its comprehensive and relatively more accurate diagnostics of defects.


identifier: Cao, Lu  (2017) Multivariate Robust Vector-Valued Range Value-at-Risk.  Masters thesis, Concordia University.

abstract:
In a multivariate setting, the dependence between random variables has to be accounted for
modeling purposes. Various of multivariate risk measures have been developed, including
bivariate lower and upper orthant Value-at-Risk (VaR) and Tail Value-at-Risk (TVaR). The
robustness of their estimators has to be discussed with the help of sensitivity functions, since
risk measures are estimated from data.
In this thesis, several univariate risk measures and their multivariate extensions are presented.
In particular, we are interested in developing the bivariate version of a robust risk
measure called Range Value-at-Risk (RVaR). Examples with different copulas, such as the
Archimedean copula, are provided. Also, properties such as translation invariance, positive
homogeneity and monotonicity are examined. Consistent empirical estimators are also presented
along with the simulation. Moreover, the sensitivity functions of the bivariate VaR,
TVaR and RVaR are obtained, which confirms the robustness of bivariate VaR and RVaR
as expected.


identifier: Huang, Yiqi  (2017) Security Analysis of Multicast/Unicast Router Key Management Protocols.  Masters thesis, Concordia University.

abstract: Key Management Protocols (KMPs) are intended to manage cryptographic keys in a cryptosystem. KMPs have been standardized for Internet Protocol Security (IPsec), and these KMPs have been formally validated for their security properties. In the Internet, routing protocols have different requirements on their KMPs, which are not met by the existing IPsec KMPs, such as IKE, IKEv2, and GDOI. Protocol modeling has been used to analyze the security of the IPsec KMPs. For routing protocols, there are new KMPs proposed by the Keying and Authentication for Routing Protocols (KARP) working group of the Internet Engineering Task Force: RKMP, MRKM, and MaRK. These KMPs are designed to have better applicability for general routing protocols. However, the security of these protocols has not been validated. In this thesis, we have summarized the necessary conditions for security of routing protocols. We have analyzed the security aspects of RKMP, MRKM, and MaRK, by formally validating those protocols using the AVISPA modeling tool. This has shown that these KMPs meet the necessary security requirements.


identifier: Martin, Alexander William David  (2017) Before You Say You're Leaving.  Masters thesis, Concordia University.

title: Before You Say You're Leaving

abstract: Before You Say You’re Leaving is a collection of four short fictions that explores human reactions to loss, isolation, and loneliness. The stories follow their protagonists as they navigate and interpret grief in their own way. By examining these different characters’ reactions to an event of loss, whether it be the loss of a loved one, a relationship, or an established sense of selfhood, the collection is meant to explore how people create meaning in their own lives through close relationships, and how or whether that meaning can be reinterpreted or re-established after the event of loss.


identifier: Damiens, Antoine ORCID: https://orcid.org/0000-0002-3388-9032 <https://orcid.org/0000-0002-3388-9032>  (2017) Festivals, Uncut: Queer/ing Festival Studies, Curating Queerness.  PhD thesis, Concordia University.

abstract:
In the past decade, scholars have increasingly paid attention to film festivals. While the constitution of festival studies as a semi-independent field seems to further legitimise festivals as a site of scholarly inquiry, film critics have long questioned the continued relevance of LGBT film festivals. In 1982, for instance, Thomas Waugh wondered why (and whether) a new film festival should be organised in Montreal. Similarly, B. Ruby Rich notes that, given the commercial success of independent queer cinema in the mid-1990s, LGBT festivals are simultaneously “outlasting their mandate and invited to cease and desist.”

In focusing on LGBT festivals’ conflicted temporalities and historiography, this dissertation explores the intersection of queer cinematic cultures, academic knowledge production, and film criticism: since their humble beginnings in 1970s adult theatres, universities, and community centres, LGBT festivals have been instrumental in shaping both gay and lesbian film studies and queer cultural memory. In that context, this dissertation centres on the tension between queering festival studies (what I call “critical festival studies”) – uncovering the disciplinary unconscious and political project of the field through a careful examination of festivals which have been ignored in traditional historical narratives – and the constitution of queer cultural memory through festivals’ curatorial practices (“the festival as a method”).

As such, this project is highly indebted to queer/feminist historiographies and epistemologies. In queering festival studies, it hopes to foreground our own attachment to objects of studies (academic research is, as festival organisers put it, a “labour of love”), to do justice to the ways queer people access history, and to open up a space for a critical re-examining of queer film scholarship.


identifier: Nie, Yu Lin  (2017) Three essays on acquisition and CSR choices and firm value: Role of managerial traits and actions.  PhD thesis, Concordia University.

abstract:
This thesis consists of three essays that examine the role of managerial traits (specifically managerial conservatism, interest alignment with shareholders and debtholders, beliefs about firm value and hubris) on their firms’ acquisition and CSR choices and their valuation effects. All the essays use hand-collected pension plan data.
	The first essay finds support for a managerial conservatism explanation for acquirer acquisition choices and M&A price effects. More conservatively managed acquirers are more likely to use cash as the method of payment and to target less risky firms (e.g. being public or having lower leverage or managerial conservatism). We find that acquirers experience poorer price effects for stock versus cash payment even after controlling for the equity price effect and that these price effects monotonically deteriorate with increasing managerial conservatism, consistent with the agency problems associated with managerial conservatism. These results remain robust using propensity score matching, a four- or five-factor model, the BHAR methodology, top five executives instead of CEO when measuring managerial conservatism, and the inclusion of various controls (e.g., multiple or single acquirers, policy uncertainty, business cycle, managerial hubris, firm mispricing and Republican orientation).
	The second essay finds that managerial interest alignment with shareholders (debtholders) of acquirers is positively related to the likelihood of using stock (cash) as the M&A payment method, positively (negatively) related with M&A acquirer equity price effects, and negatively (positively) related with M&A acquirer bond price effects. While managerial conservatism is positively related with an acquirer’s CSR ranking it is negatively related with an acquirer’s M&A price effects. Information about an acquirer’s misvaluation contained in pre-announcement short selling by investors and the abnormal trading of its executives also affects the acquirer’s choice of payment method and M&A price effects.


identifier: Tolba, Mohamed  (2017) Cryptanalysis of Block Ciphers with New Design Strategies.  PhD thesis, Concordia University.

abstract:
Block ciphers are among the mostly widely used symmetric-key cryptographic primitives, which are fundamental building blocks in cryptographic/security systems. Most of the public-key primitives are based on hard mathematical problems such as the integer factorization in the RSA algorithm and discrete logarithm problem in the DiffieHellman. Therefore, their security are mathematically proven. In contrast, symmetric-key primitives are usually not
constructed based on well-defined hard mathematical problems. Hence, in order to get some assurance in their claimed security properties, they must be studied against different types of
cryptanalytic techniques. Our research is dedicated to the cryptanalysis of block ciphers. In particular, throughout this thesis, we investigate the security of some block ciphers constructed
with new design strategies. These new strategies include (i) employing simple round function, and modest key schedule, (ii) using another input called tweak rather than the usual two
inputs of the block ciphers, the plaintext and the key, to instantiate different permutations for the same key. This type of block ciphers is called a tweakable block cipher, (iii) employing linear and non-linear components that are energy efficient to provide low energy consumption block ciphers, (iv) employing optimal diffusion linear transformation layer while following the AES-based construction to provide faster diffusion rate, and (v) using rather weak but larger
S-boxes in addition to simple linear transformation layers to provide provable security of ARX-based block ciphers against single characteristic differential and linear cryptanalysis.
The results presented in this thesis can be summarized as follows:
Initially, we analyze the security of two lightweight block ciphers, namely, Khudra and Piccolo against Meet-in-the-Middle (MitM) attack based on the Demirci and Selcuk approach exploiting the simple design of the key schedule and round function.
Next, we investigate the security of two tweakable block ciphers, namely, Kiasu-BC and SKINNY. According to the designers, the best attack on Kiasu-BC covers 7 rounds. However, we exploited the tweak to present 8-round attack using MitM with efficient enumeration cryptanalysis.
Then, we improve the previous results of the impossible differential
cryptanalysis on SKINNY exploiting the tweakey schedule and linear transformation layer.
Afterwards, we study the security of new low energy consumption block cipher, namely, Midori128 where we present the longest impossible differential distinguishers that cover complete 7 rounds. Then, we utilized 4 of these distinguishers to launch key recovery attack against 11 rounds of Midori128 to improve the previous results on this cipher using the impossible
differential cryptanalysis.
Then, using the truncated differential cryptanalysis, we are able to attack 13 rounds of Midori128 utilizing a 10-round differential distinguisher.
We also analyze Kuznyechik, the standard Russian federation block cipher, against MitM with efficient enumeration cryptanalysis where we improve the previous results on Kuznyechik, using MitM attack with efficient enumeration, by presenting 6-round attack.
Unlike the previous attack, our attack exploits the exact values of the coefficients of the MDS transformation that is used in the cipher.
Finally, we present key recovery attacks using the multidimensional zero-correlation cryptanalysis against SPARX-128, which follows the long trail design strategy, to provide provable security of ARX-based block ciphers against single characteristic differential and
linear cryptanalysis.


identifier: Kassem, Abdulrahman Ibrahim  (2017) A Decision Aiding Framework for Concentrated Solar Thermal Power Technologies Assessment in Developing Countries.  PhD thesis, Concordia University.

abstract:
The diversification of electricity generation is necessary for sustainable development. The planning for renewable energy sources (RESs) integration is an essential goal set by many developing countries. Enormous investments are allocated accordingly to renewable energy projects, including solar power utilities. Concentrated solar thermal power (CSP) technologies are advancing and are expected to play a significant role in energy portfolios in the future. CSP planning is a complex process owing to the involvement of various contradicting factors and players. This thesis proposes a structured aiding framework to assess utility-scale CSP alternatives to support national grids in developing countries. It is common in many fast growing developing countries that the power plants are owned by the state, which enlarges the scope of electric power projects beyond the technical and economic drivers to include environmental, social, and political aspects, which accordingly increases the planning process complexity.
The developed methodology consists of three main phases. The first phase is concerned with formulating a value tree for CSP technologies evaluation. This phase is intended to explicitly capture a generic evaluation criteria through a rigorous process of expert deliberation and consensus-seeking. Expert elicitation is conducted through the Delphi method, with a total of 140 experts participating from multidisciplinary solar thermal power fields from 32 countries. Based on participants’ judgments, as expressed during two rounds of Delphi questionnaires, parameters with importance and consensus degrees > 50% are incorporated to construct the final value tree. The recommendations of this phase set a foundation for stakeholders’ assessment of regional CSP utilities planning in developing countries.
The second phase considers analyzing, defining, and simulating alternative scenarios. Large-scale CSP deployment is in its infancy with a lack of sufficient data in many developing countries and various available technology combinations. Accordingly, this phase intends to focus the planning process toward practical alternatives given the regional requirements. A techno-economic analysis is conducted that considers the strengths, weaknesses, opportunities, and threats (SWOT) for each technology. As RESs are location dependent, Saudi Arabia defines the scope of this phase. The analysis outcomes are incorporated with the Saudi energy sector requirements and local weather conditions to define alternative scenarios. Six power plant scenarios are defined for performance and financial evaluation. A simulation is subsequently carried out through the System Advisor Model. The alternative scenarios are assessed by defining weather, technical, and financial parameters. Satellite observations and field measured data are integrated to synthesize a typical meteorological year weather profile. The outputs of this phase provide accurate results that represent a solid ground for the assessment of alternative CSP scenarios with consideration of all relevant parameters.
The third phase considers a comprehensive assessment of the scenario-based CSP alternatives. A multi-criteria decision-making (MCDM) model is developed in a fuzzy environment to tackle uncertainty, ambiguity, and imprecision. The evaluation is conducted based on extensive analysis of the performances of each alternative scenario in accordance with 4 main criteria and 29 sub-criteria. Quantitative and qualitative data as well as input from 44 local stakeholders are incorporated. The obtained results constitute an accurate basis to derive recommendations for CSP integration to national grids and relate them to stakeholders’ priorities.


identifier: Nakkar, Mouna  (2017) Secure Hardware Implementation of Post Quantum Cryptosystems.  Masters thesis, Concordia University.

abstract:
Solving a hard mathematical problem is the security basis of all current cryptographic systems. With the realization of a large scale quantum computer, hard mathematical problems such as integer factorization and discrete logarithmic problems will be easily solved with special algorithms implemented on such a computer. Indeed, only post-quantum cryptosystems which defy quantum attacks will survive in the post-quantum era. Each newly proposed post-quantum cryptosystem has to be scrutinized against all different types of attacks. Attacks can be classified into mathematical cryptanalysis and side channel attacks. In this thesis, we propose secure hardware implementations against side channel attacks for two of the most promising post-quantum algorithms: the lattice-based public key cryptosystem, NTRU, and the multivariate public key cryptosystem, Rainbow, against power analysis attacks and fault analysis attacks, respectively.

NTRUEncrypt is a family of public key cryptosystems that uses lattice-based cryptography. It has been accepted as an IEEE P1363 standard and as an X9.98 Standard. In addition to its small footprint compared to other number theory based public key systems, its resistance to quantum attacks makes it a very attractive candidate for post quantum cryptosystems. On the other hand, similar to other cryptographic schemes, unprotected hardware implementations of NTRUEncrypt are susceptible to side channel attacks such as timing and power analysis. In this thesis, we present an FPGA implementation of NTRUEncrypt which is resistant to first order differential power analysis (DPA) attacks. Our countermeasures are implemented at the architecture level. In particular, we split the ciphertext into two randomly generated shares. This guarantees that during the first step of the decryption process, the inputs to the convolution modules, which are convoluted with the secret key polynomial, are uniformly chosen random polynomials which are freshly generated for each convolution operation and are not under the control of the attacker. The two shares are then processed in parallel without explicitly combining them until the final stage of the decryption. Furthermore, during the final stage of the decryption, we also split the used secret key polynomial into two randomly generated shares which provides theoretical resistance against the considered class of power analysis attacks. The proposed architecture is implemented using Altera Cyclone IV FPGA and simulated on Quartus II in order to compare the non-masked architecture with the masked one. For the considered set of parameters, the area overhead of the protected implementation is about 60% while the latency overhead is between 1.4% to 6.9%.

Multivariate Public Key Cryptosystems (MPKCs) are cryptographic schemes based on the difficulty of solving a set of multivariate system of nonlinear equations over a finite field. MPKCs are considered to be secure against quantum attacks. Rainbow, an MPKC signature scheme, is among the leading MPKC candidates for post quantum cryptography. In this thesis, we propose and compare two fault analysis-resistant implementations for the Rainbow signature scheme. The hardware platform for our implementations is Xilinx FPGA Virtex 7 family. Our implementation for the Rainbow signature completes in 191 cycles using a 20ns clock period which is an improvement over the previously reported implementations. The verification completes in 141 cycles using the same clock period. The two proposed fault analysis-resistant schemes offer different levels of protections and increase the area overhead by a factor of 33% and 9%, respectively. The first protection scheme acquires a time overhead of about 72%, but the second one does not have any time overhead.


identifier: Keshani, Parinaz  (2017) Modeling green supply chain in a manufacturing environment.  Masters thesis, Concordia University.

abstract: In recent years, the importance of waste reduction and efficient use of resources has led companies to focus more on eco-friendly processes at different stages of the manufacturing process, such as acquiring raw materials, production, assembly, distribution and recycling. Additionally, manufacturers in many countries have been either under governmental pressure to follow eco-friendly guidelines in their production process, or have chosen to do so to benefit from governmental incentives such as tax reductions. Furthermore, the public interest in environmentally friendly goods has been on the rise as a result of growing awareness towards the negative consequences of industrial activities and practices that harm the environment. All of these factors have made it imperative for industries to adopt green practices in order to gain or maintain their competitive edge. However, staying green is not easy, as green production lines, products and practices are often more costly than their regular non-green counterparts. Therefore, in this study, we have developed a mathematical model based on supply chains and manufacturing facilities of all sizes producing various products with two distinct goals. First, our mathematical model helps companies maximize their profit and second it allows them stay green while the profit is maximized. This mathematical model is then solved for two scenarios in three different companies to (1) evaluate the effects of customer sensitivity towards eco-friendliness of the products and (2) the effects of changing CO2 emissions and transportation costs. The results of the calculations performed by the mathematical model shows the profit that the company stands to gain based on an allowed production volume that does not exceed the defined green criteria and the amount of raw materials to be purchased from suppliers that offer different degrees of greenness. In practice, this mathematical model can be expanded to include more constraints and can also be implemented in commercial software solutions to provide managers with valuable data to facilitate the decision making processes within the companies and among connected commercial entities.


identifier: Abdelkhalek, Ahmed  (2017) Cryptanalysis of Some Block Cipher Constructions.  PhD thesis, Concordia University.

abstract:
When the public-key cryptography was introduced in the 1970s, symmetric-key cryptography was believed to soon become outdated. Nevertheless, we still heavily rely on symmetric-key primitives as they give high-speed performance. They are used to secure mobile communication, e-commerce transactions, communication through virtual private networks and sending electronic tax returns, among many other everyday activities. However, the security of symmetric-key primitives does not depend on a well-known hard mathematical problem such as
the factoring problem, which is the basis of the RSA public-key cryptosystem. Instead, the security of symmetric-key primitives is evaluated against known cryptanalytic techniques. Accordingly, the topic of furthering the state-of-the-art of cryptanalysis of symmetric-key primitives is an ever-evolving topic. Therefore, this thesis is dedicated to the cryptanalysis of symmetric-key cryptographic primitives. Our focus is on block ciphers as well as hash functions that are built using block ciphers. Our contributions can be summarized as follows:

First, we tackle the limitation of the current Mixed Integer Linear Programming (MILP) approaches to represent the differential propagation through large S-boxes. Indeed, we present a novel approach that can efficiently model the Difference Distribution Table (DDT) of large S-boxes, i.e., 8-bit S-boxes. As a proof of the validity and efficiency of our approach, we apply it on two out of the seven AES-round based constructions that were recently proposed in FSE 2016. Using our approach, we improve the lower bound on the number of active S-boxes of one construction and the upper bound on the best differential characteristic of the other.

Then, we propose meet-in-the-middle attacks using the idea of efficient differential enumeration against two Japanese block ciphers, i.e., Hierocrypt-L1 and Hierocrypt-3. Both block ciphers were submitted to the New European Schemes for Signatures, Integrity, and Encryption (NESSIE) project, selected as one of the Japanese e-Government recommended ciphers in 2003 and reselected in the candidate recommended ciphers list in 2013. We construct five S-box layer distinguishers that we use to recover the master keys of reduced 8 S-box layer versions of both block ciphers. In addition, we present another meet-in-the-middle attack on Hierocrypt-3 with
slightly higher time and memory complexities but with much less data complexity.

Afterwards, we shift focus to another equally important cryptanalytic attack, i.e., impossible differential attack. SPARX-64/128 is selected among the SPARX family that was recently proposed to provide ARX based block cipher whose security against differential and linear cryptanalysis can be proven. We assess the security of SPARX-64/128 against impossible differential attack and show that it can reach the same number of rounds the division-based integral attack, proposed by the designers, can reach. Then, we pick Kiasu-BC as an example of a tweakable block cipher and prove that, on contrary to its designers’ claim, the freedom in choosing the
publicly known tweak decreases its security margin. Lastly, we study the impossible differential properties of the underlying block cipher of the Russian hash standard Streebog and point out the potential risk in using it as a MAC scheme in the secret-IV mode.