Roads are prominent, contiguous features covering approximately 1% of the United States land mass and have been built for decades with little consideration for ecological effects. Increasingly, the impacts of roads are being recognized and the science of road ecology is emerging as an important area of study for conservation biologists. For wildlife, the impacts of roads are disproportionate to the area of land they occupy. Direct impacts on wildlife include mortality via vehicle collision and restriction or alteration of movement. Road kill exceeds hunting as the leading direct human cause of vertebrate mortality, with approximately one million vertebrates a day killed on roads in the United States. Roadways also affect wildlife through habitat loss and fragmentation, isolation of wildlife populations, disruption of gene flow and metapopulation dynamics. A variety of strategies have been used with mixed success to mitigate the impacts of roads on wildlife. Commonly, underpasses are used to facilitate movement of wildlife across roadways in Europe, Australia, Canada and the U.S.. However, the effectiveness of these underpasses to facilitate wildlife movement depends on a number of variables, including: size, proximity to natural wildlife corridors, noise levels, substrate, vegetative cover, moisture, temperature, light, and human disturbance. Further, different species typically have different requirements. Thus if crossing structures are designed for use by a singles species, they may constitute an absolute barrier for other species that have different requirements. Most attempts to evaluate wildlife crossing structures focus exclusively on documenting wildlife use of structures. While tracking beds, cameras, and counters document the species using structures, they provide little information on those species or individuals that fail to use a structure. In contrast, telemetry, trapping and tracking studies are more useful for determining the extent to which roadways inhibit wildlife movements and the degree to which crossing structures mitigate these effects. Thus, to fully assess the effectiveness of wildlife passageways, a combination of monitoring techniques across a variety of taxa is needed to evaluate structure use impacts of transportation systems on animal movements. The goal of this study was to assess the effectiveness of wildlife crossing structures constructed as part of the Bennington Bypass (Highway 279) in southern Vermont. The bypass was completed in October 2004 and includes three wildlife crossing structures, including two extended bridges and a large culvert. This study monitored the effectiveness of these crossing structures and compared rates of wildlife movement across the highway in mitigated and unmitigated sections.

With increasing data sets for processing, there is a requirement to build faster and smaller arithmetic circuits. One of the ways to improve the performance of higher order arithmetic units is to reduce the carry propagation levels. Multi-valued logic enables this by reducing the number of digits required to represent a range of numbers. Area reduction is also obtained through fewer operations and signals required to realise a function. Though theoretically multi-valued logic has these advantages, implementation of the multi-valued logic using CMOS has not been efficient. The main reason is because multi-valued logic is emulated in CMOS using binary switches. Two main approaches are followed in CMOS in implementing multi-valued logic using CMOS. Voltage mode logic, where the logic states are encoded using the node voltages suffer from low noise margins and limitation of radix due to the power supply. Current mode logic, where the branch currents are used to represent the logic levels suffer from high power consumption due to static current flow and requirement of restoration devices. The mindset of the post-CMOS approaches explored so far for multi-valued logic circuit design has been to replace the CMOS switches with their novel nano switches. Hence they too suffer from the same issues as CMOS implementation. Our value proposition is through the use of a truly multi-state device based on electron spin. Spin waves, which are a collection of electron spins of an atom enables multi-valued logic by allowing encoding information in the amplitude and phase of the wave.Another advantage of the spin wave fabric is that the computation is through wave propagation and interference which does not involve any movement of charge. This enables building low energy,smaller and faster multi-valued circuits. In this thesis, implementation of the basic building blocks of multi-valued logic using these novel spin wave based devices is shown. Building of arithmetic circuits like adders using these building blocks have also been demonstrated. To quantify the benefits of spin wave based multi-valued circuits, they are benchmarked with CMOS. For 32-bits, our projected comparisons show a 5X increased performance, 125X area improvement and 1717X power reduction for hexa-decimal spin wave based adders compared to binary CMOS. Similarly there is a 4X increase in performance of hexa-decimal SPWF multiplier compared to CMOS for 16 bits. Finally, we have implemented the I/O circuits for smooth interface between binary CMOS and multi-valued SPWF logic.

In this dissertation, we consider extensions of dynamic programming for combinatorial optimization. We introduce two exact multi-objective optimization algorithms: the multi-stage optimization algorithm that optimizes the problem relative to the ordered sequence of objectives (lexicographic optimization) and the bi-criteria optimization algorithm that simultaneously optimizes the problem relative to two objectives (Pareto optimization). We also introduce a counting algorithm to count optimal solution before and after every optimization stage of multi-stage optimization. We propose a fairly universal approach based on so-called circuits without repetitions in which each element is generated exactly one time. Such circuits represent the sets of elements under consideration (the sets of feasible solutions) and are used by counting, multi-stage, and bi-criteria optimization algorithms. For a given optimization problem, we should describe an appropriate circuit and cost functions. Then, we can use the designed algorithms for which we already have proofs of their correctness and ways to evaluate the required number of operations and the time. We construct conventional (which work directly with elements) circuits without repetitions for matrix chain multiplication, global sequence alignment, optimal paths in directed graphs, binary search trees, convex polygon triangulation, line breaking (text justification), one-dimensional clustering, optimal bitonic tour, and segmented least squares. For these problems, we evaluate the number of operations and the time required by the optimization and counting algorithms, and consider the results of computational experiments. If we cannot find a conventional circuit without repetitions for a problem, we can either create custom algorithms for optimization and counting from scratch or can transform a circuit with repetitions into a so-called syntactical circuit, which is a circuit without repetitions that works not with elements but with formulas representing these elements. We apply both approaches to the optimization of matchings in trees and apply the second approach to the 0/1 knapsack problem. We also briefly introduce our work in operation research with applications to health care. This work extends our interest in the optimization field from developing new methods included in this dissertation towards the practical application.

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Engineering companies are sociotechnical systems in which engineers, designers, analysts, etc. use an array of software tools to follow prescribed product-development processes. The purpose of these amalgamated systems is to develop new products as quickly as possible while maintaining quality and meeting customer and market demands. Researchers at Brigham Young University have shortened engineering design cycle times through the development and use of multiengineer synchronous (MES) CAD tools. Other research teams have shortened design cycle-times by extending seamless interoperability across heterogeneous design tools and domains. Seamless multi-engineer synchronous heterogeneous (MESH) CAD environments is the focus of this dissertation. An architecture that supports both MES collaboration and interoperability is defined, tested for robustness, and proposed as the start of a new standard for interoperability. An N-tiered architecture with four layers is used. These layers are data storage, server communication, business logic, and client. Perhaps the most critical part of the architecture is the new neutral parametric database (NPDB) standard which can generically store associative CAD geometry from heterogeneous CAD systems. A practical application has been developed using the architecture which demonstrates design and modeling interoperability between Siemens NX, PTC's Creo, and Dassault Systemes CATIA CAD applications; Interoperability between Siemens' NX and Dassault Systemes' CATIA are specifically outlined in this dissertation. The 2D point, 2D line, 2D arc, 2D circle, 2D spline, 3D point, extrude, and revolve features have been developed. Complex models have successfully been modeled and exchanged in real time across heterogeneous CAD clients and have validated this approach for MESH CAD collaboration.

Collaboration in engineering product development leads to shorter product development times and better products. In product development, considerable time is spent preparing the CAD model or assembly for Finite Element Analysis (FEA). In general Computer-Aided Applications (CAx) such as FEA deter collaboration because they allow only a single user to check out and make changes to the model at a given time. Though most of these software applications come with some collaborative tools, they are limited to simple tasks such as screen sharing and instant messaging. This thesis discusses methods to convert a current commercial FEA pre-processing program into a multi-user program, where multiple people are allowed to work on a single FEA model simultaneously. This thesis discusses a method for creating a multi-user FEA pre-processor and a robust, stable multi-user FEA program with full functionality has been developed using CUBIT. A generalized method for creating a networking architecture for a multi-user FEA pre-processor is discussed and the chosen client-server architecture is demonstrated. Furthermore, a method for decomposing a model/assembly using geometry identification tags is discussed. A working prototype which consists of workspace management Graphical User Interfaces (GUI) is demonstrated. A method for handling time-consuming tasks in an asynchronous multi-user environment is presented using Central Processing Unit (CPU) time as a time indicator. Due to architectural limitations of CUBIT, this is not demonstrated. Moreover, a method for handling undo sequences in a multi-user environment is discussed. Since commercial FEA pre-processors do not allow mesh related actions to be undone using an undo option, this undo handling method is not demonstrated.

With the advent of technology cloud computing has become the next generation of network computing where cloud computing can deliver both software and hardware as on-demand services over the Internet. Cloud computing has enabled small organizations to build web and mobile apps for millions of users by utilizing the concept of “pay-as-you-go” for applications, computing, network and storage resources as on-demand services. These services can be provided to the tenants in different categories: Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). In order to decrease the costs for the cloud users and increase resource utilization, cloud providers try to share the resources between different organizations (tenants) through a shared environment which is called Multi-Tenancy. Even though multi-tenancy‟s benefits are tremendous for both cloud providers and users, security and privacy concerns are the primary obstacles to Multi-Tenancy.Since Multi-Tenancy dramatically depends on resource sharing, many experts have suggested different approaches to secure Multi-Tenancy. One of the solutions is resource allocation and isolation techniques. In most cases, resource allocation techniques consider but are not sufficient for security. OpenStack community uses a method to isolate the resources in a Multi-Tenant environment. Even though this method is based on a smart filtering technique to segregate the resources in Compute nodes (the component that the instances are running on it in OpenStack), this method is not flawless. The problem comes up in the Cinder nodes where the resources are not isolated. This failure can be considered as a security concern for a Multi-Tenant environment in OpenStack. In order to solve this problem, this project explores a method to secure MultiTenancy for both sides in the Compute node and for backend where Block Storage devices for the instances can be isolated as well. / Med tillkomsten av teknik har molnberäkning blivit nästa generation nätverksberäkning där molnberäkning kan leverera både mjukvara och hårdvara som on-demand-tjänster över Internet. Cloud computing har gjort det möjligt för små organisationer att bygga webboch mobilappar för miljontals användare genom att använda begreppet ”pay-as-you-go” för applikationer, datoranläggningar, nätverksoch lagringsresurser som on-demand-tjänster. Dessa tjänster kan tillhandahållas hyresgästerna i olika kategorier: Infrastructure as a Service (IaaS), Platform as a Service (PaaS) och Software as a Service (SaaS). För att minska kostnaderna för molnanvändarna och öka resursanvändningen, försöker molnleverantörer att dela resurserna mellan olika organisationer (hyresgäster) genom en delad miljö som kallas Multi-Tenancy. Men fördelarna med flera hyresgäster är enorma för både molnleverantörer och användare, säkerhetsoch integritetsfrågor är de främsta hindren för Multi-Tenancy. Eftersom Multi-Tenancy dramatiskt beror på resursdelning har många experter föreslagit olika metoder för att säkra Multi-Tenancy. En av lösningarna är resursallokering och isoleringstekniker. I de flesta fall beaktar resursallokeringstekniker men är inte tillräckliga för säkerhet. OpenStack community använder en metod för att isolera resurserna i en Multi-Tenant-miljö.Men denna metod är baserad på en smart filtreringsteknik för att separera resurserna i Compute-noder (komponenten som instansen körs på den i OpenStack), den här metoden är inte felfri. Problemet kommer upp i Cinder-noderna där resurserna inte är isolerade. Detta fel kan betraktas som ett säkerhetsproblem för en Multi-Tenant-miljö i OpenStack. För att lösa detta problem försöker detta projekt säkra Multi-Tenancy för båda sidor i Compute-noden och för backend där Block Storage-enheter för instanserna också kan isoleras.

Many modern-day Bioinformatics algorithms rely heavily on statistical models to analyze their biological data. Some of these statistical models lend themselves nicely to standard high performance computing optimizations such as parallelism, while others do not. One such algorithm is Markov Chain Monte Carlo (MCMC). In this thesis, we present a heterogeneous compute solution for optimizing GenSel, a genetic selection analysis tool. GenSel utilizes a MCMC algorithm to perform Bayesian inference using Gibbs sampling. Optimizing an MCMC algorithm is a difficult problem because it is inherently sequential, containing a loop carried dependence between each Markov Chain iteration. The optimization presented in this thesis utilizes GPU computing to exploit the data-level parallelism within each of these iterations. In addition, it allows for the efficient management of memory, the pipelining of CUDA kernels, and the use of multiple GPUs. The optimizations presented show performance improvements of up to 1.84 times that of the original algorithm.

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Accurate and reasonable contract time is important to all aspects of a highway construction project. Unreasonably short contract times can raise the bid price, restrict qualified bidders from submitting bids, reduce the quality of the work, and increase the potential for legal disputes. Conversely, unreasonably long contract times encourage less qualified contractors to submit a bid and are a general inconvenience to the traveling public. The Federal Highway Administration (FHWA) recognizes this, and has recommended that all state highway agencies develop a standardized method for estimating contract performance time. To date, the Virginia Department of Transportation (VDOT) does not have an established method. One major portion of this work is the development of the framework for a multi-level time estimating system to aid in the establishment of contract performance times. This system parallels the VDOT cost estimating process, refining estimates as design details become available along the Project Development Concurrent Engineering Process (PDCEP). Three distinct stages exist along the PDCEP that will facilitate the use of a tool for estimating contract time. Sufficient information to begin the conceptual estimate is known as the project enters the six year plan. The parametric estimate may commence as the project enters the scoping phase. Finally, details for the pre-advertisement time estimate are available upon project field inspection. The second major component of this work, the pre-advertisement estimating database system (BIDDS – Bid Item Duration Data System) was constructed during this work. BIDDS uses project information and characteristics to filter through historical performance time data, returning production data from similar projects. Production data is returned at the bid item level to assist in the estimation of production rates, for calculating activity durations. / Master of Science