Understanding the impacts of both natural and anthropogenic landscape features on genetic diversity, population structure and connectivity has important implications for conservation of species living in fragmented environments. Here, I combine population genetic data, detailed land cover information, and computer simulations to explore how landscape shapes genetic structure across two regional populations of the threatened eastern massasauga rattlesnake (Sistrurus catenatus catenatus) in Ontario, Canada: one along the eastern shores of Georgian Bay and the other largely confined to the northern half of the Bruce Peninsula. First I used spatial Bayesian assignment to quantify the genetic population structure within each regional population. I found marked subpopulation structure within eastern Georgian Bay with differentiation of island and mainland snakes, a north-south split within the mainland coinciding with the town of Parry Sound, and evidence of further subdivision within the cluster of snakes north of Parry Sound. In contrast I found no population subdivision within the mainland of the Bruce Peninsula, but genetic distinction of mainland and island snakes. Next, I identified the landscape features that shape spatial genetic structure within regional populations. In eastern Georgian Bay I found local variation in the effect of landscape on populations. North of Parry Sound I found no effect of landscape on inter-individual genetic differentiation, but a strong pattern of isolation-by-distance. In contrast I found that both open water and roads restrict gene flow of snakes south of Parry Sound. I found no evidence of isolation-by-distance or that landscape shape genetic structure within the Bruce Peninsula. Finally I used individual-based, spatially explicit simulations to identify the lag-time associated with the detection of contemporary landscape feature effects on genetic structure of massasaugas, and explore the consequences of using spatially correlated land cover elements in landscape genetic analyses. I found that the genetic consequences of roads could be detected within 2-12 generations when population sizes were small or juvenile dispersal was low. However, I also found that roads could be spuriously identified as impediments to gene flow when spatially correlated features such as water are included in genetic models. / Thesis (Master, Biology) -- Queen's University, 2011-10-14 15:06:35.956

Infrastructure wireless mesh networks (IWMNs) provide inexpensive deployment, flexible extension of wireless infrastructure, and easy access to the Internet. With multiple radios at each node, a capacity per node improves by transmitting over these radios simultaneously using orthogonal channels. However, without properly addressing the problem of channel assignment and routing for those nodes that form wireless infrastructures, the resulting network throughput and reliability are unlikely to meet the requirements of those highly demanding, media distribution applications. On a particular channel, poor resource allocation at a given access point/gateway of the underlying IWMN can amplify the problem even further. Motivated by these problems, we develop, based on the theory of network coding, a set of alternative solutions that addresses the above issues. We first introduce a sub-optimal solution to the joint problem of network coding, channel assignment and link scheduling for throughput optimization in the multi-channel multi-radio IWMN. We mathematically formulate the problem as a linear program, taking into account opportunistic overhearing, among other constraints. Based on this formulation, we develop a sub-optimal, auction-based algorithm for network throughput optimization. Simulation results reveal the effectiveness of our algorithm in exploiting multiple radios and channels while coping with fairness issues arising from auctions. The proposed solution also shows promising gains over traditional routing solutions. Our experimental results on an 802.11 testbed further confirm these results. The second part of this thesis then presents three AP/gateway-oriented solutions that address the link-level issues related to radio resource allocation at a particular AP/gateway node of the underlying IWMN, which operates on a given channel serving a set of wireless clients. Since the last-hop wireless link is normally a bottleneck of the IWMN, the key idea underlying all the proposed solutions is to use a version of network coding at the bottlenecked AP/gateway. We use Markov chains and the probability theory to derive several performance measures related to media distribution for both uplink and downlink applications. Via extensive simulations, we show the promising delay and reliability gains of the network-coding based schemes over the traditional schemes without network coding.

With an overview how Moodle plugin works, this paper aims to focus on those areas where open source software impact has on learning management system software which is distributed for free. One of the essential goal of this project is to develop plugin tool for Moodle, which aid users by providing less interaction time while adjusting date related tasks mainly with courses and assignments, which currently in the Moodle system is accomplished by a lot of steps. The project concentrated on two application functions, namely assignment_daterollover and course_daterollover. These two application plugin features in Moodle learning environment allows instructors to automatically update all date items in their course at the beginning of each semester. Date adjustments can easily be made to each assignments in a course through one centralized screen, rather than having to go into each individual learning activity. The two plugin tool options are one which will change the course start date by which all assignments can be simultaneously set forward by a specified number of days which is called course_daterollover and the other option is to adjust individual assignment items within a course which is called assignment_daterollover. Through the methods, the number of steps (clicks) has been counted and compared with the existing date adjustment method in Moodle for course and assignments, to evaluate and identity UI limitations Heuristic evaluation method is used. The plugin is implemented using block-plugin, because of its appearance to simply reside the content on the right or left side of each main course page, which also gives users the right to turn it on or off if they don't want to use it. In addition, the tool can be used as an option associated with the existing Moodle date adjustment system from the point of view of having a different design. The result is a user-friendly plugin tool interface for the stated two purposes which have less number of clicks than the Moodle date adjustment system for courses and assignments. The plugin tool can be used by anyone since it has been published on Github. As a conclusion, Moodle with its cost-effectiveness can serve a lot of users around the world.

This thesis is concerned with the channel assignment (CA) problem in multi-channel multi-interface wireless mesh networks (M2WNs). First, for M2WNs with general topologies, we rigorously demonstrate using the combinatorial principle of inclusion/exclusion that the CA solution space can be quantified, indicating that its cardinality is greatly influenced by the number of radio interfaces installed on each router. Based on this analysis, a novel scheme is developed to construct a new reduced search space, represented by a lattice structure, that is searched more efficiently for a CA solution. The elements in the reduced lattice-based space, labeled Solution Structures (SS), represent groupings of feasible CA solutions satisfying the radio constraints at each node. Two algorithms are presented for searching the lattice structure. The first is a greedy algorithm that finds a good SS in polynomial time, while the second provides a user-controlled depthfirst search for the optimal SS. The obtained SS is used to construct an unconstrained weighted graph coloring problem which is then solved to satisfy the soft interference constraints. For the special class of full M2WNs (fM2WNs), we show that an optimal CA solution can only be achieved with a certain number of channels; we denote this number as the characteristic channel number and derive upper and lower bounds for that number as a function of the number of radios per router. Furthermore, exact values for the required channels for minimum interference are obtained when certain relations between the number of routers and the radio interfaces in a given fM2WN are satisfied. These bounds are then employed to develop closed-form expressions for the minimum channel interference that achieves the maximum throughput for uniform traffic on all communication links. Accordingly, a polynomial-time algorithm to find a near-optimal solution for the channel assignment problem in fM2WN is developed. Experimental results confirm the obtained theoretical results and demonstrate the performance of the proposed schemes.

Infrastructure wireless mesh networks (IWMNs) provide inexpensive deployment, flexible extension of wireless infrastructure, and easy access to the Internet. With multiple radios at each node, a capacity per node improves by transmitting over these radios simultaneously using orthogonal channels. However, without properly addressing the problem of channel assignment and routing for those nodes that form wireless infrastructures, the resulting network throughput and reliability are unlikely to meet the requirements of those highly demanding, media distribution applications. On a particular channel, poor resource allocation at a given access point/gateway of the underlying IWMN can amplify the problem even further. Motivated by these problems, we develop, based on the theory of network coding, a set of alternative solutions that addresses the above issues. We first introduce a sub-optimal solution to the joint problem of network coding, channel assignment and link scheduling for throughput optimization in the multi-channel multi-radio IWMN. We mathematically formulate the problem as a linear program, taking into account opportunistic overhearing, among other constraints. Based on this formulation, we develop a sub-optimal, auction-based algorithm for network throughput optimization. Simulation results reveal the effectiveness of our algorithm in exploiting multiple radios and channels while coping with fairness issues arising from auctions. The proposed solution also shows promising gains over traditional routing solutions. Our experimental results on an 802.11 testbed further confirm these results. The second part of this thesis then presents three AP/gateway-oriented solutions that address the link-level issues related to radio resource allocation at a particular AP/gateway node of the underlying IWMN, which operates on a given channel serving a set of wireless clients. Since the last-hop wireless link is normally a bottleneck of the IWMN, the key idea underlying all the proposed solutions is to use a version of network coding at the bottlenecked AP/gateway. We use Markov chains and the probability theory to derive several performance measures related to media distribution for both uplink and downlink applications. Via extensive simulations, we show the promising delay and reliability gains of the network-coding based schemes over the traditional schemes without network coding.

Macroscopic traffic simulations are widely used in the world in order to provide assistance in the traffic infrastructure development as well as for the strategic traffic planning. When studying a large traffic network macroscopic traffic simulation can be used to model current and future traffic situations. The two most common software used for traffic simulation in Sweden today are Emme and Visum, developed by INRO respective PTV. The aim of the thesis is to perform a comparison between the software Emme and Visum with respect to the assignment of public transport, in other words how passengers choose their routes on the existing public transport lines. However, in order to make a complete software comparison the run-time, analysis capabilities, multi-modality, capacity to model various behavioural phenomena like crowding, fares etc. this will not be done in this comparison. It is of interest to study the differences between the two software algorithms and why they might occur because the Swedish Transport Administration uses Emme and the Traffic Administration in Stockholm uses Visum when planning public transport. The comparison will include the resulting volumes on transit lines, travel times, flow through specific nodes, number of boarding, auxiliary volumes and number of transits. The goal of this work is to answer the following objective: What are the differences with modelling a public transport network in Emme and in Visum, based on that the passengers only have information about the travel times and the line frequency, and why does the differences occur? In order to evaluate how the algorithms work in a larger network, Nacka municipality (in Stockholm) and the new metro route between Nacka Forum and Kungsträdgården have been used. The motivation for choosing this area and case is due to that it is interesting to see what differences could occur between the programs when there is a major change in the traffic network. The network of Nacka, and parts of Stockholm City, has been developed from an existing road network of Sweden and then restricted by "cutting out" the area of interest and then removing all public transportation lines outside the selected area. The OD-matrix was also limited and in order not to loose the correct flow of travellers portal zones was used to collect and retain volumes. To find out why the differences occur the headway-based algorithms in each software were studied carefully. An example of a small and simple network (consisting of only a start and end node) has been used to demonstrate and show how the algorithms work and why volumes split differently on the existing transit lines in Emme and Visum. The limited network of Nacka shows how the different software may produce different results in a larger public transport network. The results show that there are differences between the program algorithms but the significance varies depending on which output is being studied and the size of the network. The Visum algorithm results in more total boardings, i.e. more passengers have an optimal strategy including a transit. The algorithms are very similar in both software programs, since they include more or less parts of the optimal strategy. The parameters used are taken more or less into consideration in Emme and Visum. For example Visum will first of all focus on the shortest total travel time and then consider the other lines with respect to the maximum waiting time. Emme however, first focuses on the shortest travel time and then considers the total travel time for other lines with half the waiting time instead of the maximum wait time. This results in that less transit lines will be attractive in Emme compared to Visum. The thesis concludes that varying the parameters for public transport in each software algorithm one can obtain similar results, which implies that it is most important to choose the best parameter values and not to choose the "best" software when simulating a traffic network.

NMR spectroscopy is not only for protein structure determination, but also for drug screening and studies of dynamics and interactions. In both cases, one of the main bottleneck steps is backbone assignment. When a homologous structure is available, it can accelerate assignment. Such structure-based methods are the focus of this thesis. This thesis aims for fast and robust methods for NMR assignment problems; in particular, structure-based backbone assignment and chemical shift mapping. For speed, we identified situations where the number of 15N-labeled experiments for structure-based assignment can be reduced; in particular, when a homologous assignment or chemical shift mapping information is available. For robustness, we modeled and directly addressed the errors. Binary integer linear programming, a well-studied method in operations research, was used to model the problems and provide practically efficient solutions with optimality guarantees. Our approach improved on the most robust method for structure-based backbone assignment on 15N-labeled data by improving the accuracy by 10% on average on 9 proteins, and then by handling typing errors, which had previously been ignored. We show that such errors can have a large impact on the accuracy; decreasing the accuracy from 95% or greater to between 40% and 75%. On automatically picked peaks, which is much noisier than manually picked peaks, we achieved an accuracy of 97% on ubiquitin. In chemical shift mapping, the peak tracking is often done manually because the problem is inherently visual. We developed a computer vision approach for tracking the peak movements with average accuracy of over 95% on three proteins with less than 1.5 residues predicted per peak. One of the proteins tested is larger than any tested by existing automated methods, and it has more titration peak lists. We then combined peak tracking with backbone assignment to take into account contact information, which resulted in an average accuracy of 94% on one-to-one assignments for these three proteins. Finally, we applied peak tracking and backbone assignment to protein-ligand docking to illustrate the potential for fast 3D complex determination.

Thesis (Ph. D.)--West Virginia University, 2007. / Title from document title page. Document formatted into pages; contains xi, 86 p. : ill. Includes abstract. Includes bibliographical references (p. 82-86).

Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.

Thesis (M.S.)--West Virginia University, 2008. / Title from document title page. Document formatted into pages; contains ix, 55 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 53-55).