Transport infrastructure is closely linked to several politically relevant sustainability issues, and since 1985 a formalized environmental assessment process is linked to planning and construction of new roads and railways in the EU (EU directives 85/337/EEC and 2001/42). The aim of the environmental assessment process is to think in advance; to identify, predict and evaluate significant environmental changes resulting from a proposed activity, in order to adjust the proposed activity accordingly and to avoid unnecessary and unexpected consequences. Biodiversity is a component of sustainable development that is in many ways affected by road and railway construction, but which has been challenging to fully account for within the environmental assessment process. This thesis presents four studies on the role of biodiversity in environmental assessment of road and railway plans and projects. Paper I presents the state of the art of road and railway impacts on ecological patterns and processes sustaining biodiversity, and reviews the treatment of biodiversity in a selection of environmental assessment reports from Sweden and the UK. Paper II presents a quantitative assessment of the impact of the Swedish road network on birds and mammals, and how fragmentation and road disturbance might affect a selection of ecological profiles. Paper III demonstrates how scientific models, data and knowledge can be mobilized for the design and evaluation of railway corridors, and Paper IV analyses how habitat connectivity, as a prerequisite of genetic exchange, relates to landscape composition and size and number of fauna passages. The results from Paper I show that road and railway impacts on biodiversity need to be addressed at every level of planning; from corridor alignment in the landscape to utilization and maintenance. The review of environmental assessment reports shows that the treatment of biodiversity in environmental assessment has improved over the years, but that problems with habitat fragmentation, connectivity and the spatial delimitation of the impact assessment study area remain. The results from Paper II identify natural grasslands and southern broadleaved forest, prioritized habitat types important for biodiversity, to most likely be highly affected by road impacts, and suggest road disturbance to have a high impact on overall habitat availability. The results from Paper III demonstrate how the landscape specific distribution of ecological and geological resources can be accounted for in railway corridor design, and potentially lead to more resource efficient outcomes with less impact on ecological processes. The results from Paper IV indicate that the several small fauna passages would increase connectivity more across a barrier than the construction of a single large. Effective barrier mitigation will also depend on the selection of focal species and the understanding of how the focal species perceive the landscape in terms of resistance to movement. This thesis demonstrates how quantitative assessment can benefit biodiversity impact analysis and address issues such as habitat connectivity and fragmentation, which have been difficult to account for in environmental assessment. It is recommended that biodiversity impact analysis moves towards an increasing use of quantitative methods and tools for prediction, evaluation and sensitivity analysis. Future challenges include verification and calibration of relevant spatial ecological models, and further integration of road ecology knowledge into road and railway planning. / <p>QC 20151103</p> / GESP

The Runoff Risk Advisory Forecast (RRAF) provides Wisconsin's farmers with an innovative decision support tool which communicates the threat of undesirable conditions for manure and nutrient spreading for up to 10 days in advance. The RRAF is a pioneering example of applying the National Weather Service's hydrologic forecasting abilities towards the Nation's water quality challenges. Relying on the North Central River Forecast Center's (NCRFC) operational Snow17 and Sacramento Soil Moisture Accounting Models, runoff risk is predicted for 216 modeled watersheds in Wisconsin. The RRAF is the first-of-its-kind real-time forecast tool to incorporate 5-days of future precipitation as well as 10-days of forecast temperatures to generate runoff risk guidance. The forecast product is updated three times daily and hosted on the Wisconsin Department of Agriculture, Trade, and Consumer Protection (DATCP) website. Developed with inter-agency collaboration, the RRAF model was validated against both edge-of-field observed runoff as well as small USGS gauged basin response. This analysis indicated promising results with a Bias Score of 0.93 and a False Alarm Ratio (FAR) of only 0.34 after applying a threshold method. Although the threshold process did dampen the Probability of Detection (POD) from 0.71 to 0.53, it was found that the magnitude of the events categorized as hits was 10-times larger than those classified as misses. The encouraging results from this first generation tool are aiding State of Wisconsin officials in increasing awareness of risky runoff conditions to help minimize contaminated agriculture runoff from entering the State's water bodies.

Persistent conflicts between stakeholders and complex trade offs among forest values have created a difficult decision environment for sustainable forest management. Tools developed for decision support in land use planning are essential for managing these challenges. This research study is an interactive assessment of a land use planning Decision Support Tool (DST) in the Invermere Timber Supply Area (TSA), located in the East Kootenay area of British Columbia. The aim of this study is to explore whether stakeholders' initial stated preferences change and whether trade-offs are made between various forest values upon observation of a long-term forecast of these values using a DST. Representatives from various stakeholder groups in the area were assembled for individual sessions to interact with the multi-criteria DST. Participants were required to state their preferences for six forest values using a weighting scheme. The DST developed an output for each forest value based on the participants' preferences. Upon review of the DST output, the participant had the opportunity to alter their initial preferences iteratively until a desirable output was found. The results indicate that participants' preferences changed after reviewing the DST outputs and that participants are willing to make trade-offs between various forest values using a DST to find a desirable solution. However, the preference order of the forest values changed only slightly from the participants' initial to preferred scenarios; instead participants made drastic changes to the weighting of each value to find a desirable output. Participants also stated their willingness to use DSTs for land use planning decision-making, although underlying assumptions built into the model must be improved before stakeholders can trust the tool as an aid for decision-making. Studies such as this can further the development of DSTs to help find desirable decisions for sustainable resource management and to help create a productive and engaging process.

The main aim of the research: to offer analysis methods for development of a knowledge-based decision support system in the sphere of construction export. • To evaluate the effectiveness of construction export using methods of multiple criteria analysis. • To make use of expert methods when developing the system of feasibility study of construction export and the knowledge base of best experience. • To describe application of internet as a tool in analysis of foreign markets and provide offers to exporters of the Lithuanian construction branch on how to use Internet in their activities thus granting improvement of export effectiveness. • To provide offers on how to reduce export cost and improve effectiveness and quality by using the newest IT and knowledge systems.

This thesis focuses on the identification of experience required for solving IT (Information Technology) problems in small to medium sized enterprises. It is aimed to utilize information retrieval and data mining techniques to automatically extract information from publicly available experience data on the internet to automatically generate a knowledgebase for dynamic IT management support. In this thesis, similarity distance measures as Jaccard Index, Cosine Similarity Measure and clustering algorithms as K-Means, EM, DBScan, CES, CES+ are employed on three different datasets to evaluate their performances. CES+ algorithm gives the highest performance results in these evaluations. Moreover, Multi Objective Genetic Algorithm (MOGA) is used and is evaluated on three different data sets to aid the usage of CES+ in real life senarios by automating the selection of necessary parameters. Results show that MOGA support is not only automating the CES+, it also provides higher performance results.

Many real-world relations are networks that can be modelled with a kind of directed hypergraph named a forward hypergraph (F-graph). F-graphs capture the semantics of both conjunctive and disjunctive dependency relations. Logic statements are sometimes represented using AND/OR directed graphs and they directly correspond with F-graphs; we provide algorithms to convert between the two types of graph. One problem of interest in networks is determining the degree to which the network, with a priority on certain elements, depends upon individual nodes. We address this problem by providing an algorithm, AssetRank, which computes vertex ranks and takes into account network priorities, preferential dependencies, and extra-network influences. A second problem of interest in networks is optimizing the removal of nodes to separate two subcommunities (source and target) to the greatest practical degree, even when a complete disconnection is impractical. The problem is complicated by the need to consider the cost of removing nodes, a budget that constrains the degree to which separation is possible, cascading effects of removing a node, non-linear effects of removing nodes in combination, and removing nodes with the greatest impact on the subcommunities. To this end, we use F-graphs and introduce the concepts of vertex closures and closure-relation graphs. We created two partial-cut algorithms: the first one computes an optimal solution to this NP-hard optimization problem, and the second one estimates an optimization by exploring the closure-relation graph in a best-first search manner. Computer network defence provides a ready application area. Network defenders wish to understand which services and hosts are defence priorities (defence goals), and then, which configurations and vulnerabilities are the most useful to attackers in reaching the defence goals. The defenders' resources are constrained in terms of available person-hours, finances, and acceptable impacts to operations. The work in this thesis supports network defenders by providing actionable information that efficiently removes attack enablers and ensures defence priorities. We present an integration of our algorithms with commercial and open-source network security software. / Thesis (Ph.D, Computing) -- Queen's University, 2011-04-30 22:17:52.062

When referring physicians decide to refer their patients to specialist care, they rarely, if ever, make a referral decision with the benefit of having access to all of the desirable information. It is therefore highly unlikely that the referring physician will make the optimal choice of specialist for that particular referral. A specialist selection optimization algorithm was developed to guarantee that the “right specialist” for each patient’s referral was chosen. The specialist selection optimization algorithm was developed based on feedback from over 120 users of the e-referral program. The developed algorithm was simulated, tested, and validated in MATLAB. Results from the MATLAB simulation demonstrate that the algorithm functioned as it was designed to. The developed algorithm provides referring physicians with an unprecedented level of support for their decision of which specialist to refer their patient to.

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No description available.

A Decision Support System for the design and planning of soil conservation systems on a watershed scale was conceived and applied to southwestern Quebec. The system integrated Geographical Information System, distributed parameter hydrologic modeling and Expert System technologies. Maps of appropriate soil conservation practices were produced for two small rural basins representative of the study region. The effect of the selected practices on runoff and sediment was assessed using the ANSWERS model. Erosion sites were targeted using a once-in-25 year design storm. It was observed that small portions of the study basins produced large amounts of eroded sediment. The expert system was designed to select appropriate conservation practices for the 1-ha cells which had more than one ton of erosion as a result of the design storm. The results demonstrated that the selected conservation practices would reduce sediment yield and average erosion rates by 50% in each of the study basins.