Evaluating public risk preferences in forest land-use choices using multi-attribute utility theory

Forest policy decisions inherently involve multiple attributes and risk and uncertainty as they largely deal with complex biological, ecological, and socio-political systems. Identifying risk preferences and quantifying their inter-relationships and tradeoffs are useful in formulating better forest policy. Often, technocrats and experts deal with risky decisions, but ideally, stakeholder risk characteristics should be explicitly considered in making policy decisions. This paper analysed societal risk preferences on public forest land-use attributes using multi-attribute utility theory (MAUT). The results indicate significant risk-averse behaviour towards old-growth forest conservation and forest-based recreation but less risk-averse behaviour towards native timber extraction. Overall, the respondents preferred a more conservative forest land-use option, which is consistent with their risk attitudes. The method provides insights into risk preferences of forest stakeholders, which could lead to better understanding of forest management conflicts. Moreover, the method explicitly distinguishes the technical and value components of the decision and is useful in unravelling public risk preferences in multiple-use forest planning situations.

Analysis of forest policy using multi-attribute value theory

Contents:
1. Role of multi-criteria decision making in natural resource management /​ Gamini Herath and Tony Prato
2. Analysis of forest policy using multi-attribute value theory /​ Jayanath Ananda and Gamini Herath
3. Comparing Riparian revegetation policy options using the analytic hierarchy process /​ M. E. Qureshi and S. R. Harrison
4. Managing environmental and health risks from a lead and zinc smelter : an application of deliberative multi-criteria evaluation /​ Wendy Proctor, Chris McQuade and Anne Dekker
5. Multiple attribute evaluation of management alternatives for the Missouri River System /​ Tony Prato
6. Multi-criteria decision analysis for integrated watershed management /​ Zeyuan Qiu
7. Fuzzy multiple attribute evaluation of agricultural systems /​ Leonie A. Marks and Elizabeth G. Dunn
8. Multi-criteria decision support for energy supply assessment /​ Bram Noble
9. Seaport development in Vietnam : evaluation using the analytic hierarchy process /​ Tran Phuong Dong and David M. Chapman
10. Valuing wetland aquatic resources using the analytic hierarchy process /​ Premachandra Wattage and Simon Mardle
11. Multiple attribute evaluation for national park management /​ Tony Prato
12. The future of MCDA in natural resource management : some generalizations /​ Gamini Herath and Tony Prato.

Minimum span frequency assignment problem on triangular lattices

This paper considers the Minimum Span Frequency Assignment Problem with Interference Graph on Triangular Grid (MSFAP-TG), a special case of the Minimum Span Frequency/Channel Assignment (MSFAP) for cellular systems and optical networks. The MSFAP-TG is interesting in its own right and thus worth studying. In this paper, we propose strong integer programming formulations for the MSFAP-TG and present polyhedral results on these formulations. In solving the MSFAP-TG, we implement these integer programs to obtain exact solutions. We also develop a heuristic for obtaining feasible solutions and upper bounds for the problems. With the use of these upper bounds, and a simple lower bound, the computation time of the exact algorithm can be improved substantially. The heuristic turns out to be quite good in terms of the quality of upper bounds and is extremely efficient in computation time. Last of all, we present new concepts for tackling large scale MSFAP-TGs.

Multi-attribute preference modelling and regional land-use planning

Forest management policy decisions are complex due to the multiple-use nature of goods and services from forests, difficulty in monetary valuation of ecological services and the involvement of a large number of stakeholders. Multi-attribute decision techniques can be used to synthesise stakeholder preferences related to regional forest planning because it can accommodate conflicting, multidimensional, incommensurable and incomparable objectives. The objective of this paper is to examine how the Analytical Hierarchy Process (AHP) can be used to incorporate stakeholder preferences in determining optimal forest land-use choices. The Australian Regional Forest Agreement Programme is taken as an illustrative case for the analysis. The results show that the AHP can formalise public participation in decision making and increase the transparency and the credibility of the process.

Proactive tools for combating plagiarism : an investigation

Academic integrity is an essential graduate attribute with ignorance of the problem of plagiarism in students’ work not being an option. This study resulted from increasing concern that the prevalence of plagiarism in assessment submitted by students is on the rise and shows no sign of abating. This study supports the provision of assessment designed to specifically focus student’s attention on improving their ability to both recognise plagiarism and avoid it in their written work. All students in both the investigated courses were invited to participate in a post-assessment, electronically-administered survey consisting of sixteen questions regarding the students’ experience regarding their assessment. This study was designed to achieve two purposes - to gain insight into whether providing tertiary students with extra feedback regarding their referencing improves their confidence with respect to referencing and reduces their propensity to plagiarise as well as to increase our understanding of what factors underlie student plagiarism. The results indicate that a considerable number of the students found the assessment of assistance with respect to improving their referencing confidence. In addition, a significant proportion of the students indicated that their understanding of what constitutes plagiarism and their confidence in avoiding plagiarism improved as a result of the assignment and its associated feedback.

A rough set approach for selecting clustering attribute

A few of clustering techniques for categorical data exist to group objects having similar characteristics. Some are able to handle uncertainty in the clustering process while others have stability issues. However, the performance of these techniques is an issue due to low accuracy and high computational complexity. This paper proposes a new technique called maximum dependency attributes (MDA) for selecting clustering attribute. The proposed approach is based on rough set theory by taking into account the dependency of attributes of the database. We analyze and compare the performance of MDA technique with the bi-clustering, total roughness (TR) and min–min roughness (MMR) techniques based on four test cases. The results establish the better performance of the proposed approach.

Finding coverage using incremental attribute combinations

Coverage is the range that covers only positive samples in attribute (or feature) space. Finding coverage is the kernel problem in induction algorithms because of the fact that coverage can be used as rules to describe positive samples. To reflect the characteristic of training samples, it is desirable that the large coverage that cover more positive samples. However, it is difficult to find large coverage, because the attribute space is usually very high dimensionality. Many heuristic methods such as ID3, AQ and CN2 have been proposed to find large coverage. A robust algorithm also has been proposed to find the largest coverage, but the complexities of time and space are costly when the dimensionality becomes high. To overcome this drawback, this paper proposes an algorithm that adopts incremental feature combinations to effectively find the largest coverage. In this algorithm, the irrelevant coverage can be pruned away at early stages because potentially large coverage can be found earlier. Experiments show that the space and time needed to find the largest coverage has been significantly reduced.