Remote sensing and core data needed to support planning and policy decision making

A variety of sustainable development research efforts and related activities are attempting to reconcile the issues of conserving our natural resources without limiting economic motivation while also improving our social equity and quality of life. Land use/land cover change, occurring on a global scale, is an aggregate of local land use decisions and profoundly impacts our environment. It is therefore the local decision making process that should be the eventual target of many of the ongoing data collection and research efforts which strive toward supporting a sustainable future. Satellite imagery data is a primary source of data upon which to build a core data set for use by researchers in analyzing this global change. A process is necessary to link global change research, utilizing satellite imagery, to the local land use decision making process. One example of this is the NASA-sponsored Regional Data Center (RDC) prototype. The RDC approach is an attempt to integrate science and technology at the community level. The anticipated result of this complex interaction between research and the decision making communities will be realized in the form of long-term benefits to the public.

Quantifying economic values of coastal and marine ecosystem services and assessing their use in decision-making : applications in New Caledonia and Australia

This thesis deals with the issues of quantifying economic values of coastal and marine ecosystem services and assessing their use in decision-making. The first analytical part of the thesis focuses on estimating non-market use and non-use values, with an application in New-Caledonia using Discrete Choice Experiment. The second part examines how and to what extent the economic valuation of ecosystem services is used in coastal management decision-making with an application in Australia. Using a multi-criteria analysis, the relative importance of ecological, social and economic evaluation criteria is also assessed in the context of coastal development.

Multiple criteria-based real-time decision making by autonomous city vehicles

This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e. the autonomous vehicles’ ability to make appropriate driving decisions in city road traffic situations. After decomposing the problem into two consecutive decision making stages, and giving a short overview about previous work, the paper explains how Multiple Criteria Decision Making (MCDM) can be used in the process of selecting the most appropriate driving maneuver.

Sustainability in infrastructure investment : building the business case

Many infrastructure agencies adopt sustainability objectives at a corporate level and incorporate sustainability targets and indicators as part of corporate reporting processes. These objectives are expected to translate to all stages of the project delivery process, including project selection. For infrastructure capital works projects and programs, a robust project management approach involves the development of a business case to guide investment decision making. A key tool in the assessment of project options and selection of a delivery strategy is Cost Benefit Analysis (CBA). Infrastructure providers are required to undertake cost benefit analysis to support project selection through regulatory approval and budgetary processes. This tool has emerged through the prism of economic analysis rather than sustainability. A literature review reveals the limitations of CBA alone to effectively evaluate economic, environmental and social externalities or impacts that apply over a long time frame, and that are ultimately irreversible. Multi-Criteria Analysis (MCA) has been introduced as a means to incorporate a wider array of factors into decision making such as sustainability. This, however, presents new challenges with issues around how to transparently represent wider community values in the selection of a preferred solution. Are these tools effective in assessing the wider sustainability costs and benefits taking into account that these are public works with long life spans and significant impacts across institutional boundaries? The research indicates a need to develop clear guidelines for investment decision making in order to better align with corporate sustainability objectives. Findings from the literature review indicate that a more sustainable approach to investment decision-making framework should include: the incorporation of sustainability goals from corporate planning documents; problem definition and option generation using best practice investment management guidelines; improved guidelines for Business Case development using a combination of both Cost Benefit Analysis and Multi-Criteria Analysis; and an integrated public participation process.

Process visualization techniques for multi-perspective process comparisons

Organizations executing similar business processes need to understand the differences and similarities in activities performed across work environments. Presently, research interest is directed towards the potential of visualization for the display of process models, to support users in their analysis tasks. Although recent literature in process mining and comparison provide several methods and algorithms to perform process and log comparison, few contributions explore novel visualization approaches. This paper analyses process comparison from a design perspective, providing some practical visualization techniques as anal- ysis solutions (/to support process analysis). The design of the visual comparison has been tackled through three different points of view: the general model, the projected model and the side-by-side comparison in order to support the needs of business analysts. A case study is presented showing the application of process mining and visualization techniques to patient treatment across two Australian hospitals.

Suunnittelunäkemys metsäorganisaatioissa ja sen vaikutus tietojärjestelmälle asetettaviin vaatimuksiin

Department of Forest Resource Management in the University of Helsinki has in years 2004?2007 carried out so-called SIMO -project to develop a new generation planning system for forest management. Project parties are organisations doing most of Finnish forest planning in government, industry and private owned forests. Aim of this study was to find out the needs and requirements for new forest planning system and to clarify how parties see targets and processes in today's forest planning. Representatives responsible for forest planning in each organisation were interviewed one by one. According to study the stand-based system for managing and treating forests continues in the future. Because of variable data acquisition methods with different accuracy and sources, and development of single tree interpretation, more and more forest data is collected without field work. The benefits of using more specific forest data also calls for use of information units smaller than tree stand. In Finland the traditional way to arrange forest planning computation is divided in two elements. After updating the forest data to present situation every stand unit's growth is simulated with different alternative treatment schedule. After simulation, optimisation selects for every stand one treatment schedule so that the management program satisfies the owner's goals in the best possible way. This arrangement will be maintained in the future system. The parties' requirements to add multi-criteria problem solving, group decision support methods as well as heuristic and spatial optimisation into system make the programming work more challenging. Generally the new system is expected to be adjustable and transparent. Strict documentation and free source code helps to bring these expectations into effect. Variable growing models and treatment schedules with different source information, accuracy, methods and the speed of processing are supposed to work easily in system. Also possibilities to calibrate models regionally and to set local parameters changing in time are required. In future the forest planning system will be integrated in comprehensive data management systems together with geographic, economic and work supervision information. This requires a modular method of implementing the system and the use of a simple data transmission interface between modules and together with other systems. No major differences in parties' view of the systems requirements were noticed in this study. Rather the interviews completed the full picture from slightly different angles. In organisation the forest management is considered quite inflexible and it only draws the strategic lines. It does not yet have a role in operative activity, although the need and benefits of team level forest planning are admitted. Demands and opportunities of variable forest data, new planning goals and development of information technology are known. Party organisations want to keep on track with development. One example is the engagement in extensive SIMO-project which connects the whole field of forest planning in Finland.

Modeling multi-stakeholder multi-objective decisions during public participation in major infrastructure and construction projects: A decision rule approach

Major infrastructure and construction (MIC) projects are those with significant traffic or environmental impact, of strategic and regional significance and high sensitivity. The decision making process of schemes of this type is becoming ever more complicated, especially with the increasing number of stakeholders involved and their growing tendency to defend their own varied interests. Failing to address and meet the concerns and expectations of stakeholders may result in project failures. To avoid this necessitates a systematic participatory approach to facilitate decision-making. Though numerous decision models have been established in previous studies (e.g. ELECTRE methods, the analytic hierarchy process and analytic network process) their applicability in the decision process during stakeholder participation in contemporary MIC projects is still uncertain. To resolve this, the decision rule approach is employed for modeling multi-stakeholder multi-objective project decisions. Through this, the result is obtained naturally according to the “rules” accepted by any stakeholder involved. In this sense, consensus is more likely to be achieved since the process is more convincing and the result is easier to be accepted by all concerned. Appropriate “rules”, comprehensive enough to address multiple objectives while straightforward enough to be understood by multiple stakeholders, are set for resolving conflict and facilitating consensus during the project decision process. The West Kowloon Cultural District (WKCD) project is used as a demonstration case and a focus group meeting is conducted in order to confirm the validity of the model established. The results indicate that the model is objective, reliable and practical enough to cope with real world problems. Finally, a suggested future research agenda is provided.

Using multi-label classification for acoustic pattern detection and assisting bird species surveys

Acoustics is a rich source of environmental information that can reflect the ecological dynamics. To deal with the escalating acoustic data, a variety of automated classification techniques have been used for acoustic patterns or scene recognition, including urban soundscapes such as streets and restaurants; and natural soundscapes such as raining and thundering. It is common to classify acoustic patterns under the assumption that a single type of soundscapes present in an audio clip. This assumption is reasonable for some carefully selected audios. However, only few experiments have been focused on classifying simultaneous acoustic patterns in long-duration recordings. This paper proposes a binary relevance based multi-label classification approach to recognise simultaneous acoustic patterns in one-minute audio clips. By utilising acoustic indices as global features and multilayer perceptron as a base classifier, we achieve good classification performance on in-the-field data. Compared with single-label classification, multi-label classification approach provides more detailed information about the distributions of various acoustic patterns in long-duration recordings. These results will merit further biodiversity investigations, such as bird species surveys.

A participatory approach to tactical forest planning.

The paper examines the needs, premises and criteria for effective public participation in tactical forest planning. A method for participatory forest planning utilizing the techniques of preference analysis, professional expertise and heuristic optimization is introduced. The techniques do not cover the whole process of participatory planning, but are applied as a tool constituting the numerical core for decision support. The complexity of multi-resource management is addressed by hierarchical decision analysis which assesses the public values, preferences and decision criteria toward the planning situation. An optimal management plan is sought using heuristic optimization. The plan can further be improved through mutual negotiations, if necessary. The use of the approach is demonstrated with an illustrative example, it's merits and challenges for participatory forest planning and decision making are discussed and a model for applying it in general forest planning context is depicted. By using the approach, valuable information can be obtained about public preferences and the effects of taking them into consideration on the choice of the combination of standwise treatment proposals for a forest area. Participatory forest planning calculations, carried out by the approach presented in the paper, can be utilized in conflict management and in developing compromises between competing interests.

Análise da vulnerabilidade socioambiental na Zona de amortecimento do Parque Estadual do Ibitipoca (MG), por geoprocessamento: contribuindo no apoio à tomada de decisão.

Conservar as últimas florestas tropicais é uma preocupação mundial, e como formas de proteção legal são criadas Unidades de Conservação (UCs), dedicadas para a preservação e manutenção da biodiversidade e recursos naturais. O entorno das áreas protegidas também são locais amparados pela lei e as atividades nelas devem ser restritas, a fim de não gerar impacto sobre a UC. O Parque Estadual do Ibitipoca, localizado em Minas Gerais, possui uma zona de amortecimento (ZA) de 100,41 km que pertence aos municípios de Lima Duarte, Santa Rita do Ibitipoca e Bias Fortes. O presente trabalho, portanto, visa caracterizar a vulnerabilidade socioambiental na zona de amortecimento do Parque Estadual do Ibitipoca (PEI), utilizando para tal, técnicas de geoprocessamento. Para chegar ao resultado final foi feito uma análise da vulnerabilidade social da ZA, utilizando dados do censo de infraestrutura (água, esgoto e lixo) e renda per capita; e para a vulnerabilidade ambiental foi realizado a sobreposição dos mapas de uso da terra, declividade e tipos de solos. Esses dados foram tratados no programa ArcGis, através da análise multicritério e seguindo a metodologia proposta por Moura (2007). O mapa de vulnerabilidade socioambiental possibilitou apontar os locais que necessitam de maiores cuidados e investimento, auxiliando assim os gestores do Parque no manejo e preservação da ZA. Os processos adotados nesta pesquisa permitiram a geração de um banco de dados georreferenciado, que será disponibilizado aos gestores, à população do entorno e à comunidade técnico-científica.

Interventions to improve the appropriate use of polypharmacy for older people

Background
Inappropriate polypharmacy is a particular concern in older people and is associated with negative health outcomes. Choosing the best interventions to improve appropriate polypharmacy is a priority, hence interest in appropriate polypharmacy, where many medicines may be used to achieve better clinical outcomes for patients, is growing.

Objectives
This review sought to determine which interventions, alone or in combination, are effective in improving the appropriate use of polypharmacy and reducing medication-related problems in older people.

Search methods
In November 2013, for this first update, a range of literature databases including MEDLINE and EMBASE were searched, and handsearching of reference lists was performed. Search terms included 'polypharmacy', 'medication appropriateness' and 'inappropriate prescribing'.

Selection criteria
A range of study designs were eligible. Eligible studies described interventions affecting prescribing aimed at improving appropriate polypharmacy in people 65 years of age and older in which a validated measure of appropriateness was used (e.g. Beers criteria, Medication Appropriateness Index (MAI)).

Data collection and analysis
Two review authors independently reviewed abstracts of eligible studies, extracted data and assessed risk of bias of included studies. Study-specific estimates were pooled, and a random-effects model was used to yield summary estimates of effect and 95% confidence intervals (CIs). The GRADE (Grades of Recommendation, Assessment, Development and Evaluation) approach was used to assess the overall quality of evidence for each pooled outcome.

Main results
Two studies were added to this review to bring the total number of included studies to 12. One intervention consisted of computerised decision support; 11 complex, multi-faceted pharmaceutical approaches to interventions were provided in a variety of settings. Interventions were delivered by healthcare professionals, such as prescribers and pharmacists. Appropriateness of prescribing was measured using validated tools, including the MAI score post intervention (eight studies), Beers criteria (four studies), STOPP criteria (two studies) and START criteria (one study). Interventions included in this review resulted in a reduction in inappropriate medication usage. Based on the GRADE approach, the overall quality of evidence for all pooled outcomes ranged from very low to low. A greater reduction in MAI scores between baseline and follow-up was seen in the intervention group when compared with the control group (four studies; mean difference -6.78, 95% CI -12.34 to -1.22). Postintervention pooled data showed a lower summated MAI score (five studies; mean difference -3.88, 95% CI -5.40 to -2.35) and fewer Beers drugs per participant (two studies; mean difference -0.1, 95% CI -0.28 to 0.09) in the intervention group compared with the control group. Evidence of the effects of interventions on hospital admissions (five studies) and of medication-related problems (six studies) was conflicting.

Authors' conclusions
It is unclear whether interventions to improve appropriate polypharmacy, such as pharmaceutical care, resulted in clinically significant improvement; however, they appear beneficial in terms of reducing inappropriate prescribing.

MASCEM - an electricity market simulator providing coalition support for virtual power players

This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimization techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Players (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper details some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study based on real data.

Seleção de ferramenta para avaliação do desempenho ambiental de produtos: estudo de caso na indústria automóvel

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Química e Biológica

Adapting Meeting Tools to Agent Decision

Electricity markets are complex environments comprising several negotiation mechanisms. MASCEM (Multi- Agent System for Competitive Electricity Markets) is a simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. ALBidS (Adaptive Learning Strategic Bidding System) is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM it considers several different methodologies based on very distinct approaches. The Six Thinking Hats is a powerful technique used to look at decisions from different perspectives. This paper aims to complement ALBidS strategies usage by MASCEM players, providing, through the Six Thinking Hats group decision technique, a means to combine them and take advantages from their different perspectives. The combination of the different proposals resulting from ALBidS’ strategies is performed through the application of a Genetic Algorithm, resulting in an evolutionary learning approach.

Scenarios Generation for Multi-Agent simulation of Electricity Markets based on Intelligent Data Analysis

This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players’ profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets’ participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents’ profiles and strategies resulting in a better representation of real market players’ behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.