Emergetic ternary diagrams: five examples for application in environmental accounting for decision-making

In a recent paper, "A combined tool for environmental scientists and decision makers: ternary diagrams and emergy accounting." [Giannettti BF, Barrella FA, Almeida CMVB. A combined tool for environment scientists and decision makers: ternary diagrams and emergy accounting. J Clean Prod, in press http://dx.doi.org/10.1016/j.jclepro.2004.09.002] Ternary diagrams were proposed as a graphical tool to assist emergy analysis. The graphical representation of the emergy accounting data makes it possible to compare processes and systems with and without ecosystem services, to evaluate improvements and to follow the system performance over time. The graphic tool is versatile and adaptable to represent products, processes, systems, countries, and different periods of time.The use and the versatility of ternary diagrams for assisting in performing emergy analyses are illustrated by means of five examples taken from the literature, which are presented and discussed. It is shown that emergetic ternary diagram's properties assist the assessment of the system of the system efficiency, its dependance upon renewable and non-renewable inputs and the environmental support for dilution and abatement of process emissions. With the aid of ternary diagrams, details such as the interaction between systems and between systems and the environment are recognized and evaluated. Such a tool for graphical analysis allows a transparent presentation of the results and can serve as an interface between emergy scientists and decision makers, provided the meaning of each line in the diagram is carefully explained and understood. (c) 2005 Elsevier Ltd. All rights reserved.

A Decision-Tree-Based Approach to Smoke Spike Detection in a Heavy-Duty Diesel Engine

Smoke spikes occurring during transient engine operation have detrimental health effects and increase fuel consumption by requiring more frequent regeneration of the diesel particulate filter. This paper proposes a decision tree approach to real-time detection of smoke spikes for control and on-board diagnostics purposes. A contemporary, electronically controlled heavy-duty diesel engine was used to investigate the deficiencies of smoke control based on the fuel-to-oxygen-ratio limit. With the aid of transient and steady state data analysis and empirical as well as dimensional modeling, it was shown that the fuel-to-oxygen ratio was not estimated correctly during the turbocharger lag period. This inaccuracy was attributed to the large manifold pressure ratios and low exhaust gas recirculation flows recorded during the turbocharger lag period, which meant that engine control module correlations for the exhaust gas recirculation flow and the volumetric efficiency had to be extrapolated. The engine control module correlations were based on steady state data and it was shown that, unless the turbocharger efficiency is artificially reduced, the large manifold pressure ratios observed during the turbocharger lag period cannot be achieved at steady state. Additionally, the cylinder-to-cylinder variation during this period were shown to be sufficiently significant to make the average fuel-to-oxygen ratio a poor predictor of the transient smoke emissions. The steady state data also showed higher smoke emissions with higher exhaust gas recirculation fractions at constant fuel-to-oxygen-ratio levels. This suggests that, even if the fuel-to-oxygen ratios were to be estimated accurately for each cylinder, they would still be ineffective as smoke limiters. A decision tree trained on snap throttle data and pruned with engineering knowledge was able to use the inaccurate engine control module estimates of the fuel-to-oxygen ratio together with information on the engine control module estimate of the exhaust gas recirculation fraction, the engine speed, and the manifold pressure ratio to predict 94% of all spikes occurring over the Federal Test Procedure cycle. The advantages of this non-parametric approach over other commonly used parametric empirical methods such as regression were described. An application of accurate smoke spike detection in which the injection pressure is increased at points with a high opacity to reduce the cumulative particulate matter emissions substantially with a minimum increase in the cumulative nitrogrn oxide emissions was illustrated with dimensional and empirical modeling.

Assessing Decision Making Strategies In Construction Management By Using A Schedule-Based Simulation Framework

During the project, managers encounter numerous contingencies and are faced with the challenging task of making decisions that will effectively keep the project on track. This task is very challenging because construction projects are non-prototypical and the processes are irreversible. Therefore, it is critical to apply a methodological approach to develop a few alternative management decision strategies during the planning phase, which can be deployed to manage alternative scenarios resulting from expected and unexpected disruptions in the as-planned schedule. Such a methodology should have the following features but are missing in the existing research: (1) looking at the effects of local decisions on the global project outcomes, (2) studying how a schedule responds to decisions and disruptive events because the risk in a schedule is a function of the decisions made, (3) establishing a method to assess and improve the management decision strategies, and (4) developing project specific decision strategies because each construction project is unique and the lessons from a particular project cannot be easily applied to projects that have different contexts. The objective of this dissertation is to develop a schedule-based simulation framework to design, assess, and improve sequences of decisions for the execution stage. The contribution of this research is the introduction of applying decision strategies to manage a project and the establishment of iterative methodology to continuously assess and improve decision strategies and schedules. The project managers or schedulers can implement the methodology to develop and identify schedules accompanied by suitable decision strategies to manage a project at the planning stage. The developed methodology also lays the foundation for an algorithm towards continuously automatically generating satisfactory schedule and strategies through the construction life of a project. Different from studying isolated daily decisions, the proposed framework introduces the notion of {em decision strategies} to manage construction process. A decision strategy is a sequence of interdependent decisions determined by resource allocation policies such as labor, material, equipment, and space policies. The schedule-based simulation framework consists of two parts, experiment design and result assessment. The core of the experiment design is the establishment of an iterative method to test and improve decision strategies and schedules, which is based on the introduction of decision strategies and the development of a schedule-based simulation testbed. The simulation testbed used is Interactive Construction Decision Making Aid (ICDMA). ICDMA has an emulator to duplicate the construction process that has been previously developed and a random event generator that allows the decision-maker to respond to disruptions in the emulation. It is used to study how the schedule responds to these disruptions and the corresponding decisions made over the duration of the project while accounting for cascading impacts and dependencies between activities. The dissertation is organized into two parts. The first part presents the existing research, identifies the departure points of this work, and develops a schedule-based simulation framework to design, assess, and improve decision strategies. In the second part, the proposed schedule-based simulation framework is applied to investigate specific research problems.

New Security threats for humanitarian aid workers

Two recent events in Afghanistan and Iraq highlight the current security threats for humanitarian aid workers: Firstly, in July 2004 the humanitarian aid organisation Médecins sans Frontières (MSF) stopped its operations in Afghanistan. This decision followed the targeted killing of five MSF aid workers in Northwestern Afghanistan in June 2004, a brutal act unprecedented in the organisation’s history. Afghanistan has become a dangerous place for aid workers: Since March 2003 more than 30 humanitarian aid workers have been killed. Secondly, in September 2004 the so-called “two Simonas”, staff members of the Italian non-governemental organization (NGO) “Un ponte per” (A Bridge for Bagdad) were abducted in Iraq and, fortunately, released in October 2004. Around 130 foreigners have been seized in Iraq in a wave of abductions that began in April. Most have been released, but around 30 have been killed. Due to the tense security situation in Iraq all the expatriate staff members of Western NGOs have been evacuated in the last months.

Intelligent Decision-Making System Frameworks for a Digital Plan of Work: A Theoretical Investigation for the Construction Industry

The construction industry is characterised by fragmentation and suffers from lack of collaboration, often adopting adversarial working practices to achieve deliverables. For the UK Government and construction industry, BIM is a game changer aiming to rectify this fragmentation and promote collaboration. However it has become clear that there is an essential need to have better controls and definitions of both data deliverables and data classification. Traditional methods and techniques for collating and inputting data have shown to be time consuming and provide little to improve or add value to the overall task of improving deliverables. Hence arose the need in the industry to develop a Digital Plan of Work (DPoW) toolkit that would aid the decision making process, providing the required control over the project workflows and data deliverables, and enabling better collaboration through transparency of need and delivery. The specification for the existing Digital Plan of Work (DPoW) was to be, an industry standard method of describing geometric, requirements and data deliveries at key stages of the project cycle, with the addition of a structured and standardised information classification system. However surveys and interviews conducted within this research indicate that the current DPoW resembles a digitised version of the pre-existing plans of work and does not push towards the data enriched decision-making abilities that advancements in technology now offer. A Digital Framework is not simply the digitisation of current or historic standard methods and procedures, it is a new intelligent driven digital system that uses new tools, processes, procedures and work flows to eradicate waste and increase efficiency. In addition to reporting on conducted surveys above, this research paper will present a theoretical investigation into usage of Intelligent Decision Support Systems within a digital plan of work framework. Furthermore this paper will present findings on the suitability to utilise advancements in intelligent decision-making system frameworks and Artificial Intelligence for a UK BIM Framework. This should form the foundations of decision-making for projects implemented at BIM level 2. The gap identified in this paper is that the current digital toolkit does not incorporate the intelligent characteristics available in other industries through advancements in technology and collation of vast amounts of data that a digital plan of work framework could have access to and begin to develop, learn and adapt for decision-making through the live interaction of project stakeholders.

The use of expert systems for decision making in organizations

The research described in this thesis investigates three issues related to the use of expert systems for decision making in organizations. These are the effectiveness of ESs when used in different roles, to replace a human decision maker or to advise a human decision maker, the users' behaviourand opinions towards using an expertadvisory system and, the possibility of organization-wide deployment of expert systems and the role of an ES in different organizational levels. The research was based on the development of expert systems within a business game environment, a simulation of a manufacturing company. This was chosen to give more control over the `experiments' than would be possible in a real organization. An expert system (EXGAME) was developed based on a structure derived from Anthony's three levels of decision making to manage the simulated company in the business game itself with little user intervention. On the basis of EXGAME, an expert advisory system (ADGAME) was built to help game players to make better decisions in managing the game company. EXGAME and ADGAME are thus two expert systems in the same domain performing different roles; it was found that ADGAME had, in places, to be different from EXGAME, not simply an extension of it. EXGAME was tested several times against human rivals and was evaluated by measuring its performance. ADGAME was also tested by different users and was assessed by measuring the users' performance and analysing their opinions towards it as a helpful decision making aid. The results showed that an expert system was able to replace a human at the operational level, but had difficulty at the strategic level. It also showed the success of the organization-wide deployment of expert systems in this simulated company.

A methodology for implementing a decision support system:a small company case study

The importance of non-technical factors in the design and implementation of information systems has been increasingly recognised by both researchers and practitioners, and recent literature highlights the need for new tools and techniques with an organisational, rather than technical, focus. The gap between what is technically possible and what is generally practised, is particularly wide in the sales and marketing field. This research describes the design and implementation of a decision support system (DSS) for marketing planning and control in a small, but complex company and examines the nature of the difficulties encountered. An intermediary with functional, rather than technical, expertise is used as a strategy for overcoming these by taking control of the whole of the systems design and implementation cycle. Given the practical nature of the research, an action research approach is adopted with the researcher undertaking this role. This approach provides a detailed case study of what actually happens during the DSS development cycle, allowing the influence of organisational factors to be captured. The findings of the research show how the main focus of the intermediary's role needs to be adapted over the systems development cycle; from coordination and liaison in the pre-design and design stages, to systems champion during the first part of the implementation stage, and finally to catalyst to ensure that the DSS is integrated into the decision-making process. Two practical marketing exercises are undertaken which illustrate the nature of the gap between the provision of information and its use. The lack of a formal approach to planning and control is shown to have a significant effect on the way the DSS is used and the role of the intermediary is extended successfully to accommodate this factor. This leads to the conclusion that for the DSS to play a fully effective role, small firms may need to introduce more structure into their marketing planning, and that the role of the intermediary, or Information Coordinator, should include the responsibility for introducing new techniques and ideas to aid with this.

Supporters of abortion and Supreme Court Decision demonstrate in front of St. Patrick's Cathedral

General note: Title and date provided by Bettye Lane.

Student Financial Aid:The Roles of Loans and Grants (Working Paper 37)

This paper addresses the roles of loans and grants as forms of student financial aid. It begins with a simple choice model where individuals decide to pursue post-secondary studies if i) the net benefits of doing so are positive and ii) no financing or liquidity constraints stand in their way. The effects of loans and grants on these two elements of the schooling decision are then discussed. It is argued that based on equity, efficiency, and fiscal considerations, loans are generally best suited for helping those who want to go but face financing constraints, whereas grants are more appropriate for increasing the incentives for individuals from disadvantaged backgrounds to further their studies. Loan subsidies, which make loans part-loan and part-grant, are also discussed, including how they might be used to address “debt aversion”. Given that subsidised loans have a grant (subsidy) element, while grants help overcome the credit constraints upon which loans are targeted, the paper then attempts to establish some general rules for providing loans, for subsidising the loans awarded, and for giving “pure” grants. It concludes with an application of these principles in the form of a recent proposal for reforming the student financial system in Canada. *

Performance assessment, vulnerability, human capital, and the allocation of aid among developing countries

Developing country performance with respect to economic policies and institutional behavior is a common criterion for the allocation of aid among recipient countries. This paper examines how performance is used, arguing that performance is too narrowly defined. A more appropriate definition is one that controls for the economic vulnerability and human capital of developing countries. Econometric analysis of cross-section and panel data is presented that supports this contention. The paper also contends that performance and exogenous economic shocks are likely to be pro-cyclical. This implies a double punishment when aid is allocated according to performance. Evidence of such punishment is also provided. The paper concludes by arguing that economic vulnerability and human capital variables should augment performance measures in aid allocation decision-making.

Application of multi-criteria decision making methods to compression ignition engine efficiency and gaseous, particulate and greenhouse gas emissions

Compression ignition (CI) engine design is subject to many constraints which presents a multi-criteria optimisation problem that the engine researcher must solve. In particular, the modern CI engine must not only be efficient, but must also deliver low gaseous, particulate and life cycle greenhouse gas emissions so that its impact on urban air quality, human health, and global warming are minimised. Consequently, this study undertakes a multi-criteria analysis which seeks to identify alternative fuels, injection technologies and combustion strategies that could potentially satisfy these CI engine design constraints. Three datasets are analysed with the Preference Ranking Organization Method for Enrichment Evaluations and Geometrical Analysis for Interactive Aid (PROMETHEE-GAIA) algorithm to explore the impact of 1): an ethanol fumigation system, 2): alternative fuels (20 % biodiesel and synthetic diesel) and alternative injection technologies (mechanical direct injection and common rail injection), and 3): various biodiesel fuels made from 3 feedstocks (i.e. soy, tallow, and canola) tested at several blend percentages (20-100 %) on the resulting emissions and efficiency profile of the various test engines. The results show that moderate ethanol substitutions (~20 % by energy) at moderate load, high percentage soy blends (60-100 %), and alternative fuels (biodiesel and synthetic diesel) provide an efficiency and emissions profile that yields the most “preferred” solutions to this multi-criteria engine design problem. Further research is, however, required to reduce Reactive Oxygen Species (ROS) emissions with alternative fuels, and to deliver technologies that do not significantly reduce the median diameter of particle emissions.

Development aid: regulatory impact assessment and conditionality

The purpose of this paper is to examine how Regulatory Impact Assessment (RIA) can contribute to decision-making processes of Official Development Assistance (ODA) loans and grants. The point of departure for the discussion is the phenomenon that RIA, within a context of ODA, is applied by International Finance Institutions mainly in the context of Development Policy Loans, to introduce or strengthen country systems for Regulatory Impact Assessment. However, ODA grants, and loans, particularly when specific policy or regulatory conditions are attached to them, significantly impact economic and social conditions within the beneficiary country. This article examines what role RIA can play in facilitating a coherent decision-making process affecting the ODA allocation within a context of conditionalities requiring the introduction of new, or changes to existing, policies and regulations. The discussion considers the nexus between development aid effectiveness, conditionality and ownership, and RIA. The article argues a justification for applying RIA to ODA loans and grants which carry regulatory and policy conditionalities.