The work presented in this thesis targets the analysis and implementation of multi-criteria performance prediction methods for System-on-Chips (SoC). These new SoC architectures offer the opportunity to integrate complete heterogeneous systems into a single chip and can be used to design battery powered handhelds, security critical systems, consumer electronics devices, etc. However, this variety in terms of application usually comes with a lot of different performance objectives like power consumption, yield, design cost, production cost, silicon area and many others. These performance requirements are often very difficult to meet together so that SoC design usually relies on making the right design choices and finding the best performance compromises. In parallel with this architectural paradigm shift, new Very Deep Submicron (VDSM) silicon processes have more and more impact on the performances and deeply modify the way a VLSI system is designed even at the first stages of a design flow. In such a context where many new technological and system related variables enter the game, early exploration of the impact of design choices becomes crucial to estimate the performance of the system to design and reduce its time-to-market. In this context, this thesis presents: - A study of state-of-the-art tools and methods used to estimate the performances of VLSI systems and an original classification based on several features and concepts that they use. Based on this comparison, we highlight their weaknesses and lacks to identify new opportunities in performance prediction. - The definition of new concepts to enable the automatic exploration of large design spaces based on flexible performance criteria and degrees of freedom representing design choices. - The implementation of a couple of two new tools of our own: - Nessie, a tool enabling hierarchical representation of an application along with its platform and automatically performs the mapping and the estimation of their performance. -Yeti, a C++ library enabling the defintion and value estimation of closed-formed expressions and table-based relations. It provides the user with input and model sensitivity analysis capability, simulation scripting, run-time building and automatic plotting of the results. Additionally, Yeti can work in standalone mode to provide the user with an independent framework for model estimation and analysis. To demonstrate the use and interest of these tools, we provide in this thesis several case studies whose results are discussed and compared with the literature. Using Yeti, we successfully reproduced the results of a model estimating multi-core computation power and extended them thanks to the representation flexibility of our tool. We also built several models from the ground up to help the dimensioning of interconnect links and clock frequency optimization. Thanks to Nessie, we were able to reproduce the NoC power consumption results of an H.264/AVC decoding application running on a multicore platform. These results were then extended to the case of a 3D die stacked architecture and the performance benets are then discussed. We end up by highlighting the advantages of our technique and discuss future opportunities for performance prediction tools to explore.

Background and Motivation Unlike what is common in Europe and the rest of the world, Norway has traditionally met most of its stationary energy demand (including heating) with electricity, because of abundant access to hydropower. However, after the deregulation of the Norwegian electricity market in the 1990s, the increase in the electricity generation capacity has been less than the load demand increase. This is due to the relatively low electricity prices during the period, together with the fact that Norway’s energy companies no longer have any obligations to meet the load growth. The country’s generation capacity is currently not sufficient to meet demand, and accordingly, Norway is now a net importer of electricity, even in normal hydrological years. The situation has led to an increased focus on alternative energy solutions. It has been common that different energy infrastructures – such as electricity, district heating and natural gas networks – have been planned and commissioned by independent companies. However, such an organization of the planning means that synergistic effects of a combined energy system to a large extent are neglected. During the last decades, several traditional electricity companies have started to offer alternative energy carriers to their customers. This has led to a need for a more comprehensive and sophisticated energy-planning process, where the various energy infrastructures are planned in a coordinated way. The use of multi-criteria decision analysis (MCDA) appears to be suited for coordinated planning of energy systems with multiple energy carriers. MCDA is a generic term for different methods that help people make decisions according to their preferences in situations characterized by multiple conflicting criteria. The thesis focuses on two important stages of a multi-criteria planning task: - The initial structuring and modelling phase - The decision-making phase The Initial Structuring and Modelling Phase It is important to spend sufficient time and resources on the problem definition and structuring, so that all disagreements among the decision-maker(s) (DM(s)) and the analyst regarding the nature of the problem and the desired goals are eliminated. After the problem has been properly identified, the next step of a multi-criteria energy-planning process is the building of an energy system model (impact model). The model is used to calculate the operational attributes necessary for the multi-criteria analysis; in other words, to determine the various alternatives’ performance values for some or all of the criteria being considered. It is important that the model accounts for both the physical characteristics of the energy system components and the complex relationships between the system parameters. However, it is not propitious to choose/build an energy system model with a greater level of detail than needed to achieve the aims of the planning project. In my PhD research, I have chosen to use the eTransport model as the energy system model. This model is especially designed for planning of local and regional energy systems, where different energy carriers and technologies are considered simultaneously. However, eTransport can currently provide information only about costs and emissions directly connected to the energy system’s operation. Details about the investment plans’ performance on the remaining criteria must be found from other information sources. Guidelines should be identified regarding the extent to which different aspects should be accounted for, and on the ways these impacts can be assessed for each investment plan under consideration. However, it is important to realize that there is not one solution for how to do this that is valid for all kind of local energy-planning problems. It is therefore necessary for the DM(s) and the analyst to discuss these issues before entering the decision-making phase. The Decision-Making Phase Two case studies have been undertaken to examine to what extent the use of MCDA is suitable for local energy-planning purposes. In the two case studies, two of the most well-known MCDA methods, the Multi-Attribute Utility Theory (MAUT) and the Analytical Hierarchy Process (AHP), have been tested. Other MCDA methods, such as GP or the outranking methods, could also have been applied. However, I chose to focus on value measurement methods as AHP and MAUT, and have not tested other methods. Accordingly, my research cannot determine if value measurement methods are better suited for energy-planning purposes than GP or outranking methods are. Although all MCDA methods are constructed to help DMs explore their ‘true values’ – which theoretically should be the same regardless of the method used to elicit them – our experiments showed that different MCDA methods do not necessarily provide the same results. Some of the differences are caused by the two methods’ different ways of asking questions, as well as the DMs’ inability to express clearly their value judgements by using one or both the methods. In particular, the MAUT preference-elicitation procedure was difficult to understand and accept for DMs without previous experience with the utility concept. An additional explanation of the differences is that the external uncertainties included in the problem formulation are better accounted for in MAUT than in AHP. There are also a number of essential weaknesses in the theoretical foundation of the AHP method that may have influenced the results using that method. However, the AHP method seems to be preferred by DMs, because the method is straightforward and easier to use and understand than the relatively complex MAUT method. It was found that the post-interview process is essential for a good decision outcome. For example, the results from the preference aggregation may indicate that according to the DM’s preferences, a modification of one of the alternatives might be propitious. In such cases, it is important to realize that MCDA is an iterative process. The post-interview process also includes presentation and discussion of results with the DMs. Our experiments showed that the DMs might discover inconsistencies in the results; that the results do not reflect the DM’s actual preferences for some reason; or that the results simply do not feel right. In these cases, it is again essential to return to an earlier phase of the MCDA process and conduct a new analysis where these problems or discrepancies are taken into account. The results from an MAUT analysis are usually presented to the DMs in the form of expected total utilities given on a scale from zero to one. Expected utilities are convenient for ranking and evaluation of alternatives. However, they do not have any direct physical meaning, which quite obviously is a disadvantage from an application point of view. In order to improve the understanding of the differences between the alternatives, the Equivalent Attribute Technique (EAT) can be applied. EAT was tested in the first of the two case studies. In this case study, the cost criterion was considered important by the DMs, and the utility differences were therefore converted to equivalent cost differences. In the second case study, the preference elicitation interviews showed, quite surprisingly, that cost was not considered among the most important criteria by the DMs, and none of the other attributes were suitable to be used as the equivalent attribute. Therefore, in this case study, the use of EAT could not help the DMs interpreting the differences between the alternatives. Summarizing For MCDA to be really useful for actual local energy planning, it is necessary to find/design an MCDA method which: (1) is easy to use and has a transparent logic; (2) presents results in a way easily understandable for the DM; (3) is able to elicit and aggregate the DMs' real preferences; and (4) can handle external uncertainties in a consistent way.

La presente disertación presentan dos casos de estudio en los cuales se ha llevado a cabo una Evaluación Multi-Criterio Social (SMCE por sus siglas en inglés), además de las lecciones aprendidas a través de estas experiencias.El primer caso presenta el conflicto alrededor de la construcción de un complejo industrial (una planta reductora de aluminio y sus infraestructuras asociadas) en la Patagonia Chilena. Aquí, se analizan las ventajas de una SMCE comparada con los sistemas de Evaluación de Impacto Ambiental (EIA) comúnmente utilizados en el marco de las decisiones públicas. Se propone por tanto, la SMCE con el fin de resolver algunos de los inconvenientes ampliamente reconocidos de los EIAs.Luego, se exploran los problemas y conflictos alrededor de la construcción de parques eólicos, y se analizan los principales mecanismos para su implementación. Cabe destacar que existen diferentes niveles y dimensiones de aceptación social de tales infraestructuras: socio-política, de mercado y comunitaria. En esta disertación se sostiene que los mecanismos de mercado no son suficientes para la implementación de políticas públicas, y que la SMCE provee un marco adecuado para tratar la aceptación (o rechazo) de la comunidad local; es decir, para atender los aspectos relacionados con la justicia en términos distributivos y de proceso, y con la confianza a escala local. Finalmente, se desarrollan algunas ideas y lecciones aprendidas desde la aplicación práctica de metodologías participativas en combinación con la estructura del análisis multi-criterio, y se delinean algunas áreas para la investigación futura. / The following dissertation presents two case studies in which I have applied Social Multi-Criteria Evaluation (SMCE), and also presents some learned lessons from these experiences.The first case presents a conflict around the construction of an industrial complex (an aluminium smelter plant and its associated infrastructures) in the Chilean Patagonia. Here, I analyse the advantages of SMCE compared with the Environmental Impact Assessment systems (EIAS) commonly used in public decision-making. I propose the former in order to overcome some recognized pitfalls of the last.Then, I explore the problems and conflicts around the construction of windfarms, and I analyse the main mechanisms aimed at their implementation. There exist different levels and dimensions of social acceptance of windfarms: socio-political, market and social acceptance. I argue that market-based mechanisms are not enough for public policy implementation, and that SMCE is appropriate so as to deal with community acceptance; that is, to deal with issues related to distributional justice, procedural justice and trust at local level.Finally, I develop some ideas and learned lessons from the practical application of participatory approaches in combination with a multi-criteria analysis structure, and I delineate some areas and issues for further research.

Social Multi-Criteria Evaluation is a kind of multi-criteria analysis that combines the technical evaluation of different options according to various assessment criteria with the analysis of the social actors' conflicting values and interests.Two main ideas are at the basis of SMCE: technical incommensurability (i.e. in a complex environment one cannot express all impacts of a policy using one only unit of measurement, or, in other words, an inter/multidisciplinary analysis is needed) and social incommensurability (i.e. the social actors have different and legitimately conflicting values and interests, which must be taken into account when evaluating a policy or a project).SMCE was applied to two case-studies. In the first one, the problem at hand was how to provide some isolated rural households in a natural park near Barcelona with electricity, whether by extending the grid or installing stand-alone photovoltaic systems. The issue caused a conflict between 1995 and 2000 among the Park administration (in favour of solar energy) and the household inhabitants and owners, plus the Mayor (in favour of traditional electricity). A retrospective SMCE was performed in order to explain the positions of the involved stakeholders and the factors that help the diffusion of off-grid photovoltaic systems in rural areas.The second part of the thesis deals with the opportunity for the Italian government of supporting a large-scale biofuels production. The pros and cons of satisfying part of the energy need of the transport sector with biodiesel were analyzed through a variety of assessment criteria and taking into account different scales and dimensions.

In planning a suitable road network, planners put into consideration factors like gradients or slope of the area, available land-use and soil type, community or national landmarks and governmental interest. These different considerations and interest make the planning process complex and as such there might be confusion of interest in the decision making. The use of GIS and Multi-criteria analysis has helped planners to achieve desired and more accurate results and as such reducing the complex nature in the planning process allowing different stakeholders to reach a general conclusion. Multi-criteria analysis (MCA) prevents the imposition of limit on the form of criteria and gives opportunity to decision makers to enter their own judgments. This provides a better communication among the decision makers and the entire community and as such creating a more open choice for analysis and possible changes if necessary. The aim of this thesis is to introduce the possibility of using GIS and MCA in road path planning in Nigeria, using Lokoja, the capital of Kogi state as a case study. In actualizing the aim, satellite images of the area of study was obtained from the Landsat home page and analyzed to derive the land-use map. The land-use over the area of study was classified into five different classes using the unsupervised method of classification. A DEM over the area of study was downloaded from the website of the Consortium of Spatial information (CSI) and the DEM was used to derive the slope map over the area of study and the analytic hierarchy process (AHP) method was used in weighting the criterions according to preference. As the conclusion of the analysis, a road path between two points was obtained. The start point of the road was located on an approximate coordinate of 219002, 958986 meters and the destination point on an approximate coordinate of 320322, 878101 meters. The start and destination point were selected randomly without any pre-knowledge of the area. The thesis has succeeded in showing that it is possible to determine a road path between two points using Geographic information system (GIS) and Multi-criteria analysis in Nigeria.

This paper is part of the research programme ViSuCity, a programme with the goal of creating more sustainable urban planning through the development of better visual tools, which ultimately means better communication between various parties of public planning. The paper concerns the implementation of MCE into a 3D program for visualization. Multi criteria evaluation (MCE) is a technique that has been developed during the last 20 years. It merges GIS with AHP, forming a decision making tool for localization of, for example, new buildings.The result is an automated tool that enables advanced analysis of geographic areas.The tool has a very high potential due to the completely automated MCE and it is adapted for people without a technical background, let alone formal training in MCE. It provides great opportunities to test different scenarios, something that should be an important advantage. The incorporation of MCE into 3D models has made it easier for users to relate the maps to reality, since a detailed 3D model is very easily understood in terms of geographical placement. A brand new feature that has not previously been used is the ability to import new objects and give feedback to the analysis. A summary of research on the MCE underlines the current situation, that relatively little research exists surrounding the use and demand of MCE. This paper unfortunately contributes to this fact since no user studies have been done due to lack of time. This is something future research should focus on. / ViSuCity

Along with the rapid expansion of information technology and the urgent demand of Decision Support System, only in a few years, data warehouse have been converting absolute theory into practical technology. More and more enterprises have been plunging into the data warehouse system for supporting business process and decision. Data warehouse system does transfer big data of enterprise to useful resource or information and will not impact current history data. The data warehouse depends on enterprise various demands and plays the role of Decision Support System. It is the reason that enterprise pays attention and positive investment. This paper identifies as a set of evaluating criteria on the literature review and consults the expert to decide vendor level, design the questionnaire and retrieve weight. At last the paper uses the real case evaluating data warehouse system by ELECTRE I. The result of this study can not only contribute to the understanding of functionalities of a data warehouse system but can provide a practical guideline for selection of a data warehouse system.

Conservation science applies research in the natural and social sciences to practical problems of nature conservation, thus presupposing various goals and values. This dissertation examines normative roles for the decision sciences in biological conservation. I am primarily concerned with two philosophical problems that arise in applications of the decision sciences to biological conservation problems: commensurability of multiple values and cooperation between multiple agents. I argue that models from decision analysis should be used to construct preferences over complex tradeoffs, and game theoretical models should be used to identify situations in which multiple agents pursuing their own interests cause outcomes that are worse for everyone. While these models allow values to be made explicit for decision-making, in other situations conservationists’ goals and values are obscure. I discuss this distinct problem in the context of conservation biology, where the central concept of biodiversity is analyzed and shown to necessarily reflect the values of its users. The multiplicity of meanings of ‘biodiversity’ and measures of biological diversity raise risks for conservation biology and motivate multi-criteria approaches to conservation decision-making. Finally, the goals and values of conservation scientists and landscape managers may or may not reflect those of people who are affected by conservation policies. I argue that while decision science can aid in making values of various stakeholder groups explicit, facilitating reflection and learning, it cannot resolve ethical dilemmas on its own without input from normative and applied ethics, particularly in identifying legitimate stakeholders and weighing multiple biological concerns against concerns for rights, welfare, and social justice. / text

The use of goal programming in various real-world areas - including resource allocation, engineering, agriculture and other applications - has increased a lot in the past few years. The aim of this dissertation is to investigate goal programming approaches in determining prices. Various aspects of price determination - such as cosls, existing prices, competitors' prices, volume change due to price change and other aspects are incorporated in the model in order to suggest reasonable and realistic prices. Taking just these factors into account will not completely solve the problem, as there are usually certain goals that the decision maker would like to achieve. For example, the decision maker would probably like to attain an acceptable pre-specified minimum profit level without adjusting current prices too much whilst keeping prices competitive to insure that customers are not lost in the process of change. In this study, a goal programming model is developed for the determining of products' prices with consideration of these goals. The model makes provision for the change in demand due to the change in prices. / Mini-dissertation (M.Com. (Computer Science))--North-West University, Potchefstroom Campus, 2007.

Transformations of the various agricultural systems have been taking place in the coastal zone of Bangladesh. While some farmers continue to follow traditional practices, in recent years, others have become involved in massive shrimp cultivation, shrimp-rice cultivation, a rice-based improved agricultural system or a shrimp-rice-vegetable integrated system. All these types of agriculture are being practiced under highly vulnerable environmental conditions. The long-term livelihood, food security and adaptation of the coastal people largely depend on the sustainability of these agricultural practices. In this context, assessing the level of sustainability is extremely important and will be essential for developing future policy options in Bangladesh. This study attempts to examine the sustainability of agricultural practices in the coastal region of Bangladesh. A field study was carried out in 2011 in five villages of five upazilas in the mature and active delta areas of the country. The data were collected through in-depth questionnaire surveys, focus groups discussions, field observation, key informants and secondary materials. A comprehensive suite of indicators was developed considering productivity, efficiency, stability, durability, compatibility and equity of the coastal agriculture. The categories and the indicators were weighted using Multi-Criteria Decision Analysis (MCDA) to measure the sustainability level of five study sites. The integrated agricultural system (shrimp-rice-vegetable) of Dumuria appeared to be the most sustainable system among agricultural practices, and other integrated systems (rice-based improved agricultural system) of Kalaroa were also found to show a good level of sustainability. The massive shrimp cultivation system of Shyamnagar and Kaliganj appears to be least sustainable. A traditional agriculture system with some improved methods followed in Bhola Sadar also performed in a satisfactory manner, but there were limitations in terms of its location in the active delta. The level of the sustainability measured in this study allows for a comparison among agricultural practices of the five study sites. The information generated from the study may be used in formulating policies for this part of the country. Measuring agricultural sustainability in this way produces a useful summary of sustainability issues and also provides some vital learning experiences. A holistic and interdisciplinary approach is attempted in this study for assessing and comparing the sustainability level of coastal agricultural systems. It has the potential to become useful as one of the frameworks for sustainability assessment. / Thesis (Master, Environmental Studies) -- Queen's University, 2012-09-28 15:08:18.847