Multi-Criteria versus Data Envelopment Analysis for Assessing the Performance of Biogas Plants

This paper compares multi-criteria decision aiding (MCDA) and data envelopment analysis (DEA) approaches for assessing renewable energy plants, in order to determine their performance in terms of economic, environmental, and social criteria and indicators. The case is for a dataset of 41 agricultural biogas plants in Austria using anaerobic digestion. The results indicate that MCDA constitutes an insightful approach, to be used alternatively or in a complementary way to DEA, namely in situations requiring a meaningful expression of managerial preferences regarding the relative importance of evaluation aspects to be considered in performance assessment.Multi-criteria decision analysis; DEA; Renewable energy; Biogas

State-of-the-art on research and applications of machine learning in the building life cycle

Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of building life cycle. By conducting a literature search on the Web of Knowledge platform, we found 9579 papers in this field and selected 153 papers for an in-depth review. The number of published papers is increasing year by year, with a focus on building design, operation, and control. However, no study was found using machine learning in building commissioning. There are successful pilot studies on fault detection and diagnosis of HVAC equipment and systems, load prediction, energy baseline estimate, load shape clustering, occupancy prediction, and learning occupant behaviors and energy use patterns. None of the existing studies were adopted broadly by the building industry, due to common challenges including (1) lack of large scale labeled data to train and validate the model, (2) lack of model transferability, which limits a model trained with one data-rich building to be used in another building with limited data, (3) lack of strong justification of costs and benefits of deploying machine learning, and (4) the performance might not be reliable and robust for the stated goals, as the method might work for some buildings but could not be generalized to others. Findings from the study can inform future machine learning research to improve occupant comfort, energy efficiency, demand flexibility, and resilience of buildings, as well as to inspire young researchers in the field to explore multidisciplinary approaches that integrate building science, computing science, data science, and social science

A Methodology for the Selection of Multi-Criteria Decision Analysis Methods in Real Estate and Land Management Processes

Real estate and land management are characterised by a complex, elaborate combination of technical, regulatory and governmental factors. In Europe, Public Administrators must address the complex decision-making problems that need to be resolved, while also acting in consideration of the expectations of the different stakeholders involved in settlement transformation. In complex situations (e.g., with different aspects to be considered and multilevel actors involved), decision-making processes are often used to solve multidisciplinary and multidimensional analyses, which support the choices of those who are making the decision. Multi-Criteria Decision Analysis (MCDA) methods are included among the examination and evaluation techniques considered useful by the European Community. Such analyses and techniques are performed using methods, which aim to reach a synthesis of the various forms of input data needed to define decision-making problems of a similar complexity. Thus, one or more of the conclusions reached allow for informed, well thought-out, strategic decisions. According to the technical literature on MCDA, numerous methods are applicable in different decision-making situations, however, advice for selecting the most appropriate for the specific field of application and problem have not been thoroughly investigated. In land and real estate management, numerous queries regarding evaluations often arise. In brief, the objective of this paper is to outline a procedure with which to select the method best suited to the specific queries of evaluation, which commonly arise while addressing decision-making problems. In particular issues of land and real estate management, representing the so-called “settlement sector”. The procedure will follow a theoretical-methodological approach by formulating a taxonomy of the endogenous and exogenous variables of the multi-criteria analysis method

Economic viability of building energy efficiency measures: a review on the discount rate

How does the issue of the discount rate intersect the research on building energy efficiency and the topics into which it has branched? This contribution tries to answer the previous question through a comprehensive review of related studies. Those studies usually rely on two alternative assumptions. The first refers, explicitly or implicitly, to the notion of cost of capital and, hence, to the position of private stakeholders involved in the decision processes focusing on the adoption of energy-efficient measures in buildings. The second assumption relates to the notion of the social discount rate, which is meant to pursue intergenerational equity and environmental sustainability. As far as the results are concerned, the literature agrees that the discount rate is among the key parameters\u2014possibly the most prominent\u2014affecting the evaluation. However, despite the crucial role it plays, its calculation seldom relies on acknowledged methods and models. Furthermore, data sources sometimes lack consistency and accuracy. Some guidance and suggestions are provided as to the improvement of the discount rate estimation

Public initiatives of settlement transformation. A theoretical-methodological approach to selecting tools of multi-criteria decision analysis

In Europe, the operating context in which initiatives of settlement transformation are currently initiated is characterized by a complex, elaborate combination of technical, regulatory and governance-related factors. A similar set of considerations makes it necessary to address the complex decision-making problems to be resolved through multidisciplinary, comparative approaches designed to rationalize the process and treat the elements to be considered in systematic fashion with respect to the range of alternatives available as solutions. Within a context defined in this manner, decision-making processes must often be used to obtain multidisciplinary and multidimensional analyses to support the choices made by the decision-makers. Such analyses are carried out using multi-criteria tools designed to arrive at syntheses of the numerous forms of input data needed to describe decision-making problems of similar complexity, so that one or more outcomes of the synthesis make possible informed, well thought-out, strategic decisions. The technical literature on the topic proposes numerous tools of multi-criteria analysis for application in different decision-making contexts. Still, no specific contributions have been drawn up to date on the approach to take in selecting the tool best suited to providing adequate responses to the queries of evaluation that arise most frequently in the various fields of application, and especially in the settlement sector. The objective of this paper is to propose, by formulating a taxonomy of the endogenous and exogenous variables of tools of multi-criteria analysis, a methodology capable of selecting the tool best suited to the queries of evaluation which arise regarding the chief categories of decision-making problems, and particularly in the settlement sector

Reducing the burden of hypoglycaemia in people with diabetes through increased understanding:design of the Hypoglycaemia Redefining Solutions for Better Lives (Hypo-RESOLVE) project

Background Hypoglycaemia is the most frequent complication of treatment with insulin or insulin secretagogues in people with diabetes. Severe hypoglycaemia, i.e. an event requiring external help because of cognitive dysfunction, is associated with a higher risk of adverse cardiovascular outcomes and all‐cause mortality, but underlying mechanism(s) are poorly understood. There is also a gap in the understanding of the clinical, psychological and health economic impact of ‘non‐severe’ hypoglycaemia and the glucose level below which hypoglycaemia causes harm. Aim To increase understanding of hypoglycaemia by addressing the above issues over a 4‐year period. Methods Hypo‐RESOLVE is structured across eight work packages, each with a distinct focus. We will construct a large, sustainable database including hypoglycaemia data from >100 clinical trials to examine predictors of hypoglycaemia and establish glucose threshold(s) below which hypoglycaemia constitutes a risk for adverse biomedical and psychological outcomes, and increases healthcare costs. We will also investigate the mechanism(s) underlying the antecedents and consequences of hypoglycaemia, the significance of glucose sensor‐detected hypoglycaemia, the impact of hypoglycaemia in families, and the costs of hypoglycaemia for healthcare systems. Results The outcomes of Hypo‐RESOLVE will inform evidence‐based definitions regarding the classification of hypoglycaemia in diabetes for use in daily clinical practice, future clinical trials and as a benchmark for comparing glucose‐lowering interventions and strategies across trials. Stakeholders will be engaged to achieve broadly adopted agreement. Conclusion Hypo‐RESOLVE will advance our understanding and refine the classification of hypoglycaemia, with the ultimate aim being to alleviate the burden and consequences of hypoglycaemia in people with diabetes

Fatias de rede fim-a-fim : da extração de perfis de funções de rede a SLAs granulares

Orientador: Christian Rodolfo Esteve RothenbergTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Nos últimos dez anos, processos de softwarização de redes vêm sendo continuamente diversi- ficados e gradativamente incorporados em produção, principalmente através dos paradigmas de Redes Definidas por Software (ex.: regras de fluxos de rede programáveis) e Virtualização de Funções de Rede (ex.: orquestração de funções virtualizadas de rede). Embasado neste processo o conceito de network slice surge como forma de definição de caminhos de rede fim- a-fim programáveis, possivelmente sobre infrastruturas compartilhadas, contendo requisitos estritos de desempenho e dedicado a um modelo particular de negócios. Esta tese investiga a hipótese de que a desagregação de métricas de desempenho de funções virtualizadas de rede impactam e compõe critérios de alocação de network slices (i.e., diversas opções de utiliza- ção de recursos), os quais quando realizados devem ter seu gerenciamento de ciclo de vida implementado de forma transparente em correspondência ao seu caso de negócios de comu- nicação fim-a-fim. A verificação de tal assertiva se dá em três aspectos: entender os graus de liberdade nos quais métricas de desempenho de funções virtualizadas de rede podem ser expressas; métodos de racionalização da alocação de recursos por network slices e seus re- spectivos critérios; e formas transparentes de rastrear e gerenciar recursos de rede fim-a-fim entre múltiplos domínios administrativos. Para atingir estes objetivos, diversas contribuições são realizadas por esta tese, dentre elas: a construção de uma plataforma para automatização de metodologias de testes de desempenho de funções virtualizadas de redes; a elaboração de uma metodologia para análises de alocações de recursos de network slices baseada em um algoritmo classificador de aprendizado de máquinas e outro algoritmo de análise multi- critério; e a construção de um protótipo utilizando blockchain para a realização de contratos inteligentes envolvendo acordos de serviços entre domínios administrativos de rede. Por meio de experimentos e análises sugerimos que: métricas de desempenho de funções virtualizadas de rede dependem da alocação de recursos, configurações internas e estímulo de tráfego de testes; network slices podem ter suas alocações de recursos coerentemente classificadas por diferentes critérios; e acordos entre domínios administrativos podem ser realizados de forma transparente e em variadas formas de granularidade por meio de contratos inteligentes uti- lizando blockchain. Ao final deste trabalho, com base em uma ampla discussão as perguntas de pesquisa associadas à hipótese são respondidas, de forma que a avaliação da hipótese proposta seja realizada perante uma ampla visão das contribuições e trabalhos futuros desta teseAbstract: In the last ten years, network softwarisation processes have been continuously diversified and gradually incorporated into production, mainly through the paradigms of Software Defined Networks (e.g., programmable network flow rules) and Network Functions Virtualization (e.g., orchestration of virtualized network functions). Based on this process, the concept of network slice emerges as a way of defining end-to-end network programmable paths, possibly over shared network infrastructures, requiring strict performance metrics associated to a par- ticular business case. This thesis investigate the hypothesis that the disaggregation of network function performance metrics impacts and composes a network slice footprint incurring in di- verse slicing feature options, which when realized should have their Service Level Agreement (SLA) life cycle management transparently implemented in correspondence to their fulfilling end-to-end communication business case. The validation of such assertive takes place in three aspects: the degrees of freedom by which performance of virtualized network functions can be expressed; the methods of rationalizing the footprint of network slices; and transparent ways to track and manage network assets among multiple administrative domains. In order to achieve such goals, a series of contributions were achieved by this thesis, among them: the construction of a platform for automating methodologies for performance testing of virtual- ized network functions; an elaboration of a methodology for the analysis of footprint features of network slices based on a machine learning classifier algorithm and a multi-criteria analysis algorithm; and the construction of a prototype using blockchain to carry out smart contracts involving service level agreements between administrative systems. Through experiments and analysis we suggest that: performance metrics of virtualized network functions depend on the allocation of resources, internal configurations and test traffic stimulus; network slices can have their resource allocations consistently analyzed/classified by different criteria; and agree- ments between administrative domains can be performed transparently and in various forms of granularity through blockchain smart contracts. At the end of his thesis, through a wide discussion we answer all the research questions associated to the investigated hypothesis in such way its evaluation is performed in face of wide view of the contributions and future work of this thesisDoutoradoEngenharia de ComputaçãoDoutor em Engenharia ElétricaFUNCAM

Assessing the Domestic Energy Use and Thermal Comfort of Occupants in a Post-war Social Housing Development Estate in Famagusta, Northern Cyprus

Efforts to retrofit post-war residential buildings have gained increasing momentum recently, especially after the European Union called for a zero carbon–emission target by 2050. This study presents a novel methodological framework for determining the most effective energy policy for implementing the EPBD mandates and improving the energy efficiency of existing post-war social housing stock in the South-eastern Mediterranean climate of Cyprus. The study examines how energy policy and regulation is carried out in this area through analysis of nationally representative archetype buildings in the coastal city of Famagusta where the weather is subtropical (Csa) and partly semi-arid (Bsa). The developed empirical framework integrates the socio-technical-systems (STS) approach and provides data about households through field interviews to better understand the relations between sociodemographic characteristics, energy use and thermal comfort. The in-vivo experiences of householders’ thermal-sensation votes is assessed to predict individual aspects of adaptive thermal comfort and its relevance to overheating. Data is collected from in-situ measurements, including recordings of household indoor-air temperatures integrated with thermal-imaging surveys and heatflux measurements of building fabric elements, along with concurrent on-site monitoring of environmental conditions and a review of household energy bills to accurately determine actual energy use. The results reveal that in a non-retrofitted building, cooling and heating comprise the greatest proportion (73%) of total energy consumption. Applications for six passive cooling design strategies are then analysed, and after the life-cycle cost assessment of each is considered, off-site modular building applications are developed. After building optimisation, it is found that approximately an 81% savings related to cooling consumption can be achieved, which suggests that design, ventilation, and servicing strategies, combined with passive shading systems, can improve the energy efficiency and indoor-air quality of residential buildings