Operators for Similarity Search: Semantics, Techniques and Usage Scenarios

This book provides a comprehensive tutorial on similarity operators. The authors systematically survey the set of similarity operators, primarily focusing on their semantics, while also touching upon mechanisms for processing them effectively.

The book starts off by providing introductory material on similarity search systems, highlighting the central role of similarity operators in such systems. This is followed by a systematic categorized overview of the variety of similarity operators that have been proposed in literature over the last two decades, including advanced operators such as RkNN, Reverse k-Ranks, Skyline k-Groups and K-N-Match. Since indexing is a core technology in the practical implementation of similarity operators, various indexing mechanisms are summarized. Finally, current research challenges are outlined, so as to enable interested readers to identify potential directions for future investigations.

In summary, this book offers a comprehensive overview of the field of similarity search operators, allowing readers to understand the area of similarity operators as it stands today, and in addition providing them with the background needed to understand recent novel approaches.

Integrated techno-economic and environmental assessments of sixty scenarios for co-firing biomass with coal and natural gas

Displacement of fossil fuel-based power through biomass co-firing could reduce the greenhouse gas (GHG) emissions from fossil fuels. In this study, data-intensive techno-economic models were developed to evaluate different co-firing technologies as well as the configurations of these technologies. The models were developed to study 60 different scenarios involving various biomass feedstocks (wood chips, wheat straw, and forest residues) co-fired either with coal in a 500 MW subcritical pulverized coal (PC) plant or with natural gas in a 500 MW natural gas combined cycle (NGCC) plant to determine their technical potential and costs, as well as to determine environmental benefits. The results obtained reveal that the fully paid-off coal-fired power plant co-fired with forest residues is the most attractive option, having levelized costs of electricity (LCOE) of $53.12–$54.50/MW h and CO2 abatement costs of $27.41–$31.15/tCO2. When whole forest chips are co-fired with coal in a fully paid-off plant, the LCOE and CO2 abatement costs range from $54.68 to $56.41/MW h and $35.60 to $41.78/tCO2, respectively. The LCOE and CO2 abatement costs for straw range from $54.62 to $57.35/MW h and $35.07 to $38.48/tCO2, respectively.

Macroinvertebrate traits as biomonitoring tools in agricultural scenarios

Os ecossistemas de água doce – responsáveis por funções ambientais importantes e pelo fornecimento de bens e serviços insubstituíveis – têm vindo a ser severamente afectados por perturbações antropogénicas. A conversão de floresta em terreno agrícola afecta os sistemas aquáticos através de uma série de mecanismos: sedimentação; excesso de nutrientes; contaminação; alterações hidrológicas; e remoção de vegetação ripícola. As comunidades de macroinvertebrados de água doce – devido à sua diversidade, ubiquidade e sensibilidade às perturbações ambientais – revelam-se como particularmente adequadas para estudos de avaliação da integridade ecológica destes sistemas expostos simultaneamente a múltiplos factores de impacto. O uso sistemático de respostas biológicas para avaliação de mudanças ambientais – ou biomonitorização – pode ser levado a cabo através de diversas metodologias, que, de uma forma geral, não consideram aspectos funcionais das comunidades biológicas e têm aplicabilidade geograficamente restrita. A biomonitorização através de atributos biológicos (características que reflectem a adaptação das espécies ao seu meio ambiente) revela-se como uma ferramenta promissora na resolução dos problemas referidos, apresentando vantagens adicionais: relações causa-efeito directas; melhoria na diferenciação de impactos; e integração da variabilidade natural. O presente estudo apresenta uma revisão critica do estado-da-arte actual na área do uso de atributos biológicos em biomonitorização. Até à data de publicação, não estava disponível nenhum outro trabalho com a base conceptual do uso de atributos de macroinvertebrados enquanto descritores de comunidades e para efeitos de biomonitorização e gestão de sistemas de água doce. Descrevem-se as teorias ecológicas de suporte destas metodologias (conceitos de habitat-molde e de filtros paisagísticos) e os estudos que aplicaram estas teorias em cenários reais, tendo-se chamado a atenção para questões técnicas e possíveis soluções. As necessidades futuras nesta área englobam: o desenvolvimento de uma só ferramenta de biomonitorização de aplicação alargada; uma maior compreensão da variabilidade natural nas comunidades biológicas; diminuição dos efeitos de soluções de compromisso biológico e sindromas; realização de estudos autoecológicos adicionais; e detecção de impactos específicos em cenários de impacto complexos. Um dos objectivos deste estudo foi contribuir para a melhoria das técnicas de biomonitorização através de atributos, focalizando em comunidades de macroinvertebrados ribeirinhas em diferentes regiões biogeográficas (as bacias hidrográficas dos rios: Little e Salmon em New Brunswick, Canadá; Anllóns na Galiza, Espanha; Reventazón em Cartago, Costa Rica). Em cada região, foram estudados gradientes de uso agrícola de solo, incluindo desde bacias hidrográficas quase exclusivamente cobertas por floresta até bacias sob a influência maioritária de actividades agrícolas intensivas. Em cada gradiente de uso de solo, a caracterização da comunidade biológica (por amostragem de macroinvertebrados em troços de rápidos) foi acompanhada pela caracterização do habitat circundante (incluindo propriedades da bacia hidrográfica, análise química das águas e outras propriedades à escala local). A comunidade de macroinvertebrados foi caracterizada através de informação taxonómica, métricas estruturais, índices de diversidade, métricas de tolerância, índices bióticos e através da compilação de atributos biológicos e fisiológicos gerais, de história de vida e de resistência a perturbações. Análises estatísticas univariadas e multivariadas foram usadas para evidenciar os gradientes biológicos e físico-químicos, confirmar a sua co-variação, testar a significância da discriminação de níveis de impacto e estabelecer comparações inter-regionais. A estrutura de comunidades revelou os complexos gradientes de impacto, que por sua vez co-variaram significativamente com os gradientes de uso de solo. Os gradientes de impacto relacionaram-se sobretudo com entrada de nutrientes e sedimentação. Os gradientes biológicos definidos pelas medidas estruturais seleccionadas co-variaram com os gradientes de impacto estudados, muito embora apenas algumas variáveis estruturais tenham individualmente discriminado as categorias de uso de solo definidas a priori. Não foi detectada consistência nas respostas das medidas estruturais entre regiões biogeográficas, tendo-se confirmadado que as interpretações puramente taxonómicas de impactos são difíceis de extrapolar entre regiões. Os gradientes biológicos definidos através dos atributos seleccionados também co-variaram com os gradientes de perturbação, tendo sido possível obter uma melhor discriminação de categorias de uso de solo. Nas diferentes regiões, a discriminação de locais mais impactados foi feita com base num conjunto similar de atributos, que inclui tamanho, voltinismo, técnicas reproductivas, microhabitat, preferências de corrente e substrato, hábitos alimentares e formas de resistência. Este conjunto poderá vir a ser usado para avaliar de forma predictiva os efeitos das modificações severas de uso de solo impostas pela actividade agrícola. Quando analisadas simultaneamente através dos atributos, as comunidades das três regiões permitiram uma moderada mas significativa discriminação de níveis de impacto. Estas análises corroboram as evidências de que as mudanças nas comunidades de macroinvertebrados aquáticos em locais sob a influência de agricultura intensiva podem seguir uma trajectória convergente no espaço multidimensional, independentemente de factores geográficos. Foram fornecidas pistas para a identificação de parâmetros específicos que deverão ser tidos em conta no planeamento de novos programas de biomonitorização com comunidades de macroinvertebrados bentónicos, para aplicação numa gestão fluvial verdadeiramente ecológica, nestas e noutras regiões. Foram ainda sugeridas possíveis linhas futuras de investigação.

Adapting remote labs to learning scenarios: case studies using VISIR and RemotElectLab

Remote laboratories are an emergent technological and pedagogical tool at all education levels, and their widespread use is an important part of their own improvement and evolution. This paper describes several issues encountered on laboratorial classes, on higher education courses, when using remote laboratories based on PXI systems, either using the VISIR system or an alternate in-house solution. Three main issues are presented and explained, all reported by teachers, that gave support to students' use of remote laboratories. The first issue deals with the need to allow students to select the actual place where an ammeter is to be inserted on electric circuits, even incorrectly, therefore emulating real-world difficulties. The second one deals with problems with timing when several measurements are required at short intervals, as in the discharge cycle of a capacitor. In addition, the last issue deals with the use of a multimeter in dc mode when reading ac values, a use that collides with the lab settings. All scenarios are presented and discussed, including the solution found for each case. The conclusion derived from the described work is that the remote laboratories area is an expanding field, where practical use leads to improvement and evolution of the available solutions, requiring a strict cooperation and information-sharing between all actors, i.e., developers, teachers, and students.

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.

MASCEM Restructuring: Ontologies For Scenarios Generation in Power Systems Simulators

The electricity market restructuring, along with the increasing necessity for an adequate integration of renewable energy sources, is resulting in an rising complexity in power systems operation. Various power system simulators have been introduced in recent years with the purpose of helping operators, regulators, and involved players to understand and deal with this complex environment. This paper focuses on the development of an upper ontology which integrates the essential concepts necessary to interpret all the available information. The restructuring of MASCEM (Multi-Agent System for Competitive Electricity Markets), and this system’s integration with MASGriP (Multi-Agent Smart Grid Platform), and ALBidS (Adaptive Learning Strategic Bidding System) provide the means for the exemplification of the usefulness of this ontology. A practical example is presented, showing how common simulation scenarios for different simulators, directed to very distinct environments, can be created departing from the proposed ontology.

Load Profiling Tool to Support Smart Grid Operation Scenarios

This paper presents the characterization of high voltage (HV) electric power consumers based on a data clustering approach. The typical load profiles (TLP) are obtained selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The choice of the best partition is supported using several cluster validity indices. The proposed data-mining (DM) based methodology, that includes all steps presented in the process of knowledge discovery in databases (KDD), presents an automatic data treatment application in order to preprocess the initial database in an automatic way, allowing time saving and better accuracy during this phase. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ consumption behavior. To validate our approach, a case study with a real database of 185 HV consumers was used.

Realistic Traffic Scenarios Using a Census Methodology: Vila Real Case Study

This paper presents the first phase of the redevelopment of the Electric Vehicle Scenario Simulator (EVeSSi) tool. A new methodology to generate traffic demand scenarios for the Simulation of Urban MObility (SUMO) tool for urban traffic simulation is described. This methodology is based on a Portugal census database to generate a synthetic population for a given area under study. A realistic case study of a Portuguese city, Vila Real, is assessed. For this area the road network was created along with a synthetic population and public transport. The traffic results were obtained and an electric buses fleet was evaluated assuming that the actual fleet would be replaced in a near future. The energy requirements to charge the electric fleet overnight were estimated in order to evaluate the impacts that it would cause in the local electricity network.

Data Mining Approach to support the Generation of Realistic Scenarios for Multi-Agent simulation of Electricity Markets

This paper presents the Realistic Scenarios Generator (RealScen), a tool that processes data from real electricity markets to generate realistic scenarios that enable the modeling of electricity market players’ characteristics and strategic behavior. The proposed tool provides significant advantages to the decision making process in an electricity market environment, especially when coupled with a multi-agent electricity markets simulator. The generation of realistic scenarios is performed using mechanisms for intelligent data analysis, which are based on artificial intelligence and data mining algorithms. These techniques allow the study of realistic scenarios, adapted to the existing markets, and improve the representation of market entities as software agents, enabling a detailed modeling of their profiles and strategies. This work contributes significantly to the understanding of the interactions between the entities acting in electricity markets by increasing the capability and realism of market simulations.

A study of ethical decision-making in hypothetical scenarios by secondary school principals /

The purpose of the study,was to investigate the ways in which secondary school principals make decisions that have an ethical dimension, and the reasons they use to justify their choices. The ethical principles and concepts, as well as the scenarios, were adapted from The Ethics ofSchool Administration by Strike, Haller, and Soltis (1998). In this study, 32 secondary principals from a school board in Ontario were asked to complete a descriptive survey which was designed to have principals make administrative decisions in response to 5 hypothetical scenarios. The open-ended questions were expected to elicit responses that were reflective of the principals' actual decision-making strategies. The survey also required them to justify and explain their reasons for each decision. The data were analyzed and 4 major categories ofjustifications emerged: pedagogy, legalism, moral code, and democracy. The results indicate that the decisions made by principals are grounded in various perspectives. While the data did not indicate any explicit knowledge of ethical principles and concepts, the principals' responses suggest sound and valid reasoning for their decision making, addressing the principles and concepts from a variety of viewpoints and using diverse justifications.