On the role of pre and post-processing in environmental data mining

The quality of discovered knowledge is highly depending on data quality. Unfortunately real data use to contain noise, uncertainty, errors, redundancies or even irrelevant information. The more complex is the reality to be analyzed, the higher the risk of getting low quality data. Knowledge Discovery from Databases (KDD) offers a global framework to prepare data in the right form to perform correct analyses. On the other hand, the quality of decisions taken upon KDD results, depend not only on the quality of the results themselves, but on the capacity of the system to communicate those results in an understandable form. Environmental systems are particularly complex and environmental users particularly require clarity in their results. In this paper some details about how this can be achieved are provided. The role of the pre and post processing in the whole process of Knowledge Discovery in environmental systems is discussed

Development of a Conceptual, Mathematical and Model of System Dynamics for Landfill Water Treatment

Leachate is a major problem in landfills due to the type and amount of pollutants. In Croatia, the usual way of handling leachate is recirculation back to the landfill body. However, this method poses a danger of their leakage into the environment, especially during periods of increased precipitation. Leachate is heavily polluted with organic matter, and its spillage into the environment can cause environmental incident. This paper presents a model for efficient treatment of landfill water contaminated with organic matter, based on the operating parameters of the actual water treatment system. The aim of this scientific research is to develop a model for landfill water treatment and to design a methodology suitable for significant patterns of organic matter pollution behaviour. The developed conceptual model is a computer-based model that uses randomly selected values from the theoretical probability distribution of the applied variables. The mathematical model is based on a system of differential equations solved by the Runge-Kutta method. To validate the model, a nonparametric test was applied, given that the distributions are asymmetric non-Gaussian distributions. The methodology proposed in this paper is based on simulation modelling as a useful method in environmental protection. The developed and validated model has proven that landfill water can be effectively and economically purified. Simulation modelling and environmental informatics can effectively contribute to solving environmental problems on the computer without unnecessary risk to the environment

Mapping the global free expression landscape using machine learning

Freedom of expression is a core human right, yet the forces that seek to suppress it have intensified, increasing the need to develop tools that can measure the rates of freedom globally. In this study, we propose a novel freedom of expression index to gain a nuanced and data-led understanding of the level of censorship across the globe. For this, we used an unsupervised, probabilistic machine learning method, to model the status of the free expression landscape. This index seeks to provide legislators and other policymakers, activists and governments, and non-governmental and intergovernmental organisations, with tools to better inform policy or action decisions. The global nature of the proposed index also means it can become a vital resource/tool for engagement with international and supranational bodies

Influencing factors in energy use of housing blocks: a new methodology, based on clustering and energy simulations, for decision making in energy refurbishment projects

In recent years, big efforts have been dedicated to identify which are the factors with highest influence in the energy consumption of residential buildings. These factors include aspects such as weather dependence, user behaviour, socio-economic situation, type of the energy installations and typology of buildings. The high number of factors increases the complexity of analysis and leads to a lack of confidence in the results of the energy simulation analysis. This fact grows when we move one step up and perform global analysis of blocks of buildings. The aim of this study is to report a new methodology for the assessment of the energy performance of large groups of buildings when considering the real use of energy. We combine two clustering methods, Generative Topographic Mapping and k-means, to obtain reference dwellings that can be considered as representative of the different energy patterns and energy systems of the neighbourhood. Then, simulation of energy demand and indoor temperature against the monitored comfort conditions in a short period is performed to obtain end use load disaggregation. This methodology was applied in a district at Terrassa City (Spain), and six reference dwellings were selected. Results showed that the method was able to identify the main patterns and provide occupants with feasible recommendations so that they can make required decisions at neighbourhood level. Moreover, given that the proposed method is based on the comparison with similar buildings, it could motivate building occupants to implement community improvement actions, as well as to modify their behaviour.Peer ReviewedPostprint (author's final draft

Influencing factors in energy use of housing blocks: a new methodology, based on clustering and energy simulations, for decision making in energy refurbishment projects

In recent years, big efforts have been dedicated to identify which are the factors with highest influence in the energy consumption of residential buildings. These factors include aspects such as weather dependence, user behaviour, socio-economic situation, type of the energy installations and typology of buildings. The high number of factors increases the complexity of analysis and leads to a lack of confidence in the results of the energy simulation analysis. This fact grows when we move one step up and perform global analysis of blocks of buildings. The aim of this study is to report a new methodology for the assessment of the energy performance of large groups of buildings when considering the real use of energy. We combine two clustering methods, Generative Topographic Mapping and k-means, to obtain reference dwellings that can be considered as representative of the different energy patterns and energy systems of the neighbourhood. Then, simulation of energy demand and indoor temperature against the monitored comfort conditions in a short period is performed to obtain end use load disaggregation. This methodology was applied in a district at Terrassa City (Spain), and six reference dwellings were selected. Results showed that the method was able to identify the main patterns and provide occupants with feasible recommendations so that they can make required decisions at neighbourhood level. Moreover, given that the proposed method is based on the comparison with similar buildings, it could motivate building occupants to implement community improvement actions, as well as to modify their behaviour

Exploring the ecological status of human altered streams through Generative Topographic Mapping

13 Páginas ; 10 Figuras ; 4 TablasThe STREAMES (STream REAch Management, an Expert System) European project is an international enterprise for the development of a knowledge-based environmental decision support system to assist water managers with their decision making tasks. It involves the evaluation of the effect of substantial nutrient loads on the overall water quality and ecological status of stream ecosystems. Empirical data for the knowledge base come from several streams located throughout Europe and Israel, with emphasis on streams from the Mediterranean region. These data comprise several types of variables, including physical, chemical and biological parameters. The complexity of the data limits the amount and completeness of the available information. This study explores how similar the selected streams are on the basis of the ecological descriptors measured. The analysis of these similarities helps us to ascertain whether the same model of ecological status might hold over the variety of streams under consideration. The available data are explored and analysed through reconstruction, visualization and clustering using the Generative Topographic Mapping (GTM), a neural network-based model. Amongst the many advantages of the probabilistic setting of GTM, one is especially relevant to the problem at hand: its ability to handle and reconstruct missing data in a principled way.The authors would like to acknowledge the support of the European Union through the EVK1-CT-2000-00081 STREAMES project and the partial support of the Spanish CICyT project DPI2002-03225. This study was made possible by the collaborative effort of the STREAMES partners in creating a unified data set. Alfredo Vellido and Eugenia Martí are research fellows within the Ramón y Cajal program of the Spanish Ministry of Education and Science.Peer reviewe

Exploring the ecological status of human altered streams through Generative Topographic Mapping

13 Páginas ; 10 Figuras ; 4 TablasThe STREAMES (STream REAch Management, an Expert System) European project is an international enterprise for the development of a knowledge-based environmental decision support system to assist water managers with their decision making tasks. It involves the evaluation of the effect of substantial nutrient loads on the overall water quality and ecological status of stream ecosystems. Empirical data for the knowledge base come from several streams located throughout Europe and Israel, with emphasis on streams from the Mediterranean region. These data comprise several types of variables, including physical, chemical and biological parameters. The complexity of the data limits the amount and completeness of the available information. This study explores how similar the selected streams are on the basis of the ecological descriptors measured. The analysis of these similarities helps us to ascertain whether the same model of ecological status might hold over the variety of streams under consideration. The available data are explored and analysed through reconstruction, visualization and clustering using the Generative Topographic Mapping (GTM), a neural network-based model. Amongst the many advantages of the probabilistic setting of GTM, one is especially relevant to the problem at hand: its ability to handle and reconstruct missing data in a principled way.The authors would like to acknowledge the support of the European Union through the EVK1-CT-2000-00081 STREAMES project and the partial support of the Spanish CICyT project DPI2002-03225. This study was made possible by the collaborative effort of the STREAMES partners in creating a unified data set. Alfredo Vellido and Eugenia Martí are research fellows within the Ramón y Cajal program of the Spanish Ministry of Education and Science.Peer reviewe

Developing complex engineering water purifying systems

U radu je prikazan razvoj modela složenih, inženjerskih sustava u zaštiti okoliša, na način da su izgrađeni modeli dva stvarna, složena, inženjerska sustava za pročišćavanje vode (otpadne vode Grada Čakovca te površinske vode rijeke Drave u Gradu Belišću). Pomoću ova dva modela razvijen je adaptivni model sustava pročišćavanja vode koja po kvaliteti odgovara otpadnoj komunalnoj vodi, a pročišćuje se u vodu koja po kvaliteti odgovara vodi za ljudsku potrošnju. Predviđena su mjesta potpunog zastoja sustava koji može izazvati materijalne štete, štete u okolišu te utjecati na zdravlje ljudi.This paper presents the development of complex engineering system models in the environmental protection field of study. For this purpose, the two models of genuine complex engineering systems have been created. Explicitly, these are two water purification systems whereas in one, the municipal waste water from Cakovec has been used and in the other, surface water from the Drava river in Belisce.The two models enabled the development of the adaptive water purification system model, which improves the quality of municipal wastewater and makes it suitable for public consumption. Additionally, the total adaptive system deadlocks, which may cause material or environmental damage and even affect human health, have been predicted

Developing complex engineering water purifying systems

U radu je prikazan razvoj modela složenih, inženjerskih sustava u zaštiti okoliša, na način da su izgrađeni modeli dva stvarna, složena, inženjerska sustava za pročišćavanje vode (otpadne vode Grada Čakovca te površinske vode rijeke Drave u Gradu Belišću). Pomoću ova dva modela razvijen je adaptivni model sustava pročišćavanja vode koja po kvaliteti odgovara otpadnoj komunalnoj vodi, a pročišćuje se u vodu koja po kvaliteti odgovara vodi za ljudsku potrošnju. Predviđena su mjesta potpunog zastoja sustava koji može izazvati materijalne štete, štete u okolišu te utjecati na zdravlje ljudi.This paper presents the development of complex engineering system models in the environmental protection field of study. For this purpose, the two models of genuine complex engineering systems have been created. Explicitly, these are two water purification systems whereas in one, the municipal waste water from Cakovec has been used and in the other, surface water from the Drava river in Belisce.The two models enabled the development of the adaptive water purification system model, which improves the quality of municipal wastewater and makes it suitable for public consumption. Additionally, the total adaptive system deadlocks, which may cause material or environmental damage and even affect human health, have been predicted

Decisions on urban water systems: some support

“Water is a scarce resource and its management has to be as effective as possible”. Most of us would certainly agree with this fine sounding phrase. But developing it and putting it into practice is not easy. Firstly, because we are already having problems identifying the meaning or interpretation we give to some words. For example, water as a resource. Water is not just a natural resource, it is the basis of the industrial sector, a generator of cultural heritage and a linchpin of society. And we sometimes use the term scarce when referring to a problem of distribution or overexploitation. In any case, this means that water management is very complex. This is because there are different agents involved and all of them have different interests; these interests are often contradictory and can lead to conflict. Everyone understands the concept of efficient management differently. Efficient: why and for whom? At the same time, we have to make decisions. Decisions that involve a way of managing the resource. For example, authorising (or not) a withdrawal from a water course, building (and how) a treatment plant or defining (what and in which range) the quality parameters guaranteeing its drinkability... These examples, and many more that we could cite, are some of the aspects on which a group of people are responsible for acting, deciding and getting the decisions implemented. The hypothesis presented in this book is that to achieve this efficient management there are no simple formulas or universal solutions. However, this does not mean that all solutions are equally correct. Experience shows us that some are better than others.Postprint (published version