Evaluation of mechanical soft-abrasive blasting and chemical cleaning methods on alkyd-paint graffiti made on carbonate stones

In the context of this dissertation several studies were developed resulting in submission and publication “Evaluation of mechanical soft-abrasive blasting and chemical cleaning methods on alkyd-paint graffiti made on calcareous stones” to Journal of Cultural Heritage. (http://dx.doi.org/10.101 /j.culher.2014.10.004)

Toxicity measurement techniques for building materials with wastes

The innovative Horizon 2020 program sponsored by the European Union (EU) aims to promote and develop processes of waste integration in construction materials. However, several potential health hazards caused by building materials have been identified and, there-fore, there is an ongoing need to develop new recycling methods for hazardous wastes and effi-cient barriers in order to prevent toxic releases from the new construction solutions with wastes. This paper presents an overview that focus on two main aspects: the identification of the health risks related to radioactivity and heavy metals present in building materials and identification of these toxic substances in new construction solutions that contain recycled wastes. Different waste materials were selected and distinct methodologies of toxicity evaluation are presented to analyse the potential hazardous, the feasibility of using those wastes and the achievement of op-timal construction solutions involving wastes.

Ancient materials and techniques to improve the earthen building durability

A substantial part of the world building heritage has been performed by earthen building. The durability of this existing heritage and mainly of the new buildings built with earth is particularly conditioned by the erosion caused by water action, especially in countries with high levels of rainfall. This research aims to contribute to the increase of knowledge about the ancient building techniques that provide enhanced durability. It is possible to analyse the ancestral practices used to protect the earth material from the water action in order to understand how the old earthen buildings were preserved over the centuries, resisting to harsh weather conditions. Among these techniques are: the incorporation of biopolymers (such as oils or fats from animal or vegetable origin); the addition of some minerals; and the earth stabilization with lime. However, this knowledge seems to be forgotten, probably due to the prejudice related to earthen constructions, which several times are associated with a poor building. This research also focuses on the study of new methods of earth stabilization with lime and biopolymers, adapting the ancient knowledge to improve the durability related to the water action. Therefore, alternative solutions can be obtained to improve the performance of earthen buildings, mainly the resistance of the material in the presence of water, reducing its permeability to water. In addition, with the proposed solutions it is possible to obtain good levels of water vapour permeability, one of the major advantages of the construction with earth.

The mineralogy and chemistry of the German and Portuguese tiles used to face a historic building in the Amazon region and their natural susceptibility to tropical weathering

During the 19th century, the most prominent buildings of the city of Belém were faced entirely with tiles manufactured in Portugal and Germany, which now exhibit distinct degrees of degradation. The Pinho mansion is one of the most important of these buildings and was selected for the investigation of the action of the tropical Amazonian climate on the degradation of the tiles. To achieve this objective, the tiles were mapped for organic and inorganic degradation, and samples were collected for analysis. The minerals were determined by XRD, the chemical composition by classical wet methods and SEM/EDS, and the microorganisms under the microscope. The results show that the German and Portuguese tiles are quite different in their composition. While both ceramic bodies are composed of SiO2 and Al2O3, CaO was found only in the Portuguese tile. The low Na2O and K2O contents indicate the addition of materials to reduce the fusion temperature. SiO2 and PbO are the main constituents of the glaze, with CoO and FeO being added as pigment. The ceramic body of the German tiles is constituted of quartz, mullite, and cristobalite, in contrast with the Portuguese tiles, which are made of quartz, gehlenite, diopside, calcite, and feldspars. The glazes are XRD-amorphous. The chemical and mineralogical differences between the German and Portuguese tiles indicate that they were produced from different raw materials under distinct thermal processes. The most prominent weathering-related modifications are the thin layers (German tiles), oxidation stains, dark stains, the detachment of the tile (Portuguese tiles), loss of the glaze and powdering of the ceramic body (Portuguese tiles) through the establishment of Cyanophyta and Bacillariophyta.. The distinct degradation patterns of the tiles exposed to the tropical Amazon climate are a consequence of their distinct mineralogy and chemistry.

A integração do Building Information Modeling (BIM) num projeto de reabilitação

Dissertação de mestrado integrado em Engenharia Civil

Forensic intelligence framework. Part II: study of the main generic building blocks and challenges through the examples of illicit drugs and false identity documents monitoring

The development of forensic intelligence relies on the expression of suitable models that better represent the contribution of forensic intelligence in relation to the criminal justice system, policing and security. Such models assist in comparing and evaluating methods and new technologies, provide transparency and foster the development of new applications. Interestingly, strong similarities between two separate projects focusing on specific forensic science areas were recently observed. These observations have led to the induction of a general model (Part I) that could guide the use of any forensic science case data in an intelligence perspective. The present article builds upon this general approach by focusing on decisional and organisational issues. The article investigates the comparison process and evaluation system that lay at the heart of the forensic intelligence framework, advocating scientific decision criteria and a structured but flexible and dynamic architecture. These building blocks are crucial and clearly lay within the expertise of forensic scientists. However, it is only part of the problem. Forensic intelligence includes other blocks with their respective interactions, decision points and tensions (e.g. regarding how to guide detection and how to integrate forensic information with other information). Formalising these blocks identifies many questions and potential answers. Addressing these questions is essential for the progress of the discipline. Such a process requires clarifying the role and place of the forensic scientist within the whole process and their relationship to other stakeholders.

Advanced Kernel Methods For Remote Sensing Image Classification

Résumé Suite aux recentes avancées technologiques, les archives d'images digitales ont connu une croissance qualitative et quantitative sans précédent. Malgré les énormes possibilités qu'elles offrent, ces avancées posent de nouvelles questions quant au traitement des masses de données saisies. Cette question est à la base de cette Thèse: les problèmes de traitement d'information digitale à très haute résolution spatiale et/ou spectrale y sont considérés en recourant à des approches d'apprentissage statistique, les méthodes à noyau. Cette Thèse étudie des problèmes de classification d'images, c'est à dire de catégorisation de pixels en un nombre réduit de classes refletant les propriétés spectrales et contextuelles des objets qu'elles représentent. L'accent est mis sur l'efficience des algorithmes, ainsi que sur leur simplicité, de manière à augmenter leur potentiel d'implementation pour les utilisateurs. De plus, le défi de cette Thèse est de rester proche des problèmes concrets des utilisateurs d'images satellite sans pour autant perdre de vue l'intéret des méthodes proposées pour le milieu du machine learning dont elles sont issues. En ce sens, ce travail joue la carte de la transdisciplinarité en maintenant un lien fort entre les deux sciences dans tous les développements proposés. Quatre modèles sont proposés: le premier répond au problème de la haute dimensionalité et de la redondance des données par un modèle optimisant les performances en classification en s'adaptant aux particularités de l'image. Ceci est rendu possible par un système de ranking des variables (les bandes) qui est optimisé en même temps que le modèle de base: ce faisant, seules les variables importantes pour résoudre le problème sont utilisées par le classifieur. Le manque d'information étiquétée et l'incertitude quant à sa pertinence pour le problème sont à la source des deux modèles suivants, basés respectivement sur l'apprentissage actif et les méthodes semi-supervisées: le premier permet d'améliorer la qualité d'un ensemble d'entraînement par interaction directe entre l'utilisateur et la machine, alors que le deuxième utilise les pixels non étiquetés pour améliorer la description des données disponibles et la robustesse du modèle. Enfin, le dernier modèle proposé considère la question plus théorique de la structure entre les outputs: l'intègration de cette source d'information, jusqu'à présent jamais considérée en télédétection, ouvre des nouveaux défis de recherche. Advanced kernel methods for remote sensing image classification Devis Tuia Institut de Géomatique et d'Analyse du Risque September 2009 Abstract The technical developments in recent years have brought the quantity and quality of digital information to an unprecedented level, as enormous archives of satellite images are available to the users. However, even if these advances open more and more possibilities in the use of digital imagery, they also rise several problems of storage and treatment. The latter is considered in this Thesis: the processing of very high spatial and spectral resolution images is treated with approaches based on data-driven algorithms relying on kernel methods. In particular, the problem of image classification, i.e. the categorization of the image's pixels into a reduced number of classes reflecting spectral and contextual properties, is studied through the different models presented. The accent is put on algorithmic efficiency and the simplicity of the approaches proposed, to avoid too complex models that would not be used by users. The major challenge of the Thesis is to remain close to concrete remote sensing problems, without losing the methodological interest from the machine learning viewpoint: in this sense, this work aims at building a bridge between the machine learning and remote sensing communities and all the models proposed have been developed keeping in mind the need for such a synergy. Four models are proposed: first, an adaptive model learning the relevant image features has been proposed to solve the problem of high dimensionality and collinearity of the image features. This model provides automatically an accurate classifier and a ranking of the relevance of the single features. The scarcity and unreliability of labeled. information were the common root of the second and third models proposed: when confronted to such problems, the user can either construct the labeled set iteratively by direct interaction with the machine or use the unlabeled data to increase robustness and quality of the description of data. Both solutions have been explored resulting into two methodological contributions, based respectively on active learning and semisupervised learning. Finally, the more theoretical issue of structured outputs has been considered in the last model, which, by integrating outputs similarity into a model, opens new challenges and opportunities for remote sensing image processing.

Les méthodes d'études de cas en psychothérapie: perspectives actuelles [Methods of psychotherapy case studies: current perspectives].

There is a renewal of interest among psychotherapy researchers and psychotherapists towards psychotherapy case studies. This article presents two paradigms that have greatly influenced this increasing interest in psychotherapy case studies : the pragmatic case study and the theory-building case study paradigm. The origins, developments and key-concepts of both paradigms are presented, as well as their methodological and ethical specificities. Examples of case studies, along with models developed, are cited. The differential influence of the post-modern schools on both paradigms are presented, as well as their contribution to the field of methods of psychotherapy case studies discussed and assessed in terms of relevance for the researcher and the psychotherapist.

Implementing statistical learning methods through Bayesian networks. Part 1: a guide to Bayesian parameter estimation using forensic science data

As a thorough aggregation of probability and graph theory, Bayesian networks currently enjoy widespread interest as a means for studying factors that affect the coherent evaluation of scientific evidence in forensic science. Paper I of this series of papers intends to contribute to the discussion of Bayesian networks as a framework that is helpful for both illustrating and implementing statistical procedures that are commonly employed for the study of uncertainties (e.g. the estimation of unknown quantities). While the respective statistical procedures are widely described in literature, the primary aim of this paper is to offer an essentially non-technical introduction on how interested readers may use these analytical approaches - with the help of Bayesian networks - for processing their own forensic science data. Attention is mainly drawn to the structure and underlying rationale of a series of basic and context-independent network fragments that users may incorporate as building blocs while constructing larger inference models. As an example of how this may be done, the proposed concepts will be used in a second paper (Part II) for specifying graphical probability networks whose purpose is to assist forensic scientists in the evaluation of scientific evidence encountered in the context of forensic document examination (i.e. results of the analysis of black toners present on printed or copied documents).

The 2005 Pakistan earthquake revisited: Methods for integrated landslide assessment

Five years after the 2005 Pakistan earthquake that triggered multiple mass movements, landslides continue to pose a threat to the population of Azad Kashmir, especially during heavy monsoon rains. The thousands of landslides that were triggered by the 7.6 magnitude earthquake in 2005 were not just due to a natural phenomenon but largely induced by human activities, namely, road building, grazing, and deforestation. The damage caused by the landslides in the study area (381 km2) is estimated at 3.6 times the annual public works budget of Azad Kashmir for 2005 of US$ 1 million. In addition to human suffering, this cost constitutes a significant economic setback to the region that could have been reduced through improved land use and risk management. This article describes interdisciplinary research conducted 18 months after the earthquake to provide a more systemic approach to understanding risks posed by landslides, including the physical, environmental, and human contexts. The goal of this research is twofold: to present empirical data on the social, geological, and environmental contexts in which widespread landslides occurred following the 2005 earthquake; and, second, to describe straightforward methods that can be used for integrated landslide risk assessments in data-poor environments. The article analyzes limitations of the methodologies and challenges for conducting interdisciplinary research that integrates both social and physical data. This research concludes that reducing landslide risk is ultimately a management issue, based in land use decisions and governance.

Building the niche through time: using 13,000 years of data to predict the effects of climate change on three tree species in Europe

Aim Species distribution models (SDMs) based on current species ranges underestimate the potential distribution when projected in time and/or space. A multi-temporal model calibration approach has been suggested as an alternative, and we evaluate this using 13,000 years of data. Location Europe. Methods We used fossil-based records of presence for Picea abies, Abies alba and Fagus sylvatica and six climatic variables for the period 13,000 to 1000yr bp. To measure the contribution of each 1000-year time step to the total niche of each species (the niche measured by pooling all the data), we employed a principal components analysis (PCA) calibrated with data over the entire range of possible climates. Then we projected both the total niche and the partial niches from single time frames into the PCA space, and tested if the partial niches were more similar to the total niche than random. Using an ensemble forecasting approach, we calibrated SDMs for each time frame and for the pooled database. We projected each model to current climate and evaluated the results against current pollen data. We also projected all models into the future. Results Niche similarity between the partial and the total-SDMs was almost always statistically significant and increased through time. SDMs calibrated from single time frames gave different results when projected to current climate, providing evidence of a change in the species realized niches through time. Moreover, they predicted limited climate suitability when compared with the total-SDMs. The same results were obtained when projected to future climates. Main conclusions The realized climatic niche of species differed for current and future climates when SDMs were calibrated considering different past climates. Building the niche as an ensemble through time represents a way forward to a better understanding of a species' range and its ecology in a changing climate.

Capturing Weak Signals for Foresight Building

Tulevaisuuden hahmottamisen merkitys heikkojen signaalien avulla on korostunut viime vuosien aikana merkittävästi,koska yrityksen liiketoimintaympäristössä tapahtuvia muutoksia on ollut yhä vaikeampaa ennustaa historian perusteella. Liiketoimintaympäristössä monien muutoksien merkkejä on ollut nähtävissä, mutta niitä on ollut vaikea havaita. Heikkoja signaaleja tunnistamalla ja keräämällä sekä reagoimalla tilanteeseen riittävän ajoissa, on mahdollista saavuttaa ylivoimaista kilpailuetua. Kirjallisuustutkimus keskittyy heikkojen signaalien tunnistamisen haasteisiin liiketoimintaympäristöstä, signaalien ja informaation kehittymiseen sekä informaation hallintaan organisaatiossa. Kiinnostus näihin perustuu tarpeeseen määritellä heikkojen signaalien tunnistamiseen vaadittava prosessi, jonka avulla heikot signaalit voidaan huomioida M-real Oyj:n päätöksenteossa. Kirjallisuustutkimus osoittaa selvästi sen, että heikkoja signaaleita on olemassa ja niitä pystytään tunnistamaan liiketoimintaympäristöstä. Signaaleja voidaan rikastuttaa yrityksessä olevalla tietämyksellä ja hyödyntää edelleen päätöksenteossa. Vertailtaessa sekä kirjallisuustutkimusta että empiiristä tutkimusta tuli ilmi selkeästi tiedon moninaisuus; määrä,laatu ja tiedonsaannin oikea-aikaisuus päätöksenteossa. Tutkimuksen aikana kehittyi prosessimalli tiedon suodattamiselle, luokittelulle ja heikkojen signaalien tunnistamiselle. Työn edetessä prosessimalli kehittyi osaksi tässä työssä kehitettyä kokonaisuutta 'Weak Signal Capturing' -työkalua. Monistamalla työkalua voidaan kerätä heikkoja signaaleja eri M-realin liiketoiminnan osa-alueilta. Tietoja systemaattisesti kokoamalla voidaan kartoittaa tulevaisuutta koko M-realille.

Building Strong Brands with Sponsorship: Case Battery Energy Drink

Tutkimuksen päätavoitteena oli ymmärtää vahvojen brändien ja brändipääoman rakentamisprosessia, painottaen erityisesti sponsoroinnin roolia tässä prosessissa. Tutkimus suoritettiin laadullisena tutkimuksena, jossa käytettiintapaustutkimusmenetelmää. Tutkimuksen aineisto kerättiin suurimmista online artikkelitietokannoista sekä kolmesta henkilökohtaisesta haastattelusta case-yrityksen edustajien kanssa. Tutkimuksen teoreettisen perustan muodosti brändipääoma-käsite ja sen osa-alueet, näiden liittyminen vahvoihin brändeihin ja brändien rakentamiseen, sekä sponsoroinnin strateginen käyttö brändien rakentamisessa. Lisäksi tutkimuksen empiirinen perusta arvio ja testasi näitä oletuksia ja aikaisemmin käsiteltyjä teorioita case-brändi Battery energiajuoman valossa. Tutkimus osoitti, että nykypäivänä kovan kilpailun markkinointiympäristössä, sponsorointi edustaa vaihtoehtoista tapaa rakentaa vahvoja, omalaatuisia ja suotuisia brändejä, joilla on korkea brändipääoma. Sponsoroinnista on tullut yhä tärkeämpi kommunikointiväline brändien rakentamisessa ja erityisesti siellä missä perinteiset menetelmät ovat muuttumassa tehottomiksi. Empiirisessä osassa selvisi, että sponsorointia on käytetty menestyksekkäästi strategisena keinona vahvan ja omalaatuisen Battery brändin ja sen korkean brändipääoman rakentamisessa.

Establishing intercompany relationships: Motives and methods for successful collaborative engagement

This study explores the early phases of intercompany relationship building, which is a very important topic for purchasing and business development practitioners as well as for companies' upper management. There is a lot ofevidence that a proper engagement with markets increases a company's potential for achieving business success. Taking full advantage of the market possibilities requires, however, a holistic view of managing related decision-making chain. Most literature as well as the business processes of companies are lacking this holism. Typically they observe the process from the perspective of individual stages and thus lead to discontinuity and sub-optimization. This study contains a comprehensive introduction to and evaluation of literature related to various steps of the decision-making process. It is studied from a holistic perspective ofdetermining a company's vertical integration position within its demand/ supplynetwork context; translating the vertical integration objectives to feasible strategies and objectives; and operationalizing the decisions made through engagement with collaborative intercompany relationships. The empirical part of the research has been conducted in two sections. First the phenomenon of intercompany engagement is studied using two complementary case studies. Secondly a survey hasbeen conducted among the purchasing and business development managers of several electronics manufacturing companies, to analyze the processes, decision-makingcriteria and success factors of engagement for collaboration. The aim has been to identify the reasons why companies and their management act the way they do. As a combination of theoretical and empirical research an analysis has been produced of what would be an ideal way of engaging with markets. Based on the respective findings the study concludes by proposing a holistic framework for successful engagement. The evidence presented throughout the study demonstrates clear gaps, discontinuities and limitations in both current research and in practical purchasing decision-making chains. The most significant discontinuity is the identified disconnection between the supplier selection process and related criteria and the relationship success factors.

Global virtual teamwork. Building and communicating trust through technology

Tutkimuksen ensisijaisena tavoitteena oli tarkastella luottamuksen rakentumista virtuaalitiimissä. Keskeistä tarkastelussa olivat luottamuksen lähteiden löytäminen, suhteen rakentuminen sekä teknologiavälitteinen kommunikaatio. Myös käytännön keinoja ja sovelluksia etsittiin. Tässä tutkimuksessa luottamus nähtiin tärkeänä yhteistyön mahdollistajana sekä keskeisenä elementtinä ihmisten välisten suhteiden rakentumisessa. Tämä tutkimus oli empiirinen ja kuvaileva tapaustutkimus. Tutkimuksessa kvalitatiivista aineistoa kerättiin pääasiassa web-pohjaisen kyselyn sekä puhelinhaastattelun avulla. Aineistonkeruu toteutettiin siis pääasiassa virtuaalisesti. Saatu aineisto analysoitiin teemoittelun avulla. Tässä työssä teemoja etsittiin tekstistä pääasiassa teoriasta johdettujen oletusten perusteella. Tutkimuksen tuloksena oli, että luottamusta rakentavia mekanismeja ovat, karkeasti luokiteltuna, yhteiset päämäärät ja vastuut, kommunikaatio, sosiaalinen kanssakäyminen ja informaation jakaminen, toisten huomioiminen ja henkilökohtaiset ominaisuudet. Mekanismit eivät suuresti eronneet luottamuksen rakentumisen mekanismeista perinteisessä kontekstissa. Virtuaalitiimityön alkuvaiheessa luottamus pohjautui käsityksille toisten tiimin jäsenten kyvykkyydestä. Myös institutionaalinen identifioituminen loi pohjaa luottamukselle alkuvaiheessa. Muuten luottamus rakentui vähän kerrassaan tehtävään liittyvän kommunikaation ja sosiaalisen kommunikaation kautta. Tekojen merkitys korostui erityisesti ajan myötä. Työssä esitettiin myös käytännön keinoja luottamuksen rakentamiseksi. Olemassa olevien teknologioiden havaittiin tukevan hyvin suhteen rakentumista tiedon jakamiseen ja sen varastoimiseen liittyvissä tehtävissä. Sen sijaan vuorovaikutuksen näkökulmasta tuen ei nähty olevan yhtä kattavaa. Kaiken kaikkiaan kuitenkin parannuksella sosiaalisissa suhteissa voitaneen saada enemmän aikaan kuin parannuksilla teknologian suhteen.