Heavy-metal pollution and remediation of forest soil around the Harjavalta Cu-Ni smelter, in SW Finland

Abstract

Coarse Global Visual Localization of a Mobile Robot

Localization, which is the ability of a mobile robot to estimate its position within its environment, is a key capability for autonomous operation of any mobile robot. This thesis presents a system for indoor coarse and global localization of a mobile robot based on visual information. The system is based on image matching and uses SIFT features as natural landmarks. Features extracted from training images arestored in a database for use in localization later. During localization an image of the scene is captured using the on-board camera of the robot, features are extracted from the image and the best match is searched from the database. Feature matching is done using the k-d tree algorithm. Experimental results showed that localization accuracy increases with the number of training features used in the training database, while, on the other hand, increasing number of features tended to have a negative impact on the computational time. For some parts of the environment the error rate was relatively high due to a strong correlation of features taken from those places across the environment.

Visual measurement of laser-arc hybrid welding

Tässä työssä raportoidaan hybridihitsauksesta otettujen suurnopeuskuvasarjojen automaattisen analyysijärjestelmän kehittäminen.Järjestelmän tarkoitus oli tuottaa tietoa, joka avustaisi analysoijaa arvioimaan kuvatun hitsausprosessin laatua. Tutkimus keskittyi valokaaren taajuuden säännöllisyyden ja lisäainepisaroiden lentosuuntien mittaamiseen. Valokaaria havaittiin kuvasarjoista sumean c-means-klusterointimenetelmän avullaja perättäisten valokaarien välistä aikaväliä käytettiin valokaaren taajuuden säännöllisyyden mittarina. Pisaroita paikannettiin menetelmällä, jossa yhdistyi pääkomponenttianalyysi ja tukivektoriluokitin. Kalman-suodinta käytettiin tuottamaan arvioita pisaroiden lentosuunnista ja nopeuksista. Lentosuunnanmääritysmenetelmä luokitteli pisarat niiden arvioitujen lentosuuntien perusteella. Järjestelmän kehittämiseen käytettävissä olleet kuvasarjat poikkesivat merkittävästi toisistaan kuvanlaadun ja pisaroiden ulkomuodon osalta, johtuen eroista kuvaus- ja hitsausprosesseissa. Analyysijärjestelmä kehitettiin toimimaan pienellä osajoukolla kuvasarjoja, joissa oli tietynlainen kuvaus- ja hitsausprosessi ja joiden kuvanlaatu ja pisaroiden ulkomuoto olivat samankaltaisia, mutta järjestelmää testattiin myös osajoukon ulkopuolisilla kuvasarjoilla. Testitulokset osoittivat, että lentosuunnanmääritystarkkuus oli kohtuullisen suuri osajoukonsisällä ja pieni muissa kuvasarjoissa. Valokaaren taajuuden säännöllisyyden määritys oli tarkka useammassa kuvasarjassa.

Visual Measurement and Modelling of Tool Wear in Rough Turning

Huolimatta korkeasta automaatioasteesta sorvausteollisuudessa, muutama keskeinen ongelma estää sorvauksen täydellisen automatisoinnin. Yksi näistä ongelmista on työkalun kuluminen. Tämä työ keskittyy toteuttamaan automaattisen järjestelmän kulumisen, erityisesti viistekulumisen, mittaukseen konenäön avulla. Kulumisen mittausjärjestelmä poistaa manuaalisen mittauksen tarpeen ja minimoi ajan, joka käytetään työkalun kulumisen mittaukseen. Mittauksen lisäksi tutkitaan kulumisen mallinnusta sekä ennustamista. Automaattinen mittausjärjestelmä sijoitettiin sorvin sisälle ja järjestelmä integroitiin onnistuneesti ulkopuolisten järjestelmien kanssa. Tehdyt kokeet osoittivat, että mittausjärjestelmä kykenee mittaamaan työkalun kulumisen järjestelmän oikeassa ympäristössä. Mittausjärjestelmä pystyy myös kestämään häiriöitä, jotka ovat konenäköjärjestelmille yleisiä. Työkalun kulumista mallinnusta tutkittiin useilla eri menetelmillä. Näihin kuuluivat muiden muassa neuroverkot ja tukivektoriregressio. Kokeet osoittivat, että tutkitut mallit pystyivät ennustamaan työkalun kulumisasteen käytetyn ajan perusteella. Parhaan tuloksen antoivat neuroverkot Bayesiläisellä regularisoinnilla.

Unsupervised visual object categorization

The number of digital images has been increasing exponentially in the last few years. People have problems managing their image collections and finding a specific image. An automatic image categorization system could help them to manage images and find specific images. In this thesis, an unsupervised visual object categorization system was implemented to categorize a set of unknown images. The system is unsupervised, and hence, it does not need known images to train the system which needs to be manually obtained. Therefore, the number of possible categories and images can be huge. The system implemented in the thesis extracts local features from the images. These local features are used to build a codebook. The local features and the codebook are then used to generate a feature vector for an image. Images are categorized based on the feature vectors. The system is able to categorize any given set of images based on the visual appearance of the images. Images that have similar image regions are grouped together in the same category. Thus, for example, images which contain cars are assigned to the same cluster. The unsupervised visual object categorization system can be used in many situations, e.g., in an Internet search engine. The system can categorize images for a user, and the user can then easily find a specific type of image.

Active sulphide mine tailings impoundments as sources of contaminated drainage: controlling factors, methods of characterisation and geochemical constraints for mitigation

Low quality mine drainage from tailings facilities persists as one of the most significant global environmental concerns related to sulphide mining. Due to the large variation in geological and environmental conditions at mine sites, universal approaches to the management of mine drainage are not always applicable. Instead, site-specific knowledge of the geochemical behaviour of waste materials is required for the design and closure of the facilities. In this thesis, tailings-derived water contamination and factors causing the pollution were investigated in two coeval active sulphide mine sites in Finland: the Hitura Ni mine and the Luikonlahti Cu-Zn-Co-Ni mine and talc processing plant. A hydrogeochemical study was performed to characterise the tailingsderived water pollution at Hitura. Geochemical changes in the Hitura tailings were evaluated with a detailed mineralogical and geochemical investigation (solid-phase speciation, acid mine drainage potential, pore water chemistry) and using a spatial assessment to identify the mechanisms of water contamination. A similar spatial investigation, applying selective extractions, was carried out in the Luikonlahti tailings area for comparative purposes (Hitura low-sulphide tailings vs. Luikonlahti sulphide-rich tailings). At both sites, hydrogeochemistry of tailings seepage waters was further characterised to examine the net results of the processes observed within the impoundments and to identify constraints for water treatment. At Luikonlahti, annual and seasonal variation in effluent quality was evaluated based on a four-year monitoring period. Observations pertinent to future assessment and mine drainage prevention from existing and future tailings facilities were presented based on the results. A combination of hydrogeochemical approaches provided a means to delineate the tailings-derived neutral mine drainage at Hitura. Tailings effluents with elevated Ni, SO₄ ^2- and Fe content had dispersed to the surrounding aquifer through a levelled-out esker and underneath the seepage collection ditches. In future mines, this could be avoided with additional basal liners in tailings impoundments where the permeability of the underlying Quaternary deposits is inadequate, and with sufficiently deep ditches. Based on the studies, extensive sulphide oxidation with subsequent metal release may already initiate during active tailings disposal. The intensity and onset of oxidation depended on e.g. the Fe sulphide content of the tailings, water saturation level, and time of exposure of fresh sulphide grains. Continuous disposal decreased sulphide weathering in the surface of low-sulphide tailings, but oxidation initiated if they were left uncovered after disposal ceased. In the sulphide-rich tailings, delayed burial of the unsaturated tailings had resulted in thick oxidized layers, despite the continuous operation. Sulphide weathering and contaminant release occurred also in the border zones. Based on the results, the prevention of sulphide oxidation should already be considered in the planning of tailings disposal, taking into account the border zones. Moreover, even lowsulphide tailings should be covered without delay after active disposal ceases. The quality of tailings effluents showed wide variation within a single impoundment and between the two different types of tailings facilities assessed. The affecting factors included source materials, the intensity of weathering of tailings and embankment materials along the seepage flow path, inputs from the process waters, the water retention time in tailings, and climatic seasonality. In addition, modifications to the tailings impoundment may markedly change the effluent quality. The wide variation in the tailings effluent quality poses challenges for treatment design. The final decision on water management requires quantification of the spatial and seasonal fluctuation at the site, taking into account changes resulting from the eventual closure of the impoundment. Overall, comprehensive hydrogeochemical mapping was deemed essential in the identification of critical contaminants and their sources at mine sites. Mineralogical analysis, selective extractions, and pore water analysis were a good combination of methods for studying the weathering of tailings and in evaluating metal mobility from the facilities. Selective extractions with visual observations and pH measurements of tailings solids were, nevertheless, adequate in describing the spatial distribution of sulphide oxidation in tailings impoundments. Seepage water chemistry provided additional data on geochemical processes in tailings and was necessary for defining constraints for water treatment.

The Importance of Semantics: Visual World Studies on Drawing Inferences and Resolving Anaphors

The present thesis investigated the importance of semantics in generating inferences during discourse processing. Three aspects of semantics, gender stereotypes, implicit causality information and proto-role properties, were used to investigate whether semantics is activated elaboratively during discourse comprehension and what its relative importance is in backward inferencing compared to discourse/structural cues. Visual world eye-tracking studies revealed that semantics plays an important role in both backward and forward inferencing: Gender stereotypes and implicit causality information is activated elaboratively during online discourse comprehension. Moreover, gender stereotypes, implicit causality and proto-role properties of verbs are all used in backward inferencing. Importantly, the studies demonstrated that semantic cues are weighed against discourse/structural cues. When the structural cues consist of a combination of cues that have been independently shown to be important in backward inferencing, semantic effects may be masked, whereas when the structural cues consist of a combination of fewer prominent cues, semantics can have an earlier effect than structural factors in pronoun resolution. In addition, the type of inference matters, too: During anaphoric inferencing semantics has a prominent role, while discourse/structural salience attains more prominence during non-anaphoric inferencing. Finally, semantics exhibits a strong role in inviting new inferences to revise earlier made inferences even in the case the additional inference is not needed to establish coherence in discourse. The findings are generally in line with the Mental Model approaches. Two extended model versions are presented that incorporate the current findings into the earlier literature. These models allow both forward and backward inferencing to occur at any given moment during the course of processing; they also allow semantic and discourse/structural cues to contribute to both of these processes. However, while the Mental Model 1 does not assume interactions between semantic and discourse/structural factors in forward inferencing, the Mental Model 2 does assume such a link.