Visual Customer Segmentation and Data Exploration with the Self-Organizing Map

Advancements in information technology have made it possible for organizations to gather and store vast amounts of data of their customers. Information stored in databases can be highly valuable for organizations. However, analyzing large databases has proven to be difficult in practice. For companies in the retail industry, customer intelligence can be used to identify profitable customers, their characteristics, and behavior. By clustering customers into homogeneous groups, companies can more effectively manage their customer base and target profitable customer segments. This thesis will study the use of the self-organizing map (SOM) as a method for analyzing large customer datasets, clustering customers, and discovering information about customer behavior. Aim of the thesis is to find out whether the SOM could be a practical tool for retail companies to analyze their customer data.

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.

The power of support: an exploration of the mentoring relationship

Tutkimuksen pääasiallisena tavoitteena on selvittää ne moninaiset näkökulmat, joita mentori sekä mentoroitava läpikäyvät osallistuessaan mentorointiohjelmaan. Tutkimuksen avulla pyritään myös selvittämään vastaavanlaisen tuen saannin tehokkuutta sekä mentoroinnin sisältäminen elementtien hyödyllisyyttä. Pyrkimyksenä on myös selvittää sekä ymmärtää ne dynaamiset mentorointiprosessin ominaisuudet molempien prosessiin osallistuvien tahojen näkökulmasta. Tutkimuksen teoriaosuudessa käsitellään mentorointia, mentorointiin liittyviä vuorovaikutussuhteita sekä näihin liittyviä eri näkökulmia. Teoria koostuu monipuolisesta, kansainvälisestä sekä kotimaisesta kirjallisuudesta. Tutkimuksen aineiston keruu suoritetaan puolistrukturoiduilla avoimilla haastatteluilla, jotka suoritetaan järjestämällä kahdenkeskisiä teemahaastatteluita. Mentorointisuhteella on todettu olevan voimakas vaikutus siihen osallistuvien henkilöiden elämään. Mentorointisuhteen tarkoituksellisuus on tullut todettua myös kun itse vuorovaikutussuhde on osoittautunut hyödylliseksi osallistujille. Mentoroitavilla on odotuksia, että mentorit täyttävät seuraavanlaisia rooleja: neuvonantaja, roolimalli sekä mahdollisesti tukea antava ystävä. Kaikissa läpikäydyissä tapauksissa mentori pystyi tarjoamaan jonkun näistärooleista mentoroitavalle. Mentoroitava, puolestaan, otti tämän tuen vastaan jahyötyi siitä.

Exploration of the social dimension of corporate responsibility in a welfare state

This study focuses on corporate social responsibility (or CSR)as the latest dimension to emerge in the corporate responsibility and sustainability agenda, which in the recent past has rapidly risen to the top of the list of concerns for civil societies worldwide. Despite the continuing debates and discussions about the scope, benefits, and impacts of CSR to business and community in various sectors, levels, and types of society, many companies have moved forward to confront the opportunities and challenges of CSR. Thus, this study is about those proactive companies with a focus on the importance of CSR and its management inside and outside the company. It is an exploration and learning from the experience of Finnish companies, as well as other actors interested or involved in shaping the course of CSR, locally and globally. It also looks closely at how national culture affects the views, thinking, and management of CSR in a welfare state. This dissertation primarily draws on the analyses of information collected from a series of qualitative interviews and the existing literature in the area. This is complemented by an analysis of written and published documents on CSR from various sources. The results of the study give insightful information and detailed descriptions of a roadmap useful in learning and understanding CSR in Finnish companies. Despite the varying conceptual connotations, essential roadmap indicators point to the importance of framing CSR within the corporate responsibility concept, Finnish development and the welfare state system, globalization, stakeholders, and the pursuit of sustainable development as the main drivers of CSR, the remarkable progress of CSR in companies, and identification of key management areas and practices relevant to CSR. Similarly,the study reveals the importance of culture as essential in understanding and learning CSR. Finnish culture has a positive influence on the views, thinking, and management practices of CSR issues. Such a positive influence of culture, therefore, makes it easy for business people to discuss and understand CSR, because those CSR issues are already considered common and taken-for-granted by Finns and are implicit in the welfare state provisions. The experience of Finnish companies in implementing CSR policies in the supply chain is a concrete proactive step in advancing the message of CSR, that is, to bring companies and suppliers together to work on improving and strengthening relationships towards socially responsible practices worldwide. Such a forward step to deal with CSR issues in the supply chain reflects the companies' commitments and belief that CSR can be managed with the suppliers and gain positive benefits. Despite the problems and complexities, particularly in the global supply chain, managing CSR for Finnish companies presents new opportunities and challenges that are expected to intensify in the near future. The focus on CSR policy implementation inthe supply chain points to the importance of companies taking initiatives and forging cooperation with suppliers with the aim of addressing and improving CSR questions in the supply chains. The proactive stance of Finnish companies toward CSR is complemented by the active supporting role of important societalactors such as the government and NGOs. These actors carry out various promotional efforts and campaigns, thus bringing CSR into the mainstream of Finnish companies and strengthening the synergistic learning about CSR within the Finnish business and civil circles. The efforts of the government and NGOs to promote CSR are indicative of the importance of multipartite involvement and the emergence of better civil regulations. Likewise, their drive to learn from each other, exchange experiences, and contribute in CSR debates facilitated the evolution of CSRnetworks in the country. The results of this study add to the mounting evidence that CSR, in general, has created a new dimension in managing corporate sustainability. This study provides compelling empirical evidence and some direct quotations about CSR in the Finnish context. This information can be used to learn and gain new useful insights, approaches, and concepts for managing CSR.

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.

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.

Demonstration Platform for Visual Quality Metrics

This thesis presents two graphical user interfaces for the project DigiQ - Fusion of Digital and Visual Print Quality, a project for computationally modeling the subjective human experience of print quality by measuring the image with certain metrics. After presenting the user interfaces, methods for reducing the computation time of several of the metrics and the image registration process required to compute the metrics, and details of their performance are given. The weighted sample method for the image registration process was able to signifigantly decrease the calculation times while resulting in some error. The random sampling method for the metrics greatly reduced calculation time while maintaining excellent accuracy, but worked with only two of the metrics.

Learning Robot Motions from Visual Sensing

Learning from demonstration becomes increasingly popular as an efficient way of robot programming. Not only a scientific interest acts as an inspiration in this case but also the possibility of producing the machines that would find application in different areas of life: robots helping with daily routine at home, high performance automata in industries or friendly toys for children. One way to teach a robot to fulfill complex tasks is to start with simple training exercises, combining them to form more difficult behavior. The objective of the Master’s thesis work was to study robot programming with visual input. Dynamic movement primitives (DMPs) were chosen as a tool for motion learning and generation. Assuming a movement to be a spring system influenced by an external force, making this system move, DMPs represent the motion as a set of non-linear differential equations. During the experiments the properties of DMP, such as temporal and spacial invariance, were examined. The effect of the DMP parameters, including spring coefficient, damping factor, temporal scaling, on the trajectory generated were studied.