Generative Part-Based Gabor Object Detector

Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.

Digitalisaatio ja kuljettajakoulutusyrittäjyys

Digitalisaation myötä myös liikenteestä tulee yhä älykkäämpää. Valtiovalta purkaa sääntelyä ja sallii digitaalisten menetelmien laajempaa käyttöä. Kuljettajakoulutusta pidetään toimialana kuitenkin hyvin konventionaalisena. Diplomityön tarkoituksena on tutkia, mitä digitalisaatio tarkoittaa kuljettajakoulutusyritysten liiketoimintamalleille. Empiiristä aineistoa saatiin teemahaastatteluin ja aineistoa analysoitiin laadullisin menetelmin. Työssä esitellään alan vahvuudet, heikkoudet, mahdollisuudet ja uhat sekä tulevaisuuden skenaariot. Digitalisaatio aiheuttaa merkittäviä muutoksia kuljettajakoulutusalan yrityksille. Auto ei ole enää entisenlainen statussymboli eikä rahan käytön kohde. Digitaaliajan ihmiset eivät aina kaipaa fyysistä liikkumista, kun vielä kivijalkakaupatkin vähenevät. Ajokorttia ei useinkaan koeta välttämättömäksi aikuistumisriitiksi. Uusi teknologia voi kuitenkin radikaalisti parantaa alan yritysten suorituskykyä: palvelut muuttuvat ajasta ja paikasta riippumattomiksi sekä skaalautuviksi. Kuluttajien kannalta digitalisaatio puolestaan parantaa asiakaslähtöisyyttä. Alan liiketoimintamallien kehittymiseen vaikuttaa neljä taustavoimaa: digitalisaatio, perinteet, sääntely ja yrittäjyys. Liiketoimintamalli sisältää opetukselliset ydintoiminnot, sisäiset prosessit, liiketoiminnan tukitoiminnot ja arvoehdotuksen asiakkaalle. Liiketoiminnan kehittäminen vastaamaan digitalisaation vaatimuksia edellyttää proaktiivista innovaatiostrategiaa. Siihen perustuvien innovaatiomenetelmien avulla yritys voi kehittää liiketoimintamalliaan digitalisaation tarjoamien ja tiedon asymmetriasta kumpuavien mahdollisuuksien hyödyntämiseksi.

Towards a contextual understanding of B2B salespeople's selling competencies – An exploratory study among purchasing decision-makers of internationally-oriented technology firms

ABSTRACT Towards a contextual understanding of B2B salespeople’s selling competencies − an exploratory study among purchasing decision-makers of internationally-oriented technology firms The characteristics of modern selling can be classified as follows: customer retention and loyalty targets, database and knowledge management, customer relationship management, marketing activities, problem solving and system selling, and satisfying needs and creating value. For salespeople to be successful in this environment, they need a wide range of competencies. Salespeople’s selling skills are well documented in seller side literature through quantitative methods, but the knowledge, skills and competencies from the buyer’s perspective are under-researched. The existing research on selling competencies should be broadened and updated through a qualitative research perspective due to the dynamic nature and the contextual dependence of selling competencies. The purpose of the study is to increase understanding of the professional salesperson’s selling competencies from the industrial purchasing decision- makers’ viewpoint within the relationship selling context. In this study, competencies are defined as sales-related knowledge and skills. The scope of the study includes goods, materials and services managed by a company’s purchasing function and used by an organization on a daily basis. The abductive approach and ‘systematic combining’ have been applied as a research strategy. In this research, data were generated through semi- structured, person-to-person interviews and open-ended questions. The study was conducted among purchasing decision-makers in the technology industry in Finland. The branches consisted of the electronics and electro-technical industries and the mechanical engineering and metals industries. A total of 30 companies and one purchasing decision-maker from each company were purposively chosen for the sampling. The sample covers different company sizes based on their revenues, their differing structures – varying from public to family companies –that represent domestic and international ownerships. Before analyzing the data, they were organized by the purchasing orientations of the buyers: the buying, procurement or supply management orientation. Thematic analysis was chosen as the analysis method. After analyzing the data, the results were contrasted with the theory. There was a continuous interaction between the empirical data and the theory. Based on the findings, a total of 19 major knowledge and skills were identified from the buyers’ perspective. The specific knowledge and skills from the viewpoint of customers’ prevalent purchasing orientations were divided into two categories, generic and contextual. The generic knowledge and skills apply to all purchasing orientations, and the contextual knowledge and skills depend on customers’ prevalent purchasing orientations. Generic knowledge and skills relate to price setting, negotiation, communication and interaction skills, while contextual ones relate to knowledge brokering, ability to present solutions and relationship skills. Buying-oriented buyers value salespeople who are ‘action oriented experts, however at a bit of an arm’s length’, procurement buyers value salespeople who are ‘experts deeply dedicated to the customer and fostering the relationship’ and supply management buyers value salespeople who are ‘corporate-oriented experts’. In addition, the buyer’s perceptions on knowledge and selling skills differ from the seller’s ones. The buyer side emphasizes managing the subject matter, consisting of the expertise, understanding the customers’ business and needs, creating a customized solution and creating value, reliability and an ability to build long-term relationships, while the seller side emphasizes communica- tion, interaction and salesmanship skills. The study integrates the selling skills of the current three-component model− technical knowledge, salesmanship skills, interpersonal skills− and relationship skills and purchasing orientations, into a selling competency model. The findings deepen and update the content of these knowledges and skills in the B2B setting and create new insights into them from the buyer’s perspective, and thus the study increases contextual understanding of selling competencies. It generates new knowledge of the salesperson’s competencies for the relationship selling and personal selling and sales management literature. It also adds knowledge of the buying orientations to the buying behavior literature. The findings challenge sales management to perceive salespeople’s selling skills both from a contingency and competence perspective. The study has several managerial implications: it increases understanding of what the critical selling knowledge and skills from the buyer’s point of view are, understanding of how salespeople effectively implement the relationship marketing concept, sales management’s knowledge of how to manage the sales process more effectively and efficiently, and the knowledge of how sales management should develop a salesperson’s selling competencies when managing and developing the sales force. Keywords: selling competencies, knowledge, selling skills, relationship skills, purchasing orientations, B2B selling, abductive approach, technology firms

Multicultural Belonging. Individuals across cultures, languages and places

The article-based doctoral dissertation deals with adult individuals in Western societies who were born into multilingual and multicultural families and have parents of different nationalities. The study’s participants grew up outside their parents’ countries of origin and relate to a multitude of bonds that link them across various cultures, languages and places. The study explores the social dimension of cultural belonging and examines diverse approaches that enable the participants to create notions of belonging and identification despite possessing at times contradictory transnational allegiances. The works offers new perspectives on transnational belonging and makes a timely contribution to discussions in the fields of cultural heritage studies, ethnology and transnational studies. The dissertation combines qualitative research methods with an insider perspective. The empirical material is based on semi-structured interviews with fifteen participants, among which are also the author’s siblings. The study addresses the relevance of the author’s personal situatedness and her multi-faceted roles as well as ethical concerns related to the methodological approach of insider research. The social dimension of cultural identities affect both the participants’ identification with their multiple attachments and language use in everyday life. The key research findings present interrelated discussions of the participants’ notion of being a mixture, the importance of family bonds and multilingualism, a specific mixed family lifestyle, the notion of non-belonging and the study participants’ sense of otherness as a means of creating communality with others. The study discusses the participants’ various life strategies of flexible relativising, juggling with multiple affiliations, the approach of “blending in” and their sense of ironic nation-ness for constructing a coherent sense of belonging. The author argues that multicultural belonging is inextricably connected to an association with multiple languages, cultures and places. Multicultural belonging is relational and depends on the context, social relationships and locations. The study proposes that multicultural belonging creates a tolerant understanding of membership and enables experiences of cosmopolitanism and selected notions of allegiance.

Macro- and Microevolution of Languages: Exploring Linguistic Divergence with Approaches from Evolutionary Biology

There are more than 7000 languages in the world, and many of these have emerged through linguistic divergence. While questions related to the drivers of linguistic diversity have been studied before, including studies with quantitative methods, there is no consensus as to which factors drive linguistic divergence, and how. In the thesis, I have studied linguistic divergence with a multidisciplinary approach, applying the framework and quantitative methods of evolutionary biology to language data. With quantitative methods, large datasets may be analyzed objectively, while approaches from evolutionary biology make it possible to revisit old questions (related to, for example, the shape of the phylogeny) with new methods, and adopt novel perspectives to pose novel questions. My chief focus was on the effects exerted on the speakers of a language by environmental and cultural factors. My approach was thus an ecological one, in the sense that I was interested in how the local environment affects humans and whether this human-environment connection plays a possible role in the divergence process. I studied this question in relation to the Uralic language family and to the dialects of Finnish, thus covering two different levels of divergence. However, as the Uralic languages have not previously been studied using quantitative phylogenetic methods, nor have population genetic methods been previously applied to any dialect data, I first evaluated the applicability of these biological methods to language data. I found the biological methodology to be applicable to language data, as my results were rather similar to traditional views as to both the shape of the Uralic phylogeny and the division of Finnish dialects. I also found environmental conditions, or changes in them, to be plausible inducers of linguistic divergence: whether in the first steps in the divergence process, i.e. dialect divergence, or on a large scale with the entire language family. My findings concerning Finnish dialects led me to conclude that the functional connection between linguistic divergence and environmental conditions may arise through human cultural adaptation to varying environmental conditions. This is also one possible explanation on the scale of the Uralic language family as a whole. The results of the thesis bring insights on several different issues in both a local and a global context. First, they shed light on the emergence of the Finnish dialects. If the approach used in the thesis is applied to the dialects of other languages, broader generalizations may be drawn as to the inducers of linguistic divergence. This again brings us closer to understanding the global patterns of linguistic diversity. Secondly, the quantitative phylogeny of the Uralic languages, with estimated times of language divergences, yields another hypothesis as to the shape and age of the language family tree. In addition, the Uralic languages can now be added to the growing list of language families studied with quantitative methods. This will allow broader inferences as to global patterns of language evolution, and more language families can be included in constructing the tree of the world’s languages. Studying history through language, however, is only one way to illuminate the human past. Therefore, thirdly, the findings of the thesis, when combined with studies of other language families, and those for example in genetics and archaeology, bring us again closer to an understanding of human history.

Corporate grassroots lobbying in the European Union

The European Union has gone through significant changes in the past 20 years. The importance of public opinion in politics has increased and the new technologies are empowering the wider public to express its opinions. The purpose of this study is to explore how corporations use the tactic of grassroots lobbying in the European Union environment. The research objectives were addressed through qualitative research methods. Six expert interviews were conducted to find new perspectives and to deepen the understanding of the research objectives. Following the data collection, the research material was transcribed and analysed. In the analysis, the data was organized based on concepts and themes found from the literature review. The empirical findings on grassroots lobbying in the EU were presented. It was found that when a company is selecting grassroots lobbying tactic, the familiarity of the tactic, organizational culture, financial resources and amount of stakeholders seem to have an impact to the selection. The issues that are successfully lobbied through the grassroots-lobbying tactic were seen to be those, which have high and direct impact on lives of people, arouse strong feelings and are not very complex. Furthermore, when deciding on the timing of a campaign, in the EU it was found that a company should take into account the long policy process and limited capabilities to mobilise people. Targeting the object of the campaign and selecting the channels used in a grassrootslobbying campaign were seen to be in function of identifying the key decision-makers on the issue. The decisions of who to mobilise and the mobilisation channels were considered to be dependant on who the campaign is trying to influence. Also, it was found that when the implementing a grassroots lobbying campaign in the EU environment, the special features such as multiple cultures and languages should be taken into account. This study has provided novel practical insights for corporate grassroots lobbying in the EU environment and furthermore successfully contributed to the academic research in the field.