Pretraining Convolutional Neural Networks for Visual Recognition

Convolutional Neural Networks (CNN) have become the state-of-the-art methods on many large scale visual recognition tasks. For a lot of practical applications, CNN architectures have a restrictive requirement: A huge amount of labeled data are needed for training. The idea of generative pretraining is to obtain initial weights of the network by training the network in a completely unsupervised way and then fine-tune the weights for the task at hand using supervised learning. In this thesis, a general introduction to Deep Neural Networks and algorithms are given and these methods are applied to classification tasks of handwritten digits and natural images for developing unsupervised feature learning. The goal of this thesis is to find out if the effect of pretraining is damped by recent practical advances in optimization and regularization of CNN. The experimental results show that pretraining is still a substantial regularizer, however, not a necessary step in training Convolutional Neural Networks with rectified activations. On handwritten digits, the proposed pretraining model achieved a classification accuracy comparable to the state-of-the-art methods.

Factors of innovation creation within functional heterogeneous project teams Case study: ABB Group

The research topic of the work is: “Factors of innovation creation within functionally heterogeneous project teams”. The research question is “What are the factors of innovation creation within functionally heterogeneous project teams?” The subject of this research is to explore the teams of projects, aimed at creating innovations, and understand how innovation is generated through project team work within them in term of factors. In line with the purposes of this study, firstly, it was analyzed what factors of such teams’ work are affecting creating innovation positively and negatively on the base of chosen literature and a preliminary conceptional framework was formulated, and secondly, the research of the work of project teams in one of the divisions of ABB company has been done and other factors and interdependencies between them have been added to the conceptional framework. This final conceptional framework constitutes the essense of the work findings and can be used as a tool to analyze the innovation creation process in functionally heterogeneous project teams

The role of diaspora networks in opportunity exploitation by ethnic entrepreneurs in Finland

The thesis explores the role of diaspora network in opportunity exploitation by ethnic entrepreneurs in Finland. The purpose of this study is to how ethnic entrepreneurs in Finland can exploit diaspora networks and how significant support of these networks in comparison with governmental and other official institutional support. Increased mobility of the global population and number of immigrants all around the world contribute into interest of academics to this topic. At the same time, in comparison with other European countries for Finland this phenomenon is new. However, increasing number of immigrants add to academic interest to this topic. The theoretical background of this thesis consists of the collection of studies done on diaspora networks and ethnic entrepreneurs as internationally as in Finland. The concept of cooperation between diaspora and ethnic entrepreneurs describes how diaspora can support ethnic entrepreneur and emphasize importance of diaspora ties for business. At the end of the theoretical section theoretical a special grid was proposed as summary of the academic literature review. The empirical research for this study is based on the interviews with five ethnic entrepreneurs in Finland. Empirical data was analyzed and compared with the similar studies done internationally. During the interviews analyses were stressed aspects of the significance of governmental and other official institutional support. During the interviews analyses were stressed aspects of the significance of the governmental and other official institutional support. According to the main findings diaspora can play positive and in some cases crucial role in the business of ethnic entrepreneurs in Finland. Moreover, diaspora can be a facilitator of internationalization of ethnic entrepreneurs. At the same time, there are several factors which might increase or decrease role of diaspora. The ways of the utilization of diaspora network were combined in the empirical grid. The study enhance understanding of the challenges of ethnic entrepreneurs and provides certain recommendations for the policy makers, ethnic entrepreneurs and managers of official institutions involved in cooperation with ethnic entrepreneurs

The Role Of Social Networks In New Venture Internationalization: Case Of Russian And Finnish Firms

The purpose of current master thesis research is to investigate the role of social networks in internationalization of Russian and Finnish firms. Literature review of existing empirical researches on the topic is conducted in order to identify the gap, which is fulfilled by empirical research of 4 Russian and 1 Finnish firm that have established international operations no later than 8 years since their foundation. In-depth semi-structured interviews have shown that business network has been an influencing factor in firms’ internationalization and that even if social network is not the driver of internationalization, it becomes important when a company has established international presence and is working on its enlargement. The study has both theoretical and practical contribution by contributing to research of Russian and Finnish firms’ internationalization and by showing examples of successful foreign market entry of companies from different industries. General practical implication of current thesis is that it shows the efficient ways of entrepreneurs’ social network usage in business development in international scope.

Modelling ecological values in heterogeneous and dynamic landscapes with geospatial data

Our surrounding landscape is in a constantly dynamic state, but recently the rate of changes and their effects on the environment have considerably increased. In terms of the impact on nature, this development has not been entirely positive, but has rather caused a decline in valuable species, habitats, and general biodiversity. Regardless of recognizing the problem and its high importance, plans and actions of how to stop the detrimental development are largely lacking. This partly originates from a lack of genuine will, but is also due to difficulties in detecting many valuable landscape components and their consequent neglect. To support knowledge extraction, various digital environmental data sources may be of substantial help, but only if all the relevant background factors are known and the data is processed in a suitable way. This dissertation concentrates on detecting ecologically valuable landscape components by using geospatial data sources, and applies this knowledge to support spatial planning and management activities. In other words, the focus is on observing regionally valuable species, habitats, and biotopes with GIS and remote sensing data, using suitable methods for their analysis. Primary emphasis is given to the hemiboreal vegetation zone and the drastic decline in its semi-natural grasslands, which were created by a long trajectory of traditional grazing and management activities. However, the applied perspective is largely methodological, and allows for the application of the obtained results in various contexts. Models based on statistical dependencies and correlations of multiple variables, which are able to extract desired properties from a large mass of initial data, are emphasized in the dissertation. In addition, the papers included combine several data sets from different sources and dates together, with the aim of detecting a wider range of environmental characteristics, as well as pointing out their temporal dynamics. The results of the dissertation emphasise the multidimensionality and dynamics of landscapes, which need to be understood in order to be able to recognise their ecologically valuable components. This not only requires knowledge about the emergence of these components and an understanding of the used data, but also the need to focus the observations on minute details that are able to indicate the existence of fragmented and partly overlapping landscape targets. In addition, this pinpoints the fact that most of the existing classifications are too generalised as such to provide all the required details, but they can be utilized at various steps along a longer processing chain. The dissertation also emphases the importance of landscape history as an important factor, which both creates and preserves ecological values, and which sets an essential standpoint for understanding the present landscape characteristics. The obtained results are significant both in terms of preserving semi-natural grasslands, as well as general methodological development, giving support to science-based framework in order to evaluate ecological values and guide spatial planning.

Managing Finnish-Russian Business Relationships and Networks During Conflicts

This thesis examines management of business relationships during conflicts. The context of this study is the international political conflict which started in 2013 and is still affecting international trade relations in 2016. More specifically, this study researches the effects of the conflict in Finnish-Russian trade. The research aim is to identify the implications of a political conflict in the Finnish-Russian business relationships and networks. Furthermore, the study will explore how does a company adapt or overcome the challenges and barriers posed by the international business environment. This research combines relevant theories in management of business relationships and networks in order to review the research data through a critical research frame. The theoretical frameworks are different structures of business relationship development processes, various stages of interaction, and characteristics and functions of business relationships. Moreover, this study will examine the effect of interdependency, commitment and trust in trade relations. Also, what are the important exchange processes and how do these processes affect business relationship and overall performance of joint business operations. Qualitative single case study method was used in this research. Case company was a Finnish multinational company. To understand the changes, the data was collected and analysed through process research approach by pattern-matching and drawing temporal bracketing over two different periods of time, first period in years 2011-2013 and second period in years 2014-2016. Empirical data was collected through a semi-structured interview and additional data was collected from internal and external secondary data sources. The findings of the study confirmed the relationship between trade and conflict. However, the effects are not significant for a company in grocery retail industry which has had earlier experience in Russia and has managed its business relationships and operations effectively. Macroeconomic factors affect companies operating in foreign dynamic markets and in order to sustain changes and to adapt, companies should invest in their business relationships. Trust-based relationships and a higher level of commitment allow companies to have more efficient and beneficial outcomes before and during uncertainty. Furthermore, well-maintained and coordinated business relationships provide the ability to adapt and overcome challenges during uncertainty. Such relationships have information, financial and social exchange processes which allow the partnering firms to have successful business relationship management in dynamic market environments.

On the edge : exploring homeless women's social networks

This thesis aims to uncover the ways that previously homeless women in the Niagara region are able (or unable) to rely on friends, family and service providers in times of crisis (homelessness and poverty). Eleven women were interviewed and their experiences indicate that social networks cannot take the place of comprehensive and inclusive social policy. Time and time again, their stories showed that they were left negotiating the detritus of neo-liberal policies.

Niagara alternative food projects : networks, discourses and nature /

This thesis undertakes an exploration of the nature of alternative food projects in Niagara. A review of various theoretical approaches to the study of food and agriculture, suggests that actor-network theory offers the most useful lens through which to understand these projects. In particular, actor-network theory facilitates non-dualistic theorisations of power and scale and a commitment to the inclusion of non-humans in the 'social' sciences. The research is based on 19 in-depth interviews with actors involved in various urban and rural projects including community supported agriculture, community gardens, chefs using local seasonal food, a winery that grows organically, the good food box, a value-added small business, and organic producers. The analysis consists of four themes. The first analytical section pays special attention to the prominence of agri-tourism in Niagara, and examines the ways in which the projects in the sample interact with agri-tourist networks. In the second section the discussion focuses on the discourses and practices of resistance among Niagara alternative food actors. The participants' interviews suggest there are more discourses of resistance toward agri-tourist than toward dominant food networks. The third section questions commodity chain theorisations of alternative food projects. In particular, this section shows how the inclusion of non-human actors in an analysis confounds conceptualisations of 'short' and 'local' chains. The final analytical section assesses relations of power in Niagara alternative food projects. Three important conclusions arise from this research. First, Niagara alternative food projects cannot be conceptualised as operating at the 'local' scale. Broadening the scope of analysis to include non-human actors, it becomes apparent that these projects actually draw on a variety of extra-local actors. They are at once local and global. Second, the projects in this sample are simultaneously part of alternative, dominant and agri-tourist networks. While Niagara alternative food projects do perform many of the roles characteristic of alternative food systems, they are also involved in practices of development, business, and class distinction. Thus, alternative food networks should not be understood as separate from and in direct opposition to dominant food networks. Despite the second conclusion, this research determines that Niagara alternative food projects have made significant strides in the reworking of power. The projects represented in this thesis do engage in resistant practices and are associated with increased levels ofjustice.

'What ever happened to breakdancing?' : transnational b-boy/b-girl networks, underground video magazines and imagined affinities

In 1997, Paul Gilroy was able to write: "I have been asking myself, whatever happened to breakdancing" (21), a form of vernacular dance associated with urban youth that emerged in the 1970s. However, in the last decade, breakdancing has experienced a massive renaissance in movies (You Got Served), commercials ("Gotta Have My Pops!") and documentaries (the acclaimed Freshest Kids). In this thesis, 1 explore the historical development of global b-boy/bgirl culture through a qualitative study involving dancers and their modes of communication. Widespread circulation of breakdancing images peaked in the mid-1980s, and subsequently b-boy/b-girl culture largely disappeared from the mediated landscape. The dance did not reemerge into the mainstream of North American popular culture until the late 1990s. 1 argue that the development of major transnational networks between b-boys and b-girls during the 1990s was a key factor in the return of 'b-boying/b-girling' (known formerly as breakdancing). Street dancers toured, traveled and competed internationally throughout this decade. They also began to create 'underground' video documentaries and travel video 'magazines.' These video artefacts circulated extensively around the globe through alternative distribution channels (including the backpacks of traveling dancers). 1 argue that underground video artefacts helped to produce 'imagined affinities' between dancers in various nations. Imagined affinities are identifications expressed by a cultural producer who shares an embodied activity with other practitioners through either mediated texts or travels through new places. These 'imagined affinities' helped to sustain b-boy/b-girl culture by generating visual/audio representations of popularity for the dance movement across geographical regions.

Particle swarm optimization for two-connected networks with bounded rings

The Two-Connected Network with Bounded Ring (2CNBR) problem is a network design problem addressing the connection of servers to create a survivable network with limited redirections in the event of failures. Particle Swarm Optimization (PSO) is a stochastic population-based optimization technique modeled on the social behaviour of flocking birds or schooling fish. This thesis applies PSO to the 2CNBR problem. As PSO is originally designed to handle a continuous solution space, modification of the algorithm was necessary in order to adapt it for such a highly constrained discrete combinatorial optimization problem. Presented are an indirect transcription scheme for applying PSO to such discrete optimization problems and an oscillating mechanism for averting stagnation.

Scales, networks and uncertainty : an examination of environmental policy-making in Ontario

Through a case-study analysis of Ontario's ethanol policy, this thesis addresses a number of themes that are consequential to policy and policy-making: spatiality, democracy and uncertainty. First, I address the 'spatial debate' in Geography pertaining to the relevance and affordances of a 'scalar' versus a 'flat' ontoepistemology. I argue that policy is guided by prior arrangements, but is by no means inevitable or predetermined. As such, scale and network are pragmatic geographical concepts that can effectively address the issue of the spatiality of policy and policy-making. Second, I discuss the democratic nature of policy-making in Ontario through an examination of the spaces of engagement that facilitate deliberative democracy. I analyze to what extent these spaces fit into Ontario's environmental policy-making process, and to what extent they were used by various stakeholders. Last, I take seriously the fact that uncertainty and unavoidable injustice are central to policy, and examine the ways in which this uncertainty shaped the specifics of Ontario's ethanol policy. Ultimately, this thesis is an exercise in understanding sub-national environmental policy-making in Canada, with an emphasis on how policy-makers tackle the issues they are faced with in the context of environmental change, political-economic integration, local priorities, individual goals, and irreducible uncertainty.

Automatic Inference of Graph Models for Complex Networks with Genetic Programming

Complex networks can arise naturally and spontaneously from all things that act as a part of a larger system. From the patterns of socialization between people to the way biological systems organize themselves, complex networks are ubiquitous, but are currently poorly understood. A number of algorithms, designed by humans, have been proposed to describe the organizational behaviour of real-world networks. Consequently, breakthroughs in genetics, medicine, epidemiology, neuroscience, telecommunications and the social sciences have recently resulted. The algorithms, called graph models, represent significant human effort. Deriving accurate graph models is non-trivial, time-intensive, challenging and may only yield useful results for very specific phenomena. An automated approach can greatly reduce the human effort required and if effective, provide a valuable tool for understanding the large decentralized systems of interrelated things around us. To the best of the author's knowledge this thesis proposes the first method for the automatic inference of graph models for complex networks with varied properties, with and without community structure. Furthermore, to the best of the author's knowledge it is the first application of genetic programming for the automatic inference of graph models. The system and methodology was tested against benchmark data, and was shown to be capable of reproducing close approximations to well-known algorithms designed by humans. Furthermore, when used to infer a model for real biological data the resulting model was more representative than models currently used in the literature.

Electrophysiology of Oculomotor Delayed Response Tasks: A Model for the Maturation of Visual-Spatial Working Memory Networks

In the literature, persistent neural activity over frontal and parietal areas during the delay period of oculomotor delayed response (ODR) tasks has been interpreted as an active representation of task relevant information and response preparation. Following a recent ERP study (Tekok-Kilic, Tays, & Tkach, 2011 ) that reported task related slow wave differences over frontal and parietal sites during the delay periods of three ODR tasks, the present investigation explored developmental differences in young adults and adolescents during the same ODR tasks using 128-channel dense electrode array methodology and source localization. This exploratory study showed that neural functioning underlying visual-spatial WM differed between age groups in the Match condition. More specifically, this difference is localized anteriorly during the late delay period. Given the protracted maturation of the frontal lobes, the observed variation at the frontal site may indicate that adolescents and young adults may recruit frontal-parietal resources differently.

Heuristics for the Critical Node Detection Problem in Large Complex Networks

Complex networks have recently attracted a significant amount of research attention due to their ability to model real world phenomena. One important problem often encountered is to limit diffusive processes spread over the network, for example mitigating pandemic disease or computer virus spread. A number of problem formulations have been proposed that aim to solve such problems based on desired network characteristics, such as maintaining the largest network component after node removal. The recently formulated critical node detection problem aims to remove a small subset of vertices from the network such that the residual network has minimum pairwise connectivity. Unfortunately, the problem is NP-hard and also the number of constraints is cubic in number of vertices, making very large scale problems impossible to solve with traditional mathematical programming techniques. Even many approximation algorithm strategies such as dynamic programming, evolutionary algorithms, etc. all are unusable for networks that contain thousands to millions of vertices. A computationally efficient and simple approach is required in such circumstances, but none currently exist. In this thesis, such an algorithm is proposed. The methodology is based on a depth-first search traversal of the network, and a specially designed ranking function that considers information local to each vertex. Due to the variety of network structures, a number of characteristics must be taken into consideration and combined into a single rank that measures the utility of removing each vertex. Since removing a vertex in sequential fashion impacts the network structure, an efficient post-processing algorithm is also proposed to quickly re-rank vertices. Experiments on a range of common complex network models with varying number of vertices are considered, in addition to real world networks. The proposed algorithm, DFSH, is shown to be highly competitive and often outperforms existing strategies such as Google PageRank for minimizing pairwise connectivity.

Object-Oriented Genetic Programming for the Automatic Inference of Graph Models for Complex Networks

Complex networks are systems of entities that are interconnected through meaningful relationships. The result of the relations between entities forms a structure that has a statistical complexity that is not formed by random chance. In the study of complex networks, many graph models have been proposed to model the behaviours observed. However, constructing graph models manually is tedious and problematic. Many of the models proposed in the literature have been cited as having inaccuracies with respect to the complex networks they represent. However, recently, an approach that automates the inference of graph models was proposed by Bailey [10] The proposed methodology employs genetic programming (GP) to produce graph models that approximate various properties of an exemplary graph of a targeted complex network. However, there is a great deal already known about complex networks, in general, and often specific knowledge is held about the network being modelled. The knowledge, albeit incomplete, is important in constructing a graph model. However it is difficult to incorporate such knowledge using existing GP techniques. Thus, this thesis proposes a novel GP system which can incorporate incomplete expert knowledge that assists in the evolution of a graph model. Inspired by existing graph models, an abstract graph model was developed to serve as an embryo for inferring graph models of some complex networks. The GP system and abstract model were used to reproduce well-known graph models. The results indicated that the system was able to evolve models that produced networks that had structural similarities to the networks generated by the respective target models.