External Location Factors of Finnish Direct Investment in Central and Eastern European Transitional Economies

Tutkimuksen päätavoitteena oli selvittää suomalaisten suorien investointien maan valintaan vaikuttavia tekijöitä Itä- ja Keski-Euroopan kymmenessä siirtymätaloudessa. Empiirisessä osuudessa tarkasteltiin suomalaisten yritysten tärkeimpiä sijaintitekijöitä alueella ja yrityskohtaisten tekijöiden vaikutusta sijaintitekijöihin. Tutkimuksessa selvitettiin myös yritysten päämotiiveja investoida maihin. Laaditun investointikriteeristön mukaan maat pystyttiin laittamaan paremmuusjärjestykseen suomalaisen investoijan kannalta. Empiirisen osuuden aineisto kerättiin postikyselylomakkeella yrityksiltä, joilla on tai jotka ovat suunnittelemassa investointeja näihin maihin. Tutkimusote oli kvantitatiivinen. Tutkimustulokset osoittavat, että suomalaiset investoijat valitsevat Itä- ja Keski-Euroopan maan investointikohteeksi pääasiassa markkinapotentiaalin ja edullisten kustannusten perusteella. Myös infrastruktuuri vaikuttaa maan valintaan. Eri aloilla toimivien yritysten sijaintitekijöiden painotuksissa havaittiin eroja. Yrityksen koko ja päämotiivi vaikuttivat sijaintitekijöiden painotuksiin. Investointikriteereiden mukaan kaksi parasta investointimaata suomalaisille investoijille ovat Puola ja Viro. Vertailtaessa investointikriteereitä toteutuneisiin investointeihin voidaan todeta, että suomalaiset investoijat eivät ole hyödyntäneet investoinneilla saatavia etuja kaikissa kohdemaissa.

Foreign-Medical-School Graduates object to the VISA Qualifiying Examination

To the editor; The Visa Qualifying Examination is a two-day test composed of approximately 950 multiple-choice questions conerneing the basic and clinical sciences....

Exploring the relative DNA contribution of first and second object's users on mock touch DNA mixtures

Contact stains recovered at break-in crime scenes are frequently characterized by mixtures of DNA from several persons. Broad knowledge on the relative contribution of DNA left behind by different users overtime is of paramount importance. Such information might help crime investigators to robustly evaluate the possibility of detecting a specific (or known) individual's DNA profile based on the type and history of an object. To address this issue, a contact stain simulation-based protocol was designed. Fourteen volunteers either acting as first or second object's users were recruited. The first user was required to regularly handle/wear 9 different items during an 8-10-day period, whilst the second user for 5, 30 and 120 min, in three independent simulation sessions producing a total of 231 stains. Subsequently, the relative DNA profile contribution of each individual pair was investigated. Preliminary results showed a progressive increase of the percentage contribution of the second user compared to the first. Interestingly, the second user generally became the major DNA contributor when most objects were handled/worn for 120 min, Furthermore, the observation of unexpected additional alleles will then prompt the investigation of indirect DNA transfer events.

Most and Least Preferred Colours Differ According to Object Context : New Insights from an Unrestricted Colour Range

Humans like some colours and dislike others, but which particular colours and why remains to be understood. Empirical studies on colour preferences generally targeted most preferred colours, but rarely least preferred (disliked) colours. In addition, findings are often based on general colour preferences leaving open the question whether results generalise to specific objects. Here, 88 participants selected the colours they preferred most and least for three context conditions (general, interior walls, t-shirt) using a high-precision colour picker. Participants also indicated whether they associated their colour choice to a valenced object or concept. The chosen colours varied widely between individuals and contexts and so did the reasons for their choices. Consistent patterns also emerged, as most preferred colours in general were more chromatic, while for walls they were lighter and for t-shirts they were darker and less chromatic compared to least preferred colours. This meant that general colour preferences could not explain object specific colour preferences. Measures of the selection process further revealed that, compared to most preferred colours, least preferred colours were chosen more quickly and were less often linked to valenced objects or concepts. The high intra- and inter-individual variability in this and previous reports furthers our understanding that colour preferences are determined by subjective experiences and that most and least preferred colours are not processed equally.

Using appearance and context for outdoor scene object classification

We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down control, which uses the previously learned models (appearance and absolute location) to obtain an initial pixel-level classification. This information provides us the core of objects, which is used to acquire a more accurate object model. Therefore, their growing by specific active regions allows us to obtain an accurate recognition of known regions. Next, a stage of general segmentation provides the segmentation of unknown regions by a bottom-strategy. Finally, the last stage tries to perform a region fusion of known and unknown segmented objects. The result is both a segmentation of the image and a recognition of each segment as a given object class or as an unknown segmented object. Furthermore, experimental results are shown and evaluated to prove the validity of our proposal

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.

Commercializing technology in transitional economies. Case: Nanotechnology in Russia

The aim of the study is to find out “What are the challenges to overcome for the successful nanotechnology commercialization in Russia?” Working closely with the case country was definitely an advantage when it comes to the understanding of the research subject. The thesis is divided to two parts: first part examines the concept of technology commercialization and identifies unique aspects of the process in context of nanotechnology. Second part is dedicated to an empirical research, investigating current status of nanotechnology commercialization in Russia. For the purpose of this study, Russian and international scientists, researchers, entrepreneurs, industry and government representatives were interviewed systematically during 2007 – 2009. Based on the research done it can be concluded that immense public funding provides necessary support for the development of Russian nanotechnology industry. However, investments alone do not address important structural shortcomings of a national innovation system, which in turn slow down the progress. Taking into consideration gap between science and business and challenging IPR legislation, expected significant economic impact in Russia may be overestimated. Nevertheless it should be noted that development of nanotechnology is advancing rapidly and therefore, the state of commercialization is changing accordingly, even while this lines are written.

Hume, liberty and the object of moral evaluation

Hume's project concerning the conflict between liberty and necessity is ";reconciliatory";. But what is the nature of Hume's project? Does he solve a problem in metaphysics only? And when Hume says that the dispute between the doctrines of liberty and necessity is merely verbal, does he mean that there is no genuine metaphysical dispute between the doctrines? In the present essay I argue for: (1) there is room for liberty in Hume's philosophy, and not only because the position is pro forma compatibilist, even though this has importance for the recognition that Hume's main concern when discussing the matter is with practice; (2) the position does not involve a ";subjectivization"; of every form of necessity: it is not compatibilist because it creates a space for the claim that the operations of the will are non-problematically necessary through a weakning of the notion of necessity as it applies to external objects; (3) Hume holds that the ordinary phenomena of mental causation do not preempt the atribuition of moral responsibility, which combines perfectly with his identification of the object of moral evaluation: the whole of the character of a person, in relation to which there is, nonetheless, liberty. I intend to support my assertions by a close reading of what Hume states in section 8 of the first Enquiry.

On the development of object functions and restrictions for shapes made with a turret punch press

This study presents the information required to describe the machine and device resources in the turret punch press environment which are needed for the development of the analysing method for automated production. The description of product and device resources and their interconnectedness is the starting point for method comparison the development of expenses, production planning and the performance of optimisation. The manufacturing method cannot be optimized unless the variables and their interdependence are known. Sheet metal parts in particular may then become remarkably complex, and their automatic manufacture may be difficult or, with some automatic equipment, even impossible if not know manufacturing properties. This thesis consists of three main elements, which constitute the triangulation. In the first phase of triangulation, the manufacture occuring on a turret punch press is examined in order to find the factors that affect the efficiency of production. In the second phase of triangulation, the manufacturability of products on turret punch presses is examined through a set of laboratory tests. The third phase oftriangulation involves an examination of five industry parts. The main key findings of this study are: all possible efficiency in high automation level machining cannot be achieved unless the raw materials used in production and the dependencies of the machine and tools are well known. Machine-specific manufacturability factors for turret punch presses were not taken into account in the industrial case samples. On the grounds of the performed tests and industrial case samples, the designer of a sheet metal product can directly influence the machining time, material loss, energy consumption and the number of tools required on a turret punch press by making decisions in the way presented in the hypothesis of thisstudy. The sheet metal parts to be produced can be optimised to bemanufactured on a turret punch press when the material to be used and the kinds of machine and tool options available are known. This provides in-depth knowledge of the machine and tool properties machine and tool-specifically. None of the optimisation starting points described here is a separate entity; instead, they are all connected to each other.

Comparison of Local Feature Detectors and Descriptors for Visual Object Categorization

Local features are used in many computer vision tasks including visual object categorization, content-based image retrieval and object recognition to mention a few. Local features are points, blobs or regions in images that are extracted using a local feature detector. To make use of extracted local features the localized interest points are described using a local feature descriptor. A descriptor histogram vector is a compact representation of an image and can be used for searching and matching images in databases. In this thesis the performance of local feature detectors and descriptors is evaluated for object class detection task. Features are extracted from image samples belonging to several object classes. Matching features are then searched using random image pairs of a same class. The goal of this thesis is to find out what are the best detector and descriptor methods for such task in terms of detector repeatability and descriptor matching rate.

The effect of institutional settings on accounting conservatism – Empirical evidence from the Nordic countries and the transitional economies of Europe

The purpose of the dissertation is to investigate how different institutional settings affect accounting conservatism. These aspects are of interest because prior studies show that accounting quality is influenced not only by accounting standards, but also by incentives from the financial reporting environment. Accounting quality could be defined as the usefulness of financial reporting to investors and other parties in contractual relationships with the firm. In this thesis it is measured by a single, but important attribute, accounting conservatism. Conservatism is understood as asymmetric timeliness of loss and gain recognition. The study examines the role and the users of financial statements, and how changes in both respectively affect accounting conservatism. These two questions are explored in two different research environments, the Nordic countries and the transitional economies of Europe. The results of the dissertation indicate that the degree of accounting conservatism increases the closer the financial statement comes to fulfilling the informational role of financial reporting. Secondly, it is also implied that foreign investors demand conservative accounting numbers in order to mitigate the problem of information asymmetry. Overall, the findings suggest that earnings conservatism is useful and increases the quality of financial information for the purpose of decision-making and contracting. These results are of relevance to managers, investors and other users of financial reporting information, as well as to standard setters.

Bag-of-Features Approach to Unsupervised Visual Object Categorisation

The large and growing number of digital images is making manual image search laborious. Only a fraction of the images contain metadata that can be used to search for a particular type of image. Thus, the main research question of this thesis is whether it is possible to learn visual object categories directly from images. Computers process images as long lists of pixels that do not have a clear connection to high-level semantics which could be used in the image search. There are various methods introduced in the literature to extract low-level image features and also approaches to connect these low-level features with high-level semantics. One of these approaches is called Bag-of-Features which is studied in the thesis. In the Bag-of-Features approach, the images are described using a visual codebook. The codebook is built from the descriptions of the image patches using clustering. The images are described by matching descriptions of image patches with the visual codebook and computing the number of matches for each code. In this thesis, unsupervised visual object categorisation using the Bag-of-Features approach is studied. The goal is to find groups of similar images, e.g., images that contain an object from the same category. The standard Bag-of-Features approach is improved by using spatial information and visual saliency. It was found that the performance of the visual object categorisation can be improved by using spatial information of local features to verify the matches. However, this process is computationally heavy, and thus, the number of images must be limited in the spatial matching, for example, by using the Bag-of-Features method as in this study. Different approaches for saliency detection are studied and a new method based on the Hessian-Affine local feature detector is proposed. The new method achieves comparable results with current state-of-the-art. The visual object categorisation performance was improved by using foreground segmentation based on saliency information, especially when the background could be considered as clutter.