Institutionaaliset tekijätosuuskunnan johtamisessa ja hallinnoimisessa

Tutkimuksen tarkoituksena on osallistua omistajaohjauksen keskusteluun tuomalla esille institutionaalisen teorian tarjoamia mahdollisuuksia hah-mottaa ilmiötä. Tutkimuksen tavoitteena on ymmärtää ja kuvata sitä institu-tionaalista ympäristöä, jossa tuottaja- ja markkinointiosuuskunnat Suo-messa toimivat, selvittää millaisia vaikutuksia näillä ympäristön tekijöillä on osuuskunnan johtamiseen ja hallinnointiin sekä selvittää koetaanko toimin-taympäristön asettavan osuuskunnan toiminnalle pääomayhtiöistä poik-keavia paineita. Tutkimus on luonteeltaan laadullinen haastattelututkimus. Tutkimuksen empiirinen aineisto kerättiin haastattelemalla kolmea osuustoiminnan asi-antuntijaa sekä kuutta kohdeyritysten ylimmässä luottamusjohdossa ja operatiivisessa johdossa toimivaa henkilöä. Teemamuotoiset haastattelut suoritettiin marraskuun 2005 ja tammikuun 2006 välisenä aikana kohdeyri-tysten toimitiloissa. Tutkimustulokset osoittavat, että institutionaalisilla paineilla on vaikutuksia osuuskuntien omistajaohjaukseen. Osuuskuntien omistajaohjauksella on muista yritysmuodoista poikkeavia ominaispiirteitä erityisesti pääomaan ja johtamiseen liittyvissä institutionaalisissa tekijöissä. Osuuskuntien omista-jaohjauksen järjestelmät ovat toisaalta alttiina isomorfiselle muutokselle,jossa hallinnon rakenteet ja toimintamallit lähenevät erityisesti osakeyhti-öiden soveltamia rakenteita ja toimintamalleja.

A Topological Approach to Fuzzy Sets

This thesis presents a topological approach to studying fuzzy setsby means of modifier operators. Modifier operators are mathematical models, e.g., for hedges, and we present briefly different approaches to studying modifier operators. We are interested in compositional modifier operators, modifiers for short, and these modifiers depend on binary relations. We show that if a modifier depends on a reflexive and transitive binary relation on U, then there exists a unique topology on U such that this modifier is the closure operator in that topology. Also, if U is finite then there exists a lattice isomorphism between the class of all reflexive and transitive relations and the class of all topologies on U. We define topological similarity relation "≈" between L-fuzzy sets in an universe U, and show that the class LU/ ≈ is isomorphic with the class of all topologies on U, if U is finite and L is suitable. We consider finite bitopological spaces as approximation spaces, and we show that lower and upper approximations can be computed by means of α-level sets also in the case of equivalence relations. This means that approximations in the sense of Rough Set Theory can be computed by means of α-level sets. Finally, we present and application to data analysis: we study an approach to detecting dependencies of attributes in data base-like systems, called information systems.

A mathematical study of fuzzy logic; an algebraic approach

Fuzzy set theory and Fuzzy logic is studied from a mathematical point of view. The main goal is to investigatecommon mathematical structures in various fuzzy logical inference systems and to establish a general mathematical basis for fuzzy logic when considered as multi-valued logic. The study is composed of six distinct publications. The first paper deals with Mattila'sLPC+Ch Calculus. THis fuzzy inference system is an attempt to introduce linguistic objects to mathematical logic without defining these objects mathematically.LPC+Ch Calculus is analyzed from algebraic point of view and it is demonstratedthat suitable factorization of the set of well formed formulae (in fact, Lindenbaum algebra) leads to a structure called ET-algebra and introduced in the beginning of the paper. On its basis, all the theorems presented by Mattila and many others can be proved in a simple way which is demonstrated in the Lemmas 1 and 2and Propositions 1-3. The conclusion critically discusses some other issues of LPC+Ch Calculus, specially that no formal semantics for it is given.In the second paper the characterization of solvability of the relational equation RoX=T, where R, X, T are fuzzy relations, X the unknown one, and o the minimum-induced composition by Sanchez, is extended to compositions induced by more general products in the general value lattice. Moreover, the procedure also applies to systemsof equations. In the third publication common features in various fuzzy logicalsystems are investigated. It turns out that adjoint couples and residuated lattices are very often present, though not always explicitly expressed. Some minor new results are also proved.The fourth study concerns Novak's paper, in which Novak introduced first-order fuzzy logic and proved, among other things, the semantico-syntactical completeness of this logic. He also demonstrated that the algebra of his logic is a generalized residuated lattice. In proving that the examination of Novak's logic can be reduced to the examination of locally finite MV-algebras.In the fifth paper a multi-valued sentential logic with values of truth in an injective MV-algebra is introduced and the axiomatizability of this logic is proved. The paper developes some ideas of Goguen and generalizes the results of Pavelka on the unit interval. Our proof for the completeness is purely algebraic. A corollary of the Completeness Theorem is that fuzzy logic on the unit interval is semantically complete if, and only if the algebra of the valuesof truth is a complete MV-algebra. The Compactness Theorem holds in our well-defined fuzzy sentential logic, while the Deduction Theorem and the Finiteness Theorem do not. Because of its generality and good-behaviour, MV-valued logic can be regarded as a mathematical basis of fuzzy reasoning. The last paper is a continuation of the fifth study. The semantics and syntax of fuzzy predicate logic with values of truth in ana injective MV-algerba are introduced, and a list of universally valid sentences is established. The system is proved to be semanticallycomplete. This proof is based on an idea utilizing some elementary properties of injective MV-algebras and MV-homomorphisms, and is purely algebraic.

Background for Designing an Improved Digital Musical Keyboard Instrument

Electrical keyboard instruments and computer-aided music-making generally base on the piano keyboard that was developed for a tuning system no longer used. Alternative keyboard layout offers at least easier playing, faster adopting, new ways to play and better ergonomics. This thesis explores the development of keyboard instruments and tunings, and different keyboard layouts. This work is preliminary research for an electrical keyboard instrument to be implemented later on.

Structure learning of context-specific graphical models

Abstract The ultimate problem considered in this thesis is modeling a high-dimensional joint distribution over a set of discrete variables. For this purpose, we consider classes of context-specific graphical models and the main emphasis is on learning the structure of such models from data. Traditional graphical models compactly represent a joint distribution through a factorization justi ed by statements of conditional independence which are encoded by a graph structure. Context-speci c independence is a natural generalization of conditional independence that only holds in a certain context, speci ed by the conditioning variables. We introduce context-speci c generalizations of both Bayesian networks and Markov networks by including statements of context-specific independence which can be encoded as a part of the model structures. For the purpose of learning context-speci c model structures from data, we derive score functions, based on results from Bayesian statistics, by which the plausibility of a structure is assessed. To identify high-scoring structures, we construct stochastic and deterministic search algorithms designed to exploit the structural decomposition of our score functions. Numerical experiments on synthetic and real-world data show that the increased exibility of context-specific structures can more accurately emulate the dependence structure among the variables and thereby improve the predictive accuracy of the models.