A Classification of Tools for Learning Logic

A table showing a comparison and classification of tools (intelligent tutoring systems) for e-learning of Logic at a college level.

Power supply noise and logic error probability

Voltage fluctuations caused by parasitic impedances in the power supply rails of modern ICs are a major concern in nowadays ICs. The voltage fluctuations are spread out to the diverse nodes of the internal sections causing two effects: a degradation of performances mainly impacting gate delays anda noisy contamination of the quiescent levels of the logic that drives the node. Both effects are presented together, in thispaper, showing than both are a cause of errors in modern and future digital circuits. The paper groups both error mechanismsand shows how the global error rate is related with the voltage deviation and the period of the clock of the digital system.

Sovereign default, domestic banks and financial institutions

We present a model of sovereign debt in which, contrary to conventional wisdom, government defaultsare costly because they destroy the balance sheets of domestic banks. In our model, better financial institutionsallow banks to be more leveraged, thereby making them more vulnerable to sovereign defaults.Our predictions: government defaults should lead to declines in private credit, and these declines should belarger in countries where financial institutions are more developed and banks hold more government bonds.In these same countries, government defaults should be less likely. Using a large panel of countries, we findevidence consistent with these predictions.

Revenue Logic inSoftware Business Context

Tutkimuksen tavoitteena oli selvittää ohjelmistotoimialan avaintekijöitä, jotka vaikuttavat yrityksen ansaintalogiikkaan sekä lisätä tietoisuutta ansaintalogiikan muodostumisesta pienissä ja keskisuurissa ohjelmistoyrityksissä. Tutkimuksen teoreettisessa osassa keskityttiin tarkastelemaan ansaintalogiikan, strategian ja liiketoimintamallin käsitteiden suhteita sekä arvioitiin toimialan osatekijöiden, hinnoitteluperiaatteiden ja ansaintamallien vaikutusta ansainnan muodostumiseen ohjelmistotoimialalla. Ohjelmistotuote ja - palveluliiketoimintaa koskien oli merkityksellistä tutkia tuotteistamisasteen ja arvoketjujen vaikutusta ansaintalogiikan muodostumisessa sekä esitellä erilaisia, tyypillisiä ohjelmistotoimialalla käytettäviä hinnoittelumenetelmiä. Työn empiirisessä osassa tarkasteltiin 23 suomalaisen ohjelmistoalan yrityksen ansaintalogiikkaa. Tiedot kerättiin haastatteluin ja analysoitiin laadullisen tutkimuksen keinoin. Tutkimustulokset korostivat ansaintalogiikan 'epämääräisyyttä' terminä mutta osoittivat, että ydinliiketoimintaan keskittyminen, tuote-, palvelu-, tai projektiliiketoiminnan osaaminen, tuotteistusaste ja kanavavalinnat ovat avaintekijöitä ansaintalogiikanmuodostumisessa. Ansaintalogiikan muodostamiseen liittyy paljon yrityksen sisäisiä ja ulkoisia haasteita sekä muutospaineita, eikä ohjelmistotoimialalla ole todennettavissa yhtä yleismaailmallista, menestyksen takaavaa ansaintalogiikkaa.

Determinants of credit default swap spread: evidence from european credit derivatives market

Tämän tutkielman tavoitteena on selvittää, mitkä tekijät vaikuttavat yrityksen ja valtion velkakirjojen väliseen tuottoeroon. Strukturaalisten luottoriskin hinnoittelumallien mukaan luottoriskiin vaikuttavia tekijöitä ovat yrityksen velkaantumisaste, volatiliteetti ja riskitön korkokanta. Tavoitteena on erityisesti tutkia, kuinka hyvin nämä teoreettiset tekijät selittävät tuottoeroja ja onko olemassa muita tärkeitä selittäviä tekijöitä. Luottoriskinvaihtosopimusten noteerauksia käytetään tuottoerojen määrittämiseen. Selittävät tekijät koostuvat sekä yrityskohtaisista että markkinalaajuisista muuttujista. Luottoriskinvaihtosopimusten ja yrityskohtaisten muuttujien data on kerätty yhteensä 50 yritykselle Euroalueen maista. Aineisto koostuu kuukausittaisista havainnoista aikaväliltä 01.01.2003-31.12.2006. Empiiriset tulokset osoittavat, että strukturaalisten mallien mukaiset tekijät selittävät vain pienen osan tuottoeron muutoksista yli ajan. Toisaalta nämä teoreettiset tekijät selittävät huomattavasti paremmin tuottoeron vaihtelua yli poikkileikkauksen. Muut kuin teoreettiset tekijät pystyvät selittämään suuren osan tuottoeron vaihtelusta. Erityisen tärkeäksi tuottoeron selittäväksi tekijäksi osoittautui yleinen riskipreemio velkakirjamarkkinoilla. Tulokset osoittavat, että luottoriskin hinnoittelumalleja on kehitettävä edelleenniin, että ne ottaisivat huomioon yrityskohtaisten tekijöiden lisäksi myös markkinalaajuisia tekijöitä.

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.

Adding similarity-based reasoning capabilities to a Horn fragment of possibilistic logic with fuzzy constants

PLFC is a first-order possibilistic logic dealing with fuzzy constants and fuzzily restricted quantifiers. The refutation proof method in PLFC is mainly based on a generalized resolution rule which allows an implicit graded unification among fuzzy constants. However, unification for precise object constants is classical. In order to use PLFC for similarity-based reasoning, in this paper we extend a Horn-rule sublogic of PLFC with similarity-based unification of object constants. The Horn-rule sublogic of PLFC we consider deals only with disjunctive fuzzy constants and it is equipped with a simple and efficient version of PLFC proof method. At the semantic level, it is extended by equipping each sort with a fuzzy similarity relation, and at the syntactic level, by fuzzily “enlarging” each non-fuzzy object constant in the antecedent of a Horn-rule by means of a fuzzy similarity relation.

Formalizing argumentative reasoning in a possibilistic logic programming setting with fuzzy unification

Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating the treatment of possibilistic uncertainty at the object-language level. In spite of its expressive power, an important limitation in P-DeLP is that imprecise, fuzzy information cannot be expressed in the object language. One interesting alternative for solving this limitation is the use of PGL+, a possibilistic logic over Gödel logic extended with fuzzy constants. Fuzzy constants in PGL+ allow expressing disjunctive information about the unknown value of a variable, in the sense of a magnitude, modelled as a (unary) predicate. The aim of this article is twofold: firstly, we formalize DePGL+, a possibilistic defeasible logic programming language that extends P-DeLP through the use of PGL+ in order to incorporate fuzzy constants and a fuzzy unification mechanism for them. Secondly, we propose a way to handle conflicting arguments in the context of the extended framework.

A logic programming framework for possibilistic argumentation: formalization and logical properties

In the last decade defeasible argumentation frameworks have evolved to become a sound setting to formalize commonsense, qualitative reasoning. The logic programming paradigm has shown to be particularly useful for developing different argument-based frameworks on the basis of different variants of logic programming which incorporate defeasible rules. Most of such frameworks, however, are unable to deal with explicit uncertainty, nor with vague knowledge, as defeasibility is directly encoded in the object language. This paper presents Possibilistic Logic Programming (P-DeLP), a new logic programming language which combines features from argumentation theory and logic programming, incorporating as well the treatment of possibilistic uncertainty. Such features are formalized on the basis of PGL, a possibilistic logic based on G¨odel fuzzy logic. One of the applications of P-DeLP is providing an intelligent agent with non-monotonic, argumentative inference capabilities. In this paper we also provide a better understanding of such capabilities by defining two non-monotonic operators which model the expansion of a given program P by adding new weighed facts associated with argument conclusions and warranted literals, respectively. Different logical properties for the proposed operators are studied

Task-induced deactivation from rest extends beyond the default mode brain network

Activity decreases, or deactivations, of midline and parietal cortical brain regions are routinely observed in human functional neuroimaging studies that compare periods of task-based cognitive performance with passive states, such as rest. It is now widely held that such task-induced deactivations index a highly organized"default-mode network" (DMN): a large-scale brain system whose discovery has had broad implications in the study of human brain function and behavior. In this work, we show that common task-induced deactivations from rest also occur outside of the DMN as a function of increased task demand. Fifty healthy adult subjects performed two distinct functional magnetic resonance imaging tasks that were designed to reliably map deactivations from a resting baseline. As primary findings, increases in task demand consistently modulated the regional anatomy of DMN deactivation. At high levels of task demand, robust deactivation was observed in non-DMN regions, most notably, the posterior insular cortex. Deactivation of this region was directly implicated in a performance-based analysis of experienced task difficulty. Together, these findings suggest that task-induced deactivations from rest are not limited to the DMN and extend to brain regions typically associated with integrative sensory and interoceptive processes.