Livets källa kärleken : hälsans urkraft

This basic research focuses on the ethos of health and the human being's becoming in health. The theoretical perspective consists of the caring tradition within caring science developed at Åbo Akademy University. The aim of the present doctoral thesis is to uncover a new understanding as well as to deepen and attain a more nuanced understanding of the ethos of health, the essence of health, by penetrating to the core of what gives the human being the strength for experiencing a becoming in health. The research questions are as follows: l) What is the human being's source of strength? and 2) What reveals the source of strength so that the human being can perceive it and dedicate its strength in order to experience a becoming in health? The primary methodology used in the dissertation is hermeneutical. The material consists of the work Kärlekens gerningar by Kierkegaard, texts from focused interviews with respondents who have lived through severe personal suffering, as well as the book Det bländande mörkret by Wikström. These texts are interpreted through hermeneutical reading. The new horizon of understanding that emerges is reflected towards Eriksson's caritative theory, towards prior research within the tradition of caring science at Åbo Akademy University and towards previous national and international studies within this field. The new understanding shows that the human being's source of strength is love, the essence and origin of life. The substance of health is love, which, through the trinity of faith, hope and love, also makes possible the existence of the source of strength. Love has a deeper dignity than faith and hope, is connected with eternity and is the uniting link between temporality and eternity. The human being's inner longing entails an ontological attraction towards the source of strength. This source of strength is hidden, which provides and maintains its force, like a mystery connected with the darkness of suffering that hides the secret representing the source of strength, life's mystery, bu t w hi ch is revealed in both the darkness of suffering and in the light of joy. The dedication of strength requires freedom, willingness and courage to see the light, despite awareness of shame and guilt. Creative acts liberate the human being for the dedication of strength, which is preceded by a holy presence where, in solitude, the human being makes sacrifices for the sake of his or her human smallness and weakness, and allows himself or herself to be enclosed by the darkness of suffering to discover the light from the source. This entails being enraptured in a quiet "doing" in order to experience the beauty that bears witness to the holy which creates unity. The source of strength is revealed through beauty. The ethos of the human being and the ethos of health have the same fundamental substance, whilst the ethos of life possesses the deepest dimension and concerns the mysterious and infinite eternity. The ethos of life, eternity, which is a wellspring of strength, is not in itself strength-giving unless it is allied with love. Health can be understood in the light of life, of which death is an inevitable part. Life itself constitutes and creates the source which, through its alliance with eternity' s primordial wellspring of strength, generates strength from which the human being's source of strength, love, receives its eternal fervour. The human being is fundamentally interconnected with an abstract other, the first love, a universal wellspring of strength. Through Communion with this abstract other a dedication of the strength to experience a becoming in health becomes possible. Love for one's neighbour is the fundamental substance in the movement of becoming in health. Becoming in health presupposes a simultaneous movement in which the human being practices the human calling through ethos. As one loves one's neighbour through actions the still forces of eternity are in motion. When life emerges in the foreground and becomes the home of the human being, a dedication of the power of love is possible. Life itself determines the human being's becoming in health. A humble fundamental attitude towards life constitutes the basis for a continuous dedication of vitality from this source.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

Wood species identification by visual characterization of fibers

Kandidaatintyö tehtiin osana PulpVision-tutkimusprojektia, jonka tarkoituksena on kehittää kuvapohjaisia laskenta- ja luokittelumetodeja sellun laaduntarkkailuun paperin valmistuksessa. Tämän tutkimusprojektin osana on aiemmin kehitetty metodi, jolla etsittiin kaarevia rakenteita kuvista, ja tätä metodia hyödynnettiin kuitujen etsintään kuvista. Tätä metodia käytettiin lähtökohtana kandidaatintyölle. Työn tarkoituksena oli tutkia, voidaanko erilaisista kuitukuvista laskettujen piirteiden avulla tunnistaa kuvassa olevien kuitujen laji. Näissä kuitukuvissa oli kuituja neljästä eri puulajista ja yhdestä kasvista. Nämä lajit olivat akasia, koivu, mänty, eukalyptus ja vehnä. Jokaisesta lajista valittiin 100 kuitukuvaa ja nämä kuvat jaettiin kahteen ryhmään, joista ensimmäistä käytettiin opetusryhmänä ja toista testausryhmänä. Opetusryhmän avulla jokaiselle kuitulajille laskettiin näitä kuvaavia piirteitä, joiden avulla pyrittiin tunnistamaan testausryhmän kuvissa olevat kuitulajit. Nämä kuvat oli tuottanut CEMIS-Oulu (Center for Measurement and Information Systems), joka on mittaustekniikkaan keskittynyt yksikkö Oulun yliopistossa. Yksittäiselle opetusryhmän kuitukuvalle laskettiin keskiarvot ja keskihajonnat kolmesta eri piirteestä, jotka olivat pituus, leveys ja kaarevuus. Lisäksi laskettiin, kuinka monta kuitua kuvasta löydettiin. Näiden piirteiden eri yhdistelmien avulla testattiin tunnistamisen tarkkuutta käyttämällä k:n lähimmän naapurin menetelmää ja Naiivi Bayes -luokitinta testausryhmän kuville. Testeistä saatiin lupaavia tuloksia muun muassa pituuden ja leveyden keskiarvoja käytettäessä saavutettiin jopa noin 98 %:n tarkkuus molemmilla algoritmeilla. Tunnistuksessa kuitujen keskimäärinen pituus vaikutti olevan kuitukuvia parhaiten kuvaava piirre. Käytettyjen algoritmien välillä ei ollut suurta vaihtelua tarkkuudessa. Testeissä saatujen tulosten perusteella voidaan todeta, että kuitukuvien tunnistaminen on mahdollista. Testien perusteella kuitukuvista tarvitsee laskea vain kaksi piirrettä, joilla kuidut voidaan tunnistaa tarkasti. Käytetyt lajittelualgoritmit olivat hyvin yksinkertaisia, mutta ne toimivat testeissä hyvin.

Future of Internet News Portals after the Case of Delfi

The thesis analyzes liability of Internet news portals for third-party defamatory comments. After the case of Delfi AS v. Estonia, decided by the Grand Chamber of the European Court of Human Rights on 16 June 2015, a portal can be held liable for user-generated unlawful comments. The thesis aims at exploring consequences of the case of Delfi for Internet news portals’ business model. The model is described as a mixture of two modes of information production: traditional industrial information economy and new networked information economy. Additionally, the model has a generative comment environment. I name this model “the Delfian model”. The thesis analyzes three possible strategies which portals will likely apply in the nearest future. I will discuss these strategies from two perspectives: first, how each strategy can affect the Delfian model and, second, how changes in the model can, in their turn, affect freedom of expression. The thesis is based on the analysis of case law, legal, and law and economics literature. I follow the law and technology approach in the vein of ideas developed by Lawrence Lessig, Yochai Benkler and Jonathan Zittrain. The Delfian model is researched as an example of a local battle between industrial and networked information economy modes. The thesis concludes that this local battle is lost because the Delfian model has to be replaced with a new walled-garden model. Such a change can seriously endanger freedom of expression.