Similarity measure based classification

Luokittelujärjestelmää suunniteltaessa tarkoituksena on rakentaa systeemi, joka pystyy ratkaisemaan mahdollisimman tarkasti tutkittavan ongelma-alueen. Hahmontunnistuksessa tunnistusjärjestelmän ydin on luokitin. Luokittelun sovellusaluekenttä on varsin laaja. Luokitinta tarvitaan mm. hahmontunnistusjärjestelmissä, joista kuvankäsittely toimii hyvänä esimerkkinä. Myös lääketieteen parissa tarkkaa luokittelua tarvitaan paljon. Esimerkiksi potilaan oireiden diagnosointiin tarvitaan luokitin, joka pystyy mittaustuloksista päättelemään mahdollisimman tarkasti, onko potilaalla kyseinen oire vai ei. Väitöskirjassa on tehty similaarisuusmittoihin perustuva luokitin ja sen toimintaa on tarkasteltu mm. lääketieteen paristatulevilla data-aineistoilla, joissa luokittelutehtävänä on tunnistaa potilaan oireen laatu. Väitöskirjassa esitetyn luokittimen etuna on sen yksinkertainen rakenne, josta johtuen se on helppo tehdä sekä ymmärtää. Toinen etu on luokittimentarkkuus. Luokitin saadaan luokittelemaan useita eri ongelmia hyvin tarkasti. Tämä on tärkeää varsinkin lääketieteen parissa, missä jo pieni tarkkuuden parannus luokittelutuloksessa on erittäin tärkeää. Väitöskirjassa ontutkittu useita eri mittoja, joilla voidaan mitata samankaltaisuutta. Mitoille löytyy myös useita parametreja, joille voidaan etsiä juuri kyseiseen luokitteluongelmaan sopivat arvot. Tämä parametrien optimointi ongelma-alueeseen sopivaksi voidaan suorittaa mm. evoluutionääri- algoritmeja käyttäen. Kyseisessä työssä tähän on käytetty geneettistä algoritmia ja differentiaali-evoluutioalgoritmia. Luokittimen etuna on sen joustavuus. Ongelma-alueelle on helppo vaihtaa similaarisuusmitta, jos kyseinen mitta ei ole sopiva tutkittavaan ongelma-alueeseen. Myös eri mittojen parametrien optimointi voi parantaa tuloksia huomattavasti. Kun käytetään eri esikäsittelymenetelmiä ennen luokittelua, tuloksia pystytään parantamaan.

Opetustoimen valtionosuuden laskennallisten yksikköhintojen soveltuvuus taloudellisuuden mittaamiseen ja arvioimiseen - Case toimiala, Imatran kaupungin koulutoimi

Tämän tutkimuksen päätavoitteena oli arvioida, voidaanko opetusministeriön vahvistamia opetustoimen yksikköhintoja pitää taloudellisuuden mittarina. Tutkimukseni kohdistui peruskoulun ja lukion valtionosuuden oppilaskohtaisiin laskennallisiin yksikköhintoihin ja musiikkiopiston muun koulutuksen ja työväenopiston opetustuntikohtaisiin laskennallisiin yksikköhintoihin. Julkinen talous pyrkii toiminnassaan myös mahdollisimman tehokkaisiin ja taloudellisiin ratkaisuihin. Toiminnan taloudellisuuden määrittämiseen tarvitaan mittareita ja vertailutietoa analysointia varten. Tutkimuksen tavoitteisiin pyrittiin toiminta-analyyttisellä tutkimusotteella, mutta siinä on nähtävissä myös käsiteanalyyttisiä piirteitä. Opetustoimen valtion rahoituksen muuttuessa laskennalliseksi, valtionhallinto kumosi vanhoja sääntöjä, puhuttiin ´normipurusta´. Aikaisempi valtionosuus perustui toteutuneisiin kustannuksiin. Uudistuksella haluttiin korostaa kuntien itsenäisyyttä, taloudellista omavastuisuutta ja tehokkuutta palvelujen järjestämisessä. Lisäksi kustannuksissa oletettiin syntyvän säätöjä, joiden oli määrä koitua kuntien hyväksi, kun valtionosuus ei määräytynyt hyväksyttyjen menojen mukaan. Taloudellisuus merkitsee yksikkökustannusten tunnistamista ja analysointia. Kunnan taloustavoitteita on pyrittävä mittaamaan tunnusluvuilla. Niille on asetettava hyväksyttävät tavoitearvot. Tunnuslukujen arvot eivät sellaisenaan kerro, miten hyvä tai huono toiminnan tulos on. Vasta niiden vertailu ja analysointi antavat kuvan tästä. Kuntien oppilaskohtainen yksikköhinta soveltuu hyvin peruskoulun ja lukion taloudellisuuden mittariksi. Samoin opetustuntikohtainen yksikköhinta musiikkiopiston ja kansalaisopiston taloudellisuuden mittariksi. Kuntien keskinäinen kustannusvertailu ja analysointi antavat hyvän pohjan löytää kustannusten taloudellisuuden taso.

Word Equations and Related Topics. Independence, Decidability and Characterizations

The three main topics of this work are independent systems and chains of word equations, parametric solutions of word equations on three unknowns, and unique decipherability in the monoid of regular languages. The most important result about independent systems is a new method giving an upper bound for their sizes in the case of three unknowns. The bound depends on the length of the shortest equation. This result has generalizations for decreasing chains and for more than three unknowns. The method also leads to shorter proofs and generalizations of some old results. Hmelevksii’s theorem states that every word equation on three unknowns has a parametric solution. We give a significantly simplified proof for this theorem. As a new result we estimate the lengths of parametric solutions and get a bound for the length of the minimal nontrivial solution and for the complexity of deciding whether such a solution exists. The unique decipherability problem asks whether given elements of some monoid form a code, that is, whether they satisfy a nontrivial equation. We give characterizations for when a collection of unary regular languages is a code. We also prove that it is undecidable whether a collection of binary regular languages is a code.

Feature selection using Fuzzy Entropy measures with Yu's Similarity measure

In this study, feature selection in classification based problems is highlighted. The role of feature selection methods is to select important features by discarding redundant and irrelevant features in the data set, we investigated this case by using fuzzy entropy measures. We developed fuzzy entropy based feature selection method using Yu's similarity and test this using similarity classifier. As the similarity classifier we used Yu's similarity, we tested our similarity on the real world data set which is dermatological data set. By performing feature selection based on fuzzy entropy measures before classification on our data set the empirical results were very promising, the highest classification accuracy of 98.83% was achieved when testing our similarity measure to the data set. The achieved results were then compared with some other results previously obtained using different similarity classifiers, the obtained results show better accuracy than the one achieved before. The used methods helped to reduce the dimensionality of the used data set, to speed up the computation time of a learning algorithm and therefore have simplified the classification task

Essays on auditor independence

Auditor independence is a cornerstone of the auditing profession and the basic principle that underpins the reputation of the auditing profession in the public eye. Indeed, it is the attribute most demanded from auditors by the public. Therefore, the sustainability of the auditing profession depends on how auditors can protect this principle. This dissertation consists of four interrelated essays concerned with auditor independence. Specifically, it examines situations that can threaten and impair auditor independence. In addition, this dissertation also examines several variables that may enhance and protect auditor independence. The first essay aims to examine the impact of social pressures occurring within audit firms on auditors’ judgment in the setting of a society with “high power distance” and “low individualism” cultural dimensions. The social pressures consisted of obedience pressure exerted by an auditor’s superior and conformity pressure exerted by an auditor’s colleague. Moreover, two moderating variables—a multi-dimensional professional commitment and locus of control—were included as moderator variables in the relationship between the social pressures faced by auditors and their judgment. The findings show that obedience and conformity pressures influence auditor judgment. Auditors who face the social pressures will make a judgment that may be even diametrically opposite to the independence principle. The findings also indicate that a multi-dimensional professional commitment and locus of control may potentially influence auditor judgment in a situation with social pressures. The second essay aims to investigate the association of advocacy and familiarity threats caused by auditor fee dependence and auditor tenure on auditor independence based on Finnish data, law, and auditing environment. This essay was motivated by the Green Paper on Audit Policy, published by the European Commission in 2010 that questions whether the maximum fee collected from a client should be regulated and whether consecutive assignments should be limited, among others. Contrary to popular belief, this essay does not find evidence that audit fees and long auditor tenure will jeopardise auditor independence. Therefore, the findings do not support policies to regulate auditor fees or limit auditor tenure in Finland. The third essay aims to examine the effect of client intimidation on auditor independence in an audit-client conflict situation. Intimidation threat is one of five independence threats that are explicitly referenced in the IFAC’s independence framework. Client intimidation was manifested in the client threatening to replace the auditor if the auditor did not adopt the client’s position. In addition, this essay examines the role of auditor’s perceived pressure and multi-dimensions of professional commitment as moderator variables. The findings suggest that auditors who experience client intimidation in an audit conflict situation are more likely to have their independence impaired than those who are in a similar situation but without client intimidation. Moreover, auditors who experience client intimidation perceive higher pressure than those who do not experience intimidation. Finally, auditors’ affective and continuance professional commitment dimensions moderate the relationship between auditors’ perceived pressures and auditor independence. The aim of the fourth essay is twofold. First, it aims to develop a scale for measuring auditors’ reputation awareness. Second, it aims to examine the correlation between the levels of auditor reputation awareness and auditor independence. A seven-item scale was developed as the reputation awareness scale. The findings indicate that the scale consists of one dimension. It also has a level of satisfactory reliability and a high level of validity. The findings show that there is a positive correlation between the level of auditors’ reputation awareness and auditor independence.

Context-specific independence in graphical models

The theme of this thesis is context-speci c independence in graphical models. Considering a system of stochastic variables it is often the case that the variables are dependent of each other. This can, for instance, be seen by measuring the covariance between a pair of variables. Using graphical models, it is possible to visualize the dependence structure found in a set of stochastic variables. Using ordinary graphical models, such as Markov networks, Bayesian networks, and Gaussian graphical models, the type of dependencies that can be modeled is limited to marginal and conditional (in)dependencies. The models introduced in this thesis enable the graphical representation of context-speci c independencies, i.e. conditional independencies that hold only in a subset of the outcome space of the conditioning variables. In the articles included in this thesis, we introduce several types of graphical models that can represent context-speci c independencies. Models for both discrete variables and continuous variables are considered. A wide range of properties are examined for the introduced models, including identi ability, robustness, scoring, and optimization. In one article, a predictive classi er which utilizes context-speci c independence models is introduced. This classi er clearly demonstrates the potential bene ts of the introduced models. The purpose of the material included in the thesis prior to the articles is to provide the basic theory needed to understand the articles.

Portfolio Selection via Composite Measure Analysis: Evidence from the U.S. Stock Market

The aim of this research is to examine the pricing anomalies existing in the U.S. market during 1986 to 2011. The sample of stocks is divided into decile portfolios based on seven individual valuation ratios (E/P, B/P, S/P, EBIT/EV, EVITDA/EV, D/P, and CE/P) and price momentum to investigate the efficiency of individual valuation ratio and their combinations as portfolio formation criteria. This is the first time in financial literature when CE/P is employed as a constituent of composite value measure. The combinations are based on median scaled composite value measures and TOPSIS method. During the sample period value portfolios significantly outperform both the market portfolio and comparable glamour portfolios. The results show the highest return for the value portfolio that was based on the combination of S/P & CE/P ratios. The outcome of this research will increase the understanding on the suitability of different methodologies for portfolio selection. It will help managers to take advantage of the results of different methodologies in order to gain returns above the market.