Choice of Business Process Modeling Methodology - Case Northern Dimension Research Centre (NORDI) in Lappeenranta University of Technology

The main outcome of the master thesis is innovative solution, which can support a choice of business process modeling methodology. Potential users of this tool are people with background in business process modeling and possibilities to collect required information about organization’s business processes. Master thesis states the importance of business process modeling in implementation of strategic goals of organization. It is made by revealing the place of the concept in Business Process Management (BPM) and its particular case Business Process Reengineering (BPR). In order to support the theoretical outcomes of the thesis a case study of Northern Dimension Research Centre (NORDI) in Lappeenranta University of Technology was conducted. On its example several solutions are shown: how to apply business process modeling methodologies in practice; in which way business process models can be useful for BPM and BPR initiatives; how to apply proposed innovative solution for a choice of business process modeling methodology.

Threat modeling a factory environment using Microsoft Security Development Lifecycle methodology

The number of security violations is increasing and a security breach could have irreversible impacts to business. There are several ways to improve organization security, but some of them may be difficult to comprehend. This thesis demystifies threat modeling as part of secure system development. Threat modeling enables developers to reveal previously undetected security issues from computer systems. It offers a structured approach for organizations to find and address threats against vulnerabilities. When implemented correctly threat modeling will reduce the amount of defects and malicious attempts against the target environment. In this thesis Microsoft Security Development Lifecycle (SDL) is introduced as an effective methodology for reducing defects in the target system. SDL is traditionally meant to be used in software development, principles can be however partially adapted to IT-infrastructure development. Microsoft threat modeling methodology is an important part of SDL and it is utilized in this thesis to find threats from the Acme Corporation’s factory environment. Acme Corporation is used as a pseudonym for a company providing high-technology consumer electronics. Target for threat modeling is the IT-infrastructure of factory’s manufacturing execution system. Microsoft threat modeling methodology utilizes STRIDE –mnemonic and data flow diagrams to find threats. Threat modeling in this thesis returned results that were important for the organization. Acme Corporation now has more comprehensive understanding concerning IT-infrastructure of the manufacturing execution system. On top of vulnerability related results threat modeling provided coherent views of the target system. Subject matter experts from different areas can now agree upon functions and dependencies of the target system. Threat modeling was recognized as a useful activity for improving security.

MCMC Analysis Of Classical Time Series Algorithms

Identification of order of an Autoregressive Moving Average Model (ARMA) by the usual graphical method is subjective. Hence, there is a need of developing a technique to identify the order without employing the graphical investigation of series autocorrelations. To avoid subjectivity, this thesis focuses on determining the order of the Autoregressive Moving Average Model using Reversible Jump Markov Chain Monte Carlo (RJMCMC). The RJMCMC selects the model from a set of the models suggested by better fitting, standard deviation errors and the frequency of accepted data. Together with deep analysis of the classical Box-Jenkins modeling methodology the integration with MCMC algorithms has been focused through parameter estimation and model fitting of ARMA models. This helps to verify how well the MCMC algorithms can treat the ARMA models, by comparing the results with graphical method. It has been seen that the MCMC produced better results than the classical time series approach.

Tutorials for MeVEA Simulation Software

The objective of the thesis was to create three tutorials for MeVEA Simulation Software to instruct the new users to the modeling methodology used in the MeVEA Simulation Software. MeVEA Simulation Software is a real-time simulation software based on multibody dynamics. The simulation software is designed to create simulation models of complete mechatronical system. The thesis begins with a more detail description of the MeVEA Simulation Software and its components. The thesis presents the three simulation models and written theory of the steps of model creation. The first tutorial introduces the basic features which are used in most simulation models. The basic features include bodies, constrains, forces, basic hydraulics and motors. The second tutorial introduces the power transmission components, tyres and user input definitions for the different components in power transmission systems. The third tutorial introduces the definitions of two different types of collisions and collision graphics used in MeVEA Simulation Software.

Linguistic models for decision support

Linguistic modelling is a rather new branch of mathematics that is still undergoing rapid development. It is closely related to fuzzy set theory and fuzzy logic, but knowledge and experience from other fields of mathematics, as well as other fields of science including linguistics and behavioral sciences, is also necessary to build appropriate mathematical models. This topic has received considerable attention as it provides tools for mathematical representation of the most common means of human communication - natural language. Adding a natural language level to mathematical models can provide an interface between the mathematical representation of the modelled system and the user of the model - one that is sufficiently easy to use and understand, but yet conveys all the information necessary to avoid misinterpretations. It is, however, not a trivial task and the link between the linguistic and computational level of such models has to be established and maintained properly during the whole modelling process. In this thesis, we focus on the relationship between the linguistic and the mathematical level of decision support models. We discuss several important issues concerning the mathematical representation of meaning of linguistic expressions, their transformation into the language of mathematics and the retranslation of mathematical outputs back into natural language. In the first part of the thesis, our view of the linguistic modelling for decision support is presented and the main guidelines for building linguistic models for real-life decision support that are the basis of our modeling methodology are outlined. From the theoretical point of view, the issues of representation of meaning of linguistic terms, computations with these representations and the retranslation process back into the linguistic level (linguistic approximation) are studied in this part of the thesis. We focus on the reasonability of operations with the meanings of linguistic terms, the correspondence of the linguistic and mathematical level of the models and on proper presentation of appropriate outputs. We also discuss several issues concerning the ethical aspects of decision support - particularly the loss of meaning due to the transformation of mathematical outputs into natural language and the issue or responsibility for the final decisions. In the second part several case studies of real-life problems are presented. These provide background and necessary context and motivation for the mathematical results and models presented in this part. A linguistic decision support model for disaster management is presented here – formulated as a fuzzy linear programming problem and a heuristic solution to it is proposed. Uncertainty of outputs, expert knowledge concerning disaster response practice and the necessity of obtaining outputs that are easy to interpret (and available in very short time) are reflected in the design of the model. Saaty’s analytic hierarchy process (AHP) is considered in two case studies - first in the context of the evaluation of works of art, where a weak consistency condition is introduced and an adaptation of AHP for large matrices of preference intensities is presented. The second AHP case-study deals with the fuzzified version of AHP and its use for evaluation purposes – particularly the integration of peer-review into the evaluation of R&D outputs is considered. In the context of HR management, we present a fuzzy rule based evaluation model (academic faculty evaluation is considered) constructed to provide outputs that do not require linguistic approximation and are easily transformed into graphical information. This is achieved by designing a specific form of fuzzy inference. Finally the last case study is from the area of humanities - psychological diagnostics is considered and a linguistic fuzzy model for the interpretation of outputs of multidimensional questionnaires is suggested. The issue of the quality of data in mathematical classification models is also studied here. A modification of the receiver operating characteristics (ROC) method is presented to reflect variable quality of data instances in the validation set during classifier performance assessment. Twelve publications on which the author participated are appended as a third part of this thesis. These summarize the mathematical results and provide a closer insight into the issues of the practicalapplications that are considered in the second part of the thesis.

Pituusleikkureiden 3D-suunnittelun kehittäminen

Tämä diplomityö tehtiin Valmet Technologies Oy:n Järvenpään toimipisteelle. Työn tavoitteena oli tutkia miten pituusleikkureiden 3D-suunnittelua voidaan tehostaa hyödyntämällä uuden 3D-CAD -järjestelmän ominaisuuksia optimaalisesti. Työ koostuu teoriaosuudesta, haastattelututkimuksesta sekä käytännön osuudesta. Teoriaosuudessa perehdytään pituusleikkurin toimintaan ja rakenteeseen, 3D-suunnittelun teoriaan sekä CATIA-järjestelmään. Teoriaosuudessa etsitään myös uusia näkökulmia 3D-suunnitteluun. Haastattelututkimuksessa kartoitetaan nykyinen suunnitteluprosessi, suunnittelun kehitettäviä kohteita, sekä käytössä olevia suunnittelumenetelmiä, jotka ovat todettu toimiviksi. Haastattelututkimuksessa haastatellaan Valmet Technologies Oy:n Järvenpään toimipisteessä työskenteleviä pituusleikkureiden pääsuunnittelijoita sekä heidän esimiehiään. Lisäksi erillisten haastattelujen avulla kerätään kokemuksia CATIA V6 -ohjelmiston käytöstä sekä suunnitteluohjelmiston vaihtumisesta. Käytännön osuuden tavoitteena on arvioida pituusleikkurin parametroitujen mallirakenteiden siirtämiseen sekä korjauksiin kuluvia aikamääriä kyseisiin toimenpiteisiin tarvittavien resurssien määrittämiseksi. Käytännön osuudessa siirretään kaksi Valmet OptiWin Drum Compact -pituusleikkurin parametroitua osakokonaisuutta uuteen CAD-järjestelmään ja niille suoritetaan tarvittavat korjaustoimenpiteet Tutkimuksen tulosten perusteella yhteisen mallinnusmetodologian puuttuminen on merkittävin kehityskohde suunnittelun kehittämisessä. Lopuksi luotiin kehitysehdotukset sekä implementointisuunnitelma, joiden avulla pituusleikkureiden 3D-suunnittelua voidaan kehittää ja CATIA V6 -ohjelmisto voidaan ottaa käyttöön tehokkaasti.

Financial Modeling to Support Organizational Control

Tutkimus tarkastelee taloudellisia mallintamismahdollisuuksia metsäteollisuuden liiketoimintayksikössä. Tavoitteena on suunnitella ja luoda taloudellinen malli liiketoimintayksikölle, jonka avulla sen tuloksen analysoiminen ja ennustaminen on mahdollista. Tutkimusta tarkastellaan konstruktiivisen tutkimusmenetelmän avulla. Teoreettinen viitekehys tarkastelee olemassa olevan informaation muotoilemista keskittyen tiedon jalostamisen tarpeisiin, päätöksenteon asettamiin vaatimuksiin sekä mallintamiseen. Toiseksi, teoria esittää informaatiolle asetettavia vaatimuksia organisatorisen ohjauksen näkökulmasta.Empiirinen tieto kerätään osallistuvan havainnoinnin avulla hyödyntäen epävirallisia keskusteluja, tietojärjestelmiä ja laskentatoimen dokumentteja. Tulokset osoittavat, että liikevoiton ennustaminen mallin avulla on vaikeaa, koska taustalla vaikuttavien muuttujien määrä on suuri. Tästä johtuen malli täytyykin rakentaa niin, että se tarkastelee liikevoittoa niin yksityiskohtaisella tasolla kuin mahdollista. Testauksessa mallin tarkkuus osoittautui sitä paremmaksi, mitä tarkemmalla tasolla ennustaminen tapahtui. Lisäksi testaus osoitti, että malli on käyttökelpoinen liiketoiminnan ohjauksessa lyhyellä aikavälillä. Näin se luo myös pohjan pitkän aikavälin ennustamiselle.

A software engineering approach to distributed systems for composite modeling

The goal of this thesis is to define and validate a software engineering approach for the development of a distributed system for the modeling of composite materials, based on the analysis of various existing software development methods. We reviewed the main features of: (1) software engineering methodologies; (2) distributed system characteristics and their effect on software development; (3) composite materials modeling activities and the requirements for the software development. Using the design science as a research methodology, the distributed system for creating models of composite materials is created and evaluated. Empirical experiments which we conducted showed good convergence of modeled and real processes. During the study, we paid attention to the matter of complexity and importance of distributed system and a deep understanding of modern software engineering methods and tools.

A conspectus on estimating function theory and its applicability to recurrent modeling issues in forest biometry

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Modeling Forest Growth with Management Data: A Matrix Approach for the Italian Alps

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