Lautanauhaohjeen muodostus tavoitekuviosta geneettisellä algoritmilla

Lautanauhatekniikka on monipuolinen menetelmä esimerkiksi kuvioitujen nauhojen kutomiseen, mutta uusien kuvioaiheiden suunnittelu, tai aloittelijalle jo valmiiden ohjeettomien kuviomallien jäljittely, voi helposti käydä työlääksi menetelmän ominaispiirteiden johdosta. Tämän työn tavoitteena oli kehittää ohjelmallinen työkalu auttamaan näissä ongelmissa automatisoimalla kudontaohjeen etsintä käyttäjän laatimalle tavoitekuviolle. Ratkaisumenetelmän perustaksi valittiin geneettinen algoritmi, minkä johdosta työn keskeisintutkimusongelma oli kartoittaa algoritmin perusoperaatioiden parametrien ja tavoitekuvion kompleksisuuden keskinäisiä riippuvuuksia riittävästi toimivien arvosuositusten antamiseen ohjelman tulevassa käytännön käytössä. Työssä ei kehitetty sovellusalueeseen mukautettuja evoluutiooperaatioita, vaan keskityttiin luomaan hyvin tunnetuista elementeistä perusta, jota voi myöhemmin kehittää eteenpäin.

Inversion and assimilation methods with applications in geophysical remote sensing

Stratospheric ozone can be measured accurately using a limb scatter remote sensing technique at the UV-visible spectral region of solar light. The advantages of this technique includes a good vertical resolution and a good daytime coverage of the measurements. In addition to ozone, UV-visible limb scatter measurements contain information about NO2, NO3, OClO, BrO and aerosols. There are currently several satellite instruments continuously scanning the atmosphere and measuring the UVvisible region of the spectrum, e.g., the Optical Spectrograph and Infrared Imager System (OSIRIS) launched on the Odin satellite in February 2001, and the Scanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY (SCIAMACHY) launched on Envisat in March 2002. Envisat also carries the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument, which also measures limb-scattered sunlight under bright limb occultation conditions. These conditions occur during daytime occultation measurements. The global coverage of the satellite measurements is far better than any other ozone measurement technique, but still the measurements are sparse in the spatial domain. Measurements are also repeated relatively rarely over a certain area, and the composition of the Earth’s atmosphere changes dynamically. Assimilation methods are therefore needed in order to combine the information of the measurements with the atmospheric model. In recent years, the focus of assimilation algorithm research has turned towards filtering methods. The traditional Extended Kalman filter (EKF) method takes into account not only the uncertainty of the measurements, but also the uncertainty of the evolution model of the system. However, the computational cost of full blown EKF increases rapidly as the number of the model parameters increases. Therefore the EKF method cannot be applied directly to the stratospheric ozone assimilation problem. The work in this thesis is devoted to the development of inversion methods for satellite instruments and the development of assimilation methods used with atmospheric models.

Uso de perfis cromatográficos de voláteis de cafés arábicas torrados para a diferenciação das amostras segundo o sabor, o aroma e a qualidade global da bebida

In this work, the volatile chromatographic profiles of roasted Arabica coffees, previously analyzed for their sensorial attributes, were explored by principal component analysis. The volatile extraction technique used was the solid phase microextraction. The correlation optimized warping algorithm was used to align the gas chromatographic profiles. Fifty four compounds were found to be related to the sensorial attributes investigated. The volatiles pyrrole, 1-methyl-pyrrole, cyclopentanone, dihydro-2-methyl-3-furanone, furfural, 2-ethyl-5-methyl-pyrazine, 2-etenyl-n-methyl-pyrazine, 5-methyl-2-propionyl-furan compounds were important for the differentiation of coffee beverage according to the flavour, cleanliness and overall quality. Two figures of merit, sensitivity and specificity (or selectivity), were used to interpret the sensory attributes studied.

Preventive diagnosis of dairy cow lameness

This research aimed to develop a Fuzzy inference based on expert system to help preventing lameness in dairy cattle. Hoof length, nutritional parameters and floor material properties (roughness) were used to build the Fuzzy inference system. The expert system architecture was defined using Unified Modelling Language (UML). Data were collected in a commercial dairy herd using two different subgroups (H1 and H2), in order to validate the Fuzzy inference functions. The numbers of True Positive (TP), False Positive (FP), True Negative (TN), and False Negative (FN) responses were used to build the classifier system up, after an established gold standard comparison. A Lesion Incidence Possibility (LIP) developed function indicates the chances of a cow becoming lame. The obtained lameness percentage in H1 and H2 was 8.40% and 1.77%, respectively. The system estimated a Lesion Incidence Possibility (LIP) of 5.00% and 2.00% in H1 and H2, respectively. The system simulation presented 3.40% difference from real cattle lameness data for H1, while for H2, it was 0.23%; indicating the system efficiency in decision-making.

Innovaatioprosessin alkupään toimintamalli ja päätöksenteko

Työn tavoitteena oli tutkia innovaatioita ja organisaation innovaatiokyvykkyyttä, innovaatiokyvykkyyden taustatekijöitä sekä innovaatioprosessin alkupään (Fuzzy Front End, FFE) sekä siinä tapahtuvan päätöksenteon johtamista. Lisäksi tavoitteena oli suunnitella innovaatioprosessin alkupään toimintamalli selkeyttämään toimintaa prosessin alkupäässä sekä antaa toimenpide-ehdotuksia ja suosituksia. Tutkimuksen teoriaosuus tehtiin kirjallisuustutkimuksena. Tutkimuksen empiirinen osuus suoritettiin case -analyysinä yrityksen henkilöhaastattelu- ja toimintatutkimuksen muodossa. Innovaatioprosessin alkupäähän on tunnistettu toimintamalleja, joilla selkeytetään ja tehostetaan prosessin alkupään vaiheita. Vaiheet ovat mahdollisuuksien tunnistaminen, mahdollisuuksien analysointi, ideointi, ideoiden valitseminen ja konsepti- ja teknologiakehitys. Innovaatioprosessin rinnalla kulkee päätöksenteon prosessi, jonka suhteen tunnistetaan selkeät päätöksentekokohdat ja kriteerit prosessissa etenemiselle. Innovaatio- ja päätöksentekoprosessiin osallistuu eri vaiheissa sekä yrityksen sisäiset, kuten henkilöstö, että ulkoiset, kuten asiakkaat, toimittajat ja verkostokumppanit, sidosryhmät. Lisäksi innovaatioprosessin toimintaan vaikuttavat johdon tuki ja sitoutuminen, osallistujien kyky luovuuteen sekä muut innovaatiokyvykkyyden taustatekijät. Kaikki nämä tekijät tulee huomioida innovaatioprosessin alkupään mallia suunniteltaessa. Tutkimus tehtiin tietoliikennealan yrityksen tarpeisiin. Yrityksessä on käytössä aloitetoimintaa, mutta sen ei koeta tarjoavan riittävästi ideoita yrityksen tuotekehityksen tarpeisiin. Yrityksen henkilöstön innovaatiopotentiaali on suuri, mikä halutaan hyödyntää paremmin suunnittelemalla yrityksen käyttöön soveltuva, innovaatioprosessin alkupään toimintaan ohjaava, vakioitu ja henkilöstöä ja muita yhteistyötahoja, kuten asiakkaita, osallistava toimintamalli. Toimenpide-ehdotuksina ja suosituksina esitetään innovaatioprosessin alkupään johtamisen toimintamallia. Esitetyssä mallissa määritellään vaiheet, menetelmät, päätöksenteko ja vastuut. Toimintamalli esitetään soveltuen yhdistettäväksi yrityksessä käytössä olevaan innovaatioprosessin loppupään, tuotekehitysprojektien läpiviemisen, malliin.

Creating possibilities for collective creativity : Brokerage Functions in Practice-Based Innovation

In the network era, creative achievements like innovations are more and more often created in interaction among different actors. The complexity of today‘s problems transcends the individual human mind, requiring not only individual but also collective creativity. In collective creativity, it is impossible to trace the source of new ideas to an individual. Instead, creative activity emerges from the collaboration and contribution of many individuals, thereby blurring the contribution of specific individuals in creating ideas. Collective creativity is often associated with diversity of knowledge, skills, experiences and perspectives. Collaboration between diverse actors thus triggers creativity and gives possibilities for collective creativity. This dissertation investigates collective creativity in the context of practice-based innovation. Practice-based innovation processes are triggered by problem setting in a practical context and conducted in non-linear processes utilising scientific and practical knowledge production and creation in cross-disciplinary innovation networks. In these networks diversity or distances between innovation actors are essential. Innovation potential may be found in exploiting different kinds of distances. This dissertation presents different kinds of distances, such as cognitive, functional and organisational which could be considered as sources of creativity and thus innovation. However, formation and functioning of these kinds of innovation networks can be problematic. Distances between innovating actors may be so great that a special interpretation function is needed – that is, brokerage. This dissertation defines factors that enhance collective creativity in practice-based innovation and especially in the fuzzy front end phase of innovation processes. The first objective of this dissertation is to study individual and collective creativity at the employee level and identify those factors that support individual and collective creativity in the organisation. The second objective is to study how organisations use external knowledge to support collective creativity in their innovation processes in open multi-actor innovation. The third objective is to define how brokerage functions create possibilities for collective creativity especially in the context of practice-based innovation. The research objectives have been studied through five substudies using a case-study strategy. Each substudy highlights various aspects of creativity and collective creativity. The empirical data consist of materials from innovation projects arranged in the Lahti region, Finland, or materials from the development of innovation methods in the Lahti region. The Lahti region has been chosen as the research context because the innovation policy of the region emphasises especially the promotion of practice-based innovations. The results of this dissertation indicate that all possibilities of collective creativity are not utilised in internal operations of organisations. The dissertation introduces several factors that could support collective creativity in organisations. However, creativity as a social construct is understood and experienced differently in different organisations, and these differences should be taken into account when supporting creativity in organisations. The increasing complexity of most potential innovations requires collaborative creative efforts that often exceed the boundaries of the organisation and call for the involvement of external expertise. In practice-based innovation different distances are considered as sources of creativity. This dissertation gives practical implications on how it is possible to exploit different kinds of distances knowingly. It underlines especially the importance of brokerage functions in open, practice-based innovation in order to create possibilities for collective creativity. As a contribution of this dissertation, a model of brokerage functions in practice-based innovation is formulated. According to the model, the results and success of brokerage functions are based on the context of brokerage as well as the roles, tasks, skills and capabilities of brokers. The brokerage functions in practice-based innovation are also possible to divide into social and cognitive brokerage.

Sumea suositin elokuville

Suositusmenetelmien tarkoituksena on auttaa käyttäjää löytämään häntä kiinnostavia asioita ja välttämään asioita, joista hän ei pitäisi. Suositusmenetelmät antavat suosituk- set yleensä terävinä lukuina. Tässä työssä kehitetään suositusmenetelmä, joka antaa suo- situkset arvosanojen sumeina jäsenyysasteina. Menetelmän antamat suositukset voidaan myös perustella käyttäjälle. Menetelmä kuuluu pääosin yhteisösuodatusmenetelmiin, jois- sa suositukset tehdään käyttäjien antamien arvosanojen perusteella, mutta myös tietoa elokuvien tyylilajeista hyödynnetään suositustarkkuuden parantamiseksi. Sumeiden suo- situsten suositeltavuusjärjestyksen laskemiseen esitetään myös menetelmä. Käyttäjien elokuville antamat arvosanat voidaan käsittää sumeana datana. Käyttäjä voi kuvata arvosanaa esimerkiksi ilmaisulla ”noin 4”. Tästä syystä on loogista esittää suo- situksetkin sumeina lukuina. Tällöin käyttäjälle voidaan antaa tietoa suosituksen tark- kuudesta ja mahdollisista ristiriidoista. Epävarmojen suositusten tapauksessa käyttäjä voi painottaa enemmän muita tietolähteitä. Kokeiden perusteella kehitetty menetelmä antaa joissa tapauksissa selvästi vertailtavia menetelmiä parempia suosituksia, kun taas toisissa tapauksissa suositukset ovat selvästi heikompia.

Novel Methods for Error Modeling and Parameter Identification of a Redundant Serial-Parallel Hybrid Robot

To obtain the desirable accuracy of a robot, there are two techniques available. The first option would be to make the robot match the nominal mathematic model. In other words, the manufacturing and assembling tolerances of every part would be extremely tight so that all of the various parameters would match the “design” or “nominal” values as closely as possible. This method can satisfy most of the accuracy requirements， but the cost would increase dramatically as the accuracy requirement increases. Alternatively, a more cost-effective solution is to build a manipulator with relaxed manufacturing and assembling tolerances. By modifying the mathematical model in the controller, the actual errors of the robot can be compensated. This is the essence of robot calibration. Simply put, robot calibration is the process of defining an appropriate error model and then identifying the various parameter errors that make the error model match the robot as closely as possible. This work focuses on kinematic calibration of a 10 degree-of-freedom (DOF) redundant serial-parallel hybrid robot. The robot consists of a 4-DOF serial mechanism and a 6-DOF hexapod parallel manipulator. The redundant 4-DOF serial structure is used to enlarge workspace and the 6-DOF hexapod manipulator is used to provide high load capabilities and stiffness for the whole structure. The main objective of the study is to develop a suitable calibration method to improve the accuracy of the redundant serial-parallel hybrid robot. To this end, a Denavit–Hartenberg (DH) hybrid error model and a Product-of-Exponential (POE) error model are developed for error modeling of the proposed robot. Furthermore, two kinds of global optimization methods, i.e. the differential-evolution (DE) algorithm and the Markov Chain Monte Carlo (MCMC) algorithm, are employed to identify the parameter errors of the derived error model. A measurement method based on a 3-2-1 wire-based pose estimation system is proposed and implemented in a Solidworks environment to simulate the real experimental validations. Numerical simulations and Solidworks prototype-model validations are carried out on the hybrid robot to verify the effectiveness, accuracy and robustness of the calibration algorithms.

Strategic external deployment of intellectual assets

Globalization, pervasiveness of technology and ICT, and the buildup of information societies and policies have lead to a growing abundance of knowledge and highly educated labour supply that is distributed widely. These changes have shifted the foundation of competitiveness to valuable knowledge resources which are now distributed widely across the globe, across actors in the value chain and across educated individuals in multiple organizations. Against this backdrop, the paradigm of open innovation (OI) has emerged as a new response to managing the increased amount of boundary-spanning knowledge flows in and out of the innovation process. The outbound mode of open innovation, that is to say the external exploitation of knowledge assets outside of the firm’s own products and services, has been the less-researched aspect of the concept and so far typically seen as concerning the outlicensing of unused technological assets to generate additional revenue. Given that open innovation is essentially a framework for the holistic structuring and management of crossboundary knowledge flows to improve a firm’s innovative performance, a close integration to corporate strategy seems imperative in order to fully benefit from it. Integrating open innovation to strategy leads to elevating its role from a fringe activity to a central innovation management issue that needs to be systematically managed. Building a structure that allows effective management necessitates linking open innovation activities to each phase of the innovation process. Previously, the connection between outbound OI and the earlier stages of innovation has not been studied. The thesis finds that connecting outbound OI to the entire innovation process of the firm, including the fuzzy front end of innovation, is critical for attaining strategic objectives and to the successful implementation and management of the activity. The practical purpose for the research is to enable companies to fully utilize their potential for outbound open innovation and to be able to implement and manage it from a strategic standpoint.

Evaluation of Bubble Formation and Break Up in Suppression Pools by Using Pattern Recognition Methods

During a possible loss of coolant accident in BWRs, a large amount of steam will be released from the reactor pressure vessel to the suppression pool. Steam will be condensed into the suppression pool causing dynamic and structural loads to the pool. The formation and break up of bubbles can be measured by visual observation using a suitable pattern recognition algorithm. The aim of this study was to improve the preliminary pattern recognition algorithm, developed by Vesa Tanskanen in his doctoral dissertation, by using MATLAB. Video material from the PPOOLEX test facility, recorded during thermal stratification and mixing experiments, was used as a reference in the development of the algorithm. The developed algorithm consists of two parts: the pattern recognition of the bubbles and the analysis of recognized bubble images. The bubble recognition works well, but some errors will appear due to the complex structure of the pool. The results of the image analysis were reasonable. The volume and the surface area of the bubbles were not evaluated. Chugging frequencies calculated by using FFT fitted well into the results of oscillation frequencies measured in the experiments. The pattern recognition algorithm works in the conditions it is designed for. If the measurement configuration will be changed, some modifications have to be done. Numerous improvements are proposed for the future 3D equipment.

ERP Systems as Investments: Analysing Costs vs. Benefits

An ERP system investment analysis method using a Fuzzy Pay-Off approach for Real Option valuation is examined. It is studied, how the investment can be incrementally adopted and analyzed as a compounding Real Option model. The modeling allows follow-up. IS system development model COCOMO is presented as an example for investment analysis. The thesis presents the usage of Real Options as an alternative for the valuation of an investment. An idea is presented to use a continuous investment follow-up during the investment. This analysis can be performed using Real Options. As a tool for the analysis, the Fuzzy Pay-Off method is presented as an alternative for investment valuation.

Stiffness based trajectory planning and feedforward based vibration suppression control of parallel robot machines

The dissertation proposes two control strategies, which include the trajectory planning and vibration suppression, for a kinematic redundant serial-parallel robot machine, with the aim of attaining the satisfactory machining performance. For a given prescribed trajectory of the robot's end-effector in the Cartesian space, a set of trajectories in the robot's joint space are generated based on the best stiffness performance of the robot along the prescribed trajectory. To construct the required system-wide analytical stiffness model for the serial-parallel robot machine, a variant of the virtual joint method (VJM) is proposed in the dissertation. The modified method is an evolution of Gosselin's lumped model that can account for the deformations of a flexible link in more directions. The effectiveness of this VJM variant is validated by comparing the computed stiffness results of a flexible link with the those of a matrix structural analysis (MSA) method. The comparison shows that the numerical results from both methods on an individual flexible beam are almost identical, which, in some sense, provides mutual validation. The most prominent advantage of the presented VJM variant compared with the MSA method is that it can be applied in a flexible structure system with complicated kinematics formed in terms of flexible serial links and joints. Moreover, by combining the VJM variant and the virtual work principle, a systemwide analytical stiffness model can be easily obtained for mechanisms with both serial kinematics and parallel kinematics. In the dissertation, a system-wide stiffness model of a kinematic redundant serial-parallel robot machine is constructed based on integration of the VJM variant and the virtual work principle. Numerical results of its stiffness performance are reported. For a kinematic redundant robot, to generate a set of feasible joints' trajectories for a prescribed trajectory of its end-effector, its system-wide stiffness performance is taken as the constraint in the joints trajectory planning in the dissertation. For a prescribed location of the end-effector, the robot permits an infinite number of inverse solutions, which consequently yields infinite kinds of stiffness performance. Therefore, a differential evolution (DE) algorithm in which the positions of redundant joints in the kinematics are taken as input variables was employed to search for the best stiffness performance of the robot. Numerical results of the generated joint trajectories are given for a kinematic redundant serial-parallel robot machine, IWR (Intersector Welding/Cutting Robot), when a particular trajectory of its end-effector has been prescribed. The numerical results show that the joint trajectories generated based on the stiffness optimization are feasible for realization in the control system since they are acceptably smooth. The results imply that the stiffness performance of the robot machine deviates smoothly with respect to the kinematic configuration in the adjacent domain of its best stiffness performance. To suppress the vibration of the robot machine due to varying cutting force during the machining process, this dissertation proposed a feedforward control strategy, which is constructed based on the derived inverse dynamics model of target system. The effectiveness of applying such a feedforward control in the vibration suppression has been validated in a parallel manipulator in the software environment. The experimental study of such a feedforward control has also been included in the dissertation. The difficulties of modelling the actual system due to the unknown components in its dynamics is noticed. As a solution, a back propagation (BP) neural network is proposed for identification of the unknown components of the dynamics model of the target system. To train such a BP neural network, a modified Levenberg-Marquardt algorithm that can utilize an experimental input-output data set of the entire dynamic system is introduced in the dissertation. Validation of the BP neural network and the modified Levenberg- Marquardt algorithm is done, respectively, by a sinusoidal output approximation, a second order system parameters estimation, and a friction model estimation of a parallel manipulator, which represent three different application aspects of this method.

Managing Customer Co-creation: Empirical Evidence from Finnish High-tech SMEs

The purpose of this thesis is to find out how customer co-creation activities are managed in Finnish high-tech SMEs by understanding managers’ views on relevant issues. According to theory, issues such as firm size, customer knowledge implementation, lead customers, the fuzzy front-end of product/service development as well as the reluctance to engage in customer co-creation are some of the field’s focal issues. The views of 145 Finnish SME managers on these issues were gathered as empirical evidence through an online questionnaire and analyzed with SPSS statistics software. The results show, firstly, that Finnish SME managers are aware of the issues associated with customer co-creation and are able to actively manage them. Additionally, managers performed well in regards to collaborating with lead customers and implemented customer knowledge evenly in various stages of their new product and service development processes. Intellectual property rights emerged as an obstacle deterring managers from engaging in co-creation. The results suggest that in practice managers would do well by looking for more opportunities to implement customer knowledge in the early and late stages of new product and service development, as well as by actively searching for lead customers.

Differentiating origins of outflow tract ventricular arrhythmias: a comparison of three different electrocardiographic algorithms

Our objective is to evaluate the accuracy of three algorithms in differentiating the origins of outflow tract ventricular arrhythmias (OTVAs). This study involved 110 consecutive patients with OTVAs for whom a standard 12-lead surface electrocardiogram (ECG) showed typical left bundle branch block morphology with an inferior axis. All the ECG tracings were retrospectively analyzed using the following three recently published ECG algorithms: 1) the transitional zone (TZ) index, 2) the V2 transition ratio, and 3) V2 R wave duration and R/S wave amplitude indices. Considering all patients, the V2 transition ratio had the highest sensitivity (92.3%), while the R wave duration and R/S wave amplitude indices in V2 had the highest specificity (93.9%). The latter finding had a maximal area under the ROC curve of 0.925. In patients with left ventricular (LV) rotation, the V2 transition ratio had the highest sensitivity (94.1%), while the R wave duration and R/S wave amplitude indices in V2 had the highest specificity (87.5%). The former finding had a maximal area under the ROC curve of 0.892. All three published ECG algorithms are effective in differentiating the origin of OTVAs, while the V2 transition ratio, and the V2 R wave duration and R/S wave amplitude indices are the most sensitive and specific algorithms, respectively. Amongst all of the patients, the V2 R wave duration and R/S wave amplitude algorithm had the maximal area under the ROC curve, but in patients with LV rotation the V2 transition ratio algorithm had the maximum area under the ROC curve.

Forced-air, vacuum, and hydro precooling of cauliflower (Brassica oleracea L. var. botrytis cv. Freemont): part I. determination of precooling parameters

The aim of the present study was to precool cauliflower using forced-air, vacuum and high and low flow hydro cooling methods. The weight of the precooled cauliflower heads (5000±5 g) was measured before they were placed in standard plastic crates. Cauliflower heads, whose initial temperature was 23.5 ± 0.5 ºC, were cooled until the temperature reached at 1 ºC. During the precooling process, time-dependent temperature and energy consumption were measured, and during vacuum precooling, the decreasing pressure values were recorded, and a curve of time-dependent pressure decrease (vacuum) was built. The most suitable cooling method to precool cauliflower in terms of cooling time and energy consumption was vacuum, followed by the high and low flow hydro and forced-air precooling methods, respectively. The highest weight loss was observed in the vacuum precooling method, followed by the forced-air method. However, there was an increase in the weight of the cauliflower heads in the high and low flow hydro precooling method. The best colour and hardness values were found in the vacuum precooling method. Among all methods tested, the most suitable method to precool cauliflower in terms of cooling and quality parameters was the vacuum precooling method.