A Graphical Pattern Editor for Java Frameworks

Ohjelmistojen uudelleenkäyttö on hyvin tärkeä käsite ohjelmistotekniikan alueella.Ohjelmistojen uudelleenkäyttötekniikat parantavat ohjelmistokehitysprosessin laatua. Yleisiä ratkaisuja sekä ohjelmiston suunnittelun että arkkitehtuurin uudelleenkäyttöön ovat olio-ohjelmointi ja sovelluskehykset. Tähän asti ei ole ollut olemassa yleisiä tapoja sovelluskehysten erikoistamiseen. Monet nykyääntunnetuista sovelluskehyksistä ovat hyvin suuria ja mutkikkaita. Tällaisten sovelluskehyksien käyttö on monimutkaista myös kokeneille ohjelmoijille. Hyvin dokumentoidut uudelleenkäytettävät sovelluskehyksen rajapinnat parantavat kehyksen käytettävyyttä ja tehostavat myös erikoistamisprosessiakin sovelluskehyksen käyttäjille. Sovelluskehyseditori (framework editor, JavaFrames) on prototyyppityökalu, jota voidaan käyttää yksinkertaistamaan sovelluskehyksen käyttöä. Perusajatus JavaFrames lähestymistavassa ovat erikoistamismallit, joita käytetään kuvamaan sovelluskehyksen uudelleenkäytettäviä rajapintoja. Näihin malleihin perustuen JavaFrames tarjoaa automaattisen lähdekoodi generaattorin, dokumentoinninja arkkitehtuurisääntöjen tarkistuksen. Tämä opinnäyte koskee graafisen mallieditorin kehittämistä JavaFrames ympäristöön. Työssä on laadittu työkalu,jonka avulla voidaan esittää graafisesti erikoistamismalli. Editori sallii uusien mallien luomisen, vanhojen käyttämättä olevien poistamisen, kuten myös yhteyksien lisäämisen mallien välille. Tällainen graafinen tuki JavaFrames ympäristöönvoi huomattavasti yksinkertaistaa sen käyttöä ja tehdä sovellusten kehittämisprosessista joustavamman.

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.

Model-View-Controller architectural pattern and its evolution in graphical user interface frameworks

Model-View-Controller (MVC) is an architectural pattern used in software development for graphical user interfaces. It was one of the first proposed solutions in the late 1970s to the Smart UI anti-pattern, which refers to the act of writing all domain logic into a user interface. The original MVC pattern has since evolved in multiple directions, with various names and may confuse many. The goal of this thesis is to present the origin of the MVC pattern and how it has changed over time. Software architecture in general and the MVC’s evolution within web applications are not the primary focus. Fundamen- tal designs are abstracted, and then used to examine the more recent versions. Prob- lems with the subject and its terminology are also presented.

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.