Remote sensing for three-dimensional modelling of hydromorphology

Successful management of rivers requires an understanding of the fluvial processes that govern them. This, in turn cannot be achieved without a means of quantifying their geomorphology and hydrology and the spatio-temporal interactions between them, that is, their hydromorphology. For a long time, it has been laborious and time-consuming to measure river topography, especially in the submerged part of the channel. The measurement of the flow field has been challenging as well, and hence, such measurements have long been sparse in natural environments. Technological advancements in the field of remote sensing in the recent years have opened up new possibilities for capturing synoptic information on river environments. This thesis presents new developments in fluvial remote sensing of both topography and water flow. A set of close-range remote sensing methods is employed to eventually construct a high-resolution unified empirical hydromorphological model, that is, river channel and floodplain topography and three-dimensional areal flow field. Empirical as well as hydraulic theory-based optical remote sensing methods are tested and evaluated using normal colour aerial photographs and sonar calibration and reference measurements on a rocky-bed sub-Arctic river. The empirical optical bathymetry model is developed further by the introduction of a deep-water radiance parameter estimation algorithm that extends the field of application of the model to shallow streams. The effect of this parameter on the model is also assessed in a study of a sandy-bed sub-Arctic river using close-range high-resolution aerial photography, presenting one of the first examples of fluvial bathymetry modelling from unmanned aerial vehicles (UAV). Further close-range remote sensing methods are added to complete the topography integrating the river bed with the floodplain to create a seamless high-resolution topography. Boat- cart- and backpack-based mobile laser scanning (MLS) are used to measure the topography of the dry part of the channel at a high resolution and accuracy. Multitemporal MLS is evaluated along with UAV-based photogrammetry against terrestrial laser scanning reference data and merged with UAV-based bathymetry to create a two-year series of seamless digital terrain models. These allow the evaluation of the methodology for conducting high-resolution change analysis of the entire channel. The remote sensing based model of hydromorphology is completed by a new methodology for mapping the flow field in 3D. An acoustic Doppler current profiler (ADCP) is deployed on a remote-controlled boat with a survey-grade global navigation satellite system (GNSS) receiver, allowing the positioning of the areally sampled 3D flow vectors in 3D space as a point cloud and its interpolation into a 3D matrix allows a quantitative volumetric flow analysis. Multitemporal areal 3D flow field data show the evolution of the flow field during a snow-melt flood event. The combination of the underwater and dry topography with the flow field yields a compete model of river hydromorphology at the reach scale.

Päätöspuut tiedonlouhinnassa

Tallennustekniikan kehittymisen ja internetin murroksen seurauksena tietomäärät ovat kasvaneet dramaattisesti. Tietomäärien yhä kasvaessa on kehitetty erilaisia menetelmiä relevantin tiedon noutamiseksi tällaisesta tietomassasta, prosessia kutsutaan tiedonlouhinnaksi. Erilaisten tiedonlouhinta-algoritmien joukosta tässä tutkielmassa käsitellään päätöspuualgoritmeja. Päätöspuilla on lukuisia etuja muihin tiedonlouhinta-algoritmeihin nähden: Tietoa tarvitsee yleisesti esikäsitellä hyvin minimaalisesti ennen algoritmille syöttämistään, lisäksi päätöspuilla voidaan tarkastella muuttujien välisiä epälineaarisia riippuvuksia. Kenties tärkeimpänä päätöspuiden käyttöä puoltavana asiana voidaan kuitenkin pitää niiden palauttamaa selkeää puumaista esitysmuotoa, josta johtopäätösten tekeminen on suhteellisen helppoa. Tutkielmassa selvitetään ensin korkealla abstraktiotasolla päätöspuualgoritmien perustoiminta ja ongelmat, jonka jälkeen käydään läpi algoritmien toiminnan kannalta olennaisia tilastollisia käsitteitä. Tämän jälkeen analysoidaan relevanteiksi koettuja päätöspuualgoritmeja matalammalla abstraktiotasolla ja lopuksi vertaillaan algoritmien yhtäläisyyksiä ja eroavaisuuksia esimerkiksi laskentatehokkuuden, toimintatarkkuuden ja tuottetujen puiden koon muodossa. Tutkielmassa vastataan siihen minkälaisen ongelman ratkaisuun on suositeltavaa valita minkäkin tyyppinen päätöspuualgoritmi. Apuna käytetään paitsi alan kirjallisuutta, myös omia käytännön kokeita Weka-tiedonlouhintatyökalulla. Tutkielmassa tullaan siihen tulokseen että CHAID-algoritmia suositellaan käytettävän pääsääntöisesti datan piirteiden analysointiin, kun taas muita tutkielmassa esiteltäviä algoritmeja käytetään lähinnä luokittelutehtäviin. ID3 on vanhentunut algoritmi, jota tulee käyttää enää lähinnä opetus- tai demonstraatiotarkoituksissa. Lopputulosten pohjalta voidaan myös sanoa että pääsääntöisesti haluttaessa suoritusnopeutta tulee hyödyntää C4.5:en pohjalta kehitettyä J48-algoritmia ja mikäli taasen halutaan pienempiä malleja suositellaan käytettäväksi CART:in pohjalta kehitettyä SimpleCart-algoritmia.

Control of a line robot system with Embedded Linux

Many, if not all, aspects of our everyday lives are related to computers and control. Microprocessors and wireless communications are involved in our lives. Embedded systems are an attracting field because they combine three key factors, small size, low power consumption and high computing capabilities. The aim of this thesis is to study how Linux communicates with the hardware, to answer the question if it is possible to use an operating system like Debian for embedded systems and finally, to build a Mechatronic real time application. In the thesis a presentation of Linux and the Xenomai real time patch is given, the bootloader and communication with the hardware is analyzed. BeagleBone the evaluation board is presented along with the application project consisted of a robot cart with a driver circuit, a line sensor reading a black line and two Xbee antennas. It makes use of Xenomai threads, the real time kernel. According to the obtained results, Linux is able to operate as a real time operating system. The issue of future research is the area of embedded Linux is also discussed.

Toward a Reliable Classifier For Arrhythmia Diagnosis

Illnesses related to the heart are one of the major reasons for death all over the world causing many people to lose their lives in last decades. The good news is that many of those sicknesses are preventable if they are spotted in early stages. On the other hand, the number of the doctors are much lower than the number of patients. This will makes the auto diagnosing of diseases even more and more essential for humans today. Furthermore, when it comes to the diagnosing methods and algorithms, the current state of the art is lacking a comprehensive study on the comparison between different diagnosis solutions. Not having a single valid diagnosing solution has increased the confusion among scholars and made it harder for them to take further steps. This master thesis will address the issue of reliable diagnosing algorithm. We investigate ECG signals and the relation between different diseases and the heart’s electrical activity. Also, we will discuss the necessary steps needed for auto diagnosing the heart diseases including the literatures discussing the topic. The main goal of this master thesis is to find a single reliable diagnosing algorithm and quest for the best classifier to date for heart related sicknesses. Five most suited and most well-known classifiers, such as KNN, CART, MLP, Adaboost and SVM, have been investigated. To have a fair comparison, the ex-periment condition is kept the same for all classification methods. The UCI repository arrhythmia dataset will be used and the data will not be preprocessed. The experiment results indicates that AdaBoost noticeably classifies different diseases with a considera-bly better accuracy.