Automatic traffic sign inventory- and condition analysis

This thesis researches automatic traffic sign inventory and condition analysis using machine vision and pattern recognition methods. Automatic traffic sign inventory and condition analysis can be used to more efficient road maintenance, improving the maintenance processes, and to enable intelligent driving systems. Automatic traffic sign detection and classification has been researched before from the viewpoint of self-driving vehicles, driver assistance systems, and the use of signs in mapping services. Machine vision based inventory of traffic signs consists of detection, classification, localization, and condition analysis of traffic signs. The produced machine vision system performance is estimated with three datasets, from which two of have been been collected for this thesis. Based on the experiments almost all traffic signs can be detected, classified, and located and their condition analysed. In future, the inventory system performance has to be verified in challenging conditions and the system has to be pilot tested.

Do retail investors use technical analysis? Evidence from Stuttgart stock exchange.

Tutkielma käyttää automaattista kuviontunnistusalgoritmia ja yleisiä kahden liukuvan keskiarvon leikkauspiste –sääntöjä selittääkseen Stuttgartin pörssissä toimivien yksityissijoittajien myynti-osto –epätasapainoa ja siten vastatakseen kysymykseen ”käyttävätkö yksityissijoittajat teknisen analyysin menetelmiä kaupankäyntipäätöstensä perustana?” Perusolettama sijoittajien käyttäytymisestä ja teknisen analyysin tuottavuudesta tehtyjen tutkimusten perusteella oli, että yksityissijoittajat käyttäisivät teknisen analyysin metodeja. Empiirinen tutkimus, jonka aineistona on DAX30 yhtiöiden data vuosilta 2009 – 2013, ei tuottanut riittävän selkeää vastausta tutkimuskysymykseen. Heikko todistusaineisto näyttää kuitenkin osoittavan, että yksityissijoittajat muuttavat kaupankäyntikäyttäytymistänsä eräiden kuvioiden ja leikkauspistesääntöjen ohjastamaan suuntaan.

Nasopharyngeal colonization by pathogenic bacteria: effect of polymorphisms in innate immune genes of young children

Nasopharyngeal bacteria can asymptomatically colonize the nasopharynx of infants and young children but are also associated with the development of respiratory infections and diseases. Such nasopharyngeal bacteria include Streptococcus pneumoniae, Moraxella catarrhalis, Haemophilus influenzae and Staphylococcus aureus. The host defense against invading pathogens is largely relies germline-encoded pattern recognition receptors (PRR), which are expressed on the cells of innate immunity, and different cytokines. These include toll-like receptors (TLR), mannose-binding lectin (MBL) and different cytokines such as IL-17A. Single nucleotide polymorphisms (SNP) in these receptors and cytokines have been reported. The aim of this study was to investigate genetic polymorphisms in the genes for TLR2, 3 and 4, MBL as well as for IL-17A and their associations with nasopharyngeal pathogenic bacterial colonization during a two-year follow-up. The study revealed that polymorphisms in TLRs, MBL2 and IL17A are associated with the nasopharyngeal bacterial colonization in young children. Healthy young (2.6 months of age) children with variant types of MBL2, TLR2 R753Q or TLR4 D299G had an increased risk to be colonized by S. pneumonia, S. aureus or M. catarrhalis, respectively. Moreover, variant types of MBL2 in healthy children with might facilitate human rhinovirus (HRV)-induced S. pneumoniae colonization at 2.6 months of age. The polymorphism of TLR4 D299G was shown to be associated with M. catarrhalis colonization throughout the whole two-year follow-up (2.6, 13 and 24 months of age) and also with the bacterial load of this pathogen. Also, the polymorphism of IL17A G152A was shown to be associated with increased risk to be colonized by S. pneumoniae at 13 and 24 months of age. Furthermore, the results suggest that IL17A G152A has an effect on production of serum IL-17A already at young age. In conclusion, the results of this study indicate that polymorphisms in the key PRRs and IL17A seem to play an important role to colonization of S. pneumoniae, M. catarrhalis, and S. aureus in healthy young Finnish children. The nasopharyngeal colonization by these pathogenic bacteria may further promote the development of respiratory infections and may be related to development of asthma and allergy in the later life of children. These findings offer a possible explanation why some children have more respiratory infections than other children and provide a rational basis for future studies in this field.

Design and implementation of machine vision system for the mobile assembly robot

The review of intelligent machines shows that the demand for new ways of helping people in perception of the real world is becoming higher and higher every year. This thesis provides information about design and implementation of machine vision for mobile assembly robot. The work has been done as a part of LUT project in Laboratory of Intelligent Machines. The aim of this work is to create a working vision system. The qualitative and quantitative research were done to complete this task. In the first part, the author presents the theoretical background of such things as digital camera work principles, wireless transmission basics, creation of live stream, methods used for pattern recognition. Formulas, dependencies and previous research related to the topic are shown. In the second part, the equipment used for the project is described. There is information about the brands, models, capabilities and also requirements needed for implementation. Although, the author gives a description of LabVIEW software, its add-ons and OpenCV which are used in the project. Furthermore, one can find results in further section of considered thesis. They mainly represented by screenshots from cameras, working station and photos of the system. The key result of this thesis is vision system created for the needs of mobile assembly robot. Therefore, it is possible to see graphically what was done on examples. Future research in this field includes optimization of the pattern recognition algorithm. This will give less response time for recognizing objects. Presented by author system can be used also for further activities which include artificial intelligence usage.