Keraamisten laattojen luokittelu väripiirteiden avulla

Vaikka keraamisten laattojen valmistusprosessi onkin täysin automatisoitu, viimeinen vaihe eli laaduntarkistus ja luokittelu tehdään yleensä ihmisvoimin. Automaattinen laaduntarkastus laattojen valmistuksessa voidaan perustella taloudellisuus- ja turvallisuusnäkökohtien avulla. Tämän työn tarkoituksena on kuvata tutkimusprojektia keraamisten laattojen luokittelusta erilaisten väripiirteiden avulla. Oleellisena osana tutkittiin RGB- ja spektrikuvien välistä eroa. Työn teoreettinen osuus käy läpi aiemmin aiheesta tehdyn tutkimuksen sekä antaa taustatietoa konenäöstä, hahmontunnistuksesta, luokittelijoista sekä väriteoriasta. Käytännön osan aineistona oli 25 keraamista laattaa, jotka olivat viidestä eri luokasta. Luokittelussa käytettiin apuna k:n lähimmän naapurin (k-NN) luokittelijaa sekä itseorganisoituvaa karttaa (SOM). Saatuja tuloksia verrattiin myös ihmisten tekemään luokitteluun. Neuraalilaskenta huomattiin tärkeäksi työkaluksi spektrianalyysissä. SOM:n ja spektraalisten piirteiden avulla saadut tulokset olivat lupaavia ja ainoastaan kromatisoidut RGB-piirteet olivat luokittelussa parempia kuin nämä.

Innate Immune Sensing of Fusarium culmorum by Mouse Dendritic Cells.

Chronic inhalation of grain dust is associated with asthma and chronic bronchitis in grain worker populations. Exposure to fungal particles was postulated to be an important etiologic agent of these pathologies. Fusarium species frequently colonize grain and straw and produce a wide array of mycotoxins that impact human health, necessitating an evaluation of risk exposure by inhalation of Fusarium and its consequences on immune responses. Data showed that Fusarium culmorum is a frequent constituent of aerosols sampled during wheat harvesting in the Vaud region of Switzerland. The aim of this study was to examine cytokine/chemokine responses and innate immune sensing of F. culmorum in bone-marrow-derived dendritic cells and macrophages. Overall, dendritic cells and macrophages responded to F. culmorum spores but not to its secreted components (i.e., mycotoxins) by releasing large amounts of macrophage inflammatory protein (MIP)-1α, MIP-1β, MIP-2, monocyte chemoattractant protein (MCP)-1, RANTES, and interleukin (IL)-12p40, intermediate amounts of tumor necrosis factor (TNF), IL-6, IL-12p70, IL-33, granulocyte colony-stimulating factor (G-CSF), and interferon gamma-induced protein (IP-10), but no detectable amounts of IL-4 and IL-10, a pattern of mediators compatible with generation of Th1 or Th17 antifungal protective immune responses rather than with Th2-dependent allergic responses. The sensing of F. culmorum spores by dendritic cells required dectin-1, the main pattern recognition receptor involved in β-glucans detection, but likely not MyD88 and TRIF-dependent Toll-like receptors. Taken together, our results indicate that F. culmorum stimulates potently innate immune cells in a dectin-1-dependent manner, suggesting that inhalation of F. culmorum from grain dust may promote immune-related airway diseases in exposed worker populations.

Sidelobe elimination for generalized synthetic discriminant functions by a two-filter correlation and subsequent postprocessing of the intensity distributions

One of the most important problems in optical pattern recognition by correlation is the appearance of sidelobes in the correlation plane, which causes false alarms. We present a method that eliminate sidelobes of up to a given height if certain conditions are satisfied. The method can be applied to any generalized synthetic discriminant function filter and is capable of rejecting lateral peaks that are even higher than the central correlation. Satisfactory results were obtained in both computer simulations and optical implementation.

NLRP12 is a neutrophil-specific, negative regulator of in vitro cell migration but does not modulate LPS- or infection-induced NF-κB or ERK signalling.

NOD-like receptors (NLR) are a family of cytosolic pattern recognition receptors that include many key drivers of innate immune responses. NLRP12 is an emerging member of the NLR family that is closely related to the well-known inflammasome scaffold, NLRP3. Since its discovery, various functions have been proposed for NLRP12, including the positive regulation of dendritic cell (DC) and neutrophil migration and the inhibition of NF-κB and ERK signalling in DC and macrophages. We show here that NLRP12 is poorly expressed in murine macrophages and DC, but is strongly expressed in neutrophils. Using myeloid cells from WT and Nlrp12(-/)(-) mice, we show that, contrary to previous reports, NLRP12 does not suppress LPS- or infection-induced NF-κB or ERK activation in myeloid cells, and is not required for DC migration in vitro. Surprisingly, we found that Nlrp12 deficiency caused increased rather than decreased neutrophil migration towards the chemokine CXCL1 and the neutrophil parasite Leishmania major, revealing NLRP12 as a negative regulator of directed neutrophil migration under these conditions.

Sensing Gram-negative bacteria: a phylogenetic perspective.

Gram-negative bacteria represent a major group of pathogens that infect all eukaryotes from plants to mammals. Gram-negative microbe-associated molecular patterns include lipopolysaccharides and peptidoglycans, major immunostimulatory determinants across phyla. Recent advances have furthered our understanding of Gram-negative detection beyond the well-defined pattern recognition receptors such as TLR4. A B-type lectin receptor for LPS and Lysine-motif containing receptors for peptidoglycans were recently added to the plant arsenal. Caspases join the ranks of mammalian cytosolic immune detectors by binding LPS, and make TLR4 redundant for septic shock. Fascinating bacterial evasion mechanisms lure the host into tolerance or promote inter-bacterial competition. Our review aims to cover recent advances on bacterial messages and host decoding systems across phyla, and highlight evolutionarily recurrent strategies.

Correcció postural esportiva utilitzant un sensor Kinect

Aquest projecte s’emmarca dins de l’àmbit de la visió per computador, concretament en la utilització de dades de profunditat obtingudes a través d’un emissor i sensor de llum infraroja.El propòsit principal d’aquest projecte és mostrar com adaptar aquestes tecnologies, a l’abast de qualsevol particular, de forma que un usuari durant la pràctica d’una activitat esportiva concreta, rebi informació visual continua dels moviments i gestos incorrectes que està realitzant, en base a uns paràmetres prèviament establerts.L’objectiu d’aquest projecte consisteix en fer una lectura constant en temps real d’una persona practicant una selecció de diverses activitats esportives estàtiques utilitzant un sensor Kinect. A través de les dades obtingudes pel sensor Kinect i utilitzant les llibreries de “skeleton traking” proporcionades per Microsoft s’haurà d’interpretar les dades posturals obtingudes per cada tipus d’esport i indicar visualment i d’una manera intuïtiva els errors que està cometent en temps real, de manera que es vegi clarament a quina part del seu cos realitza un moviment incorrecte per tal de poder corregir-lo ràpidament. El entorn de desenvolupament que s’utilitza per desenvolupar aquesta aplicació es Microsoft Viusal Studio 2010.El llenguatge amb el qual es treballarà sobre Microsoft Visual Studio 2010 és C#

Classifier combination for in vivo magnetic resonance spectra of brain tumours

Peer-reviewed

A Sparse Bayesian Approach for Joint Feature Selection and Classifier Learning

Peer-reviewed

A Hierarchical Approach for Multi-task Logistic Regression

Peer-reviewed

Using appearance and context for outdoor scene object classification

We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down control, which uses the previously learned models (appearance and absolute location) to obtain an initial pixel-level classification. This information provides us the core of objects, which is used to acquire a more accurate object model. Therefore, their growing by specific active regions allows us to obtain an accurate recognition of known regions. Next, a stage of general segmentation provides the segmentation of unknown regions by a bottom-strategy. Finally, the last stage tries to perform a region fusion of known and unknown segmented objects. The result is both a segmentation of the image and a recognition of each segment as a given object class or as an unknown segmented object. Furthermore, experimental results are shown and evaluated to prove the validity of our proposal

Avaliação quimiométrica da distribuição de metais pesados em composto de lixo urbano domiciliar

The main obstacle to the use of compost from urban waste in agriculture is the presence of heavy metals. Once in the soil, their effect is accumulative and they may contaminate crops and water. The present study reports the evaluation of the chemical distributions of Cu, Pb, Mn and Zn in three different sized fractions (unsieved, < 1,18mm and > 1,18mm) of compost, by means of a sequencial extraction procedure and a chemometric analysis of the total content of all metals in each fraction. The pattern recognition methods showed significant differences in total heavy metal contents for the different fractions. The finest one was the most contaminated. Meanwhile, this fraction presented lower amounts of metals in avaliable forms. This behavior can be attributed to the presence of metal particles in their elemental states in this fraction.

Flavonoids affect host-microbiota crosstalk through TLR modulation

Interaction between host cells and microbes is known as crosstalk. Among other mechanisms, this takes place when certain molecules of the micro-organisms are recognized by the toll-like receptors (TLRs) in the body cells, mainly in the intestinal epithelial cells and in the immune cells. TLRs belong to the pattern-recognition receptors and represent the first line of defense against pathogens, playing a pivotal role in both innate and adaptive immunity. Dysregulation in the activity of such receptors can lead to the development of chronic and severe inflammation as well as immunological disorders. Among components present in the diet, flavonoids have been suggested as antioxidant dietary factors able to modulate TLR-mediated signaling pathways. This review focuses on the molecular targets involved in the modulatory action of flavonoids on TLR-mediated signaling pathways, providing an overview of the mechanisms involved in such action. Particular flavonoids have been able to modify the composition of the microbiota, to modulate TLR gene and protein expression, and to regulate the downstream signaling molecules involved in the TLR pathway. These synergistic mechanisms suggest the role of some flavonoids in the preventive effect on certain chronic diseases.