Statistical reference criteria for adaptive signal processing in digital communications

A general criterion for the design of adaptive systemsin digital communications called the statistical reference criterionis proposed. The criterion is based on imposition of the probabilitydensity function of the signal of interest at the outputof the adaptive system, with its application to the scenario ofhighly powerful interferers being the main focus of this paper.The knowledge of the pdf of the wanted signal is used as adiscriminator between signals so that interferers with differingdistributions are rejected by the algorithm. Its performance isstudied over a range of scenarios. Equations for gradient-basedcoefficient updates are derived, and the relationship with otherexisting algorithms like the minimum variance and the Wienercriterion are examined.

Wigner higher-order spectra: definition, properties, computation and application to transient signal analysis

The Wigner higher order moment spectra (WHOS)are defined as extensions of the Wigner-Ville distribution (WD)to higher order moment spectra domains. A general class oftime-frequency higher order moment spectra is also defined interms of arbitrary higher order moments of the signal as generalizations of the Cohen’s general class of time-frequency representations. The properties of the general class of time-frequency higher order moment spectra can be related to theproperties of WHOS which are, in fact, extensions of the properties of the WD. Discrete time and frequency Wigner higherorder moment spectra (DTF-WHOS) distributions are introduced for signal processing applications and are shown to beimplemented with two FFT-based algorithms. One applicationis presented where the Wigner bispectrum (WB), which is aWHOS in the third-order moment domain, is utilized for thedetection of transient signals embedded in noise. The WB iscompared with the WD in terms of simulation examples andanalysis of real sonar data. It is shown that better detectionschemes can be derived, in low signal-to-noise ratio, when theWB is applied.

On the Condition Monitoring of Induction machines

The research of condition monitoring of electric motors has been wide for several decades. The research and development at universities and in industry has provided means for the predictive condition monitoring. Many different devices and systems are developed and are widely used in industry, transportation and in civil engineering. In addition, many methods are developed and reported in scientific arenas in order to improve existing methods for the automatic analysis of faults. The methods, however, are not widely used as a part of condition monitoring systems. The main reasons are, firstly, that many methods are presented in scientific papers but their performance in different conditions is not evaluated, secondly, the methods include parameters that are so case specific that the implementation of a systemusing such methods would be far from straightforward. In this thesis, some of these methods are evaluated theoretically and tested with simulations and with a drive in a laboratory. A new automatic analysis method for the bearing fault detection is introduced. In the first part of this work the generation of the bearing fault originating signal is explained and its influence into the stator current is concerned with qualitative and quantitative estimation. The verification of the feasibility of the stator current measurement as a bearing fault indicatoris experimentally tested with the running 15 kW induction motor. The second part of this work concentrates on the bearing fault analysis using the vibration measurement signal. The performance of the micromachined silicon accelerometer chip in conjunction with the envelope spectrum analysis of the cyclic bearing faultis experimentally tested. Furthermore, different methods for the creation of feature extractors for the bearing fault classification are researched and an automatic fault classifier using multivariate statistical discrimination and fuzzy logic is introduced. It is often important that the on-line condition monitoring system is integrated with the industrial communications infrastructure. Two types of a sensor solutions are tested in the thesis: the first one is a sensor withcalculation capacity for example for the production of the envelope spectra; the other one can collect the measurement data in memory and another device can read the data via field bus. The data communications requirements highly depend onthe type of the sensor solution selected. If the data is already analysed in the sensor the data communications are needed only for the results but in the other case, all measurement data need to be transferred. The complexity of the classification method can be great if the data is analysed at the management level computer, but if the analysis is made in sensor itself, the analyses must be simple due to the restricted calculation and memory capacity.

Lon protease negatively affects GacA protein stability and expression of the Gac/Rsm signal transduction pathway in Pseudomonas protegens.

In Pseudomonas protegens CHA0 and other fluorescent pseudomonads, the Gac/Rsm signal transduction pathway controls secondary metabolism and suppression of fungal root pathogens via the expression of regulatory small RNAs (sRNAs). Because of its high cost, this pathway needs to be protected from overexpression and to be turned off in response to environmental stress such as the lack of nutrients. However, little is known about its underlying molecular mechanisms. In this study, we demonstrated that Lon protease, a member of the ATP-dependent protease family, negatively regulated the Gac/Rsm cascade. In a lon mutant, the steady-state levels and the stability of the GacA protein were significantly elevated at the end of exponential growth. As a consequence, the expression of the sRNAs RsmY and RsmZ and that of dependent physiological functions such as antibiotic production were significantly enhanced. Biocontrol of Pythium ultimum on cucumber roots required fewer lon mutant cells than wild-type cells. In starved cells, the loss of Lon function prolonged the half-life of the GacA protein. Thus, Lon protease is an important negative regulator of the Gac/Rsm signal transduction pathway in P. protegens.

Characterization of board impurities with a Raman device

Erilaisia epäpuhtauksia kulkeutuu paperinvalmistusprosessiin ja monenlaisia saostumia muodostuu paperinvalmistuksen prosesseissa. Epäpuhtaudet voivat aiheuttaa prosessiongelmia sekä alentaa tuotteen laatua. Epäpuhtauksien alkuperän ja koostumuksen selvittäminen edellyttää usein erilaisten analyysimenetelmien käyttöä. Epäpuhtauksien luokittelu on useasti välttämätöntä ennen tarkempaa kemiallista analyysia. Paperinvalmistuksen epäpuhtauksien kvalitatiiviseen luokitteluun on yleisimmin käytetty mikroskopian, IR-spektroskopian ja analyyttisen pyrolyysin menetelmiä. Raman spektroskopia on harvinaisempi menetelmä paperiteollisuuden tutkimuksessa. Raman instrumenttien kehittyminen on ollut voimakasta viimeisen vuosikymmenen aikana. Raman spektroskopia onkin osoittanut mandollisuutensa polymeerien, lääketeollisuuden ja polttoaineteollisuuden tutkimuksissa. Tässä työssä tutkittiin erään elintarvikepakkauskartongin epäpuhtauksia Raman spektroskoopilla. Työn tavoitteena oli selvittää Raman analyysin käyttökelpoisuutta kartongin epäpuhtauksien online-luokittelussa. Tutkimukset suoritettiin Spectracoden RP-1 Raman instrumentilla. Tutkimukset osoittivat, että näytteen fluoresenssi ja näytteen hajoaminen asettavat rajoituksia epäpuhtauksien Raman analyysille. Epäpuhtauksien online-tunnistaminen toimii käytettäessä suuria lasertehoja ja säteilytysaikoja. Näytteiden laserherkkyys ja fluoresenssi rajoittavat kuitenkin suurien laiteparametrien käyttöä. Laiteparametrien pienentäminen johti mittauksien signaali-kohina suhteen alenemiseen, mikä puolestaan aiheutti online-tunnistuksen toimimattomuuden.

Bayesian classification of forest ecological type from satellite data

The main objective of this study was todo a statistical analysis of ecological type from optical satellite data, using Tipping's sparse Bayesian algorithm. This thesis uses "the Relevence Vector Machine" algorithm in ecological classification betweenforestland and wetland. Further this bi-classification technique was used to do classification of many other different species of trees and produces hierarchical classification of entire subclasses given as a target class. Also, we carried out an attempt to use airborne image of same forest area. Combining it with image analysis, using different image processing operation, we tried to extract good features and later used them to perform classification of forestland and wetland.

Cluster-based active learning for compact image classification

In this paper, we consider active sampling to label pixels grouped with hierarchical clustering. The objective of the method is to match the data relationships discovered by the clustering algorithm with the user's desired class semantics. The first is represented as a complete tree to be pruned and the second is iteratively provided by the user. The active learning algorithm proposed searches the pruning of the tree that best matches the labels of the sampled points. By choosing the part of the tree to sample from according to current pruning's uncertainty, sampling is focused on most uncertain clusters. This way, large clusters for which the class membership is already fixed are no longer queried and sampling is focused on division of clusters showing mixed labels. The model is tested on a VHR image in a multiclass classification setting. The method clearly outperforms random sampling in a transductive setting, but cannot generalize to unseen data, since it aims at optimizing the classification of a given cluster structure.

Phosphorylation of phosphatidylinositol-3-kinase-protein kinase B and extracellular signal-regulated kinases 1/2 mediate reoxygenation-induced cardioprotection during hypoxia.

In vivo exposure to chronic hypoxia (CH) depresses myocardial performance and tolerance to ischemia, but daily reoxyenation during CH (CHR) confers cardioprotection. To elucidate the underlying mechanism, we tested the role of phosphatidylinositol-3-kinase-protein kinase B (Akt) and p42/p44 extracellular signal-regulated kinases (ERK1/2), which are known to be associated with protection against ischemia/reperfusion (I/R). Male Sprague-Dawley rats were maintained for two weeks under CH (10% O(2)) or CHR (as CH but with one-hour daily exposure to room air). Then, hearts were either frozen for biochemical analyses or Langendorff-perfused to determine performance (intraventricular balloon) and tolerance to 30-min global ischemia and 45-min reperfusion, assessed as recovery of performance after I/R and infarct size (tetrazolium staining). Additional hearts were perfused in the presence of 15 micromol/L LY-294002 (inhibitor of Akt), 10 micromol/L UO-126 (inhibitor of ERK1/2) or 10 micromol/L PD-98059 (less-specific inhibitor of ERK1/2) given 15 min before ischemia and throughout the first 20 min of reperfusion. Whereas total Akt and ERK1/2 were unaffected by CH and CHR in vivo, in CHR hearts the phosphorylation of both proteins was higher than in CH hearts. This was accompanied by better performance after I/R (heart rate x developed pressure), lower end-diastolic pressure and reduced infarct size. Whereas the treatment with LY-294002 decreased the phosphorylation of Akt only, the treatment with UO-126 decreased ERK1/2, and that with PD-98059 decreased both Akt and ERK1/2. In all cases, the cardioprotective effect led by CHR was lost. In conclusion, in vivo daily reoxygenation during CH enhances Akt and ERK1/2 signaling. This response was accompanied by a complex phenotype consisting in improved resistance to stress, better myocardial performance and lower infarct size after I/R. Selective inhibition of Akt and ERK1/2 phosphorylation abolishes the beneficial effects of the reoxygenation. Therefore, Akt and ERK1/2 have an important role to mediate cardioprotection by reoxygenation during CH in vivo.

The Development of Weak Signal Concept

Tämän hetken trendit kuten globalisoituminen, ympäristömme turbulenttisuus, elintason nousu, turvallisuuden tarpeen kasvu ja teknologian kehitysnopeus korostavatmuutosten ennakoinnin tarpeellisuutta. Pysyäkseen kilpailukykyisenä yritysten tulee kerätä, analysoida ja hyödyntää liiketoimintatietoa, jokatukee niiden toimintaa viranomaisten, kilpailijoiden ja asiakkaiden toimenpiteiden ennakoinnissa. Innovoinnin ja uusien konseptien kehittäminen, kilpailijoiden toiminnan arviointi, asiakkaiden tarpeet muun muassa vaativatennakoivaa arviointia. Heikot signaalit ovat keskeisessä osassa organisaatioiden valmistautumisessa tulevaisuuden tapahtumiin. Opinnäytetyön tarkoitus on luoda ja kehittää heikkojen signaalien ymmärrystä ja hallintaa sekäkehittää konseptuaalinen ja käytännöllinen lähestymistapa ennakoivan toiminnan edistämiselle. Heikkojen signaalien tyyppien luokittelu perustuu ominaisuuksiin ajan, voimakkuuden ja liiketoimintaan integroinnin suhteen. Erityyppiset heikot signaalit piirteineen luovat reunaehdot laatutekijöiden keräämiselle ja siitä edelleen laatujärjestelmän ja matemaattiseen malliin perustuvan työvälineen kehittämiselle. Heikkojen signaalien laatutekijät on kerätty yhteen kaikista heikkojen signaalien konseptin alueista. Analysoidut ja kohdistetut laatumuuttujat antavat mahdollisuuden kehittää esianalyysiä ja ICT - työvälineitä perustuen matemaattisen mallin käyttöön. Opinnäytetyön tavoitteiden saavuttamiseksi tehtiin ensin Business Intelligence -kirjallisuustutkimus. Hiekkojen signaalien prosessi ja systeemi perustuvat koottuun Business Intelligence - systeemiin. Keskeisinä kehitysalueina tarkasteltiin liiketoiminnan integraatiota ja systemaattisen menetelmän kehitysaluetta. Heikkojen signaalien menetelmien ja määritelmien kerääminen sekä integrointi määriteltyyn prosessiin luovat uuden konseptin perustan, johon tyypitys ja laatutekijät kytkeytyvät. Käytännöllisen toiminnan tarkastelun ja käyttöönoton mahdollistamiseksi toteutettiin Business Intelligence markkinatutkimus (n=156) sekä yhteenveto muihin saatavilla oleviin markkinatutkimuksiin. Syvähaastatteluilla (n=21) varmennettiin laadullisen tarkastelun oikeellisuus. Lisäksi analysoitiin neljä käytännön projektia, joiden yhteenvedot kytkettiin uuden konseptin kehittämiseen. Prosessi voidaan jakaa kahteen luokkaan: yritysten markkinasignaalit vuoden ennakoinnilla ja julkisen sektorin verkostoprojektit kehittäen ennakoinnin struktuurin luonnin 7-15 vuoden ennakoivalle toiminnalle. Tutkimus rajattiin koskemaan pääasiassa ulkoisen tiedon aluetta. IT työvälineet ja lopullisen laatusysteemin kehittäminen jätettiin tutkimuksen ulkopuolelle. Opinnäytetyön tavoitteena ollut heikkojen signaalien konseptin kehittäminen toteutti sille asetetut odotusarvot. Heikkojen signaalien systemaattista tarkastelua ja kehittämistyötä on mahdollista edistää Business Intelligence - systematiikan hyödyntämisellä. Business Intelligence - systematiikkaa käytetään isojen yritysten liiketoiminnan suunnittelun tukena.Organisaatioiden toiminnassa ei ole kuitenkaan yleisesti hyödynnetty laadulliseen analyysiin tukeutuvaa ennakoinnin weak signals - toimintaa. Ulkoisenja sisäisen tiedon integroinnin ja systematiikan hyödyt PK -yritysten tukena vaativat merkittävää panostusta julkishallinnon rahoituksen ja kehitystoiminnan tukimuotoina. Ennakointi onkin tuottanut lukuisia julkishallinnon raportteja, mutta ei käytännön toteutuksia. Toisaalta analysoitujen case-tapausten tuloksena voidaan nähdä, ettei organisaatioissa välttämättä tarvita omaa projektipäällikköä liiketoiminnan tuen kehittämiseksi. Business vastuun ottamiseksi ja asiaan sitoutumiseen on kuitenkin löydyttävä oikea henkilö

Blood-Borne Circadian Signal Stimulates Daily Oscillations in Actin Dynamics and SRF Activity.

In peripheral tissues circadian gene expression can be driven either by local oscillators or by cyclic systemic cues controlled by the master clock in the brain's suprachiasmatic nucleus. In the latter case, systemic signals can activate immediate early transcription factors (IETFs) and thereby control rhythmic transcription. In order to identify IETFs induced by diurnal blood-borne signals, we developed an unbiased experimental strategy, dubbed Synthetic TAndem Repeat PROMoter (STAR-PROM) screening. This technique relies on the observation that most transcription factor binding sites exist at a relatively high frequency in random DNA sequences. Using STAR-PROM we identified serum response factor (SRF) as an IETF responding to oscillating signaling proteins present in human and rodent sera. Our data suggest that in mouse liver SRF is regulated via dramatic diurnal changes of actin dynamics, leading to the rhythmic translocation of the SRF coactivator Myocardin-related transcription factor-B (MRTF-B) into the nucleus.

Current Issues in the Diagnosis and Classification of Peripheral T-Cell Lymphomas

Mature T-cell and T/NK-cell neoplasms are both uncommon and heterogeneous, among the broad category of non-Hodgkin's lymphomas. Due to the lack of specific genetic alterations in the vast majority of cases, most currently defined entities show overlapping morphologic and immunophenotypic features and therefore pose a challenge to the diagnostic pathologist. The goal of the symposium is to address current criteria for the recognition of specific subtypes of T-cell lymphoma, and to highlight new data regarding emerging immunophenotypic or molecular markers. This activity has been designed to meet the needs of practicing pathologists, and residents and fellows enrolled in training programs in anatomic and clinical pathology. It should be a particular benefit to those with an interest in hematopathology. Upon completion of this activity, participants should be better able to: -To be able to state the basis for the classification of mature T-cell malignancies involving nodal and extranodal sites. -To recognize and accurately diagnose the various subtypes of nodal and extranodal peripheral T-cell lymphomas. -To utilize immunohistochemical and molecular tests to characterize atypical T-cell proliferations. -To recognize and accurately diagnose T-cell lymphoproliferative lesions involving the skin and gastrointestinal tract, and be able to provide guidance regarding their clinical aggressiveness and management -To be able to utilize flow cytometric data to identify diverse functional T-cell subsets.

Image-Based Coral Reef Classification and Thematic Mapping

This paper presents a novel image classification scheme for benthic coral reef images that can be applied to both single image and composite mosaic datasets. The proposed method can be configured to the characteristics (e.g., the size of the dataset, number of classes, resolution of the samples, color information availability, class types, etc.) of individual datasets. The proposed method uses completed local binary pattern (CLBP), grey level co-occurrence matrix (GLCM), Gabor filter response, and opponent angle and hue channel color histograms as feature descriptors. For classification, either k-nearest neighbor (KNN), neural network (NN), support vector machine (SVM) or probability density weighted mean distance (PDWMD) is used. The combination of features and classifiers that attains the best results is presented together with the guidelines for selection. The accuracy and efficiency of our proposed method are compared with other state-of-the-art techniques using three benthic and three texture datasets. The proposed method achieves the highest overall classification accuracy of any of the tested methods and has moderate execution time. Finally, the proposed classification scheme is applied to a large-scale image mosaic of the Red Sea to create a completely classified thematic map of the reef benthos

Development of the Acoustic Emission Based Diagnostics Concept for the Rotary Lime Kiln

Reaaliaikainen, ennakoiva kunnonvalvonta on erittäin tärkeä osa modernin tehtaan tai tuotantolinjan toimintaa. Diplomityön teettäjä haluaa edelleen kehittää akustiseen emissioon perustuvaa kunnonvalvonta järjestelmäänsä, jotta siitä olisi enemmän hyötyä asiakkaalle. Diplomityö sisältää johdannonakustiseen emissioon ja akustisiin emissio sensoreihin. Työn tavoitteena oli kehittää päätöksentekojärjestelmä, jota käytettäisiin työn teettäjän valmistamien sensoreiden antaman tiedon automatisoituun analysointiin. Työssä on vertailtu kolmea eri ohjelmistotoimittajaa ja heidän ohjelmiaan, ja tehty ehdotus hankittavasta ohjelmistosta. Lisäksi työssä on kehitetty ohjeita, joiden avulla ohjelmisto ohjelmoidaan tuottamaan reaaliaikaista tietoa ja huolto-ohjeita sen käyttäjille. Lisäksi työssä annetaan ehdotuksia kunnonvalvonta- ja päätöksentekojärjestelmän edelleen kehittämiseen.