Improving gender classification accuracy in the wild

[EN]In this paper, we focus on gender recognition in challenging large scale scenarios. Firstly, we review the literature results achieved for the problem in large datasets, and select the currently hardest dataset: The Images of Groups. Secondly, we study the extraction of features from the face and its local context to improve the recognition accuracy. Diff erent descriptors, resolutions and classfii ers are studied, overcoming previous literature results, reaching an accuracy of 89.8%.

People semantic description and re-identification from point cloud geometry

The automatic extraction of biometric descriptors of anonymous people is a challenging scenario in camera networks. This task is typically accomplished making use of visual information. Calibrated RGBD sensors make possible the extraction of point cloud information. We present a novel approach for people semantic description and re-identification using the individual point cloud information. The proposal combines the use of simple geometric features with point cloud features based on surface normals.

New approaches to open problems in gene expression microarray data

In the past decade, the advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to enormous progress in the life science. Among the most important innovations is the microarray tecnology. It allows to quantify the expression for thousands of genes simultaneously by measurin the hybridization from a tissue of interest to probes on a small glass or plastic slide. The characteristics of these data include a fair amount of random noise, a predictor dimension in the thousand, and a sample noise in the dozens. One of the most exciting areas to which microarray technology has been applied is the challenge of deciphering complex disease such as cancer. In these studies, samples are taken from two or more groups of individuals with heterogeneous phenotypes, pathologies, or clinical outcomes. these samples are hybridized to microarrays in an effort to find a small number of genes which are strongly correlated with the group of individuals. Eventhough today methods to analyse the data are welle developed and close to reach a standard organization (through the effort of preposed International project like Microarray Gene Expression Data -MGED- Society [1]) it is not unfrequant to stumble in a clinician's question that do not have a compelling statistical method that could permit to answer it.The contribution of this dissertation in deciphering disease regards the development of new approaches aiming at handle open problems posed by clinicians in handle specific experimental designs. In Chapter 1 starting from a biological necessary introduction, we revise the microarray tecnologies and all the important steps that involve an experiment from the production of the array, to the quality controls ending with preprocessing steps that will be used into the data analysis in the rest of the dissertation. While in Chapter 2 a critical review of standard analysis methods are provided stressing most of problems that In Chapter 3 is introduced a method to adress the issue of unbalanced design of miacroarray experiments. In microarray experiments, experimental design is a crucial starting-point for obtaining reasonable results. In a two-class problem, an equal or similar number of samples it should be collected between the two classes. However in some cases, e.g. rare pathologies, the approach to be taken is less evident. We propose to address this issue by applying a modified version of SAM [2]. MultiSAM consists in a reiterated application of a SAM analysis, comparing the less populated class (LPC) with 1,000 random samplings of the same size from the more populated class (MPC) A list of the differentially expressed genes is generated for each SAM application. After 1,000 reiterations, each single probe given a "score" ranging from 0 to 1,000 based on its recurrence in the 1,000 lists as differentially expressed. The performance of MultiSAM was compared to the performance of SAM and LIMMA [3] over two simulated data sets via beta and exponential distribution. The results of all three algorithms over low- noise data sets seems acceptable However, on a real unbalanced two-channel data set reagardin Chronic Lymphocitic Leukemia, LIMMA finds no significant probe, SAM finds 23 significantly changed probes but cannot separate the two classes, while MultiSAM finds 122 probes with score >300 and separates the data into two clusters by hierarchical clustering. We also report extra-assay validation in terms of differentially expressed genes Although standard algorithms perform well over low-noise simulated data sets, multi-SAM seems to be the only one able to reveal subtle differences in gene expression profiles on real unbalanced data. In Chapter 4 a method to adress similarities evaluation in a three-class prblem by means of Relevance Vector Machine [4] is described. In fact, looking at microarray data in a prognostic and diagnostic clinical framework, not only differences could have a crucial role. In some cases similarities can give useful and, sometimes even more, important information. The goal, given three classes, could be to establish, with a certain level of confidence, if the third one is similar to the first or the second one. In this work we show that Relevance Vector Machine (RVM) [2] could be a possible solutions to the limitation of standard supervised classification. In fact, RVM offers many advantages compared, for example, with his well-known precursor (Support Vector Machine - SVM [3]). Among these advantages, the estimate of posterior probability of class membership represents a key feature to address the similarity issue. This is a highly important, but often overlooked, option of any practical pattern recognition system. We focused on Tumor-Grade-three-class problem, so we have 67 samples of grade I (G1), 54 samples of grade 3 (G3) and 100 samples of grade 2 (G2). The goal is to find a model able to separate G1 from G3, then evaluate the third class G2 as test-set to obtain the probability for samples of G2 to be member of class G1 or class G3. The analysis showed that breast cancer samples of grade II have a molecular profile more similar to breast cancer samples of grade I. Looking at the literature this result have been guessed, but no measure of significance was gived before.

On using periocular biometric for gender classification in the wild

[EN]Gender information may serve to automatically modulate interaction to the user needs, among other applications. Within the Computer Vision community, gender classification (GC) has mainly been accomplished with the facial pattern. Periocular biometrics has recently attracted researchers attention with successful results in the context of identity recognition. But, there is a lack of experimental evaluation of the periocular pattern for GC in the wild. The aim of this paper is to study the performance of this specific facial area in the currently most challenging large dataset for the problem.

An analysis of automatic gender classification

[EN]Different researches suggest that inner facial features are not the only discriminative features for tasks such as person identification or gender classification. Indeed, they have shown an influence of features which are part of the local face context, such as hair, on these tasks. However, object-centered approaches which ignore local context dominate the research in computational vision based facial analysis. In this paper, we performed an analysis to study which areas and which resolutions are diagnostic for the gender classification problem. We first demonstrate the importance of contextual features in human observers for gender classification using a psychophysical ”bubbles” technique.

Algorithms for on-line image registration from multiple views

Images of a scene, static or dynamic, are generally acquired at different epochs from different viewpoints. They potentially gather information about the whole scene and its relative motion with respect to the acquisition device. Data from different (in the spatial or temporal domain) visual sources can be fused together to provide a unique consistent representation of the whole scene, even recovering the third dimension, permitting a more complete understanding of the scene content. Moreover, the pose of the acquisition device can be achieved by estimating the relative motion parameters linking different views, thus providing localization information for automatic guidance purposes. Image registration is based on the use of pattern recognition techniques to match among corresponding parts of different views of the acquired scene. Depending on hypotheses or prior information about the sensor model, the motion model and/or the scene model, this information can be used to estimate global or local geometrical mapping functions between different images or different parts of them. These mapping functions contain relative motion parameters between the scene and the sensor(s) and can be used to integrate accordingly informations coming from the different sources to build a wider or even augmented representation of the scene. Accordingly, for their scene reconstruction and pose estimation capabilities, nowadays image registration techniques from multiple views are increasingly stirring up the interest of the scientific and industrial community. Depending on the applicative domain, accuracy, robustness, and computational payload of the algorithms represent important issues to be addressed and generally a trade-off among them has to be reached. Moreover, on-line performance is desirable in order to guarantee the direct interaction of the vision device with human actors or control systems. This thesis follows a general research approach to cope with these issues, almost independently from the scene content, under the constraint of rigid motions. This approach has been motivated by the portability to very different domains as a very desirable property to achieve. A general image registration approach suitable for on-line applications has been devised and assessed through two challenging case studies in different applicative domains. The first case study regards scene reconstruction through on-line mosaicing of optical microscopy cell images acquired with non automated equipment, while moving manually the microscope holder. By registering the images the field of view of the microscope can be widened, preserving the resolution while reconstructing the whole cell culture and permitting the microscopist to interactively explore the cell culture. In the second case study, the registration of terrestrial satellite images acquired by a camera integral with the satellite is utilized to estimate its three-dimensional orientation from visual data, for automatic guidance purposes. Critical aspects of these applications are emphasized and the choices adopted are motivated accordingly. Results are discussed in view of promising future developments.

Verkehrsmonitoring mit Hilfe von Radarfernerkundung

Für die Zukunft wird eine Zunahme an Verkehr prognostiziert, gleichzeitig herrscht ein Mangel an Raum und finanziellen Mitteln, um weitere Straßen zu bauen. Daher müssen die vorhandenen Kapazitäten durch eine bessere Verkehrssteuerung sinnvoller genutzt werden, z.B. durch Verkehrsleitsysteme. Dafür werden räumlich aufgelöste, d.h. den Verkehr in seiner flächenhaften Verteilung wiedergebende Daten benötigt, die jedoch fehlen. Bisher konnten Verkehrsdaten nur dort erhoben werden, wo sich örtlich feste Meßeinrichtungen befinden, jedoch können damit die fehlenden Daten nicht erhoben werden. Mit Fernerkundungssystemen ergibt sich die Möglichkeit, diese Daten flächendeckend mit einem Blick von oben zu erfassen. Nach jahrzehntelangen Erfahrungen mit Fernerkundungsmethoden zur Erfassung und Untersuchung der verschiedensten Phänomene auf der Erdoberfläche wird nun diese Methodik im Rahmen eines Pilotprojektes auf den Themenbereich Verkehr angewendet. Seit Ende der 1990er Jahre wurde mit flugzeuggetragenen optischen und Infrarot-Aufnahmesystemen Verkehr beobachtet. Doch bei schlechten Wetterbedingungen und insbesondere bei Bewölkung, sind keine brauchbaren Aufnahmen möglich. Mit einem abbildenden Radarverfahren werden Daten unabhängig von Wetter- und Tageslichtbedingungen oder Bewölkung erhoben. Im Rahmen dieser Arbeit wird untersucht, inwieweit mit Hilfe von flugzeuggetragenem synthetischem Apertur Radar (SAR) Verkehrsdaten aufgenommen, verarbeitet und sinnvoll angewendet werden können. Nicht nur wird die neue Technik der Along-Track Interferometrie (ATI) und die Prozessierung und Verarbeitung der aufgenommenen Verkehrsdaten ausführlich dargelegt, es wird darüberhinaus ein mit dieser Methodik erstellter Datensatz mit einer Verkehrssimulation verglichen und bewertet. Abschließend wird ein Ausblick auf zukünftige Entwicklungen der Radarfernerkundung zur Verkehrsdatenerfassung gegeben.

Il Problema della Sicurezza nel Cloud Computing

Il termine cloud ha origine dal mondo delle telecomunicazioni quando i provider iniziarono ad utilizzare servizi basati su reti virtuali private (VPN) per la comunicazione dei dati. Il cloud computing ha a che fare con la computazione, il software, l’accesso ai dati e servizi di memorizzazione in modo tale che l’utente finale non abbia idea della posizione fisica dei dati e la configurazione del sistema in cui risiedono. Il cloud computing è un recente trend nel mondo IT che muove la computazione e i dati lontano dai desktop e dai pc portatili portandoli in larghi data centers. La definizione di cloud computing data dal NIST dice che il cloud computing è un modello che permette accesso di rete on-demand a un pool condiviso di risorse computazionali che può essere rapidamente utilizzato e rilasciato con sforzo di gestione ed interazione con il provider del servizio minimi. Con la proliferazione a larga scala di Internet nel mondo le applicazioni ora possono essere distribuite come servizi tramite Internet; come risultato, i costi complessivi di questi servizi vengono abbattuti. L’obbiettivo principale del cloud computing è utilizzare meglio risorse distribuite, combinarle assieme per raggiungere un throughput più elevato e risolvere problemi di computazione su larga scala. Le aziende che si appoggiano ai servizi cloud risparmiano su costi di infrastruttura e mantenimento di risorse computazionali poichè trasferiscono questo aspetto al provider; in questo modo le aziende si possono occupare esclusivamente del business di loro interesse. Mano a mano che il cloud computing diventa più popolare, vengono esposte preoccupazioni riguardo i problemi di sicurezza introdotti con l’utilizzo di questo nuovo modello. Le caratteristiche di questo nuovo modello di deployment differiscono ampiamente da quelle delle architetture tradizionali, e i meccanismi di sicurezza tradizionali risultano inefficienti o inutili. Il cloud computing offre molti benefici ma è anche più vulnerabile a minacce. Ci sono molte sfide e rischi nel cloud computing che aumentano la minaccia della compromissione dei dati. Queste preoccupazioni rendono le aziende restie dall’adoperare soluzioni di cloud computing, rallentandone la diffusione. Negli anni recenti molti sforzi sono andati nella ricerca sulla sicurezza degli ambienti cloud, sulla classificazione delle minacce e sull’analisi di rischio; purtroppo i problemi del cloud sono di vario livello e non esiste una soluzione univoca. Dopo aver presentato una breve introduzione sul cloud computing in generale, l’obiettivo di questo elaborato è quello di fornire una panoramica sulle vulnerabilità principali del modello cloud in base alle sue caratteristiche, per poi effettuare una analisi di rischio dal punto di vista del cliente riguardo l’utilizzo del cloud. In questo modo valutando i rischi e le opportunità un cliente deve decidere se adottare una soluzione di tipo cloud. Alla fine verrà presentato un framework che mira a risolvere un particolare problema, quello del traffico malevolo sulla rete cloud. L’elaborato è strutturato nel modo seguente: nel primo capitolo verrà data una panoramica del cloud computing, evidenziandone caratteristiche, architettura, modelli di servizio, modelli di deployment ed eventuali problemi riguardo il cloud. Nel secondo capitolo verrà data una introduzione alla sicurezza in ambito informatico per poi passare nello specifico alla sicurezza nel modello di cloud computing. Verranno considerate le vulnerabilità derivanti dalle tecnologie e dalle caratteristiche che enucleano il cloud, per poi passare ad una analisi dei rischi. I rischi sono di diversa natura, da quelli prettamente tecnologici a quelli derivanti da questioni legali o amministrative, fino a quelli non specifici al cloud ma che lo riguardano comunque. Per ogni rischio verranno elencati i beni afflitti in caso di attacco e verrà espresso un livello di rischio che va dal basso fino al molto alto. Ogni rischio dovrà essere messo in conto con le opportunità che l’aspetto da cui quel rischio nasce offre. Nell’ultimo capitolo verrà illustrato un framework per la protezione della rete interna del cloud, installando un Intrusion Detection System con pattern recognition e anomaly detection.

Kostimulatorische Rezeptoren in der Aktivierung humaner neutrophiler Granulozyten

Neutrophile Granulozyten spielen eine wichtige Rolle in der ersten Phase der Inflammation. Sie infiltrieren den Infektionsort um den eingedrungenen Erreger zu bekämpfen und Ihre Effektor Funktion auszuführen. Neben den Mustererkennenden Rezeptoren des angeborenen Immunsystems (pattern recognition receptors) werden weitere Rezeptoren auf der Oberfläche von neutrophilen Granulozyten exprimiert, welche zur Aktivierung der Zelle beitragen können. In dieser arbeit wurden der Herpes Virus Entry Mediator (HVEM) und Triggering Receptor expressed on Myeloid Cells-1 (TREM-1) auf neutrophilen untersucht. Für HVEM konnte eine synergistische Aktivierung von neutrophilen Granulozyten im Zusammenspiel mit Toll like Rezeptor (TLR) Liganden nachgewiesen werden. Für TREM-1 konnte ein Vorhandensein eines Liganden auch Thrombozyten beschrieben. Es wurden weiterhin Mechanismen untersucht und beschrieben, welche für die synergistische Aktivierung von neutrophilen Granulozyten verantwortlich sind, welche nach TREM-1 und TLR Stimulation erkennbar ist.

Aspects of poriferan (Suberites domuncula) apoptosis and innate immune system and evolutionary implications

Survivin, a unique member of the family of inhibitors of apoptosis (IAP) proteins, orchestrates intracellular pathways during cell division and apoptosis. Its central regulatory function in vertebrate molecular pathways as mitotic regulator and inhibitor of apoptotic cell death has major implications for tumor cell proliferation and viability, and has inspired several approaches that target survivin for cancer therapy. Analyses in early-branching Metazoa so far propose an exclusive role of survivin as a chromosomal passenger protein, whereas only later during evolution the second, complementary antiapoptotic function might have arisen, concurrent with increased organismal complexity. To lift the veil on the ancestral function(s) of this key regulatory molecule, a survivin homologue of the phylogenetically oldest extant metazoan taxon (phylum Porifera) was identified and functionally characterized. SURVL of the demosponge Suberites domuncula shares significant similarities with its metazoan homologues, ranging from conserved exon/intron structures to the presence of localization signal and protein-interaction domains, characteristic of IAP proteins. Whereas sponge tissue displayed a very low steady-state level, SURVL expression was significantly up-regulated in rapidly proliferating primmorph cells. In addition, challenge of sponge tissue and primmorphs with cadmium and the lipopeptide Pam3Cys-Ser-(Lys)4 stimulated SURVL expression, concurrent with the expression of newly discovered poriferan caspases (CASL and CASL2). Complementary functional analyses in transfected HEK-293 revealed that heterologous expression of poriferan survivin in human cells not only promotes cell proliferation but also augments resistance to cadmium-induced cell death. Taken together, these results demonstrate both a deep evolutionary conserved and fundamental dual role of survivin, and an equally conserved central position of this key regulatory molecule in interconnected pathways of cell cycle and apoptosis. Additionally, SDCASL, SDCASL2, and SDTILRc (TIR-LRR containing protein) may represent new components of the innate defense sentinel in sponges. SDCASL and SDCASL2 are two new caspase-homolog proteins with a singular structure. In addition to their CASc domains, SDCASL and SDCASL2 feature a small prodomain NH2-terminal (effector caspases) and a remarkably long COOH-terminal domain containing one or several functional double stranded RNA binding domains (dsrm). This new caspase prototype can characterize a caspase specialization coupling pathogen sensing and apoptosis, and could represent a very efficient defense mechanism. SDTILRc encompasses also a unique combination of domains: several leucine rich repeats (LRR) and a Toll/IL-1 receptor (TIR) domain. This unusual domain association may correspond to a new family of intracellular sensing protein, forming a subclass of pattern recognition receptors (PRR).

Studio di geometrie di antenne su pcb per trasmissione wireless ultra-wideband

La presente tesi tratta la progettazione e la simulazione via software di geometrie di antenne da realizzare direttamente su Printed Circuit Board (PCB) per schede di trasmissione dati wireless Ultra Wide Band. L’obiettivo principale di questo studio è la realizzazione di un prototipo per impieghi biomedici umani (ad esempio trasmissione di dati provenienti da un ECG). Lo scopo del lavoro svolto è quello di trovare la miglior soluzione di integrazione per un’antenna il più possibile compatta da realizzare poi direttamente sul substrato dove verrà stampato il circuito del trasmettitore stesso. L’antenna verrà quindi realizzata esclusivamente attraverso microstrisce conduttrici (le medesime che formeranno i collegamenti tra i vari componenti del circuito) prendendo in considerazione le grandezze parassite di ogni conduttore, quali resistenza, induttanza, capacità ecc. In conclusione, il circuito di trasmissione wireless completo di antenna sopra descritto è attualmente in fase di realizzazione e nel prossimo futuro verrà testato in laboratorio.

Role of αvβ3 – Integrin and TLR2 in the innate response to Herpes Simplex Virus infection and Delivery of retargeted oncolytic Herpes Simplex via carrier cells

In the first part of my thesis I studied the mechanism of initiation of the innate response to HSV-1. Innate immune response is the first line of defense set up by the cell to counteract pathogens infection and it is elicited by the activation of a number of membrane or intracellular receptors and sensors, collectively indicated as PRRs, Patter Recognition Receptors. We reported that the HSV pathogen-associated molecular patterns (PAMP) that activate Toll-like receptor 2 (TLR2) and lead to the initiation of innate response are the virion glycoproteins gH/gL and gB, which constitute the conserved fusion core apparatus across the Herpesvirus. Specifically gH/gL is sufficient to initiate a signaling cascade which leads to NF-κB activation. Then, by gain and loss-of-function approaches, we found that αvβ3-integrin is a sensor of and plays a crucial role in the innate defense against HSV-1. We showed that αvβ3-integrin signals through a pathway that concurs with TLR2, affects activation/induction of interferons type 1, NF-κB, and a polarized set of cytokines and receptors. Thus, we demonstrated that gH/gL is sufficient to induce IFN1 and NF-κB via this pathway. From these data, we proposed that αvβ3-integrin is considered a class of non-TLR pattern recognition receptors. In the second part of my thesis I studied the capacity of human mesenchymal stromal cells isolated by fetal membranes (FM-hMSCs) to be used as carrier cells for the delivery of retargeted R-LM249 virus. The use of systemically administrated carrier cells to deliver oncolytic viruses to tumoral targets is a promising strategy in oncolytic virotherapy. We observed that FM-hMSCs can be infected by R-LM249 and we optimized the infection condition; then we demonstrate that stromal cells sustain the replication of retargeted R-LM249 and spread it to target tumoral cells. From these preliminary data FM-hMSCs resulted suitable to be used as carrier cells

Imaging and modeling of pore scale processes in porous media using X-ray computed tomography and lattice Boltzmann solver

In der Erdöl– und Gasindustrie sind bildgebende Verfahren und Simulationen auf der Porenskala im Begriff Routineanwendungen zu werden. Ihr weiteres Potential lässt sich im Umweltbereich anwenden, wie z.B. für den Transport und Verbleib von Schadstoffen im Untergrund, die Speicherung von Kohlendioxid und dem natürlichen Abbau von Schadstoffen in Böden. Mit der Röntgen-Computertomografie (XCT) steht ein zerstörungsfreies 3D bildgebendes Verfahren zur Verfügung, das auch häufig für die Untersuchung der internen Struktur geologischer Proben herangezogen wird. Das erste Ziel dieser Dissertation war die Implementierung einer Bildverarbeitungstechnik, die die Strahlenaufhärtung der Röntgen-Computertomografie beseitigt und den Segmentierungsprozess dessen Daten vereinfacht. Das zweite Ziel dieser Arbeit untersuchte die kombinierten Effekte von Porenraumcharakteristika, Porentortuosität, sowie die Strömungssimulation und Transportmodellierung in Porenräumen mit der Gitter-Boltzmann-Methode. In einer zylindrischen geologischen Probe war die Position jeder Phase auf Grundlage der Beobachtung durch das Vorhandensein der Strahlenaufhärtung in den rekonstruierten Bildern, das eine radiale Funktion vom Probenrand zum Zentrum darstellt, extrahierbar und die unterschiedlichen Phasen ließen sich automatisch segmentieren. Weiterhin wurden Strahlungsaufhärtungeffekte von beliebig geformten Objekten durch einen Oberflächenanpassungsalgorithmus korrigiert. Die Methode der „least square support vector machine” (LSSVM) ist durch einen modularen Aufbau charakterisiert und ist sehr gut für die Erkennung und Klassifizierung von Mustern geeignet. Aus diesem Grund wurde die Methode der LSSVM als pixelbasierte Klassifikationsmethode implementiert. Dieser Algorithmus ist in der Lage komplexe geologische Proben korrekt zu klassifizieren, benötigt für den Fall aber längere Rechenzeiten, so dass mehrdimensionale Trainingsdatensätze verwendet werden müssen. Die Dynamik von den unmischbaren Phasen Luft und Wasser wird durch eine Kombination von Porenmorphologie und Gitter Boltzmann Methode für Drainage und Imbibition Prozessen in 3D Datensätzen von Böden, die durch synchrotron-basierte XCT gewonnen wurden, untersucht. Obwohl die Porenmorphologie eine einfache Methode ist Kugeln in den verfügbaren Porenraum einzupassen, kann sie dennoch die komplexe kapillare Hysterese als eine Funktion der Wassersättigung erklären. Eine Hysterese ist für den Kapillardruck und die hydraulische Leitfähigkeit beobachtet worden, welche durch die hauptsächlich verbundenen Porennetzwerke und der verfügbaren Porenraumgrößenverteilung verursacht sind. Die hydraulische Konduktivität ist eine Funktion des Wassersättigungslevels und wird mit einer makroskopischen Berechnung empirischer Modelle verglichen. Die Daten stimmen vor allem für hohe Wassersättigungen gut überein. Um die Gegenwart von Krankheitserregern im Grundwasser und Abwässern vorhersagen zu können, wurde in einem Bodenaggregat der Einfluss von Korngröße, Porengeometrie und Fluidflussgeschwindigkeit z.B. mit dem Mikroorganismus Escherichia coli studiert. Die asymmetrischen und langschweifigen Durchbruchskurven, besonders bei höheren Wassersättigungen, wurden durch dispersiven Transport aufgrund des verbundenen Porennetzwerks und durch die Heterogenität des Strömungsfeldes verursacht. Es wurde beobachtet, dass die biokolloidale Verweilzeit eine Funktion des Druckgradienten als auch der Kolloidgröße ist. Unsere Modellierungsergebnisse stimmen sehr gut mit den bereits veröffentlichten Daten überein.