A comparison of face and facial feature detectors based on the viola-jones general object detection framework

[EN]The human face provides useful information during interaction; therefore, any system integrating Vision- BasedHuman Computer Interaction requires fast and reliable face and facial feature detection. Different approaches have focused on this ability but only open source implementations have been extensively used by researchers. A good example is the Viola–Jones object detection framework that particularly in the context of facial processing has been frequently used.

A new snowfall detection algorithm for high latitude regions based on a combination of active and passive sensors

Precipitation retrieval over high latitudes, particularly snowfall retrieval over ice and snow, using satellite-based passive microwave spectrometers, is currently an unsolved problem. The challenge results from the large variability of microwave emissivity spectra for snow and ice surfaces, which can mimic, to some degree, the spectral characteristics of snowfall. This work focuses on the investigation of a new snowfall detection algorithm specific for high latitude regions, based on a combination of active and passive sensors able to discriminate between snowing and non snowing areas. The space-borne Cloud Profiling Radar (on CloudSat), the Advanced Microwave Sensor units A and B (on NOAA-16) and the infrared spectrometer MODIS (on AQUA) have been co-located for 365 days, from October 1st 2006 to September 30th, 2007. CloudSat products have been used as truth to calibrate and validate all the proposed algorithms. The methodological approach followed can be summarised into two different steps. In a first step, an empirical search for a threshold, aimed at discriminating the case of no snow, was performed, following Kongoli et al. [2003]. This single-channel approach has not produced appropriate results, a more statistically sound approach was attempted. Two different techniques, which allow to compute the probability above and below a Brightness Temperature (BT) threshold, have been used on the available data. The first technique is based upon a Logistic Distribution to represent the probability of Snow given the predictors. The second technique, defined Bayesian Multivariate Binary Predictor (BMBP), is a fully Bayesian technique not requiring any hypothesis on the shape of the probabilistic model (such as for instance the Logistic), which only requires the estimation of the BT thresholds. The results obtained show that both methods proposed are able to discriminate snowing and non snowing condition over the Polar regions with a probability of correct detection larger than 0.5, highlighting the importance of a multispectral approach.

Development of muliplexed analytical methods based on bioluminescent whole-cell biosensors

The subject of this Ph.D. research thesis is the development and application of multiplexed analytical methods based on bioluminescent whole-cell biosensors. One of the main goals of analytical chemistry is multianalyte testing in which two or more analytes are measured simultaneously in a single assay. The advantages of multianalyte testing are work simplification, high throughput, and reduction in the overall cost per test. The availability of multiplexed portable analytical systems is of particular interest for on-field analysis of clinical, environmental or food samples as well as for the drug discovery process. To allow highly sensitive and selective analysis, these devices should combine biospecific molecular recognition with ultrasensitive detection systems. To address the current need for rapid, highly sensitive and inexpensive devices for obtaining more data from each sample,genetically engineered whole-cell biosensors as biospecific recognition element were combined with ultrasensitive bioluminescence detection techniques. Genetically engineered cell-based sensing systems were obtained by introducing into bacterial, yeast or mammalian cells a vector expressing a reporter protein whose expression is controlled by regulatory proteins and promoter sequences. The regulatory protein is able to recognize the presence of the analyte (e.g., compounds with hormone-like activity, heavy metals…) and to consequently activate the expression of the reporter protein that can be readily measured and directly related to the analyte bioavailable concentration in the sample. Bioluminescence represents the ideal detection principle for miniaturized analytical devices and multiplexed assays thanks to high detectability in small sample volumes allowing an accurate signal localization and quantification. In the first chapter of this dissertation is discussed the obtainment of improved bioluminescent proteins emitting at different wavelenghts, in term of increased thermostability, enhanced emission decay kinetic and spectral resolution. The second chapter is mainly focused on the use of these proteins in the development of whole-cell based assay with improved analytical performance. In particular since the main drawback of whole-cell biosensors is the high variability of their analyte specific response mainly caused by variations in cell viability due to aspecific effects of the sample’s matrix, an additional bioluminescent reporter has been introduced to correct the analytical response thus increasing the robustness of the bioassays. The feasibility of using a combination of two or more bioluminescent proteins for obtaining biosensors with internal signal correction or for the simultaneous detection of multiple analytes has been demonstrated by developing a dual reporter yeast based biosensor for androgenic activity measurement and a triple reporter mammalian cell-based biosensor for the simultaneous monitoring of two CYP450 enzymes activation, involved in cholesterol degradation, with the use of two spectrally resolved intracellular luciferases and a secreted luciferase as a control for cells viability. In the third chapter is presented the development of a portable multianalyte detection system. In order to develop a portable system that can be used also outside the laboratory environment even by non skilled personnel, cells have been immobilized into a new biocompatible and transparent polymeric matrix within a modified clear bottom black 384 -well microtiter plate to obtain a bioluminescent cell array. The cell array was placed in contact with a portable charge-coupled device (CCD) light sensor able to localize and quantify the luminescent signal produced by different bioluminescent whole-cell biosensors. This multiplexed biosensing platform containing whole-cell biosensors was successfully used to measure the overall toxicity of a given sample as well as to obtain dose response curves for heavy metals and to detect hormonal activity in clinical samples (PCT/IB2010/050625: “Portable device based on immobilized cells for the detection of analytes.” Michelini E, Roda A, Dolci LS, Mezzanotte L, Cevenini L , 2010). At the end of the dissertation some future development steps are also discussed in order to develop a point of care (POCT) device that combine portability, minimum sample pre-treatment and highly sensitive multiplexed assays in a short assay time. In this POCT perspective, field-flow fractionation (FFF) techniques, in particular gravitational variant (GrFFF) that exploit the earth gravitational field to structure the separation, have been investigated for cells fractionation, characterization and isolation. Thanks to the simplicity of its equipment, amenable to miniaturization, the GrFFF techniques appears to be particularly suited for its implementation in POCT devices and may be used as pre-analytical integrated module to be applied directly to drive target analytes of raw samples to the modules where biospecifc recognition reactions based on ultrasensitive bioluminescence detection occurs, providing an increase in overall analytical output.

Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

Functional dextran-based hydrogels

Dextran-based polymers are versatile hydrophilic materials, which can provide functionalized surfaces in various areas including biological and medical applications. Functional, responsive, dextran based hydrogels are crosslinked, dextran based polymers allowing the modulation of response towards external stimuli. The controlled modulation of hydrogel properties towards specific applications and the detailed characterization of the optical, mechanical, and chemical properties are of strong interest in science and further applications. Especially, the structural characteristics of swollen hydrogel matrices and the characterization of their variations upon environmental changes are challenging. Depending on their properties hydrogels are applied as actuators, biosensors, in drug delivery, tissue engineering, or for medical coatings. However, the field of possible applications still shows potential to be expanded. rnSurface attached hydrogel films with a thickness of several micrometers can serve as waveguiding matrix for leaky optical waveguide modes. On the basis of highly swelling and waveguiding dextran based hydrogel films an optical biosensor concept was developed. The synthesis of a dextran based hydrogel matrix, its functionalization to modulate its response towards external stimuli, and the characterization of the swollen hydrogel films were main interests within this biosensor project. A second focus was the optimization of the hydrogel characteristics for cell growth with the aim of creating scaffolds for bone regeneration. Matrix modification towards successful cell growth experiments with endothelial cells and osteoblasts was achieved.rnA photo crosslinkable, carboxymethylated dextran based hydrogel (PCMD) was synthesized and characterized in terms of swelling behaviour and structural properties. Further functionalization was carried out before and after crosslinking. This functionalization aimed towards external manipulation of the swelling degree and the charge of the hydrogel matrix important for biosensor experiments as well as for cell adhesion. The modulation of functionalized PCMD hydrogel responses to pH, ion concentration, electrochemical switching, or a magnetic force was investigated. rnThe PCMD hydrogel films were optically characterized by combining surface plasmon resonance (SPR) and optical waveguide mode spectroscopy (OWS). This technique allows a detailed analysis of the refractive index profile perpendicular to the substrate surface by applying the Wentzel Kramers Brillouin (WKB) approximation. rnIn order to perform biosensor experiments, analyte capturing units such as proteins or antibodies were covalently coupled to the crosslinked hydrogel backbone by applying active ester chemistry. Consequently, target analytes could be located inside the waveguiding matrix. By using labeled analytes, fluorescence enhancement was achieved by fluorescence excitation with the electromagnetic field in the center of the optical waveguide modes. The fluorescence excited by the evanescent electromagnetic field of the surface plasmon was 2 3 orders of magnitude lower. Furthermore, the signal to noise ratio was improved by the fluorescence excitation with leaky optical waveguide modes.rnThe applicability of the PCMD hydrogel sensor matrix for clinically relevant samples was proofed in a cooperation project for the detection of PSA in serum with long range surface plasmon spectroscopy (LRSP) and fluorescence excitation by LRSP (LR SPFS). rn

Diagnosis and Fault detection in Electrical Machines and Drives based on Advanced Signal Processing Techniques

In the present thesis, a new methodology of diagnosis based on advanced use of time-frequency technique analysis is presented. More precisely, a new fault index that allows tracking individual fault components in a single frequency band is defined. More in detail, a frequency sliding is applied to the signals being analyzed (currents, voltages, vibration signals), so that each single fault frequency component is shifted into a prefixed single frequency band. Then, the discrete Wavelet Transform is applied to the resulting signal to extract the fault signature in the frequency band that has been chosen. Once the state of the machine has been qualitatively diagnosed, a quantitative evaluation of the fault degree is necessary. For this purpose, a fault index based on the energy calculation of approximation and/or detail signals resulting from wavelet decomposition has been introduced to quantify the fault extend. The main advantages of the developed new method over existing Diagnosis techniques are the following: - Capability of monitoring the fault evolution continuously over time under any transient operating condition; - Speed/slip measurement or estimation is not required; - Higher accuracy in filtering frequency components around the fundamental in case of rotor faults; - Reduction in the likelihood of false indications by avoiding confusion with other fault harmonics (the contribution of the most relevant fault frequency components under speed-varying conditions are clamped in a single frequency band); - Low memory requirement due to low sampling frequency; - Reduction in the latency of time processing (no requirement of repeated sampling operation).

An inter-comparison between a VIS/IR and a MW satellite-based methods for cloud detection and classification

This thesis is aimed to assess similarities and mismatches between the outputs from two independent methods for the cloud cover quantification and classification based on quite different physical basis. One of them is the SAFNWC software package designed to process radiance data acquired by the SEVIRI sensor in the VIS/IR. The other is the MWCC algorithm, which uses the brightness temperatures acquired by the AMSU-B and MHS sensors in their channels centered in the MW water vapour absorption band. At a first stage their cloud detection capability has been tested, by comparing the Cloud Masks they produced. These showed a good agreement between two methods, although some critical situations stand out. The MWCC, in effect, fails to reveal clouds which according to SAFNWC are fractional, cirrus, very low and high opaque clouds. In the second stage of the inter-comparison the pixels classified as cloudy according to both softwares have been. The overall observed tendency of the MWCC method, is an overestimation of the lower cloud classes. Viceversa, the more the cloud top height grows up, the more the MWCC not reveal a certain cloud portion, rather detected by means of the SAFNWC tool. This is what also emerges from a series of tests carried out by using the cloud top height information in order to evaluate the height ranges in which each MWCC category is defined. Therefore, although the involved methods intend to provide the same kind of information, in reality they return quite different details on the same atmospheric column. The SAFNWC retrieval being very sensitive to the top temperature of a cloud, brings the actual level reached by this. The MWCC, by exploiting the capability of the microwaves, is able to give an information about the levels that are located more deeply within the atmospheric column.

Evaluation of cartilage repair tissue after matrix-associated autologous chondrocyte transplantation using a hyaluronic-based or a collagen-based scaffold with morphological MOCART scoring and biochemical T2 mapping: preliminary results

In cartilage repair, bioregenerative approaches using tissue engineering techniques have tried to achieve a close resemblance to hyaline cartilage, which might be visualized using advanced magnetic resonance imaging.

A Decision-Tree-Based Approach to Smoke Spike Detection in a Heavy-Duty Diesel Engine

Smoke spikes occurring during transient engine operation have detrimental health effects and increase fuel consumption by requiring more frequent regeneration of the diesel particulate filter. This paper proposes a decision tree approach to real-time detection of smoke spikes for control and on-board diagnostics purposes. A contemporary, electronically controlled heavy-duty diesel engine was used to investigate the deficiencies of smoke control based on the fuel-to-oxygen-ratio limit. With the aid of transient and steady state data analysis and empirical as well as dimensional modeling, it was shown that the fuel-to-oxygen ratio was not estimated correctly during the turbocharger lag period. This inaccuracy was attributed to the large manifold pressure ratios and low exhaust gas recirculation flows recorded during the turbocharger lag period, which meant that engine control module correlations for the exhaust gas recirculation flow and the volumetric efficiency had to be extrapolated. The engine control module correlations were based on steady state data and it was shown that, unless the turbocharger efficiency is artificially reduced, the large manifold pressure ratios observed during the turbocharger lag period cannot be achieved at steady state. Additionally, the cylinder-to-cylinder variation during this period were shown to be sufficiently significant to make the average fuel-to-oxygen ratio a poor predictor of the transient smoke emissions. The steady state data also showed higher smoke emissions with higher exhaust gas recirculation fractions at constant fuel-to-oxygen-ratio levels. This suggests that, even if the fuel-to-oxygen ratios were to be estimated accurately for each cylinder, they would still be ineffective as smoke limiters. A decision tree trained on snap throttle data and pruned with engineering knowledge was able to use the inaccurate engine control module estimates of the fuel-to-oxygen ratio together with information on the engine control module estimate of the exhaust gas recirculation fraction, the engine speed, and the manifold pressure ratio to predict 94% of all spikes occurring over the Federal Test Procedure cycle. The advantages of this non-parametric approach over other commonly used parametric empirical methods such as regression were described. An application of accurate smoke spike detection in which the injection pressure is increased at points with a high opacity to reduce the cumulative particulate matter emissions substantially with a minimum increase in the cumulative nitrogrn oxide emissions was illustrated with dimensional and empirical modeling.

Sensitive and rapid detection of ganciclovir resistance by PCR based MALDI-TOF analysis

Cytomegalovirus (CMV) infection is associated with significant morbidity and mortality in transplant recipients. Resistance against ganciclovir is increasingly observed. According to current guidelines, direct drug resistance testing is not always performed due to high costs and work effort, even when resistance is suspected.

The performance of conventional and fluorescence-based methods for occlusal caries detection: an in vivo study with histologic validation

The authors conducted an in vivo study to determine clinical cutoffs for a laser fluorescence (LF) device, an LF pen and a fluorescence camera (FC), as well as to evaluate the clinical performance of these methods and conventional methods in detecting occlusal caries in permanent teeth by using the histologic gold standard for total validation of the sample.

Bovine pericardium based non-cross linked collagen matrix for successful root coverage, a clinical study in human

Introduction The aim of this study was to clinically assess the capacity of a novel bovine pericardium based, non-cross linked collagen matrix in root coverage. Methods 62 gingival recessions of Miller class I or II were treated. The matrix was adapted underneath a coronal repositioned split thickness flap. Clinical values were assessed at baseline and after six months. Results The mean recession in each patient was 2.2 mm at baseline. 6 Months after surgery 86.7% of the exposed root surfaces were covered. On average 0,3 mm of recession remained. The clinical attachment level changed from 3.5 ± 1.3 mm to 1,8 ( ± 0,7) mm during the observational time period. No statistically significant difference was found in the difference of probing depth. An increase in the width of gingiva was significant. With a baseline value of 1.5 ± 0.9 mm an improvement of 2.4 ± 0.8 mm after six month could be observed. 40 out of 62 recessions were considered a thin biotype at baseline. After 6 months all 62 sites were assessed thick. Conclusions The results demonstrate the capacity of the bovine pericardium based non-cross linked collagen matrix for successful root coverage. This material was able to enhance gingival thickness and the width of keratinized gingiva. The percentage of root coverage achieved thereby is comparable to existing techniques. This method might contribute to an increase of patient's comfort and an enhanced aesthetical outcome.

Detection of Mycoplasma mycoides subsp. mycoides SC in bronchoalveolar lavage fluids of cows based on a TaqMan real-time PCR discriminating wild type strains from an lppQ(-) mutant vaccine strain used for DIVA-strategies

Contagious bovine pleuropneumonia (CBPP) is the most serious cattle disease in Africa, caused by Mycoplasma mycoides subsp. mycoides small-colony type (SC). CBPP control strategies currently rely on vaccination with a vaccine based on live attenuated strains of the organism. Recently, an lppQ(-) mutant of the existing vaccine strain T1/44 has been developed (Janis et al., 2008). This T1lppQ(-) mutant strain is devoid of lipoprotein LppQ, a potential virulence attribute of M. mycoides subsp. mycoides SC. It is designated as a potential live DIVA (Differentiating Infected from Vaccinated Animals) vaccine strain allowing both serological and etiological differentiation. The present paper reports on the validation of a control strategy for CBPP in cattle, whereby a TaqMan real-time PCR based on the lppQ gene has been developed for the direct detection of M. mycoides subsp. mycoides SC in ex vivo bronchoalveolar lavage fluids of cows and for the discrimination of wild type strains from the lppQ(-) mutant vaccine strain.