Incorporating label dependency into the binary relevance framework for multi-label classification

In multi-label classification, examples can be associated with multiple labels simultaneously. The task of learning from multi-label data can be addressed by methods that transform the multi-label classification problem into several single-label classification problems. The binary relevance approach is one of these methods, where the multi-label learning task is decomposed into several independent binary classification problems, one for each label in the set of labels, and the final labels for each example are determined by aggregating the predictions from all binary classifiers. However, this approach fails to consider any dependency among the labels. Aiming to accurately predict label combinations, in this paper we propose a simple approach that enables the binary classifiers to discover existing label dependency by themselves. An experimental study using decision trees, a kernel method as well as Naive Bayes as base-learning techniques shows the potential of the proposed approach to improve the multi-label classification performance.

Texture analysis by multi-resolution fractal descriptors

This work proposes a novel texture descriptor based on fractal theory. The method is based on the Bouligand- Minkowski descriptors. We decompose the original image recursively into four equal parts. In each recursion step, we estimate the average and the deviation of the Bouligand-Minkowski descriptors computed over each part. Thus, we extract entropy features from both average and deviation. The proposed descriptors are provided by concatenating such measures. The method is tested in a classification experiment under well known datasets, that is, Brodatz and Vistex. The results demonstrate that the novel technique achieves better results than classical and state-of-the-art texture descriptors, such as Local Binary Patterns, Gabor-wavelets and co-occurrence matrix.

Multi-parameter observations from coastal waters to the deepest trenche: challenges studying the carbón system with optode technology

[EN]This presentation will give examples on how multi-parameter platforms have been used in a variety of applications ranging from shallow coastal on-line observatories down to measuring in the deepest Ocean trenches. Focus will be on projects in which optode technology (primarily for CO2 and O2) has served to study different aspects of the carbon system including primary production/consumption, air-sea exchange, leakage detection from underwater storage of CO2 and measurements from moving platforms like gliders and ferries. The performance of recently developed pH optodes will als

Multi-Sensor people counting

[EN]An accurate estimation of the number of people entering / leaving a controlled area is an interesting capability for automatic surveil- lance systems. Potential applications where this technology can be ap- plied include those related to security, safety, energy saving or fraud control. In this paper we present a novel con guration of a multi-sensor system combining both visual and range data specially suited for trou- blesome scenarios such as public transportation. The approach applies probabilistic estimation lters on raw sensor data to create intermediate level hypothesis that are later fused using a certainty-based integration stage. Promising results have been obtained in several tests performed on a realistic test bed scenario under variable lightning conditions.

EXAM-S: an Analysis tool for Multi-Domain Policy Sets

As distributed collaborative applications and architectures are adopting policy based management for tasks such as access control, network security and data privacy, the management and consolidation of a large number of policies is becoming a crucial component of such policy based systems. In large-scale distributed collaborative applications like web services, there is the need of analyzing policy interactions and integrating policies. In this thesis, we propose and implement EXAM-S, a comprehensive environment for policy analysis and management, which can be used to perform a variety of functions such as policy property analyses, policy similarity analysis, policy integration etc. As part of this environment, we have proposed and implemented new techniques for the analysis of policies that rely on a deep study of state of the art techniques. Moreover, we propose an approach for solving heterogeneity problems that usually arise when considering the analysis of policies belonging to different domains. Our work focuses on analysis of access control policies written in the dialect of XACML (Extensible Access Control Markup Language). We consider XACML policies because XACML is a rich language which can represent many policies of interest to real world applications and is gaining widespread adoption in the industry.

Cluster-derived Gold/Iron catalysts for environmental applications

During the last years we assisted to an exponential growth of scientific discoveries for catalysis by gold and many applications have been found for Au-based catalysts. In the literature there are several studies concerning the use of gold-based catalysts for environmental applications and good results are reported for the catalytic combustion of different volatile organic compounds (VOCs). Recently it has also been established that gold-based catalysts are potentially capable of being effectively employed in fuel cells in order to remove CO traces by preferential CO oxidation in H2-rich streams. Bi-metallic catalysts have attracted increasing attention because of their markedly different properties from either of the costituent metals, and above all their enhanced catalytic activity, selectivity and stability. In the literature there are several studies demostrating the beneficial effect due to the addition of an iron component to gold supported catalysts in terms of enhanced activity, selectivity, resistence to deactivation and prolonged lifetime of the catalyst. In this work we tried to develop a methodology for the preparation of iron stabilized gold nanoparticles with controlled size and composition, particularly in terms of obtaining an intimate contact between different phases, since it is well known that the catalytic behaviour of multi-component supported catalysts is strongly influenced by the size of the metal particles and by their reciprocal interaction. Ligand stabilized metal clusters, with nanometric dimensions, are possible precursors for the preparation of catalytically active nanoparticles with controlled dimensions and compositions. Among these, metal carbonyl clusters are quite attractive, since they can be prepared with several different sizes and compositions and, moreover, they are decomposed under very mild conditions. A novel preparation method was developed during this thesis for the preparation of iron and gold/iron supported catalysts using bi-metallic carbonyl clusters as precursors of highly dispersed nanoparticles over TiO2 and CeO2, which are widely considered two of the most suitable supports for gold nanoparticles. Au/FeOx catalysts were prepared by employing the bi-metallic carbonyl cluster salts [NEt4]4[Au4Fe4(CO)16] (Fe/Au=1) and [NEt4][AuFe4(CO)16] (Fe/Au=4), and for comparison FeOx samples were prepared by employing the homometallic [NEt4][HFe3(CO)11] cluster. These clusters were prepared by Prof. Longoni research group (Department of Physical and Inorganic Chemistry- University of Bologna). Particular attention was dedicated to the optimization of a suitable thermal treatment in order to achieve, apart from a good Au and Fe metal dispersion, also the formation of appropriate species with good catalytic properties. A deep IR study was carried out in order to understand the physical interaction between clusters and different supports and detect the occurrence of chemical reactions between them at any stage of the preparation. The characterization by BET, XRD, TEM, H2-TPR, ICP-AES and XPS was performed in order to investigate the catalysts properties, whit particular attention to the interaction between Au and Fe and its influence on the catalytic activity. This novel preparation method resulted in small gold metallic nanoparticles surrounded by highly dispersed iron oxide species, essentially in an amorphous phase, on both TiO2 and CeO2. The results presented in this thesis confirmed that FeOx species can stabilize small Au particles, since keeping costant the gold content but introducing a higher iron amount a higher metal dispersion was achieved. Partial encapsulation of gold atoms by iron species was observed since the Au/Fe surface ratio was found much lower than bulk ratio and a strong interaction between gold and oxide species, both of iron oxide and supports, was achieved. The prepared catalysts were tested in the total oxidation of VOCs, using toluene and methanol as probe molecules for aromatics and alchols, respectively, and in the PROX reaction. Different performances were observed on titania and ceria catalysts, on both toluene and methanol combustion. Toluene combustion on titania catalyst was found to be enhanced increasing iron loading while a moderate effect on FeOx-Ti activity was achieved by Au addition. In this case toluene combustion was improved due to a higher oxygen mobility depending on enhanced oxygen activation by FeOx and Au/FeOx dispersed on titania. On the contrary ceria activity was strongly decreased in the presence of FeOx, while the introduction of gold was found to moderate the detrimental effect of iron species. In fact, excellent ceria performances are due to its ability to adsorb toluene and O2. Since toluene activation is the determining factor for its oxidation, the partial coverage of ceria sites, responsible of toluene adsorption, by FeOx species finely dispersed on the surface resulted in worse efficiency in toluene combustion. Better results were obtained for both ceria and titania catalysts on methanol total oxidation. In this case, the performances achieved on differently supported catalysts indicate that the oxygen mobility is the determining factor in this reaction. The introduction of gold on both TiO2 and CeO2 catalysts, lead to a higher oxygen mobility due to the weakening of both Fe-O and Ce-O bonds and consequently to enhanced methanol combustion. The catalytic activity was found to strongly depend on oxygen mobility and followed the same trend observed for catalysts reducibility. Regarding CO PROX reaction, it was observed that Au/FeOx titania catalysts are less active than ceria ones, due to the lower reducibility of titania compared to ceria. In fact the availability of lattice oxygen involved in PROX reaction is much higher in the latter catalysts. However, the CO PROX performances observed for ceria catalysts are not really high compared to data reported in literature, probably due to the very low Au/Fe surface ratio achieved with this preparation method. CO preferential oxidation was found to strongly depend on Au particle size but also on surface oxygen reducibility, depending on the different oxide species which can be formed using different thermal treatment conditions or varying the iron loading over the support.

Refined Estimation of Earthquake Source Parameters: Methods, Applications and Scaling Relationships

The objective of this work of thesis is the refined estimations of source parameters. To such a purpose we used two different approaches, one in the frequency domain and the other in the time domain. In frequency domain, we analyzed the P- and S-wave displacement spectra to estimate spectral parameters, that is corner frequencies and low frequency spectral amplitudes. We used a parametric modeling approach which is combined with a multi-step, non-linear inversion strategy and includes the correction for attenuation and site effects. The iterative multi-step procedure was applied to about 700 microearthquakes in the moment range 1011-1014 N•m and recorded at the dense, wide-dynamic range, seismic networks operating in Southern Apennines (Italy). The analysis of the source parameters is often complicated when we are not able to model the propagation accurately. In this case the empirical Green function approach is a very useful tool to study the seismic source properties. In fact the Empirical Green Functions (EGFs) consent to represent the contribution of propagation and site effects to signal without using approximate velocity models. An EGF is a recorded three-component set of time-histories of a small earthquake whose source mechanism and propagation path are similar to those of the master event. Thus, in time domain, the deconvolution method of Vallée (2004) was applied to calculate the source time functions (RSTFs) and to accurately estimate source size and rupture velocity. This technique was applied to 1) large event, that is Mw=6.3 2009 L’Aquila mainshock (Central Italy), 2) moderate events, that is cluster of earthquakes of 2009 L’Aquila sequence with moment magnitude ranging between 3 and 5.6, 3) small event, i.e. Mw=2.9 Laviano mainshock (Southern Italy).

Multi Processor Systems On Chip with Configurable Hardware Acceleration

The evolution of the electronics embedded applications forces electronics systems designers to match their ever increasing requirements. This evolution pushes the computational power of digital signal processing systems, as well as the energy required to accomplish the computations, due to the increasing mobility of such applications. Current approaches used to match these requirements relies on the adoption of application specific signal processors. Such kind of devices exploits powerful accelerators, which are able to match both performance and energy requirements. On the other hand, the too high specificity of such accelerators often results in a lack of flexibility which affects non-recurrent engineering costs, time to market, and market volumes too. The state of the art mainly proposes two solutions to overcome these issues with the ambition of delivering reasonable performance and energy efficiency: reconfigurable computing and multi-processors computing. All of these solutions benefits from the post-fabrication programmability, that definitively results in an increased flexibility. Nevertheless, the gap between these approaches and dedicated hardware is still too high for many application domains, especially when targeting the mobile world. In this scenario, flexible and energy efficient acceleration can be achieved by merging these two computational paradigms, in order to address all the above introduced constraints. This thesis focuses on the exploration of the design and application spectrum of reconfigurable computing, exploited as application specific accelerators for multi-processors systems on chip. More specifically, it introduces a reconfigurable digital signal processor featuring a heterogeneous set of reconfigurable engines, and a homogeneous multi-core system, exploiting three different flavours of reconfigurable and mask-programmable technologies as implementation platform for applications specific accelerators. In this work, the various trade-offs concerning the utilization multi-core platforms and the different configuration technologies are explored, characterizing the design space of the proposed approach in terms of programmability, performance, energy efficiency and manufacturing costs.

Constraint based methods for allocation and scheduling of periodic applications

This work presents exact algorithms for the Resource Allocation and Cyclic Scheduling Problems (RA&CSPs). Cyclic Scheduling Problems arise in a number of application areas, such as in hoist scheduling, mass production, compiler design (implementing scheduling loops on parallel architectures), software pipelining, and in embedded system design. The RA&CS problem concerns time and resource assignment to a set of activities, to be indefinitely repeated, subject to precedence and resource capacity constraints. In this work we present two constraint programming frameworks facing two different types of cyclic problems. In first instance, we consider the disjunctive RA&CSP, where the allocation problem considers unary resources. Instances are described through the Synchronous Data-flow (SDF) Model of Computation. The key problem of finding a maximum-throughput allocation and scheduling of Synchronous Data-Flow graphs onto a multi-core architecture is NP-hard and has been traditionally solved by means of heuristic (incomplete) algorithms. We propose an exact (complete) algorithm for the computation of a maximum-throughput mapping of applications specified as SDFG onto multi-core architectures. Results show that the approach can handle realistic instances in terms of size and complexity. Next, we tackle the Cyclic Resource-Constrained Scheduling Problem (i.e. CRCSP). We propose a Constraint Programming approach based on modular arithmetic: in particular, we introduce a modular precedence constraint and a global cumulative constraint along with their filtering algorithms. Many traditional approaches to cyclic scheduling operate by fixing the period value and then solving a linear problem in a generate-and-test fashion. Conversely, our technique is based on a non-linear model and tackles the problem as a whole: the period value is inferred from the scheduling decisions. The proposed approaches have been tested on a number of non-trivial synthetic instances and on a set of realistic industrial instances achieving good results on practical size problem.

A numerical methodology for the multi-objective optimization of the DI Diesel engine combustion

DI Diesel engine are widely used both for industrial and automotive applications due to their durability and fuel economy. Nonetheless, increasing environmental concerns force that type of engine to comply with increasingly demanding emission limits, so that, it has become mandatory to develop a robust design methodology of the DI Diesel combustion system focused on reduction of soot and NOx simultaneously while maintaining a reasonable fuel economy. In recent years, genetic algorithms and CFD three-dimensional combustion simulations have been successfully applied to that kind of problem. However, combining GAs optimization with actual CFD three-dimensional combustion simulations can be too onerous since a large number of calculations is usually needed for the genetic algorithm to converge, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes. In order to make the optimization process less time-consuming, CFD simulations can be more conveniently used to generate a training set for the learning process of an artificial neural network which, once correctly trained, can be used to forecast the engine outputs as a function of the design parameters during a GA optimization performing a so-called virtual optimization. In the current work, a numerical methodology for the multi-objective virtual optimization of the combustion of an automotive DI Diesel engine, which relies on artificial neural networks and genetic algorithms, was developed.

The Dynamics of Passive Torsional Fatigue Test Rigs: Innovative Applications of Universal Joints

The dynamics of a passive back-to-back test rig have been characterised, leading to a multi-coordinate approach for the analysis of arbitrary test configurations. Universal joints have been introduced into a typical pre-loaded back-to-back system in order to produce an oscillating torsional moment in a test specimen. Two different arrangements have been investigated using a frequency-based sub-structuring approach: the receptance method. A numerical model has been developed in accordance with this theory, allowing interconnection of systems with two-coordinates and closed multi-loop schemes. The model calculates the receptance functions and modal and deflected shapes of a general system. Closed form expressions of the following individual elements have been developed: a servomotor, damped continuous shaft and a universal joint. Numerical results for specific cases have been compared with published data in literature and experimental measurements undertaken in the present work. Due to the complexity of the universal joint and its oscillating dynamic effects, a more detailed analysis of this component has been developed. Two models have been presented. The first represents the joint as two inertias connected by a massless cross-piece. The second, derived by the dynamic analysis of a spherical four-link mechanism, considers the contribution of the floating element and its gyroscopic effects. An investigation into non-linear behaviour has led to a time domain model that utilises the Runge-Kutta fourth order method for resolution of the dynamic equations. It has been demonstrated that the torsional receptances of a universal joint, derived using the simple model, result in representation of the joint as an equivalent variable inertia. In order to verify the model, a test rig has been built and experimental validation undertaken. The variable inertia of a universal joint has lead to a novel application of the component as a passive device for the balancing of inertia variations in slider-crank mechanisms.

Variation of stable silicon isotopes: Analytical developments and applications in Precambrian geochemistry

Die vorliegende Dissertation behandelt die Gesamtgesteinsanalyse stabiler Siliziumisotope mit Hilfe einer „Multi Collector-ICP-MS“. Die Analysen fanden in Kooperation mit dem „Royal Museum for Central Africa“ in Belgien statt. Einer der Schwerpunkte des ersten Kapitels ist die erstmalige Analyse des δ30Si –Wertes an einem konventionellen Nu PlasmaTM „Multi-Collector ICP-MS“ Instrument, durch die Eliminierung der den 30Si “peak” überlagernden 14N16O Interferenz. Die Analyse von δ30Si wurde durch technische Modifikationen der Anlage erreicht, welche eine höherer Massenauflösung ermöglichten. Die sorgsame Charakterisierung eines adäquaten Referenzmaterials ist unabdingbar für die Abschätzung der Genauigkeit einer Messung. Die Bestimmung der „U.S. Geological Survey“ Referenzmaterialien bildet den zweiten Schwerpunkt dieses Kapitales. Die Analyse zweier hawaiianischer Standards (BHVO-1 and BHVO-2), belegt die präzise und genaue δ30Si Bestimmung und bietet Vergleichsdaten als Qualitätskontrolle für andere Labore. Das zweite Kapitel befasst sich mit kombinierter Silizium-/Sauerstoffisotope zur Untersuchung der Entstehung der Silizifizierung vulkanischer Gesteine des „Barberton Greenstone Belt“, Südafrika. Im Gegensatz zu heute, war die Silizifizierung der Oberflächennahen Schichten, einschließlich der „Chert“ Bildung, weitverbreitete Prozesse am präkambrischen Ozeanboden. Diese Horizonte sind Zeugen einer extremen Siliziummobilisierung in der Frühzeit der Erde. Dieses Kapitel behandelt die Analyse von Silizium- und Sauerstoffisotopen an drei unterschiedlichen Gesteinsprofilen mit unterschiedlich stark silizifizierten Basalten und überlagernden geschichteten „Cherts“ der 3.54, 3.45 und 3.33 Mill. Jr. alten Theespruit, Kromberg und Hooggenoeg Formationen. Siliziumisotope, Sauerstoffisotope und die SiO2-Gehalte demonstrieren in allen drei Gesteinsprofilen eine positive Korrelation mit dem Silizifizierungsgrad, jedoch mit unterschiedlichen Steigungen der δ30Si-δ18O-Verhältnisse. Meerwasser wird als Quelle des Siliziums für den Silizifizierungsprozess betrachtet. Berechnungen haben gezeigt, dass eine klassische Wasser-Gestein Wechselwirkung die Siliziumisotopenvariation nicht beeinflussen kann, da die Konzentration von Si im Meerwasser zu gering ist (49 ppm). Die Daten stimmen mit einer Zwei-Endglieder-Komponentenmischung überein, mit Basalt und „Chert“ als jeweilige Endglieder. Unsere gegenwärtigen Daten an den „Cherts“ bestätigen einen Anstieg der Isotopenzusammensetzung über der Zeit. Mögliche Faktoren, die für unterschiedliche Steigungen der δ30Si-δ18O Verhältnisse verantwortlich sein könnten sind Veränderungen in der Meerwasserisotopie, der Wassertemperatur oder sekundäre Alterationseffekte. Das letzte Kapitel beinhaltet potentielle Variationen in der Quellregion archaischer Granitoide: die Si-Isotopen Perspektive. Natriumhaltige Tonalit-Trondhjemit-Granodiorit (TTG) Intrusiva repräsentieren große Anteile der archaischen Kruste. Im Gegensatz dazu ist die heutige Kruste kaliumhaltiger (GMS-Gruppe: Granit-Monzonite-Syenite). Prozesse, die zu dem Wechsel von natriumhaltiger zu kaliumhaltiger Kruste führten sind die Thematik diesen Kapitels. Siliziumisotopenmessungen wurden hier kombiniert mit Haupt- und Spurenelementanalysen an unterschiedlichen Generationen der 3.55 bis 3.10 Mill. Yr. alten TTG und GMS Intrusiva aus dem Arbeitsgebiet. Die δ30Si-Werte in den unterschiedlichen Plutonit Generationen zeigen einen leichten Anstieg der Isotopie mit der Zeit, wobei natriumhaltige Intrusiva die niedrigste Si-Isotopenzusammensetzung aufweisen. Der leichte Anstieg in der Siliziumisotopenzusammensetzung über die Zeit könnte auf unterschiedliche Temperaturbedingungen in der Quellregion der Granitoide hinweisen. Die Entstehung von Na-reichen, leichten d30Si Granitoiden würde demnach bei höheren Temperaturen erfolgen. Die Ähnlichkeit der δ30Si-Werte in archaischen K-reichen Plutoniten und phanerozoischen K-reichen Plutoniten wird ebenfalls deutlich.

Use of shared memory in the context of embedded multi-core processors: exploration of the technology and its limits

Modern embedded systems embrace many-core shared-memory designs. Due to constrained power and area budgets, most of them feature software-managed scratchpad memories instead of data caches to increase the data locality. It is therefore programmers’ responsibility to explicitly manage the memory transfers, and this make programming these platform cumbersome. Moreover, complex modern applications must be adequately parallelized before they can the parallel potential of the platform into actual performance. To support this, programming languages were proposed, which work at a high level of abstraction, and rely on a runtime whose cost hinders performance, especially in embedded systems, where resources and power budget are constrained. This dissertation explores the applicability of the shared-memory paradigm on modern many-core systems, focusing on the ease-of-programming. It focuses on OpenMP, the de-facto standard for shared memory programming. In a first part, the cost of algorithms for synchronization and data partitioning are analyzed, and they are adapted to modern embedded many-cores. Then, the original design of an OpenMP runtime library is presented, which supports complex forms of parallelism such as multi-level and irregular parallelism. In the second part of the thesis, the focus is on heterogeneous systems, where hardware accelerators are coupled to (many-)cores to implement key functional kernels with orders-of-magnitude of speedup and energy efficiency compared to the “pure software” version. However, three main issues rise, namely i) platform design complexity, ii) architectural scalability and iii) programmability. To tackle them, a template for a generic hardware processing unit (HWPU) is proposed, which share the memory banks with cores, and the template for a scalable architecture is shown, which integrates them through the shared-memory system. Then, a full software stack and toolchain are developed to support platform design and to let programmers exploiting the accelerators of the platform. The OpenMP frontend is extended to interact with it.

Development and applications of hollow fiber flow field-flow fractionation in the bioanalytical field. Studies of aggregation phenomena in complex protein samples

Recent advances in the fast growing area of therapeutic/diagnostic proteins and antibodies - novel and highly specific drugs - as well as the progress in the field of functional proteomics regarding the correlation between the aggregation of damaged proteins and (immuno) senescence or aging-related pathologies, underline the need for adequate analytical methods for the detection, separation, characterization and quantification of protein aggregates, regardless of the their origin or formation mechanism. Hollow fiber flow field-flow fractionation (HF5), the miniaturized version of FlowFFF and integral part of the Eclipse DUALTEC FFF separation system, was the focus of this research; this flow-based separation technique proved to be uniquely suited for the hydrodynamic size-based separation of proteins and protein aggregates in a very broad size and molecular weight (MW) range, often present at trace levels. HF5 has shown to be (a) highly selective in terms of protein diffusion coefficients, (b) versatile in terms of bio-compatible carrier solution choice, (c) able to preserve the biophysical properties/molecular conformation of the proteins/protein aggregates and (d) able to discriminate between different types of protein aggregates. Thanks to the miniaturization advantages and the online coupling with highly sensitive detection techniques (UV/Vis, intrinsic fluorescence and multi-angle light scattering), HF5 had very low detection/quantification limits for protein aggregates. Compared to size-exclusion chromatography (SEC), HF5 demonstrated superior selectivity and potential as orthogonal analytical method in the extended characterization assays, often required by therapeutic protein formulations. In addition, the developed HF5 methods have proven to be rapid, highly selective, sensitive and repeatable. HF5 was ideally suitable as first dimension of separation of aging-related protein aggregates from whole cell lysates (proteome pre-fractionation method) and, by HF5-(UV)-MALS online coupling, important biophysical information on the fractionated proteins and protein aggregates was gathered: size (rms radius and hydrodynamic radius), absolute MW and conformation.

Nanocrystalline Silicon Based Films for Renewable Energy Applications

The present thesis is focused on the study of innovative Si-based materials for third generation photovoltaics. In particular, silicon oxi-nitride (SiOxNy) thin films and multilayer of Silicon Rich Carbide (SRC)/Si have been characterized in view of their application in photovoltaics. SiOxNy is a promising material for applications in thin-film solar cells as well as for wafer based silicon solar cells, like silicon heterojunction solar cells. However, many issues relevant to the material properties have not been studied yet, such as the role of the deposition condition and precursor gas concentrations on the optical and electronic properties of the films, the composition and structure of the nanocrystals. The results presented in the thesis aim to clarify the effects of annealing and oxygen incorporation within nc-SiOxNy films on its properties in view of the photovoltaic applications. Silicon nano-crystals (Si NCs) embedded in a dielectric matrix were proposed as absorbers in all-Si multi-junction solar cells due to the quantum confinement capability of Si NCs, that allows a better match to the solar spectrum thanks to the size induced tunability of the band gap. Despite the efficient solar radiation absorption capability of this structure, its charge collection and transport properties has still to be fully demonstrated. The results presented in the thesis aim to the understanding of the transport mechanisms at macroscopic and microscopic scale. Experimental results on SiOxNy thin films and SRC/Si multilayers have been obtained at macroscopical and microscopical level using different characterizations techniques, such as Atomic Force Microscopy, Reflection and Transmission measurements, High Resolution Transmission Electron Microscopy, Energy-Dispersive X-ray spectroscopy and Fourier Transform Infrared Spectroscopy. The deep knowledge and improved understanding of the basic physical properties of these quite complex, multi-phase and multi-component systems, made by nanocrystals and amorphous phases, will contribute to improve the efficiency of Si based solar cells.