Fingerprint Recognition: Enhancement, Feature Extraction and Automatic Evaluation of Algorithms

The identification of people by measuring some traits of individual anatomy or physiology has led to a specific research area called biometric recognition. This thesis is focused on improving fingerprint recognition systems considering three important problems: fingerprint enhancement, fingerprint orientation extraction and automatic evaluation of fingerprint algorithms. An effective extraction of salient fingerprint features depends on the quality of the input fingerprint. If the fingerprint is very noisy, we are not able to detect a reliable set of features. A new fingerprint enhancement method, which is both iterative and contextual, is proposed. This approach detects high-quality regions in fingerprints, selectively applies contextual filtering and iteratively expands like wildfire toward low-quality ones. A precise estimation of the orientation field would greatly simplify the estimation of other fingerprint features (singular points, minutiae) and improve the performance of a fingerprint recognition system. The fingerprint orientation extraction is improved following two directions. First, after the introduction of a new taxonomy of fingerprint orientation extraction methods, several variants of baseline methods are implemented and, pointing out the role of pre- and post- processing, we show how to improve the extraction. Second, the introduction of a new hybrid orientation extraction method, which follows an adaptive scheme, allows to improve significantly the orientation extraction in noisy fingerprints. Scientific papers typically propose recognition systems that integrate many modules and therefore an automatic evaluation of fingerprint algorithms is needed to isolate the contributions that determine an actual progress in the state-of-the-art. The lack of a publicly available framework to compare fingerprint orientation extraction algorithms, motivates the introduction of a new benchmark area called FOE (including fingerprints and manually-marked orientation ground-truth) along with fingerprint matching benchmarks in the FVC-onGoing framework. The success of such framework is discussed by providing relevant statistics: more than 1450 algorithms submitted and two international competitions.

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.

Progetto di reti Sensori Wireless e tecniche di Fusione Sensoriale

Ambient Intelligence (AmI) envisions a world where smart, electronic environments are aware and responsive to their context. People moving into these settings engage many computational devices and systems simultaneously even if they are not aware of their presence. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. The dependence on a large amount of fixed and mobile sensors embedded into the environment makes of Wireless Sensor Networks one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes, simple devices that typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. In order to handle the large amount of data generated by a WSN several multi sensor data fusion techniques have been developed. The aim of multisensor data fusion is to combine data to achieve better accuracy and inferences than could be achieved by the use of a single sensor alone. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas: Multimodal Surveillance and Activity Recognition. Novel techniques to handle data from a network of low-cost, low-power Pyroelectric InfraRed (PIR) sensors are presented. Such techniques allow the detection of the number of people moving in the environment, their direction of movement and their position. We discuss how a mesh of PIR sensors can be integrated with a video surveillance system to increase its performance in people tracking. Furthermore we embed a PIR sensor within the design of a Wireless Video Sensor Node (WVSN) to extend its lifetime. Activity recognition is a fundamental block in natural interfaces. A challenging objective is to design an activity recognition system that is able to exploit a redundant but unreliable WSN. We present our activity in building a novel activity recognition architecture for such a dynamic system. The architecture has a hierarchical structure where simple nodes performs gesture classification and a high level meta classifiers fuses a changing number of classifier outputs. We demonstrate the benefit of such architecture in terms of increased recognition performance, and fault and noise robustness. Furthermore we show how we can extend network lifetime by performing a performance-power trade-off. Smart objects can enhance user experience within smart environments. We present our work in extending the capabilities of the Smart Micrel Cube (SMCube), a smart object used as tangible interface within a tangible computing framework, through the development of a gesture recognition algorithm suitable for this limited computational power device. Finally the development of activity recognition techniques can greatly benefit from the availability of shared dataset. We report our experience in building a dataset for activity recognition. Such dataset is freely available to the scientific community for research purposes and can be used as a testbench for developing, testing and comparing different activity recognition techniques.

The firm. Techno-organizational changes, industrial relations and performances. An enquiry on Reggio Emilia local industrial system

It is not unknown that the evolution of firm theories has been developed along a path paved by an increasing awareness of the organizational structure importance. From the early “neoclassical” conceptualizations that intended the firm as a rational actor whose aim is to produce that amount of output, given the inputs at its disposal and in accordance to technological or environmental constraints, which maximizes the revenue (see Boulding, 1942 for a past mid century state of the art discussion) to the knowledge based theory of the firm (Nonaka & Takeuchi, 1995; Nonaka & Toyama, 2005), which recognizes in the firm a knnowledge creating entity, with specific organizational capabilities (Teece, 1996; Teece & Pisano, 1998) that allow to sustaine competitive advantages. Tracing back a map of the theory of the firm evolution, taking into account the several perspectives adopted in the history of thought, would take the length of many books. Because of that a more fruitful strategy is circumscribing the focus of the description of the literature evolution to one flow connected to a crucial question about the nature of firm’s behaviour and about the determinants of competitive advantages. In so doing I adopt a perspective that allows me to consider the organizational structure of the firm as an element according to which the different theories can be discriminated. The approach adopted starts by considering the drawbacks of the standard neoclassical theory of the firm. Discussing the most influential theoretical approaches I end up with a close examination of the knowledge based perspective of the firm. Within this perspective the firm is considered as a knowledge creating entity that produce and mange knowledge (Nonaka, Toyama, & Nagata, 2000; Nonaka & Toyama, 2005). In a knowledge intensive organization, knowledge is clearly embedded for the most part in the human capital of the individuals that compose such an organization. In a knowledge based organization, the management, in order to cope with knowledge intensive productions, ought to develop and accumulate capabilities that shape the organizational forms in a way that relies on “cross-functional processes, extensive delayering and empowerment” (Foss 2005, p.12). This mechanism contributes to determine the absorptive capacity of the firm towards specific technologies and, in so doing, it also shape the technological trajectories along which the firm moves. After having recognized the growing importance of the firm’s organizational structure in the theoretical literature concerning the firm theory, the subsequent point of the analysis is that of providing an overview of the changes that have been occurred at micro level to the firm’s organization of production. The economic actors have to deal with challenges posed by processes of internationalisation and globalization, increased and increasing competitive pressure of less developed countries on low value added production activities, changes in technologies and increased environmental turbulence and volatility. As a consequence, it has been widely recognized that the main organizational models of production that fitted well in the 20th century are now partially inadequate and processes aiming to reorganize production activities have been widespread across several economies in recent years. Recently, the emergence of a “new” form of production organization has been proposed both by scholars, practitioners and institutions: the most prominent characteristic of such a model is its recognition of the importance of employees commitment and involvement. As a consequence it is characterized by a strong accent on the human resource management and on those practices that aim to widen the autonomy and responsibility of the workers as well as increasing their commitment to the organization (Osterman, 1994; 2000; Lynch, 2007). This “model” of production organization is by many defined as High Performance Work System (HPWS). Despite the increasing diffusion of workplace practices that may be inscribed within the concept of HPWS in western countries’ companies, it is an hazard, to some extent, to speak about the emergence of a “new organizational paradigm”. The discussion about organizational changes and the diffusion of HPWP the focus cannot abstract from a discussion about the industrial relations systems, with a particular accent on the employment relationships, because of their relevance, in the same way as production organization, in determining two major outcomes of the firm: innovation and economic performances. The argument is treated starting from the issue of the Social Dialogue at macro level, both in an European perspective and Italian perspective. The model of interaction between the social parties has repercussions, at micro level, on the employment relationships, that is to say on the relations between union delegates and management or workers and management. Finding economic and social policies capable of sustaining growth and employment within a knowledge based scenario is likely to constitute the major challenge for the next generation of social pacts, which are the main social dialogue outcomes. As Acocella and Leoni (2007) put forward the social pacts may constitute an instrument to trade wage moderation for high intensity in ICT, organizational and human capital investments. Empirical evidence, especially focused on the micro level, about the positive relation between economic growth and new organizational designs coupled with ICT adoption and non adversarial industrial relations is growing. Partnership among social parties may become an instrument to enhance firm competitiveness. The outcome of the discussion is the integration of organizational changes and industrial relations elements within a unified framework: the HPWS. Such a choice may help in disentangling the potential existence of complementarities between these two aspects of the firm internal structure on economic and innovative performance. With the third chapter starts the more original part of the thesis. The data utilized in order to disentangle the relations between HPWS practices, innovation and economic performance refer to the manufacturing firms of the Reggio Emilia province with more than 50 employees. The data have been collected through face to face interviews both to management (199 respondents) and to union representatives (181 respondents). Coupled with the cross section datasets a further data source is constituted by longitudinal balance sheets (1994-2004). Collecting reliable data that in turn provide reliable results needs always a great effort to which are connected uncertain results. Data at micro level are often subjected to a trade off: the wider is the geographical context to which the population surveyed belong the lesser is the amount of information usually collected (low level of resolution); the narrower is the focus on specific geographical context, the higher is the amount of information usually collected (high level of resolution). For the Italian case the evidence about the diffusion of HPWP and their effects on firm performances is still scanty and usually limited to local level studies (Cristini, et al., 2003). The thesis is also devoted to the deepening of an argument of particular interest: the existence of complementarities between the HPWS practices. It has been widely shown by empirical evidence that when HPWP are adopted in bundles they are more likely to impact on firm’s performances than when adopted in isolation (Ichniowski, Prennushi, Shaw, 1997). Is it true also for the local production system of Reggio Emilia? The empirical analysis has the precise aim of providing evidence on the relations between the HPWS dimensions and the innovative and economic performances of the firm. As far as the first line of analysis is concerned it must to be stressed the fundamental role that innovation plays in the economy (Geroski & Machin, 1993; Stoneman & Kwoon 1994, 1996; OECD, 2005; EC, 2002). On this point the evidence goes from the traditional innovations, usually approximated by R&D investment expenditure or number of patents, to the introduction and adoption of ICT, in the recent years (Brynjolfsson & Hitt, 2000). If innovation is important then it is critical to analyse its determinants. In this work it is hypothesised that organizational changes and firm level industrial relations/employment relations aspects that can be put under the heading of HPWS, influence the propensity to innovate in product, process and quality of the firm. The general argument may goes as follow: changes in production management and work organization reconfigure the absorptive capacity of the firm towards specific technologies and, in so doing, they shape the technological trajectories along which the firm moves; cooperative industrial relations may lead to smother adoption of innovations, because not contrasted by unions. From the first empirical chapter emerges that the different types of innovations seem to respond in different ways to the HPWS variables. The underlying processes of product, process and quality innovations are likely to answer to different firm’s strategies and needs. Nevertheless, it is possible to extract some general results in terms of the most influencing HPWS factors on innovative performance. The main three aspects are training coverage, employees involvement and the diffusion of bonuses. These variables show persistent and significant relations with all the three innovation types. The same do the components having such variables at their inside. In sum the aspects of the HPWS influence the propensity to innovate of the firm. At the same time, emerges a quite neat (although not always strong) evidence of complementarities presence between HPWS practices. In terns of the complementarity issue it can be said that some specific complementarities exist. Training activities, when adopted and managed in bundles, are related to the propensity to innovate. Having a sound skill base may be an element that enhances the firm’s capacity to innovate. It may enhance both the capacity to absorbe exogenous innovation and the capacity to endogenously develop innovations. The presence and diffusion of bonuses and the employees involvement also spur innovative propensity. The former because of their incentive nature and the latter because direct workers participation may increase workers commitment to the organizationa and thus their willingness to support and suggest inovations. The other line of analysis provides results on the relation between HPWS and economic performances of the firm. There have been a bulk of international empirical studies on the relation between organizational changes and economic performance (Black & Lynch 2001; Zwick 2004; Janod & Saint-Martin 2004; Huselid 1995; Huselid & Becker 1996; Cappelli & Neumark 2001), while the works aiming to capture the relations between economic performance and unions or industrial relations aspects are quite scant (Addison & Belfield, 2001; Pencavel, 2003; Machin & Stewart, 1990; Addison, 2005). In the empirical analysis the integration of the two main areas of the HPWS represent a scarcely exploited approach in the panorama of both national and international empirical studies. As remarked by Addison “although most analysis of workers representation and employee involvement/high performance work practices have been conducted in isolation – while sometimes including the other as controls – research is beginning to consider their interactions” (Addison, 2005, p.407). The analysis conducted exploiting temporal lags between dependent and covariates, possibility given by the merger of cross section and panel data, provides evidence in favour of the existence of HPWS practices impact on firm’s economic performance, differently measured. Although it does not seem to emerge robust evidence on the existence of complementarities among HPWS aspects on performances there is evidence of a general positive influence of the single practices. The results are quite sensible to the time lags, inducing to hypothesize that time varying heterogeneity is an important factor in determining the impact of organizational changes on economic performance. The implications of the analysis can be of help both to management and local level policy makers. Although the results are not simply extendible to other local production systems it may be argued that for contexts similar to the Reggio Emilia province, characterized by the presence of small and medium enterprises organized in districts and by a deep rooted unionism, with strong supporting institutions, the results and the implications here obtained can also fit well. However, a hope for future researches on the subject treated in the present work is that of collecting good quality information over wider geographical areas, possibly at national level, and repeated in time. Only in this way it is possible to solve the Gordian knot about the linkages between innovation, performance, high performance work practices and industrial relations.

Interactions between the gut microbiota, short-chain fatty acids and the immune system in pediatric patients undergoing hematopoietic stem cell transplantation

The gut microbiota (GM) is essential for human health and contributes to several diseases; indeed it can be considered an extension of the self and, together with the genetic makeup, determines the physiology of an organism. In this thesis has been studied the peripheral immune system reconstitution in pediatric patients undergoing allogeneic hematopoietic stem cell transplantation (aHSCT) in the early phase; in parallel, have been also explored the gut microbiota variations as one of the of primary factors in governing the fate of the immunological recovery, predisposing or protecting from complications such as the onset of acute graft-versus-host disease (GvHD). Has been demonstrated, to our knowledge for the first time, that aHSCT in pediatric patients is associated to a profound modification of the GM ecosystem with a disruption of its mutualistic asset. aGvHD and non-aGvHD subjects showed differences in the process of GM recovery, in members abundance of the phylum Bacteroidetes, and in propionate fecal concentration; the latter are higher in the pre-HSCT composition of non-GvHD subjects than GvHD ones. Short-chain fatty acids (SCFAs), such as acetate, butyrate and propionate, are end-products of microbial fermentation of macronutrients and distribute systemically from the gut to blood. For this reason, has been studied their effect in vitro on human DCs, the key regulators of our immune system and the main player of aGvHD onset. Has been observed that propionate and, particularly, butyrate show a strong and direct immunomodulatory activity on DCs reducing inflammatory markers such as chemokines and interleukins. This study, with the needed caution, suggests that the pre-existing GM structure can be protective against aGvHD onset, exerting its protective role through SCFAs. They, indeed, may regulate cell traffic within secondary lymphoid tissues, influence T cell development during antigen recognition, and, thus, directly shape the immune system.

Real-Time Engine Diagnostic and Control Based on Acoustic Emissions Analysis

Engine developers are putting more and more emphasis on the research of maximum thermal and mechanical efficiency in the recent years. Research advances have proven the effectiveness of downsized, turbocharged and direct injection concepts, applied to gasoline combustion systems, to reduce the overall fuel consumption while respecting exhaust emissions limits. These new technologies require more complex engine control units. The sound emitted from a mechanical system encloses many information related to its operating condition and it can be used for control and diagnostic purposes. The thesis shows how the functions carried out from different and specific sensors usually present on-board, can be executed, at the same time, using only one multifunction sensor based on low-cost microphone technology. A theoretical background about sound and signal processing is provided in chapter 1. In modern turbocharged downsized GDI engines, the achievement of maximum thermal efficiency is precluded by the occurrence of knock. Knock emits an unmistakable sound perceived by the human ear like a clink. In chapter 2, the possibility of using this characteristic sound for knock control propose, starting from first experimental assessment tests, to the implementation in a real, production-type engine control unit will be shown. Chapter 3 focus is on misfire detection. Putting emphasis on the low frequency domain of the engine sound spectrum, features related to each combustion cycle of each cylinder can be identified and isolated. An innovative approach to misfire detection, which presents the advantage of not being affected by the road and driveline conditions is introduced. A preliminary study of air path leak detection techniques based on acoustic emissions analysis has been developed, and the first experimental results are shown in chapter 4. Finally, in chapter 5, an innovative detection methodology, based on engine vibration analysis, that can provide useful information about combustion phase is reported.

Active Control of the Acoustic Field in a Vehicle Cabin

In this thesis, a thorough investigation on acoustic noise control systems for realistic automotive scenarios is presented. The thesis is organized in two parts dealing with the main topics treated: Active Noise Control (ANC) systems and Virtual Microphone Technique (VMT), respectively. The technology of ANC allows to increase the driver's/passenger's comfort and safety exploiting the principle of mitigating the disturbing acoustic noise by the superposition of a secondary sound wave of equal amplitude but opposite phase. Performance analyses of both FeedForwrd (FF) and FeedBack (FB) ANC systems, in experimental scenarios, are presented. Since, environmental vibration noises within a car cabin are time-varying, most of the ANC solutions are adaptive. However, in this work, an effective fixed FB ANC system is proposed. Various ANC schemes are considered and compared with each other. In order to find the best possible ANC configuration which optimizes the performance in terms of disturbing noise attenuation, a thorough research of \gls{KPI}, system parameters and experimental setups design, is carried out. In the second part of this thesis, VMT, based on the estimation of specific acoustic channels, is investigated with the aim of generating a quiet acoustic zone around a confined area, e.g., the driver's ears. Performance analysis and comparison of various estimation approaches is presented. Several measurement campaigns were performed in order to acquire a sufficient duration and number of microphone signals in a significant variety of driving scenarios and employed cars. To do this, different experimental setups were designed and their performance compared. Design guidelines are given to obtain good trade-off between accuracy performance and equipment costs. Finally, a preliminary analysis with an innovative approach based on Neural Networks (NNs) to improve the current state of the art in microphone virtualization is proposed.