Estimating persistent Betti numbers for discrete shape analysis

Persistent Topology is an innovative way of matching topology and geometry, and it proves to be an effective mathematical tool in shape analysis. In order to express its full potential for applications, it has to interface with the typical environment of Computer Science: It must be possible to deal with a finite sampling of the object of interest, and with combinatorial representations of it. Following that idea, the main result claims that it is possible to construct a relation between the persistent Betti numbers (PBNs; also called rank invariant) of a compact, Riemannian submanifold X of R^m and the ones of an approximation U of X itself, where U is generated by a ball covering centered in the points of the sampling. Moreover we can state a further result in which, this time, we relate X with a finite simplicial complex S generated, thanks to a particular construction, by the sampling points. To be more precise, strict inequalities hold only in "blind strips'', i.e narrow areas around the discontinuity sets of the PBNs of U (or S). Out of the blind strips, the values of the PBNs of the original object, of the ball covering of it, and of the simplicial complex coincide, respectively.

Fresh Produce Safety and Good Agricultural Practices: Stakeholders' Perception and Consumers' Choice in Thailand

Concerns of Thai consumers on food safety have been recently increasing, especially in urban areas and for fresh produce because food safety scandals, such as chemical residues on fresh produce (e.g., cabbage) still frequently occur. The Thai government tried to meet consumer needs by imposing in the domestic market a stronger regulation aimed at increasing the baseline level of food safety assurance and by introducing a voluntary standard (based on Good Agricultural Practices or GAPs and known as Q-GAP) and the related food safety label (i.e., Q mark). However, since standards and regulations are weakly implemented in the domestic market compared to exported products, there is still a lack of Thai consumers’ confidence in the safety of local food products. In this work the current situation of GAPs adoption in Thai fresh produce production is analysed. Furthermore, it is studied whether Thai consumers place value on food safety labels available on the market, to know whether consumer demand could drive the market of certified safer products. This study contains three essays: 1) a review of the literature, 2) a qualitative study on stakeholders' perception toward GAPs adoption and 3) a quantitative study, aimed at analysing consumers' preferences and willingness-to-pay for food safety labels on fresh produce using a discrete choice experiment. This dissertation contributes to the economics of quality assurance and labelling, specifically addressing GAPs and food safety label in the fresh produce supply chain. Results show that Q-GAP could be effectively used to improve food safety in Thai domestic market, but its credibility should be improved. Stakeholder’s awareness toward food safety issues and the delivery of reliable and sound information are crucial. Thai consumers are willing to pay a premium price for food safety labelled produce over unlabelled ones. Implications for both government and business decision-makers are discussed.

An equilibrium approach to modelling social interaction

The aim of this work is to put forward a statistical mechanics theory of social interaction, generalizing econometric discrete choice models. After showing the formal equivalence linking econometric multinomial logit models to equilibrium statical mechanics, a multi- population generalization of the Curie-Weiss model for ferromagnets is considered as a starting point in developing a model capable of describing sudden shifts in aggregate human behaviour. Existence of the thermodynamic limit for the model is shown by an asymptotic sub-additivity method and factorization of correlation functions is proved almost everywhere. The exact solution for the model is provided in the thermodynamical limit by nding converging upper and lower bounds for the system's pressure, and the solution is used to prove an analytic result regarding the number of possible equilibrium states of a two-population system. The work stresses the importance of linking regimes predicted by the model to real phenomena, and to this end it proposes two possible procedures to estimate the model's parameters starting from micro-level data. These are applied to three case studies based on census type data: though these studies are found to be ultimately inconclusive on an empirical level, considerations are drawn that encourage further refinements of the chosen modelling approach, to be considered in future work.

Analisi delle preferenze per le diverse categorie di pomodoro trasformato nel food service

Il pomodoro è una delle colture principali del panorama agro-alimentare italiano e rappresenta un ingrediente base della tradizione culinaria nazionale. Il pomodoro lavorato dall’industria conserviera può essere trasformato in diverse tipologie merceologiche, che si differenziano in base alla tecniche di lavorazione impiegate ed alle caratteristiche del prodotto finito. la percentuale di spesa totale destinata all’acquisto di cibo fuori casa è in aumento a livello globale e l’interesse dell’industria alimentare nei confronti di questo canale di vendita è quindi crescente. Mentre sono numerose le indagine in letteratura che studiano i processi di acquisto dei consumatori finali, non ci sono evidenze di studi simili condotti sugli operatori del Food Service. Obiettivo principale della ricerca è quello di valutare le preferenze dei responsabili acquisti del settore Food Service per diverse tipologie di pomodoro trasformato, in relazione ad una gamma di attributi rilevanti del prodotto e di caratteristiche del cliente. La raccolta dei dati è avvenuta attraverso un esperimento di scelta ipotetico realizzato in Italia e alcuni mercati esteri. Dai risultati ottenuti dall’indagine emerge che i Pelati sono la categoria di pomodoro trasformato preferita dai responsabili degli acquisti del settore Food Service intervistati, con il 35% delle preferenze dichiarate nell'insieme dei contesti di scelta proposti, seguita dalla Polpa (25%), dalla Passata (20%) e dal Concentrato (15%). Dai risultati ottenuti dalla stima del modello econometrico Logit a parametri randomizzati è emerso che alcuni attributi qualitativi di fiducia (credence), spesso impiegati nelle strategie di differenziazione e posizionamento da parte dell’industria alimentare nel mercato Retail, possono rivestire un ruolo importante anche nell’influenzare le preferenze degli operatori del Food Service. Questo potrebbe quindi essere un interessante filone di ricerca da sviluppare nel futuro, possibilmente con l'impiego congiunto di metodologie di analisi basate su esperimenti di scelta ipotetici e non ipotetici.

Variability analysis of discrete event series and wavefront patterns in surface electrocardiogram: contributions to psychophysiological and clinical research

The surface electrocardiogram (ECG) is an established diagnostic tool for the detection of abnormalities in the electrical activity of the heart. The interest of the ECG, however, extends beyond the diagnostic purpose. In recent years, studies in cognitive psychophysiology have related heart rate variability (HRV) to memory performance and mental workload. The aim of this thesis was to analyze the variability of surface ECG derived rhythms, at two different time scales: the discrete-event time scale, typical of beat-related features (Objective I), and the “continuous” time scale of separated sources in the ECG (Objective II), in selected scenarios relevant to psychophysiological and clinical research, respectively. Objective I) Joint time-frequency and non-linear analysis of HRV was carried out, with the goal of assessing psychophysiological workload (PPW) in response to working memory engaging tasks. Results from fourteen healthy young subjects suggest the potential use of the proposed indices in discriminating PPW levels in response to varying memory-search task difficulty. Objective II) A novel source-cancellation method based on morphology clustering was proposed for the estimation of the atrial wavefront in atrial fibrillation (AF) from body surface potential maps. Strong direct correlation between spectral concentration (SC) of atrial wavefront and temporal variability of the spectral distribution was shown in persistent AF patients, suggesting that with higher SC, shorter observation time is required to collect spectral distribution, from which the fibrillatory rate is estimated. This could be time and cost effective in clinical decision-making. The results held for reduced leads sets, suggesting that a simplified setup could also be considered, further reducing the costs. In designing the methods of this thesis, an online signal processing approach was kept, with the goal of contributing to real-world applicability. An algorithm for automatic assessment of ambulatory ECG quality, and an automatic ECG delineation algorithm were designed and validated.

Discrete Event Systems based Design Patterns for Diagnosability Analysis of Automated Manufacturing Systems

The main goal of this thesis is to facilitate the process of industrial automated systems development applying formal methods to ensure the reliability of systems. A new formulation of distributed diagnosability problem in terms of Discrete Event Systems theory and automata framework is presented, which is then used to enforce the desired property of the system, rather then just verifying it. This approach tackles the state explosion problem with modeling patterns and new algorithms, aimed for verification of diagnosability property in the context of the distributed diagnosability problem. The concepts are validated with a newly developed software tool.

What do rendering options tell us about the translating mind? Testing the choice network analysis hypothesis

Frame. Assessing the difficulty of source texts and parts thereof is important in CTIS, whether for research comparability, for didactic purposes or setting price differences in the market. In order to empirically measure it, Campbell & Hale (1999) and Campbell (2000) developed the Choice Network Analysis (CNA) framework. Basically, the CNA’s main hypothesis is that the more translation options (a group of) translators have to render a given source text stretch, the higher the difficulty of that text stretch will be. We will call this the CNA hypothesis. In a nutshell, this research project puts the CNA hypothesis to the test and studies whether it does actually measure difficulty. Data collection. Two groups of participants (n=29) of different profiles and from two universities in different countries had three translation tasks keylogged with Inputlog, and filled pre- and post-translation questionnaires. Participants translated from English (L2) into their L1s (Spanish or Italian), and worked—first in class and then at home—using their own computers, on texts ca. 800–1000 words long. Each text was translated in approximately equal halves in two 1-hour sessions, in three consecutive weeks. Only the parts translated at home were considered in the study. Results. A very different picture emerged from data than that which the CNA hypothesis might predict: there was no prevalence of disfluent task segments when there were many translation options, nor was a prevalence of fluent task segments associated to fewer translation options. Indeed, there was no correlation between the number of translation options (many and few) and behavioral fluency. Additionally, there was no correlation between pauses and both behavioral fluency and typing speed. The discussed theoretical flaws and the empirical evidence lead to the conclusion that the CNA framework does not and cannot measure text and translation difficulty.

Image analysis in the morphological and morphometric study of teeth

The subject of this doctoral dissertation concerns the definition of a new methodology for the morphological and morphometric study of fossilized human teeth, and therefore strives to provide a contribution to the reconstruction of human evolutionary history that proposes to extend to the different species of hominid fossils. Standardized investigative methodologies are lacking both regarding the orientation of teeth subject to study and in the analysis that can be carried out on these teeth once they are oriented. The opportunity to standardize a primary analysis methodology is furnished by the study of certain early Neanderthal and preneanderthal molars recovered in two caves in southern Italy [Grotta Taddeo (Taddeo Cave) and Grotta del Poggio (Poggio Cave), near Marina di Camerata, Campania]. To these we can add other molars of Neanderthal and modern man of the upper Paleolithic era, specifically scanned in the paleoanthropology laboratory of the University of Arkansas (Fayetteville, Arkansas, USA), in order to increase the paleoanthropological sample data and thereby make the final results of the analyses more significant. The new analysis methodology is rendered as follows: 1. Standardization of an orientation system for primary molars (superior and inferior), starting from a scan of a sample of 30 molars belonging to modern man (15 M1 inferior and 15 M1 superior), the definition of landmarks, the comparison of various systems and the choice of a system of orientation for each of the two dental typologies. 2. The definition of an analysis procedure that considers only the first 4 millimeters of the dental crown starting from the collar: 5 sections parallel to the plane according to which the tooth has been oriented are carried out, spaced 1 millimeter between them. The intention is to determine a method that allows for the differentiation of fossilized species even in the presence of worn teeth. 3. Results and Conclusions. The new approach to the study of teeth provides a considerable quantity of information that can better be evaluated by increasing the fossil sample data. It has been demonstrated to be a valid tool in evolutionary classification that has allowed (us) to differentiate the Neanderthal sample from that of modern man. In a particular sense the molars of Grotta Taddeo, which up until this point it has not been possible to determine with exactness their species of origin, through the present research they are classified as Neanderthal.

Non-Markovian stochastic processes and their applications: from anomalous diffusion to time series analysis

This work provides a forward step in the study and comprehension of the relationships between stochastic processes and a certain class of integral-partial differential equation, which can be used in order to model anomalous diffusion and transport in statistical physics. In the first part, we brought the reader through the fundamental notions of probability and stochastic processes, stochastic integration and stochastic differential equations as well. In particular, within the study of H-sssi processes, we focused on fractional Brownian motion (fBm) and its discrete-time increment process, the fractional Gaussian noise (fGn), which provide examples of non-Markovian Gaussian processes. The fGn, together with stationary FARIMA processes, is widely used in the modeling and estimation of long-memory, or long-range dependence (LRD). Time series manifesting long-range dependence, are often observed in nature especially in physics, meteorology, climatology, but also in hydrology, geophysics, economy and many others. We deepely studied LRD, giving many real data examples, providing statistical analysis and introducing parametric methods of estimation. Then, we introduced the theory of fractional integrals and derivatives, which indeed turns out to be very appropriate for studying and modeling systems with long-memory properties. After having introduced the basics concepts, we provided many examples and applications. For instance, we investigated the relaxation equation with distributed order time-fractional derivatives, which describes models characterized by a strong memory component and can be used to model relaxation in complex systems, which deviates from the classical exponential Debye pattern. Then, we focused in the study of generalizations of the standard diffusion equation, by passing through the preliminary study of the fractional forward drift equation. Such generalizations have been obtained by using fractional integrals and derivatives of distributed orders. In order to find a connection between the anomalous diffusion described by these equations and the long-range dependence, we introduced and studied the generalized grey Brownian motion (ggBm), which is actually a parametric class of H-sssi processes, which have indeed marginal probability density function evolving in time according to a partial integro-differential equation of fractional type. The ggBm is of course Non-Markovian. All around the work, we have remarked many times that, starting from a master equation of a probability density function f(x,t), it is always possible to define an equivalence class of stochastic processes with the same marginal density function f(x,t). All these processes provide suitable stochastic models for the starting equation. Studying the ggBm, we just focused on a subclass made up of processes with stationary increments. The ggBm has been defined canonically in the so called grey noise space. However, we have been able to provide a characterization notwithstanding the underline probability space. We also pointed out that that the generalized grey Brownian motion is a direct generalization of a Gaussian process and in particular it generalizes Brownain motion and fractional Brownain motion as well. Finally, we introduced and analyzed a more general class of diffusion type equations related to certain non-Markovian stochastic processes. We started from the forward drift equation, which have been made non-local in time by the introduction of a suitable chosen memory kernel K(t). The resulting non-Markovian equation has been interpreted in a natural way as the evolution equation of the marginal density function of a random time process l(t). We then consider the subordinated process Y(t)=X(l(t)) where X(t) is a Markovian diffusion. The corresponding time-evolution of the marginal density function of Y(t) is governed by a non-Markovian Fokker-Planck equation which involves the same memory kernel K(t). We developed several applications and derived the exact solutions. Moreover, we considered different stochastic models for the given equations, providing path simulations.

Multiresolution spherical wavelet analysis in global seismic tomography

Every seismic event produces seismic waves which travel throughout the Earth. Seismology is the science of interpreting measurements to derive information about the structure of the Earth. Seismic tomography is the most powerful tool for determination of 3D structure of deep Earth's interiors. Tomographic models obtained at the global and regional scales are an underlying tool for determination of geodynamical state of the Earth, showing evident correlation with other geophysical and geological characteristics. The global tomographic images of the Earth can be written as a linear combinations of basis functions from a specifically chosen set, defining the model parameterization. A number of different parameterizations are commonly seen in literature: seismic velocities in the Earth have been expressed, for example, as combinations of spherical harmonics or by means of the simpler characteristic functions of discrete cells. With this work we are interested to focus our attention on this aspect, evaluating a new type of parameterization, performed by means of wavelet functions. It is known from the classical Fourier theory that a signal can be expressed as the sum of a, possibly infinite, series of sines and cosines. This sum is often referred as a Fourier expansion. The big disadvantage of a Fourier expansion is that it has only frequency resolution and no time resolution. The Wavelet Analysis (or Wavelet Transform) is probably the most recent solution to overcome the shortcomings of Fourier analysis. The fundamental idea behind this innovative analysis is to study signal according to scale. Wavelets, in fact, are mathematical functions that cut up data into different frequency components, and then study each component with resolution matched to its scale, so they are especially useful in the analysis of non stationary process that contains multi-scale features, discontinuities and sharp strike. Wavelets are essentially used in two ways when they are applied in geophysical process or signals studies: 1) as a basis for representation or characterization of process; 2) as an integration kernel for analysis to extract information about the process. These two types of applications of wavelets in geophysical field, are object of study of this work. At the beginning we use the wavelets as basis to represent and resolve the Tomographic Inverse Problem. After a briefly introduction to seismic tomography theory, we assess the power of wavelet analysis in the representation of two different type of synthetic models; then we apply it to real data, obtaining surface wave phase velocity maps and evaluating its abilities by means of comparison with an other type of parametrization (i.e., block parametrization). For the second type of wavelet application we analyze the ability of Continuous Wavelet Transform in the spectral analysis, starting again with some synthetic tests to evaluate its sensibility and capability and then apply the same analysis to real data to obtain Local Correlation Maps between different model at same depth or between different profiles of the same model.

Analysis and developments of uncertainty processors for real time flood forecasting

The hydrologic risk (and the hydro-geologic one, closely related to it) is, and has always been, a very relevant issue, due to the severe consequences that may be provoked by a flooding or by waters in general in terms of human and economic losses. Floods are natural phenomena, often catastrophic, and cannot be avoided, but their damages can be reduced if they are predicted sufficiently in advance. For this reason, the flood forecasting plays an essential role in the hydro-geological and hydrological risk prevention. Thanks to the development of sophisticated meteorological, hydrologic and hydraulic models, in recent decades the flood forecasting has made a significant progress, nonetheless, models are imperfect, which means that we are still left with a residual uncertainty on what will actually happen. In this thesis, this type of uncertainty is what will be discussed and analyzed. In operational problems, it is possible to affirm that the ultimate aim of forecasting systems is not to reproduce the river behavior, but this is only a means through which reducing the uncertainty associated to what will happen as a consequence of a precipitation event. In other words, the main objective is to assess whether or not preventive interventions should be adopted and which operational strategy may represent the best option. The main problem for a decision maker is to interpret model results and translate them into an effective intervention strategy. To make this possible, it is necessary to clearly define what is meant by uncertainty, since in the literature confusion is often made on this issue. Therefore, the first objective of this thesis is to clarify this concept, starting with a key question: should be the choice of the intervention strategy to adopt based on the evaluation of the model prediction based on its ability to represent the reality or on the evaluation of what actually will happen on the basis of the information given by the model forecast? Once the previous idea is made unambiguous, the other main concern of this work is to develope a tool that can provide an effective decision support, making possible doing objective and realistic risk evaluations. In particular, such tool should be able to provide an uncertainty assessment as accurate as possible. This means primarily three things: it must be able to correctly combine all the available deterministic forecasts, it must assess the probability distribution of the predicted quantity and it must quantify the flooding probability. Furthermore, given that the time to implement prevention strategies is often limited, the flooding probability will have to be linked to the time of occurrence. For this reason, it is necessary to quantify the flooding probability within a horizon time related to that required to implement the intervention strategy and it is also necessary to assess the probability of the flooding time.

Determinants of the Economic Use of Patented Inventions: An Analysis of European Patents

The purpose of this research is to provide empirical evidence on determinants of the economic use of patented inventions in order to contribute to the literature on technology and innovation management. The current work consists of three main parts, each of which constitutes a self-consistent research paper. The first paper uses a meta-analytic approach to review and synthesize the existing body of empirical research on the determinants of technology licensing. The second paper investigates the factors affecting the choice between the following alternative economic uses of patented inventions: pure internal use, pure licensing, and mixed use. Finally, the third paper explores the least studied option of the economic use of patented inventions, namely, the sale of patent rights. The data to empirically test the hypotheses come from a large-scale survey of European Patent inventors resident in 21 European countries, Japan, and US. The findings provided in this dissertation contribute to a better understanding of the economic use of patented inventions by expanding the limits of previous research in several different dimensions.

Movement Analysis by means of inertial sensors: from bench to bedside

in the everyday clinical practice. Having this in mind, the choice of a simple setup would not be enough because, even if the setup is quick and simple, the instrumental assessment would still be in addition to the daily routine. The will to overcome this limit has led to the idea of instrumenting already existing and widely used functional tests. In this way the sensor based assessment becomes an integral part of the clinical assessment. Reliable and validated signal processing methods have been successfully implemented in Personal Health Systems based on smartphone technology. At the end of this research project there is evidence that such solution can really and easily used in clinical practice in both supervised and unsupervised settings. Smartphone based solution, together or in place of dedicated wearable sensing units, can truly become a pervasive and low-cost means for providing suitable testing solutions for quantitative movement analysis with a clear clinical value, ultimately providing enhanced balance and mobility support to an aging population.

Inverse Static Analysis of Massive Parallel Arrays of Three-State Actuators via Artificial Intelligence

Massive parallel robots (MPRs) driven by discrete actuators are force regulated robots that undergo continuous motions despite being commanded through a finite number of states only. Designing a real-time control of such systems requires fast and efficient methods for solving their inverse static analysis (ISA), which is a challenging problem and the subject of this thesis. In particular, five Artificial intelligence methods are proposed to investigate the on-line computation and the generalization error of ISA problem of a class of MPRs featuring three-state force actuators and one degree of revolute motion.

Social housing: interventions of densification in urban regeneration (1995-2010). Critical analysis of strategies adopted in Milan, London, São Paulo

The prospect of the continuous multiplication of life styles, the obsolescence of the traditional typological diagrams, the usability of spaces on different territorial scales, imposes on contemporary architecture the search for new models of living. Limited densities in urban development have produced the erosion of territory, the increase of the harmful emissions and energy consumption. High density housing cannot refuse the social emergency to ensure high quality and low cost dwellings, to a new people target: students, temporary workers, key workers, foreign, young couples without children, large families and, in general, people who carry out public services. Social housing strategies have become particularly relevant in regenerating high density urban outskirts. The choice of this research topic derives from the desire to deal with the recent accommodation emergency, according to different perspectives, with a view to give a contribution to the current literature, by proposing some tools for a correct design of the social housing, by ensuring good quality, cost-effective, and eco-sustainable solutions, from the concept phase, through management and maintenance, until the end of the building life cycle. The purpose of the thesis is defining a framework of guidelines that become effective instruments to be used in designing the social housing. They should also integrate the existing regulations and are mainly thought for those who work in this sector. They would aim at supporting students who have to cope with this particular residential theme, and also the users themselves. The scientific evidence of either the recent specialized literature or the solutions adopted in some case studies within the selected metropolitan areas of Milan, London and São Paulo, it is possible to identify the principles of this new design approach, in which the connection between typology, morphology and technology pursues the goal of a high living standard.