Assessing the fit of unidimensional IRT models for binary data under model misspecification

Model misspecification affects the classical test statistics used to assess the fit of the Item Response Theory (IRT) models. Robust tests have been derived under model misspecification, as the Generalized Lagrange Multiplier and Hausman tests, but their use has not been largely explored in the IRT framework. In the first part of the thesis, we introduce the Generalized Lagrange Multiplier test to detect differential item response functioning in IRT models for binary data under model misspecification. By means of a simulation study and a real data analysis, we compare its performance with the classical Lagrange Multiplier test, computed using the Hessian and the cross-product matrix, and the Generalized Jackknife Score test. The power of these tests is computed empirically and asymptotically. The misspecifications considered are local dependence among items and non-normal distribution of the latent variable. The results highlight that, under mild model misspecification, all tests have good performance while, under strong model misspecification, the performance of the tests deteriorates. None of the tests considered show an overall superior performance than the others. In the second part of the thesis, we extend the Generalized Hausman test to detect non-normality of the latent variable distribution. To build the test, we consider a seminonparametric-IRT model, that assumes a more flexible latent variable distribution. By means of a simulation study and two real applications, we compare the performance of the Generalized Hausman test with the M2 limited information goodness-of-fit test and the Likelihood-Ratio test. Additionally, the information criteria are computed. The Generalized Hausman test has a better performance than the Likelihood-Ratio test in terms of Type I error rates and the M2 test in terms of power. The performance of the Generalized Hausman test and the information criteria deteriorates when the sample size is small and with a few items.

Stima dei parametri di modelli idrologici mediante ottimizzazione dell’utilità

Tradizionalmente, l'obiettivo della calibrazione di un modello afflussi-deflussi è sempre stato quello di ottenere un set di parametri (o una distribuzione di probabilità dei parametri) che massimizzasse l'adattamento dei dati simulati alla realtà osservata, trattando parzialmente le finalità applicative del modello. Nel lavoro di tesi viene proposta una metodologia di calibrazione che trae spunto dell'evidenza che non sempre la corrispondenza tra dati osservati e simulati rappresenti il criterio più appropriato per calibrare un modello idrologico. Ai fini applicativi infatti, può risultare maggiormente utile una miglior rappresentazione di un determinato aspetto dell'idrogramma piuttosto che un altro. Il metodo di calibrazione che viene proposto mira a valutare le prestazioni del modello stimandone l'utilità nell'applicazione prevista. Tramite l'utilizzo di opportune funzioni, ad ogni passo temporale viene valutata l'utilità della simulazione ottenuta. La calibrazione viene quindi eseguita attraverso la massimizzazione di una funzione obiettivo costituita dalla somma delle utilità stimate nei singoli passi temporali. Le analisi mostrano come attraverso l'impiego di tali funzioni obiettivo sia possibile migliorare le prestazioni del modello laddove ritenute di maggior interesse per per le finalità applicative previste.

A New Test Rig for In-Vitro Evaluation of the Knee Joint Behaviour

The evaluation of the knee joint behavior is fundamental in many applications, such as joint modeling, prosthesis and orthosis design. In-vitro tests are important in order to analyse knee behavior when simulating various loading conditions and studying physiology of the joint. A new test rig for in-vitro evaluation of the knee joint behavior is presented in this paper. It represents the evolution of a previously proposed rig, designed to overcome its principal limitations and to improve its performances. The design procedure and the adopted solution in order to satisfy the specifications are presented here. Thanks to its 6-6 Gough-Stewart parallel manipulator loading system, the rig replicates general loading conditions, like daily actions or clinical tests, on the specimen in a wide range of flexion angles. The restraining actions of knee muscles can be simulated when active actions are simulated. The joint motion in response to the applied loads, guided by passive articular structures and muscles, is permitted by the characteristics of the loading system which is force controlled. The new test rig guarantees visibility so that motion can be measured by an optoelectronic system. Furthermore, the control system of the new test rig allows the estimation of the contribution of the principal leg muscles in guaranteeing the equilibrium of the joint by the system for muscle simulation. Accuracy in positioning is guaranteed by the designed tibia and femur fixation systems,which allow unmounting and remounting the specimen in the same pose. The test rig presented in this paper permits the analysis of the behavior of the knee joint and comparative analysis on the same specimen before and after surgery, in a way to assess the goodness of prostheses or surgical treatments.

Analysis of slip distribution of large earthquakes oriented to tsunamigenesis characterisation

The present thesis focuses on the on-fault slip distribution of large earthquakes in the framework of tsunami hazard assessment and tsunami warning improvement. It is widely known that ruptures on seismic faults are strongly heterogeneous. In the case of tsunamigenic earthquakes, the slip heterogeneity strongly influences the spatial distribution of the largest tsunami effects along the nearest coastlines. Unfortunately, after an earthquake occurs, the so-called finite-fault models (FFM) describing the coseismic on-fault slip pattern becomes available over time scales that are incompatible with early tsunami warning purposes, especially in the near field. Our work aims to characterize the slip heterogeneity in a fast, but still suitable way. Using finite-fault models to build a starting dataset of seismic events, the characteristics of the fault planes are studied with respect to the magnitude. The patterns of the slip distribution on the rupture plane, analysed with a cluster identification algorithm, reveal a preferential single-asperity representation that can be approximated by a two-dimensional Gaussian slip distribution (2D GD). The goodness of the 2D GD model is compared to other distributions used in literature and its ability to represent the slip heterogeneity in the form of the main asperity is proven. The magnitude dependence of the 2D GD parameters is investigated and turns out to be of primary importance from an early warning perspective. The Gaussian model is applied to the 16 September 2015 Illapel, Chile, earthquake and used to compute early tsunami predictions that are satisfactorily compared with the available observations. The fast computation of the 2D GD and its suitability in representing the slip complexity of the seismic source make it a useful tool for the tsunami early warning assessments, especially for what concerns the near field.

Design and characterization of automated agricultural vehicle systems

Nowadays, technological advancements have brought industry and research towards the automation of various processes. Automation brings a reduction in costs and an improvement in product quality. For this reason, companies are pushing research to investigate new technologies. The agriculture industry has always looked towards automating various processes, from product processing to storage. In the last years, the automation of harvest and cultivation phases also has become attractive, pushed by the advancement of autonomous driving. Nevertheless, ADAS systems are not enough. Merging different technologies will be the solution to obtain total automation of agriculture processes. For example, sensors that estimate products' physical and chemical properties can be used to evaluate the maturation level of fruit. Therefore, the fusion of these technologies has a key role in industrial process automation. In this dissertation, ADAS systems and sensors for precision agriculture will be both treated. Several measurement procedures for characterizing commercial 3D LiDARs will be proposed and tested to cope with the growing need for comparison tools. Axial errors and transversal errors have been investigated. Moreover, a measurement method and setup for evaluating the fog effect on 3D LiDARs will be proposed. Each presented measurement procedure has been tested. The obtained results highlight the versatility and the goodness of the proposed approaches. Regarding the precision agriculture sensors, a measurement approach for the Moisture Content and density estimation of crop directly on the field is presented. The approach regards the employment of a Near Infrared spectrometer jointly with Partial Least Square statistical analysis. The approach and the model will be described together with a first laboratory prototype used to evaluate the NIRS approach. Finally, a prototype for on the field analysis is realized and tested. The test results are promising, evidencing that the proposed approach is suitable for Moisture Content and density estimation.

Governing the water conservation in the Urmia Lake Basin: addressing macro systems’ fit and micro users’ behavior

To change unadapted water governing systems, and water users’ traditional conducts in line with climate change, understanding of systems’ structures and users’ behaviors is necessary. To this aim, comprehensive and pragmatic research was designed and implemented in the Urmia Lake Basin where due to the severe droughts, and human-made influences, especially through the agricultural development, the lake has been shrunken drastically. To analyze the water governance and conservation issues in the basin, an innovative framework was developed based on mathematical physics concepts and pro-environmental behavior theories. Accordingly, in system level (macro/meso), the problem of fit of the early-shaped water governing system associating with the function of “political-security” and “political-economic” factors in the basin was identified through mean-field models. Furthermore, the effect of a “political-environmental” factor, the Urmia Lake Restoration Program (ULRP), on reforming the system structure and hence its fit was assessed. The analysis results revealed that by revising the provincial boundaries (horizontal alternation) for the entity of Kurdistan province to permit that interact with the headquarter of West Azerbaijan province for its water demand-supply initiatives, the system fit can increase. Also, the constitution of the ULRP (vertical arrangement) not only could increase the structural fit of the water governing system to the basin, but also significantly could enhance the system fit through its water-saving policy. Besides, in individual level (micro), the governing factors of water conservation behavior of the major users/farmers were identified through rational and moral socio-psychological models. In rational approach, incorporating PMT and TPB, the SEM results demonstrated that “Perceived Vulnerability”, “Self-Efficacy”, “Response Efficacy”, “Response Cost”, “Subjective Norms” and “Institutional Trust” significantly affect the water-saving intention/behavior. Likewise, NAM based analysis as a moral approach, uncovered the significant effects of “Awareness of Consequences”, “Appraisal of Responsibility”, “Personal Norms” as well as “Place Attachment” and “Emotions” on water-saving intention.

Deep and near space tracking stations in support of lunar and planetary exploration missions

The aim of this dissertation is to describe the methodologies required to design, operate, and validate the performance of ground stations dedicated to near and deep space tracking, as well as the models developed to process the signals acquired, from raw data to the output parameters of the orbit determination of spacecraft. This work is framed in the context of lunar and planetary exploration missions by addressing the challenges in receiving and processing radiometric data for radio science investigations and navigation purposes. These challenges include the designing of an appropriate back-end to read, convert and store the antenna voltages, the definition of appropriate methodologies for pre-processing, calibration, and estimation of radiometric data for the extraction of information on the spacecraft state, and the definition and integration of accurate models of the spacecraft dynamics to evaluate the goodness of the recorded signals. Additionally, the experimental design of acquisition strategies to perform direct comparison between ground stations is described and discussed. In particular, the evaluation of the differential performance between stations requires the designing of a dedicated tracking campaign to maximize the overlap of the recorded datasets at the receivers, making it possible to correlate the received signals and isolate the contribution of the ground segment to the noise in the single link. Finally, in support of the methodologies and models presented, results from the validation and design work performed on the Deep Space Network (DSN) affiliated nodes DSS-69 and DSS-17 will also be reported.

Uncovering the encoding and transmission of behaviourally relevant information in neural activity

Most cognitive functions require the encoding and routing of information across distributed networks of brain regions. Information propagation is typically attributed to physical connections existing between brain regions, and contributes to the formation of spatially correlated activity patterns, known as functional connectivity. While structural connectivity provides the anatomical foundation for neural interactions, the exact manner in which it shapes functional connectivity is complex and not yet fully understood. Additionally, traditional measures of directed functional connectivity only capture the overall correlation between neural activity, and provide no insight on the content of transmitted information, limiting their ability in understanding neural computations underlying the distributed processing of behaviorally-relevant variables. In this work, we first study the relationship between structural and functional connectivity in simulated recurrent spiking neural networks with spike timing dependent plasticity. We use established measures of time-lagged correlation and overall information propagation to infer the temporal evolution of synaptic weights, showing that measures of dynamic functional connectivity can be used to reliably reconstruct the evolution of structural properties of the network. Then, we extend current methods of directed causal communication between brain areas, by deriving an information-theoretic measure of Feature-specific Information Transfer (FIT) quantifying the amount, content and direction of information flow. We test FIT on simulated data, showing its key properties and advantages over traditional measures of overall propagated information. We show applications of FIT to several neural datasets obtained with different recording methods (magneto and electro-encephalography, spiking activity, local field potentials) during various cognitive functions, ranging from sensory perception to decision making and motor learning. Overall, these analyses demonstrate the ability of FIT to advance the investigation of communication between brain regions, uncovering the previously unaddressed content of directed information flow.

Multiple testing in spatial epidemiology: a Bayesian approach

In this work we aim to propose a new approach for preliminary epidemiological studies on Standardized Mortality Ratios (SMR) collected in many spatial regions. A preliminary study on SMRs aims to formulate hypotheses to be investigated via individual epidemiological studies that avoid bias carried on by aggregated analyses. Starting from collecting disease counts and calculating expected disease counts by means of reference population disease rates, in each area an SMR is derived as the MLE under the Poisson assumption on each observation. Such estimators have high standard errors in small areas, i.e. where the expected count is low either because of the low population underlying the area or the rarity of the disease under study. Disease mapping models and other techniques for screening disease rates among the map aiming to detect anomalies and possible high-risk areas have been proposed in literature according to the classic and the Bayesian paradigm. Our proposal is approaching this issue by a decision-oriented method, which focus on multiple testing control, without however leaving the preliminary study perspective that an analysis on SMR indicators is asked to. We implement the control of the FDR, a quantity largely used to address multiple comparisons problems in the eld of microarray data analysis but which is not usually employed in disease mapping. Controlling the FDR means providing an estimate of the FDR for a set of rejected null hypotheses. The small areas issue arises diculties in applying traditional methods for FDR estimation, that are usually based only on the p-values knowledge (Benjamini and Hochberg, 1995; Storey, 2003). Tests evaluated by a traditional p-value provide weak power in small areas, where the expected number of disease cases is small. Moreover tests cannot be assumed as independent when spatial correlation between SMRs is expected, neither they are identical distributed when population underlying the map is heterogeneous. The Bayesian paradigm oers a way to overcome the inappropriateness of p-values based methods. Another peculiarity of the present work is to propose a hierarchical full Bayesian model for FDR estimation in testing many null hypothesis of absence of risk.We will use concepts of Bayesian models for disease mapping, referring in particular to the Besag York and Mollié model (1991) often used in practice for its exible prior assumption on the risks distribution across regions. The borrowing of strength between prior and likelihood typical of a hierarchical Bayesian model takes the advantage of evaluating a singular test (i.e. a test in a singular area) by means of all observations in the map under study, rather than just by means of the singular observation. This allows to improve the power test in small areas and addressing more appropriately the spatial correlation issue that suggests that relative risks are closer in spatially contiguous regions. The proposed model aims to estimate the FDR by means of the MCMC estimated posterior probabilities b i's of the null hypothesis (absence of risk) for each area. An estimate of the expected FDR conditional on data (\FDR) can be calculated in any set of b i's relative to areas declared at high-risk (where thenull hypothesis is rejected) by averaging the b i's themselves. The\FDR can be used to provide an easy decision rule for selecting high-risk areas, i.e. selecting as many as possible areas such that the\FDR is non-lower than a prexed value; we call them\FDR based decision (or selection) rules. The sensitivity and specicity of such rule depend on the accuracy of the FDR estimate, the over-estimation of FDR causing a loss of power and the under-estimation of FDR producing a loss of specicity. Moreover, our model has the interesting feature of still being able to provide an estimate of relative risk values as in the Besag York and Mollié model (1991). A simulation study to evaluate the model performance in FDR estimation accuracy, sensitivity and specificity of the decision rule, and goodness of estimation of relative risks, was set up. We chose a real map from which we generated several spatial scenarios whose counts of disease vary according to the spatial correlation degree, the size areas, the number of areas where the null hypothesis is true and the risk level in the latter areas. In summarizing simulation results we will always consider the FDR estimation in sets constituted by all b i's selected lower than a threshold t. We will show graphs of the\FDR and the true FDR (known by simulation) plotted against a threshold t to assess the FDR estimation. Varying the threshold we can learn which FDR values can be accurately estimated by the practitioner willing to apply the model (by the closeness between\FDR and true FDR). By plotting the calculated sensitivity and specicity (both known by simulation) vs the\FDR we can check the sensitivity and specicity of the corresponding\FDR based decision rules. For investigating the over-smoothing level of relative risk estimates we will compare box-plots of such estimates in high-risk areas (known by simulation), obtained by both our model and the classic Besag York Mollié model. All the summary tools are worked out for all simulated scenarios (in total 54 scenarios). Results show that FDR is well estimated (in the worst case we get an overestimation, hence a conservative FDR control) in small areas, low risk levels and spatially correlated risks scenarios, that are our primary aims. In such scenarios we have good estimates of the FDR for all values less or equal than 0.10. The sensitivity of\FDR based decision rules is generally low but specicity is high. In such scenario the use of\FDR = 0:05 or\FDR = 0:10 based selection rule can be suggested. In cases where the number of true alternative hypotheses (number of true high-risk areas) is small, also FDR = 0:15 values are well estimated, and \FDR = 0:15 based decision rules gains power maintaining an high specicity. On the other hand, in non-small areas and non-small risk level scenarios the FDR is under-estimated unless for very small values of it (much lower than 0.05); this resulting in a loss of specicity of a\FDR = 0:05 based decision rule. In such scenario\FDR = 0:05 or, even worse,\FDR = 0:1 based decision rules cannot be suggested because the true FDR is actually much higher. As regards the relative risk estimation, our model achieves almost the same results of the classic Besag York Molliè model. For this reason, our model is interesting for its ability to perform both the estimation of relative risk values and the FDR control, except for non-small areas and large risk level scenarios. A case of study is nally presented to show how the method can be used in epidemiology.

On Designing Compliant Actuators Based On Dielectric Elastomers

Dielectric Elastomers (DE) are incompressible dielectrics which can experience deviatoric (isochoric) finite deformations in response to applied large electric fields. Thanks to the strong electro-mechanical coupling, DE intrinsically offer great potentialities for conceiving novel solid-state mechatronic devices, in particular linear actuators, which are more integrated, lightweight, economic, silent, resilient and disposable than equivalent devices based on traditional technologies. Such systems may have a huge impact in applications where the traditional technology does not allow coping with the limits of weight or encumbrance, and with problems involving interaction with humans or unknown environments. Fields such as medicine, domotic, entertainment, aerospace and transportation may profit. For actuation usage, DE are typically shaped in thin films coated with compliant electrodes on both sides and piled one on the other to form a multilayered DE. DE-based Linear Actuators (DELA) are entirely constituted by polymeric materials and their overall performance is highly influenced by several interacting factors; firstly by the electromechanical properties of the film, secondly by the mechanical properties and geometry of the polymeric frame designed to support the film, and finally by the driving circuits and activation strategies. In the last decade, much effort has been focused in the devolvement of analytical and numerical models that could explain and predict the hyperelastic behavior of different types of DE materials. Nevertheless, at present, the use of DELA is limited. The main reasons are 1) the lack of quantitative and qualitative models of the actuator as a whole system 2) the lack of a simple and reliable design methodology. In this thesis, a new point of view in the study of DELA is presented which takes into account the interaction between the DE film and the film supporting frame. Hyperelastic models of the DE film are reported which are capable of modeling the DE and the compliant electrodes. The supporting frames are analyzed and designed as compliant mechanisms using pseudo-rigid body models and subsequent finite element analysis. A new design methodology is reported which optimize the actuator performances allowing to specifically choose its inherent stiffness. As a particular case, the methodology focuses on the design of constant force actuators. This class of actuators are an example of how the force control could be highly simplified. Three new DE actuator concepts are proposed which highlight the goodness of the proposed method.

Neutrino velocity measurement with the OPERA experiment in the CNGS beam

In the thesis is presented the measurement of the neutrino velocity with the OPERA experiment in the CNGS beam, a muon neutrino beam produced at CERN. The OPERA detector observes muon neutrinos 730 km away from the source. Previous measurements of the neutrino velocity have been performed by other experiments. Since the OPERA experiment aims the direct observation of muon neutrinos oscillations into tau neutrinos, a higher energy beam is employed. This characteristic together with the higher number of interactions in the detector allows for a measurement with a much smaller statistical uncertainty. Moreover, a much more sophisticated timing system (composed by cesium clocks and GPS receivers operating in “common view mode”), and a Fast Waveform Digitizer (installed at CERN and able to measure the internal time structure of the proton pulses used for the CNGS beam), allows for a new measurement with a smaller systematic error. Theoretical models on Lorentz violating effects can be investigated by neutrino velocity measurements with terrestrial beams. The analysis has been carried out with blind method in order to guarantee the internal consistency and the goodness of each calibration measurement. The performed measurement is the most precise one done with a terrestrial neutrino beam, the statistical accuracy achieved by the OPERA measurement is about 10 ns and the systematic error is about 20 ns.

"Tracciature Digitali": la conoscenza nell'era informazionale

La specificità dell'acquisizione di contenuti attraverso le interfacce digitali condanna l'agente epistemico a un'interazione frammentata, insufficiente da un punto di vista computazionale, mnemonico e temporale, rispetto alla mole informazionale oggi accessibile attraverso una qualunque implementazione della relazione uomo-computer, e invalida l'applicabilità del modello standard di conoscenza, come credenza vera e giustificata, sconfessando il concetto di credenza razionalmente fondata, per formare la quale, sarebbe invece richiesto all'agente di poter disporre appunto di risorse concettuali, computazionali e temporali inaccessibili. La conseguenza è che l'agente, vincolato dalle limitazioni ontologiche tipiche dell'interazione con le interfacce culturali, si vede costretto a ripiegare su processi ambigui, arbitrari e spesso più casuali di quanto creda, di selezione e gestione delle informazioni che danno origine a veri e propri ibridi (alla Latour) epistemologici, fatti di sensazioni e output di programmi, credenze non fondate e bit di testimonianze indirette e di tutta una serie di relazioni umano-digitali che danno adito a rifuggire in una dimensione trascendente che trova nel sacro il suo più immediato ambito di attuazione. Tutto ciò premesso, il presente lavoro si occupa di costruire un nuovo paradigma epistemologico di conoscenza proposizionale ottenibile attraverso un'interfaccia digitale di acquisizione di contenuti, fondato sul nuovo concetto di Tracciatura Digitale, definito come un un processo di acquisizione digitale di un insieme di tracce, ossia meta-informazioni di natura testimoniale. Tale dispositivo, una volta riconosciuto come un processo di comunicazione di contenuti, si baserà sulla ricerca e selezione di meta-informazioni, cioè tracce, che consentiranno l'implementazione di approcci derivati dall'analisi decisionale in condizioni di razionalità limitata, approcci che, oltre ad essere quasi mai utilizzati in tale ambito, sono ontologicamente predisposti per una gestione dell'incertezza quale quella riscontrabile nell'istanziazione dell'ibrido informazionale e che, in determinate condizioni, potranno garantire l'agente sulla bontà epistemica del contenuto acquisito.

La storia di Iefte (Jdc 10,6-12,7). Studi sul testo biblico e sulla sua ricezione nell'Antichità

La tesi tratta la storia veterotestamentaria di Iefte (Jdg 10,6-12,7). Il lavoro è diviso in due parti: la prima concerne la formazione del testo biblico e propone una nuova analisi critico-testuale del passo attraverso il confronto tra TM, LXX, Vg e altre fonti. Questo raffronto esamina i rapporti tra il TM e il modello ebraico dei LXX e le differenze tra le diverse recensioni dei LXX; inoltre, lo studio del lessico e dei temi in esso presenti porta alla formulazione di una nuova ipotesi sul tempo della composizione e sulla contestualizzazione storica e letteraria dell'episodio all'interno del corpus biblico. La seconda parte si concentra sulla storia delle interpretazioni del passo nel mondo latino e greco dal I secolo d.C. all'inizio del V secolo, e ha portato alla costituzione di un dossier di brani, esaminati nel loro contesto, che commentano o citano l'episodio. L'attenzione al contesto ha permesso di risolvere alcuni problemi che finora hanno impedito la ricostruzione del percorso esegetico del brano (attribuzione di alcuni frammenti catenari, datazione del De virginitate di Ambrogio, ecc.) Questo nuovo approccio di ricerca combina un'analisi completa dell'episodio biblico con uno studio approfondito della sua esegesi. Rivela così, da un lato, le scelte effettuate durante la composizione di un testo scritturistico problematico, e, dall'altro, i diversi meccanismi utilizzati dagli esegeti per spiegare il significato di una storia in cui la bontà di Dio, che ha tollerato il sacrificio umano, è messa in discussione.