Response times in computerized adaptive testing: a method for cheating detection

In the field of educational and psychological measurement, the shift from paper-based to computerized tests has become a prominent trend in recent years. Computerized tests allow for more complex and personalized test administration procedures, like Computerized Adaptive Testing (CAT). CAT, following the Item Response Theory (IRT) models, dynamically generates tests based on test-taker responses, driven by complex statistical algorithms. Even if CAT structures are complex, they are flexible and convenient, but concerns about test security should be addressed. Frequent item administration can lead to item exposure and cheating, necessitating preventive and diagnostic measures. In this thesis a method called "CHeater identification using Interim Person fit Statistic" (CHIPS) is developed, designed to identify and limit cheaters in real-time during test administration. CHIPS utilizes response times (RTs) to calculate an Interim Person fit Statistic (IPS), allowing for on-the-fly intervention using a more secret item bank. Also, a slight modification is proposed to overcome situations with constant speed, called Modified-CHIPS (M-CHIPS). A simulation study assesses CHIPS, highlighting its effectiveness in identifying and controlling cheaters. However, it reveals limitations when cheaters possess all correct answers. The M-CHIPS overcame this limitation. Furthermore, the method has shown not to be influenced by the cheaters��� ability distribution or the level of correlation between ability and speed of test-takers. Finally, the method has demonstrated flexibility for the choice of significance level and the transition from fixed-length tests to variable-length ones. The thesis discusses potential applications, including the suitability of the method for multiple-choice tests, assumptions about RT distribution and level of item pre-knowledge. Also limitations are discussed to explore future developments such as different RT distributions, unusual honest respondent behaviors, and field testing in real-world scenarios. In summary, CHIPS and M-CHIPS offer real-time cheating detection in CAT, enhancing test security and ability estimation while not penalizing test respondents.

A Design Methodology for Computer Security Testing

The field of "computer security" is often considered something in between Art and Science. This is partly due to the lack of widely agreed and standardized methodologies to evaluate the degree of the security of a system. This dissertation intends to contribute to this area by investigating the most common security testing strategies applied nowadays and by proposing an enhanced methodology that may be effectively applied to different threat scenarios with the same degree of effectiveness. Security testing methodologies are the first step towards standardized security evaluation processes and understanding of how the security threats evolve over time. This dissertation analyzes some of the most used identifying differences and commonalities, useful to compare them and assess their quality. The dissertation then proposes a new enhanced methodology built by keeping the best of every analyzed methodology. The designed methodology is tested over different systems with very effective results, which is the main evidence that it could really be applied in practical cases. Most of the dissertation discusses and proves how the presented testing methodology could be applied to such different systems and even to evade security measures by inverting goals and scopes. Real cases are often hard to find in methodology' documents, in contrary this dissertation wants to show real and practical cases offering technical details about how to apply it. Electronic voting systems are the first field test considered, and Pvote and Scantegrity are the two tested electronic voting systems. The usability and effectiveness of the designed methodology for electronic voting systems is proved thanks to this field cases analysis. Furthermore reputation and anti virus engines have also be analyzed with similar results. The dissertation concludes by presenting some general guidelines to build a coordination-based approach of electronic voting systems to improve the security without decreasing the system modularity.

Testing future weak lensing surveys through simulations of observations

Weak lensing experiments such as the future ESA-accepted mission Euclid aim to measure cosmological parameters with unprecedented accuracy. It is important to assess the precision that can be obtained in these measurements by applying analysis software on mock images that contain many sources of noise present in the real data. In this Thesis, we show a method to perform simulations of observations, that produce realistic images of the sky according to characteristics of the instrument and of the survey. We then use these images to test the performances of the Euclid mission. In particular, we concentrate on the precision of the photometric redshift measurements, which are key data to perform cosmic shear tomography. We calculate the fraction of the total observed sample that must be discarded to reach the required level of precision, that is equal to 0.05(1+z) for a galaxy with measured redshift z, with different ancillary ground-based observations. The results highlight the importance of u-band observations, especially to discriminate between low (z < 0.5) and high (z ~ 3) redshifts, and the need for good observing sites, with seeing FWHM < 1. arcsec. We then construct an optimal filter to detect galaxy clusters through photometric catalogues of galaxies, and we test it on the COSMOS field, obtaining 27 lensing-confirmed detections. Applying this algorithm on mock Euclid data, we verify the possibility to detect clusters with mass above 10^14.2 solar masses with a low rate of false detections.

Design, production and testing of innovative key components of HEV/BEV powertrains

Through modelling activity, experimental campaigns, test bench and on-field validation, a complete powertrain for a BEV has been designed, assembled and used in a motorsport competition. The activity can be split in three main subjects, representing the three key components of an BEV vehicle. First of all a model of the entire powertrain has been developed in order to understand how the various design choices will influence the race lap-time. The data obtained was then used to design, build and test a first battery pack. After bench tests and track tests, it was understood that by using all the cell charac-teristics, without breaking the rules limitations, higher energy and power densities could have been achieved. An updated battery pack was then designed, produced and raced with at Motostudent 2018 re-sulting in a third place at debut. The second topic of this PhD was the design of novel inverter topologies. Three inverters have been de-signed, two of them using Gallium Nitride devices, a promising semiconductor technology that can achieve high switching speeds while maintaining low switching losses. High switching frequency is crucial to reduce the DC-Bus capacitor and then increase the power density of 3 phase inverters. The third in-verter uses classic Silicon devices but employs a ZVS (Zero Voltage Switching) topology. Despite the in-creased complexity of both the hardware and the control software, it can offer reduced switching losses by using conventional and established silicon mosfet technology. Finally, the mechanical parts of a three phase permanent magnet motor have been designed with the aim to employ it in UniBo Motorsport���s 2020 Formula Student car.

Advanced Mission Synthesis Algorithms for Vibration-based Accelerated Life-testing

In the field of vibration qualification testing, with the popular Random Control mode of shakers, the specimen is excited by random vibrations typically set in the form of a Power Spectral Density (PSD). The corresponding signals are stationary and Gaussian, i.e. featuring a normal distribution. Conversely, real-life excitations are frequently non-Gaussian, exhibiting high peaks and/or burst signals and/or deterministic harmonic components. The so-called kurtosis is a parameter often used to statistically describe the occurrence and significance of high peak values in a random process. Since the similarity between test input profiles and real-life excitations is fundamental for qualification test reliability, some methods of kurtosis-control can be implemented to synthesize realistic (non-Gaussian) input signals. Durability tests are performed to check the resistance of a component to vibration-based fatigue damage. A procedure to synthesize test excitations which starts from measured data and preserves both the damage potential and the characteristics of the reference signals is desirable. The Fatigue Damage Spectrum (FDS) is generally used to quantify the fatigue damage potential associated with the excitation. The signal synthesized for accelerated durability tests (i.e. with a limited duration) must feature the same FDS as the reference vibration computed for the component���s expected lifetime. Current standard procedures are efficient in synthesizing signals in the form of a PSD, but prove inaccurate if reference data are non-Gaussian. This work presents novel algorithms for the synthesis of accelerated durability test profiles with prescribed FDS and a non-Gaussian distribution. An experimental campaign is conducted to validate the algorithms, by testing their accuracy, robustness, and practical effectiveness. Moreover, an original procedure is proposed for the estimation of the fatigue damage potential, aiming to minimize the computational time. The research is thus supposed to improve both the effectiveness and the efficiency of excitation profile synthesis for accelerated durability tests.

Development and testing of innovative methodologies for modelling and control of normal and knocking combustion and implementation of novel rapid prototyping solutions

The thesis work deals with topics that led to the development of innovative control-oriented models and control algorithms for modern gasoline engines. Knock in boosted spark ignition engines is the widest topic discussed in this document because it remains one of the most limiting factors for maximizing combustion efficiency in this kind of engine. First chapter is thus focused on knock and a wide literature review is proposed to summarize the preliminary knowledge that even represents the background and the reference for discussed activities. Most relevant results achieved during PhD course in the field of knock modelling and control are then presented, describing every control-oriented model that led to the development of an adaptive model-based combustion control system. The complete controller has been developed in the context of the collaboration with Ferrari GT and it allowed to completely redefine the knock intensity evaluation as well as the combustion phase control. The second chapter is focused on the activity related to a prototyping Port Water Injection system that has been developed and tested on a turbocharged spark ignition engine, within the collaboration with Magneti Marelli. Such system and the effects of injected water on the combustion process were then modeled in a 1-D simulation environment (GT Power). Third chapter shows the development and validation of a control-oriented model for the real-time calculation of exhaust gas temperature that represents another important limitation to the performance increase in modern boosted engines. Indeed, modelling of exhaust gas temperature and thermocouple behavior are themes that play a key role in the optimization of combustion and catalyst efficiency.

Testing the effectiveness of phytoscreening to monitor shallow groundwater contamination by chlorinated ethenes

The research presented herein aims to investigate the strengths and weaknesses of a relatively new technique called phytoscreening. Parallel to the well-known phytoremediation, it consists of exploiting the absorbing potential of trees to delineate groundwater contamination plumes, especially for chlorinated ethenes (i.e., PCE, TCE, 1,2-cis DCE, and VC). The latter are prevalent contaminants in groundwater but their fate and transport in surface ecosystems, such as trees, are still poorly understood and subjected to high variability. Moreover, the analytical validity of tree-coring is still limited in many countries due to a lack of knowledge of its application opportunities. Tree-cores are extracted from trunks and generally analyzed by gas chromatography/mass spectrometry. A systematic review of former literature on phytoscreening for chlorinated ethenes is presented in this PhD thesis to evaluate the factors influencing the effectiveness of the technique. Besides, we tested the technique by probing eight sites contaminated by chlorinated ethenes in Italy (Emilia-Romagna) in different hydrogeological and seasonal settings. We coupled the technique with the assessment of gaseous-phase concentrations directly on-site, inserting detector tubes or a photoionization detector in the tree-holes left by the coring tool. Finally, we applied rank order statistic analysis on field data along with literature data to assess under which conditions phytoscreening should be applied to either screen or monitor environmental contamination issues. A relatively high correlation exists between tree-core and groundwater concentrations (Spearman���s �� > 0.6), being higher for compounds with higher sorption, for sites with shallower and thinner aquifers, and when sampling specific tree types with standardized sampling and extraction protocols. These results indicate the opportunities for assessing the occurrence, type, and concentration of solvents directly from the stem of trees. This can reduce the costs of characterization surveys, allowing rapid identification of hotspots and plume direction and thus optimizing the drilling of boreholes.

Supporting requirement elicitation and ontology testing in knowledge graph engineering

Knowledge graphs and ontologies are closely related concepts in the field of knowledge representation. In recent years, knowledge graphs have gained increasing popularity and are serving as essential components in many knowledge engineering projects that view them as crucial to their success. The conceptual foundation of the knowledge graph is provided by ontologies. Ontology modeling is an iterative engineering process that consists of steps such as the elicitation and formalization of requirements, the development, testing, refactoring, and release of the ontology. The testing of the ontology is a crucial and occasionally overlooked step of the process due to the lack of integrated tools to support it. As a result of this gap in the state-of-the-art, the testing of the ontology is completed manually, which requires a considerable amount of time and effort from the ontology engineers. The lack of tool support is noticed in the requirement elicitation process as well. In this aspect, the rise in the adoption and accessibility of knowledge graphs allows for the development and use of automated tools to assist with the elicitation of requirements from such a complementary source of data. Therefore, this doctoral research is focused on developing methods and tools that support the requirement elicitation and testing steps of an ontology engineering process. To support the testing of the ontology, we have developed XDTesting, a web application that is integrated with the GitHub platform that serves as an ontology testing manager. Concurrently, to support the elicitation and documentation of competency questions, we have defined and implemented RevOnt, a method to extract competency questions from knowledge graphs. Both methods are evaluated through their implementation and the results are promising.