Statistical verification and differential privacy in cyber-physical systems

This thesis studies the statistical verification and differential privacy in Cyber-Physical Systems. The first part focuses on the statistical verification of stochastic hybrid system, a class of formal models for Cyber-Physical Systems. Model reduction techniques are performed on both Discrete-Time and Continuous-Time Stochastic Hybrid Systems to reduce them to Discrete-Time Markov Chains and Continuous-Time Markov Chains, respectively; and statistical verification algorithms are proposed to verify Linear Inequality LTL and Metric Interval Temporal Logic on these discrete probabilistic models. In addition, the advantage of stratified sampling in verifying Probabilistic Computation Tree Logic on Labeled Discrete-Time Markov Chains is studied; this method can potentially be extended to other statistical verification algorithms to reduce computational costs. The second part focuses on the Differential Privacy in multi-agent systems that involve share information sharing to achieve overall control goals. A general formulation of the systems and a notion of Differential Privacy are proposed, and a trade-off between the Differential Privacy and the tracking performance of the systems is demonstrated. In addition, it is proved that there is a trade-off between Differential Privacy and the entropy of the unbiased estimator of the private data, and an optimal algorithm to achieve the best trade-off is given

Identification of a 3-gene model as a powerful diagnostic tool for the recognition of ALK-negative anaplastic large-cell lymphoma

16siAnaplastic large-cell lymphomas (ALCLs) are a group of clinically and biologically heterogeneous diseases including the ALK+ and ALK+ systemic forms. Whereas ALK+ ALCLs are molecularly characterized and can be readily diagnosed, specific immunophenotypic or genetic features to define ALK- ALCL are missing, and their distinction from other T-cell non-Hodgkin lymphomas (T-NHLs) remains controversial. In the present study, we undertook a transcriptional profiling meta-analysis of 309 cases, including ALCL and other primary T-NHL samples. Pathway discovery and prediction analyses defined a minimum set of genes capable of recognizing ALK- ALCL. Application of quantitative RT-PCR in independent datasets from cryopreserved and formalin-fixed paraffin-embedded samples validated a 3-gene model (TNFRSF8, BATF3, and TMOD1) able to successfully separate ALK- ALCL from peripheral T-cell lymphoma not otherwise specified, with overall accuracy near 97%. In conclusion, our data justify the possibility of translating quantitative RT-PCR protocols to routine clinical settings as a new approach to objectively dissect T-NHL and to select more appropriate therapeutic protocols. © 2012 by The American Society of Hematology.openopenAgnelli L.; Mereu E.; Pellegrino E.; Limongi T.; Kwee I.; Bergaggio E.; Ponzoni M.; Zamo A.; Iqbal J.; Piccaluga P.P.; Neri A.; Chan W.C.; Pileri S.; Bertoni F.; Inghirami G.; Piva R.Agnelli, L.; Mereu, E.; Pellegrino, E.; Limongi, T.; Kwee, I.; Bergaggio, E.; Ponzoni, M.; Zamo, A.; Iqbal, J.; Piccaluga, P. P.; Neri, A.; Chan, W. C.; Pileri, S.; Bertoni, F.; Inghirami, G.; Piva, R

Automatic Selection of Statistical Model Checkers for Analysis of Biological Models

Statistical Model Checking (SMC) blends the speed of simulation with the rigorous analytical capabilities of model checking, and its success has prompted researchers to implement a number of SMC tools whose availability provides flexibility and fine-tuned control over model analysis. However, each tool has its own practical limitations, and different tools have different requirements and performance characteristics. The performance of different tools may also depend on the specific features of the input model or the type of query to be verified. Consequently, choosing the most suitable tool for verifying any given model requires a significant degree of experience, and in most cases, it is challenging to predict the right one. The aim of our research has been to simplify the model checking process for researchers in biological systems modelling by simplifying and rationalising the model selection process. This has been achieved through delivery of the various key contributions listed below. • We have developed a software component for verification of kernel P (kP) system models, using the NuSMV model checker. We integrated it into a larger software platform (www.kpworkbench.org). • We surveyed five popular SMC tools, comparing their modelling languages, external dependencies, expressibility of specification languages, and performance. To best of our knowledge, this is the first known attempt to categorise the performance of SMC tools based on the commonly used property specifications (property patterns) for model checking. • We have proposed a set of model features which can be used for predicting the fastest SMC for biological model verification, and have shown, moreover, that the proposed features both reduce computation time and increase predictive power. • We used machine learning algorithms for predicting the fastest SMC tool for verification of biological models, and have shown that this approach can successfully predict the fastest SMC tool with over 90% accuracy. • We have developed a software tool, SMC Predictor, that predicts the fastest SMC tool for a given model and property query, and have made this freely available to the wider research community (www.smcpredictor.com). Our results show that using our methodology can generate significant savings in the amount of time and resources required for model verification

On the Modeling and Verification of Collective and Cooperative Systems

none1noThe formal description and verification of networks of cooperative and interacting agents is made difficult by the interplay of several different behavioral patterns, models of communication, scalability issues. In this paper, we will explore the functionalities and the expressiveness of a general-purpose process algebraic framework for the specification and model checking based analysis of collective and cooperative systems. The proposed syntactic and semantic schemes are general enough to be adapted with small modifications to heterogeneous application domains, like, e.g., crowdsourcing systems, trustworthy networks, and distributed ledger technologies.Aldini, AlessandroAldini, Alessandr

CLINICAL, GENETICS AND MOLECULAR RISK FACTORS OF DENGUE SEVERITY

Ph.DDOCTOR OF PHILOSOPH

Causes and Treatment of Herpes simplex Virus Recurrences

Trials have demonstrated that prophylactic acyclovir treatment reduces the cumulative risk of first herpes simplex virus (HSV) recurrence after randomization, and studies have suggested that ultraviolet (UV) exposure may increase the risk of HSV recurrence. We estimated the effect of acyclovir on cumulative risk of multiple recurrences and time outdoors on risk of ocular HSV recurrences. These goals were accomplished using the Herpetic Eye Disease study, a 12-month placebo-controlled randomized trial of twice-daily oral acyclovir to prevent ocular HSV recurrence. Of the trial's 703 participants, 241 (34%) participants who started weekly report completion within 30 days of randomization were included in a nested study of orofacial herpetic recurrences. The estimated cumulative risk of non-ocular recurrence in the placebo and acyclovir groups after 180 days was 27% and 12% for first recurrences, and 11% and 3% for second recurrences, yielding risk differences of 15% (95% confidence interval (CI): 4, 26) and 8% (95% CI: 0, 15), respectively (homogeneity P value = 0.15). The unadjusted hazard ratios estimates for first and second recurrences were 0.51 (95% CI: 0.28, 0.92) and 0.55 (95% CI: 0.29, 1.03), respectively (homogeneity P value = 0.82); adjusted results were similar. Acyclovir was observed to have a smaller absolute effect and a similar relative effect on second as compared to first non-ocular HSV recurrence. A total of 308 participants were included in a nested observational study that included reports of time spent outdoors. We matched weekly UV index values from the National Oceanic and Atmospheric Administration to each participant and used marginal structural Cox models to account for confounding due to time-varying psychological stress and contact lens use and selection bias from drop-out. The weighted hazard ratios comparing those with 8+ hours of time outdoors to those with less exposure were 0.84 (95% CI: 0.27, 2.63) and 3.10 (95% CI: 1.14, 8.48), for weeks with a UV index below 4, and 4+, respectively (ratio of hazard ratios: 3.68, 95% CI: 0.43, 31.4). Though imprecise, when UV index was higher (i.e. 4+), eight or more hours per week spent outdoors was associated with increased risk of ocular HSV recurrences.Doctor of Philosoph

How religion influences the use of social media : the impact of the online user’s religiosity on perceived online privacy and the use of technology in Saudi Arabia.

Religion has a significant effect on people’s lives. It impacts human behaviour, thoughts, morale standards, attitudes and values. The literature shows that religiosity has an effect also on consumer behaviour. However, the concept of religiosity has been under-researched due to the sensitivity of religion (Swimberghe, Flurry, & Parker, 2011). According to Vitell (2009) there is still a need to develop a vigorous theoretical understanding of the impact of religiosity on the consumer behaviour. This thesis contributes to that knowledge by developing a model to explain the effect of the religiosity of the online user on their use of social media. Current research does not fully explain the specifics of religious influences on online user behaviours. This thesis main goal is to build a model that can measure the effect of intrinsic religiosity on the use of social media. The proposed model uses the unified theory of acceptance and use of technology (UTAUT2) along with Privacy concern to measure the effect of religiosity on the use of social media. This thesis empirically tests the proposed model linking religiosity, privacy concerns, technology acceptance and the use of social media. Allport and Ross' (1967) religious orientation scale (ROS) is used to measure the intrinsic religiosity. Xu et al's., (2011a) model of privacy concern is used to measure privacy concerns when using social media. Venkatesh, Thong and Xu's (2012) unified theory of acceptance and use of technology (UTAUT2) is used to measure the user acceptance of social media. Using partial least square structural equation modelling, intrinsic religiosity (ROS), and privacy concerns along with technology acceptance are shown to influence the use of social media. The results show that religion has an indirect effect on the use of social media through privacy concerns and technology acceptance. The results also show that the model can predict the effect of intrinsic religiosity on the use of social media to share and disclose information. The implications from this study are significant both for policy and practice for social media companies as well as users. Information from this study will help social media companies to maximize users’ involvement with social media. It will also benefit the industry and the literature by providing a sound model that can measure the impact of religion on the behaviour of users