1,725 research outputs found

    Polanski and Perception

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    Filmmaker Roman Polanski declares in his autobiography that he was greatly influenced by renowned neuropsychologist Richard L. Gregory (1923-2010), whose work, Polanski claims, gave scientific confirmation to many of his own beliefs regarding the nature of perception. Gregory was a strong advocate for what is referred to as the ‚Äėindirect‚Äô theory of perception, a theoretical model that stresses the agency of cognition, specifically hypothesisation, in the act of perceiving. This analysis of Polanski‚Äôs cinema is guided by an exploration of perceptual psychology, with special attention paid to how the theory of indirect perception differs from competing, and often more intuitive, models of perception. The two main focuses of this thesis are: a) to identify the ways in which Polanski‚Äôs cinematography is actively informed by neuropsychological research on perception, and b) to discuss the various ways in which the key philosophical implications of the theory of indirect perception find expression in his cinema. My analysis will focus primarily on two (unofficial) ‚Äėtrilogies‚Äô, what I refer to as the ‚ÄėApartment Trilogy‚Äô of Repulsion (1965), Rosemary‚Äôs Baby (1968), and The Tenant (1976), and the ‚ÄėInvestigation Trilogy‚Äô of Chinatown (1974), Frantic (1988) and The Ninth Gate (1999). Also included are minor case studies of Knife in the Water (1962), Death and the Maiden (1994), and The Ghost (2010). This thesis hopes to demonstrate the manner in which Polanski‚Äôs cinematic engagement with perceptual psychology evolves over his career, from more psychologically intimate explorations of the perceptual mechanism via portrayals of schizophrenia in his earlier films, to more distant studies of highly proficient perceiving bodies who are nevertheless confronted with serious challenges to their perceptual (and epistemological) frameworks.AHR

    On the Security and Privacy Challenges in Android-based Environments

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    In the last decade, we have faced the rise of mobile devices as a fundamental tool in our everyday life. Currently, there are above 6 billion smartphones, and 72% of them are Android devices. The functionalities of smartphones are enriched by mobile apps through which users can perform operations that in the past have been made possible only on desktop/laptop computing. Besides, users heavily rely on them for storing even the most sensitive information from a privacy point of view. However, apps often do not satisfy all minimum security requirements and can be targeted to indirectly attack other devices managed or connected to them (e.g., IoT nodes) that may perform sensitive operations such as health checks, control a smart car or open a smart lock. This thesis discusses some research activities carried out to enhance the security and privacy of mobile apps by i) proposing novel techniques to detect and mitigate security vulnerabilities and privacy issues, and ii) defining techniques devoted to the security evaluation of apps interacting with complex environments (e.g., mobile-IoT-Cloud). In the first part of this thesis, I focused on the security and privacy of Mobile Apps. Due to the widespread adoption of mobile apps, it is relatively straightforward for researchers or users to quickly retrieve the app that matches their tastes, as Google provides a reliable search engine. However, it is likewise almost impossible to select apps according to a security footprint (e.g., all apps that enforce SSL pinning). To overcome this limitation, I present APPregator, a platform that allows users to select apps according to a specific security footprint. This tool aims to implement state-of-the-art static and dynamic analysis techniques for mobile apps and provide security researchers and analysts with a tool that makes it possible to search for mobile applications under specific functional or security requirements. Regarding the security status of apps, I studied a particular context of mobile apps: hybrid apps composed of web technologies and native technologies (i.e., Java or Kotlin). In this context, I studied a vulnerability that affected only hybrid apps: the Frame Confusion. This vulnerability, despite being discovered several years ago, it is still very widespread. I proposed a methodology implemented in FCDroid that exploits static and dynamic analysis techniques to detect and trigger the vulnerability automatically. The results of an extensive analysis carried out through FCDroid on a set of the most downloaded apps from the Google Play Store prove that 6.63% (i.e., 1637/24675) of hybrid apps are potentially vulnerable to Frame Confusion. A side effect of the analysis I carried out through APPregator was suggesting that very few apps may have a privacy policy, despite Google Play Store imposes some strict rules about it and contained in the Google Play Privacy Guidelines. To empirically verify if that was the case, I proposed a methodology based on the combination of static analysis, dynamic analysis, and machine learning techniques. The proposed methodology verifies whether each app contains a privacy policy compliant with the Google Play Privacy Guidelines, and if the app accesses privacy-sensitive information only upon the acceptance of the policy by the user. I then implemented the methodology in a tool, 3PDroid, and evaluated a number of recent and most downloaded Android apps in the Google Play Store. Experimental results suggest that over 95% of apps access sensitive user privacy information, but only a negligible subset of it (~ 1%) fully complies with the Google Play Privacy Guidelines. Furthermore, the obtained results have also suggested that the user privacy could be put at risk by mobile apps that keep collecting a plethora of information regarding the user's and the device behavior by relying on third-party analytics libraries. However, collecting and using such data raised several privacy concerns, mainly because the end-user - i.e., the actual data owner - is out of the loop in this collection process. The existing privacy-enhanced solutions that emerged in the last years follow an ``all or nothing" approach, leaving to the user the sole option to accept or completely deny access to privacy-related data. To overcome the current state-of-the-art limitations, I proposed a data anonymization methodology, called MobHide, that provides a compromise between the usefulness and privacy of the data collected and gives the user complete control over the sharing process. For evaluating the methodology, I implemented it in a prototype called HideDroid and tested it on 4500 most-used Android apps of the Google Play Store between November 2020 and January 2021. In the second part of this thesis, I extended privacy and security considerations outside the boundary of the single mobile device. In particular, I focused on two scenarios. The first is composed of an IoT device and a mobile app that have a fruitful integration to resolve and perform specific actions. From a security standpoint, this leads to a novel and unprecedented attack surface. To deal with such threats, applying state-of-the-art security analysis techniques on each paradigm can be insufficient. I claimed that novel analysis methodologies able to systematically analyze the ecosystem as a whole must be put forward. To this aim, I introduced the idea of APPIoTTe, a novel approach to the security testing of Mobile-IoT hybrid ecosystems, as well as some notes on its implementation working on Android (Mobile) and Android Things (IoT) applications. The second scenario is composed of an IoT device widespread in the Smart Home environment: the Smart Speaker. Smart speakers are used to retrieving information, interacting with other devices, and commanding various IoT nodes. To this aim, smart speakers typically take advantage of cloud architectures: vocal commands of the user are sampled, sent through the Internet to be processed, and transmitted back for local execution, e.g., to activate an IoT device. Unfortunately, even if privacy and security are enforced through state-of-the-art encryption mechanisms, the features of the encrypted traffic, such as the throughput, the size of protocol data units, or the IP addresses, can leak critical information about the users' habits. In this perspective, I showcase this kind of risk by exploiting machine learning techniques to develop black-box models to classify traffic and implement privacy leaking attacks automatically

    Quality in point of care testing

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    Part of this document has been endorsed as a Position Statement on Point of Care testing (in-hospital setting) of the Italian Society of Laboratory Medicine (Società Italiana di Medicina di Laboratorio, SIMeL) and also refers to official documents and International standards to for generalities (ISO 15189/2003) and specific items (ISO 22870/2006). As such, this article is based on to professional standards, guidelines and peer reviews documents, and it is aimed to improve the pre-analytical, analytical and post-analytical phase of point of care testing (POCT), by providing insights into definitions, key aspects in developing a diagnostic system for POCT, benefits and risks of POCT and leading sources of errors

    Interaction and coherence of a plasmon-exciton polariton condensate

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    Polaritons are quasiparticles arising from the strong coupling of electromagnetic waves in cavities and dipolar oscillations in a material medium. In this framework, localized surface plasmon in metallic nanoparticles defining optical nanocavities have attracted increasing interests in the last decade. This interest results from their sub-diffraction mode volume, which offers access to extremely high photonic densities by exploiting strong scattering cross-sections. However, high absorption losses in metals have hindered the observation of collective coherent phenomena, such as condensation. In this work we demonstrate the formation of a non-equilibrium room temperature plasmon-exciton-polariton condensate with a long range spatial coherence, extending a hundred of microns, well over the excitation area, by coupling Frenkel excitons in organic molecules to a multipolar mode in a lattice of plasmonic nanoparticles. Time-resolved experiments evidence the picosecond dynamics of the condensate and a sizeable blueshift, thus measuring for the first time the effect of polariton interactions in plasmonic cavities. Our results pave the way to the observation of room temperature superfluidity and novel nonlinear phenomena in plasmonic systems, challenging the common belief that absorption losses in metals prevent the realization of macroscopic quantum states.Comment: 23 pages, 5 figures, SI 7 pages, 5 figure

    Genetical Swarm Optimization of Multihop Routes in Wireless Sensor Networks

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    In recent years, wireless sensor networks have been attracting considerable research attention for a wide range of applications, but they still present significant network communication challenges, involving essentially the use of large numbers of resource-constrained nodes operating unattended and exposed to potential local failures. In order to maximize the network lifespan, in this paper, genetical swarm optimization (GSO) is applied, a class of hybrid evolutionary techniques developed in order to exploit in the most effective way the uniqueness and peculiarities of two classical optimization approaches; particle swarm optimization (PSO) and genetic algorithms (GA). This procedure is here implemented to optimize the communication energy consumption in a wireless network by selecting the optimal multihop routing schemes, with a suitable hybridization of different routing criteria, confirming itself as a flexible and useful tool for engineering applications

    Wettability conversion of colloidal TiO2 nanocrystal thin films with UV-switchable hydrophilicity

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    Under pulsed laser UV irradiation, thin-film coatings made of close-packed TiO2 nanorods individually coated with surfactants can exhibit a temporary increase in their degree of surface hydroxylation without any apparent photocatalytic removal of the capping molecules. This mechanism provides a basis for achieving light-driven conversion from a highly hydrophobic to a highly hydrophilic, metastable state, followed by extremely slow recovery of the original conditions under dark ambient environment. A deeper insight into the wetting dynamics is gained by time-dependent water contact-angle and infrared spectroscopy monitoring of the film properties under different post-UV storage conditions. Our study reveals that, for reversible switchability between extreme wettability excursions and long-term repeatability of such changes to be achieved, specific modifications in the polar and nonpolar components of the TiO2 films need to be guaranteed along with preservation of the original geometric arrangement of the nanocrystal building blocks. The application of moderate vacuum is found to be an effective method for accelerating the post-UV hydrophilic-to-hydrophobic conversion, thereby enabling fast and cyclic hydrophilization/hydrophobicization alternation without any detrimental signs of significant fatigue

    Integration of capillary and EWOD technologies for autonomous and low-power consumption micro-analytical systems

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    This work presents a miniaturized system combining, on the same microfluidic chip, capillarity and electrowetting-on-dielectric (EWOD) techniques for movement and control of fluids. The change in hydrophobicity occurring at the edge between a capillary channel and a hydrophobic layer is successfully exploited as a stop-and-go valve, whose operation is electronically controlled through the EWOD electrodes. Taking into account the variety of microfluidic operation resulting from the combination of the two handling techniques and their characteristic features, this work prompts the development of autonomous, compact and low-power consumption lab-on-chip systems

    A robotic arm for safe and accurate control of biomedical equipment during COVID-19

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    Purpose Hospital facilities and social life, along with the global economy, have been severely challenged by COVID-19 since the World Health Organization (WHO) declared it a pandemic in March 2020. Since then, countless ordinary citizens, as well as healthcare workers, have contracted the virus by just coming into contact with infected surfaces. In order to minimise the risk of getting infected by contact with such surfaces, our study aims to design, prototype, and test a new device able to connect users, such as common citizens, doctors or paramedics, with either common-use interfaces (e.g., lift and snack machine keyboards, trafc light push-buttons) or medical-use interfaces (e.g., any medical equipment keypad) Method To this purpose, the device was designed with the help of Unifed Modelling Language (UML) schemes, and was informed by a risk analysis, that highlighted some of its essential requirements and specifcations. Consequently, the chosen constructive solution of the robotic system, i.e., a robotic-arm structure, was designed and manufactured using computeraided design and 3D printing. Result The fnal prototype included a properly programmed micro-controller, linked via Bluetooth to a multi-platform mobile phone app, which represents the user interface. The system was then successfully tested on diferent physical keypads and touch screens. Better performance of the system can be foreseen by introducing improvements in the industrial production phase. Conclusion This frst prototype paves the way for further research in this area, allowing for better management and preparedness of next pandemic emergencies. © 2023, The Author(s)
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