Fine-grain circuit hardening through VHDL datatype substitution

Radiation effects can induce, amongst other phenomena, logic errors in digital circuits and systems. These logic errors corrupt the states of the internal memory elements of the circuits and can propagate to the primary outputs, affecting other onboard systems. In order to avoid this, Triple Modular Redundancy is typically used when full robustness against these phenomena is needed. When full triplication of the complete design is not required, selective hardening can be applied to the elements in which a radiation-induced upset is more likely to propagate to the main outputs of the circuit. The present paper describes a new approach for selectively hardening digital electronic circuits by design, which can be applied to digital designs described in the VHDL Hardware Description Language. When the designer changes the datatype of a signal or port to a hardened type, the necessary redundancy is automatically inserted. The automatically hardening features have been compiled into a VHDL package, and have been validated both in simulation and by means of fault injection.Ministerio de Economía y Competitividad ESP2015-68245-C4-2-PComisión Europea ID 687220

LPsec: a fast and secure cryptographic system for optical connections

High capacity and low latency of optical connections are ideal for supporting current and future communication services, including 5G and beyond. Although some of those services are already secured at the packet layer using standard stream ciphers, like the Advanced Encryption Standard and ChaCha, secure transmission at the optical layer is still not implemented. To secure the optical layer, cryptographic methods need to be fast enough to support high-speed optical transmission and cannot introduce significant delay. Moreover, methods for key exchange, key generation, and key expansion are required, which can be implemented on standard coherent transponders. In this paper, we propose Light Path SECurity (LPsec), a secure cryptographic solution for optical connections that involves fast data encryption using stream ciphers and key exchange using Diffie–Hellman protocol through the optical channel. To support encryption of high-speed data streams, a fast, general-purpose pseudorandom number generator is used. Moreover, to make the scheme more secure against exhaustive search attacks, an additional substitution cipher is proposed. In contrast to the limited encryption speeds that standard stream ciphers can support, LPsec can support high-speed rates. Numerical simulation for 16 quadrature amplitude modulation (QAM), 32-QAM, and 64-QAM show that LPsec provides a sufficient security level while introducing only negligible delay.H2020 Industrial Leadership [H2020 B5G-OPEN (101016663)]; H2020 Marie Skłodowska-Curie Actions [REALNET (813144)]; Agencia Estatal de Investigación [IBON (PID2020- 114135RB-I00)]; Institució Catalana de Recerca i Estudis Avançats.Peer ReviewedPostprint (author's final draft

Evidence-based Development of Trustworthy Mobile Medical Apps

abstract: Widespread adoption of smartphone based Mobile Medical Apps (MMAs) is opening new avenues for innovation, bringing MMAs to the forefront of low cost healthcare delivery. These apps often control human physiology and work on sensitive data. Thus it is necessary to have evidences of their trustworthiness i.e. maintaining privacy of health data, long term operation of wearable sensors and ensuring no harm to the user before actual marketing. Traditionally, clinical studies are used to validate the trustworthiness of medical systems. However, they can take long time and could potentially harm the user. Such evidences can be generated using simulations and mathematical analysis. These methods involve estimating the MMA interactions with human physiology. However, the nonlinear nature of human physiology makes the estimation challenging. This research analyzes and develops MMA software while considering its interactions with human physiology to assure trustworthiness. A novel app development methodology is used to objectively evaluate trustworthiness of a MMA by generating evidences using automatic techniques. It involves developing the Health-Dev β tool to generate a) evidences of trustworthiness of MMAs and b) requirements assured code generation for vulnerable components of the MMA without hindering the app development process. In this method, all requests from MMAs pass through a trustworthy entity, Trustworthy Data Manager which checks if the app request satisfies the MMA requirements. This method is intended to expedite the design to marketing process of MMAs. The objectives of this research is to develop models, tools and theory for evidence generation and can be divided into the following themes: • Sustainable design configuration estimation of MMAs: Developing an optimization framework which can generate sustainable and safe sensor configuration while considering interactions of the MMA with the environment. • Evidence generation using simulation and formal methods: Developing models and tools to verify safety properties of the MMA design to ensure no harm to the human physiology. • Automatic code generation for MMAs: Investigating methods for automatically • Performance analysis of trustworthy data manager: Evaluating response time generating trustworthy software for vulnerable components of a MMA and evidences.performance of trustworthy data manager under interactions from non-MMA smartphone apps.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Efficient PID Controller based Hexapod Wall Following Robot

This paper presents a design of wall following behaviour for hexapod robot based on PID controller. PID controller is proposed here because of its ability to control many cases of non-linear systems. In this case, we proposed a PID controller to improve the speed and stability of hexapod robot movement while following the wall. In this paper, PID controller is used to control the robot legs, by adjusting the value of swing angle during forward or backward movement to maintain the distance between the robot and the wall. The experimental result was verified by implementing the proposed control method into actual prototype of hexapod robot

Evidence for public health on novel psychoactive substance use: a mixed-methods study

Background: Novel psychoactive substances (NPSs) contribute to the public health impact of substance misuse. This report provides research evidence addressing 11 research questions related to NPSs, covering types, patterns and settings of use; supply sources; and implications for policy and practice. Methods: The study used a conceptually linked three-phase mixed-methods design with a shared conceptual framework based on multiple-context risk and protective factors. Phase 1 was a quantitative phase involving secondary data analysis of the longitudinal Belfast Youth Development Study (BYDS), a latent class analysis using the 2039 BYDS participants. Phase 2 was an extensive qualitative analysis via narrative interviews with participants, sampled from BYDS, drug/alcohol services and prisons, to explore NPS use trajectories. Phase 3 was the final quantitative phase; generalisability of the shared risk factor part of the model was tested using the manual three-step approach to examine risk factors associated with latent class membership. The quantitative and qualitative analyses were integrated, thus allowing emerging findings to be further explored. Results: The data suggest that NPSs have a place within a range of polydrug use trajectories. Models showed no distinctive NPS class, with no clear evidence of differential risks for NPS use compared with the use of other substances. From the qualitative analysis, a taxonomy of groups was derived that explored how and where NPSs featured in a range of trajectories. This taxonomy was used to structure the analysis of factors linked to use within a risk and protective framework. Drivers for use were considered alongside knowledge, perceptions and experience of harms. Suggestions about how interventions could best respond to the various patterns of use – with special consideration of synthetic cannabinoids (SCs), including how they relate to the use of heroin and the potential for NPSs to operate as a ‘snare’ to more problem use – were also presented. Limitations: The study was conducted during 2016/17; generalisability beyond this sample and time point is limited. The level of missing data for some of the BYDS analysis was a limitation, as was the fact that the BYDS data were collected in 2011, so in a different context from the data collected during the narrative interviews. The Psychoactive Substances Act 2016 (Great Britain. Psychoactive Substances Act 2016. London: The Stationery Office; 2016) came into force during qualitative fieldwork and, although not particularly influential in this study, may be influential in future work. It is acknowledged that many of the data related to SCs and mephedrone. Although drug use was measured by self-report, the strength of rapport within interviews, reflective diaries and methodological acceptability checks helped to mitigate self-report bias. Conclusions: NPSs continue to present significant challenges for legislation and monitoring, researching and developing interventions. Understanding of usage patterns remains poor, with most information based on populations and settings where problems have already occurred. This research contributes to the evidence base by providing much needed further empirical data on the lived experiences of NPS users across a range of settings. In the light of these data, implications for policy and practice are discussed. Future work: Future research must generate improved epidemiological data on the extent, patterns and motivations for use longitudinally. The uniqueness of the information concerning SC use points to a specific set of findings not evidenced in other literature (e.g. intensity of SC withdrawal). Future research should focus on the symbiotic link between SC and heroin use

Using machine learning techniques to create AI controlled players for video games

This study aims to achieve higher replay and entertainment value in a game through human-like AI behaviour in computer controlled characters called bats. In order to achieve that, an artificial intelligence system capable of learning from observation of human player play was developed. The artificial intelligence system makes use of machine learning capabilities to control the state change mechanism of the bot. The implemented system was tested by an audience of gamers and compared against bats controlled by static scripts. The data collected was focused on qualitative aspects of replay and entertainment value of the game and subjected to quantitative analysi

HCC Architecture - Hormonal Communications and Control Architecture

This thesis aims to provide a novel framework for a multiagent system implementation. The major feature of the proposed architecture is the introduction of the biological concept of hormones. The hormones are passed via the communication network to convey limited global system state knowledge. The agents\u27 response to a hormone is interpreted depending on its own local agent state. The primary focus of this thesis is the development of the particulars of the architecture. Prior work of multiagent systems research is reviewed and studied for contributions. Biological studies of hormones are employed to draw out interaction rules and analyze control mechanisms in a biological organism. The hormonal communication and control architecture is constructed, with major components detailed by flowcharts. The proposal is tested with two simulations: A minesweeping problem that has been modeled by other models, and an application of the architecture to a hypothetical ant colony. Research on biological ants is presented to suggest the behavior and goals of a model configured to employ the HCC architecture. The model is fleshed out, and the decisions made by considerations to the architecture are explained. The implementation of the simulation programming with the SWARM programming libraries for the Objective-C language is discussed. The data from experimental runs are analyzed with attention to global action