Formation of Polycyclic Aromatic Hydrocarbons and Nitrogen Containing Polycyclic Aromatic Compounds in Titan's Atmosphere, the Interstellar Medium and Combustion

Several different mechanisms leading to the formation of (substituted) naphthalene and azanaphthalenes were examined using theoretical quantum chemical calculations. As a result, a series of novel synthetic routes to Polycyclic Aromatic Hydrocarbons (PAHs) and Nitrogen Containing Polycyclic Aromatic Compounds (N-PACs) have been proposed. On Earth, these aromatic compounds originate from incomplete combustion and are released into our environment, where they are known to be major pollutants, often with carcinogenic properties. In the atmosphere of a Saturn's moon Titan, these PAH and N-PACs are believed to play a critical role in organic haze formation, as well as acting as chemical precursors to biologically relevant molecules. The theoretical calculations were performed by employing the ab initio G3(MP2,CC)/B3LYP/6-311G** method to effectively probe the Potential Energy Surfaces (PES) relevant to the PAH and N-PAC formation. Following the construction of the PES, Rice-Ramsperger-Kassel-Markus (RRKM) theory was used to evaluate all unimolecular rate constants as a function of collision energy under single-collision conditions. Branching ratios were then evaluated by solving phenomenological rate expressions for the various product concentrations. The most viable pathways to PAH and N-PAC formation were found to be those where the initial attack by the ethynyl (C2H) or cyano (CN) radical toward a unsaturated hydrocarbon molecule led to the formation of an intermediate which could not effectively lose a hydrogen atom. It is not until ring cyclization has occurred, that hydrogen elimination leads to a closed shell product. By quenching the possibility of the initial hydrogen atom elimination, one of the most competitive processes preventing the PAH or N-PAC formation was avoided, and the PAH or N-PAC formation was allowed to proceed. It is concluded that these considerations should be taken into account when attempting to explore any other potential routes towards aromatic compounds in cold environments, such as on Titan or in the interstellar medium.

Cooperative routing for collision minimization in wireless sensor networks

Cooperative communication has gained much interest due to its ability to exploit the broadcasting nature of the wireless medium to mitigate multipath fading. There has been considerable amount of research on how cooperative transmission can improve the performance of the network by focusing on the physical layer issues. During the past few years, the researchers have started to take into consideration cooperative transmission in routing and there has been a growing interest in designing and evaluating cooperative routing protocols. Most of the existing cooperative routing algorithms are designed to reduce the energy consumption; however, packet collision minimization using cooperative routing has not been addressed yet. This dissertation presents an optimization framework to minimize collision probability using cooperative routing in wireless sensor networks. More specifically, we develop a mathematical model and formulate the problem as a large-scale Mixed Integer Non-Linear Programming problem. We also propose a solution based on the branch and bound algorithm augmented with reducing the search space (branch and bound space reduction). The proposed strategy builds up the optimal routes from each source to the sink node by providing the best set of hops in each route, the best set of relays, and the optimal power allocation for the cooperative transmission links. To reduce the computational complexity, we propose two near optimal cooperative routing algorithms. In the first near optimal algorithm, we solve the problem by decoupling the optimal power allocation scheme from optimal route selection. Therefore, the problem is formulated by an Integer Non-Linear Programming, which is solved using a branch and bound space reduced method. In the second near optimal algorithm, the cooperative routing problem is solved by decoupling the transmission power and the relay node se- lection from the route selection. After solving the routing problems, the power allocation is applied in the selected route. Simulation results show the algorithms can significantly reduce the collision probability compared with existing cooperative routing schemes.

Mitigate DoS and DDoS Attack in Ad Hoc Networks

This paper proposes a technique to defeat Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks in Ad Hoc Networks. The technique is divided into two main parts and with game theory and cryptographic puzzles. Introduced first is a new client puzzle to prevent DoS attacks in such networks. The second part presents a multiplayer game that takes place between the nodes of an ad hoc network and based on fundamental principles of game theory. By combining computational problems with puzzles, improvement occurs in the efficiency and latency of the communicating nodes and resistance in DoS and DDoS attacks. Experimental results show the effectiveness of the approach for devices with limited resources and for environments like ad hoc networks where nodes must exchange information quickly.

Multiple robots formation manoeuvring and collision avoidance strategy

This paper presents a multiple robots formation manoeuvring and its collision avoidance strategy. The direction priority sequential selection algorithm is employed to achieve the raw path, and a new algorithm is then proposed to calculate the turning compliant waypoints supporting the multi-robot formation manoeuvre. The collision avoidance strategy based on the formation control is presented to translate the collision avoidance problem into the stability problem of the formation. The extension-decomposition-aggregation scheme is next applied to solve the formation control problem and subsequently achieve the collision avoidance during the formation manoeuvre. Simulation study finally shows that the collision avoidance problem can be conveniently solved if the stability of the constructed formation including unidentified objects can be satisfied.

High resolution numerical simulation of triple point collision and origin of unburned gas pockets in turbulent detonations

A key issue in pulse detonation engine development is better understanding of the detonation structure and its propagation mechanism. Thus, in the present work the turbulent structure of an irregular detonation is studied through very high resolution numerical simulations of 600 points per half reaction length. The aim is to explore the nature of the transverse waves during the collision and reflection processes of the triple point with the channel walls. Consequently the formation and consumption mechanism of unreacted gas pockets is studied. Results show that the triple point and the transverse wave collide simultaneously with the wall. The strong transverse wave switches from a primary triple point before collision to a new one after reflection. Due to simultaneous interaction of the triple point and the transverse wave with the wall in the second half of the detonation cell, a larger high-pressurised region appears on the wall. During the reflection the reaction zone detaches from the shock front and produces a pocket of unburned gas. Three mechanisms found to be of significance in the re-initiation mechanism of detonation at the end of the detonation cell; i: energy resealed via consumption of unburned pockets by turbulent mixing ii: compression waves arise due to collision of the triple point on the wall which helps the shock to jump abruptly to an overdriven detonation iii: drastic growth of the Richtmyer–Meshkov instability causing a part of the front to accelerate with respect to the neighbouring portions.

Oceans Deep: Lesson B (Shark Attack)

Teacher resources for Lesson B in the Discover Oceanography 'Scheme of Work' for use in schools.

Sviluppo e sperimentazione di un sistema "obstacle detection & collision avoidance" per velivoli multirotori

Il lavoro di tesi svolto riguarda lo sviluppo e la sperimentazione di un primo prototipo di sistema per l’obstacle detection e collision avoidance, capace di identificare un ostacolo e inibire i comandi del pilota in modo da evitare collisioni.

Attack simulation based software protection assessment method

Software protection is an essential aspect of information security to withstand malicious activities on software, and preserving software assets. However, software developers still lacks a methodology for the assessment of the deployed protections. To solve these issues, we present a novel attack simulation based software protection assessment method to assess and compare various protection solutions. Our solution relies on Petri Nets to specify and visualize attack models, and we developed a Monte Carlo based approach to simulate attacking processes and to deal with uncertainty. Then, based on this simulation and estimation, a novel protection comparison model is proposed to compare different protection solutions. Lastly, our attack simulation based software protection assessment method is presented. We illustrate our method by means of a software protection assessment process to demonstrate that our approach can provide a suitable software protection assessment for developers and software companies.

Mesure de sections efficaces absolues vibrationnelles pour la collision d’électrons de basse énergie (1-19 eV) avec le tétrahydrofurane (THF) condensé

Résumé: Ce mémoire de maîtrise est une étude des probabilités d’interactions (sections efficaces) des électrons de basse énergie avec une molécule d’intérêt biologique. Cette molécule est le tétrahydrofurane (THF) qui est un bon modèle de la molécule constituant la colonne vertébrale de l’ADN; le désoxyribose. Étant donné la grande quantité d’électrons secondaires libérés lors du passage des radiations à travers la matière biologique et sachant que ceux-ci déposent la majorité de l’énergie, l’étude de leurs interactions avec les molécules constituant l’ADN devient rapidement d’une grande importance. Les mesures de sections efficaces sont faites à l’aide d’un spectromètre à haute résolution de pertes d’énergie de l’électron. Les spectres de pertes d’énergie de l’électron obtenus de cet appareil permettent de calculer les valeurs de sections efficaces pour chaque vibration en fonction de l’énergie incidente de l’électron. L’article présenté dans ce mémoire traite de ces mesures et des résultats. En effet, il présente et explique en détail les conditions expérimentales, il décrit la méthode de déconvolution qui est utilisée pour obtenir les valeurs de sections efficaces et il présente et discute des 4 résonances observées dans la dépendance en énergie des sections efficaces. En effet, cette étude a permis de localiser en énergie 4 résonances et celles-ci ont toutes été confirmées par des recherches expérimentales et théoriques antérieures sur le sujet des collisions électrons lents-THF. En outre, jamais ces résonances n’avaient été observées simultanément dans une même étude et jamais la résonance trouvée à basse énergie n’avait été observée avec autant d’intensité que cette présente étude. Cette étude a donc permis de raffiner notre compréhension fondamentale des processus résonants impliqués lors de collisions d’électrons secondaires avec le THF. Les valeurs de sections efficaces sont, quant à elles, très prisées par les théoriciens et sont nécessaires pour les simulations Monte Carlo pour prédire, par exemple, le nombre d’ions formées après le passage des radiations. Ces valeurs pourront justement être utilisées dans les modèles de distribution et dépôt d’énergie au niveau nanoscopique dans les milieux biologiques et ceux-ci pourront éventuellement améliorer l’efficacité des modalités radiothérapeutiques.

Analysis of Automotive Cybersecurity - Attack surfaces and users’ privacy concerns

Modern automobiles are no longer just mechanical tools. The electronics and computing services they are shipping with are making them not less than a computer. They are massive kinetic devices with sophisticated computing power. Most of the modern vehicles are made with the added connectivity in mind which may be vulnerable to outside attack. Researchers have shown that it is possible to infiltrate into a vehicle’s internal system remotely and control the physical entities such as steering and brakes. It is quite possible to experience such attacks on a moving vehicle and unable to use the controls. These massive connected computers can be life threatening as they are related to everyday lifestyle. First part of this research studied the attack surfaces in the automotive cybersecurity domain. It also illustrated the attack methods and capabilities of the damages. Online survey has been deployed as data collection tool to learn about the consumers’ usage of such vulnerable automotive services. The second part of the research portrayed the consumers’ privacy in automotive world. It has been found that almost hundred percent of modern vehicles has the capabilities to send vehicle diagnostic data as well as user generated data to their manufacturers, and almost thirty five percent automotive companies are collecting them already. Internet privacy has been studies before in many related domain but no privacy scale were matched for automotive consumers. It created the research gap and motivation for this thesis. A study has been performed to use well established consumers privacy scale – IUIPC to match with the automotive consumers’ privacy situation. Hypotheses were developed based on the IUIPC model for internet consumers’ privacy and they were studied by the finding from the data collection methods. Based on the key findings of the research, all the hypotheses were accepted and hence it is found that automotive consumers’ privacy did follow the IUIPC model under certain conditions. It is also found that a majority of automotive consumers use the services and devices that are vulnerable and prone to cyber-attacks. It is also established that there is a market for automotive cybersecurity services and consumers are willing to pay certain fees to avail that.

Applied web traffic analysis for numerical encoding of SQL Injection attack features.

SQL Injection Attack (SQLIA) remains a technique used by a computer network intruder to pilfer an organisation’s confidential data. This is done by an intruder re-crafting web form’s input and query strings used in web requests with malicious intent to compromise the security of an organisation’s confidential data stored at the back-end database. The database is the most valuable data source, and thus, intruders are unrelenting in constantly evolving new techniques to bypass the signature’s solutions currently provided in Web Application Firewalls (WAF) to mitigate SQLIA. There is therefore a need for an automated scalable methodology in the pre-processing of SQLIA features fit for a supervised learning model. However, obtaining a ready-made scalable dataset that is feature engineered with numerical attributes dataset items to train Artificial Neural Network (ANN) and Machine Leaning (ML) models is a known issue in applying artificial intelligence to effectively address ever evolving novel SQLIA signatures. This proposed approach applies numerical attributes encoding ontology to encode features (both legitimate web requests and SQLIA) to numerical data items as to extract scalable dataset for input to a supervised learning model in moving towards a ML SQLIA detection and prevention model. In numerical attributes encoding of features, the proposed model explores a hybrid of static and dynamic pattern matching by implementing a Non-Deterministic Finite Automaton (NFA). This combined with proxy and SQL parser Application Programming Interface (API) to intercept and parse web requests in transition to the back-end database. In developing a solution to address SQLIA, this model allows processed web requests at the proxy deemed to contain injected query string to be excluded from reaching the target back-end database. This paper is intended for evaluating the performance metrics of a dataset obtained by numerical encoding of features ontology in Microsoft Azure Machine Learning (MAML) studio using Two-Class Support Vector Machines (TCSVM) binary classifier. This methodology then forms the subject of the empirical evaluation.

Early analysis of fault-attack effects for cryptographic hardware

International audience