Multiclass Adaboost Based on an Ensemble of Binary Adaboosts

This paper presents a multi-class AdaBoost based on incorporating an ensemble of binary AdaBoosts which is organized as Binary Decision Tree (BDT). It is proved that binary AdaBoost is extremely successful in producing accurate classification but it does not perform very well for multi-class problems. To avoid this performance degradation, the multi-class problem is divided into a number of binary problems and binary AdaBoost classifiers are invoked to solve these classification problems. This approach is tested with a dataset consisting of 6500 binary images of traffic signs. Haar-like features of these images are computed and the multi-class AdaBoost classifier is invoked to classify them. A classification rate of 96.7% and 95.7% is achieved for the traffic sign boarders and pictograms, respectively. The proposed approach is also evaluated using a number of standard datasets such as Iris, Wine, Yeast, etc. The performance of the proposed BDT classifier is quite high as compared with the state of the art and it converges very fast to a solution which indicates it as a reliable classifier.

User Behavioral Modeling of Web-based Systems for Continuous User Authentication

Authentication plays an important role in how we interact with computers, mobile devices, the web, etc. The idea of authentication is to uniquely identify a user before granting access to system privileges. For example, in recent years more corporate information and applications have been accessible via the Internet and Intranet. Many employees are working from remote locations and need access to secure corporate files. During this time, it is possible for malicious or unauthorized users to gain access to the system. For this reason, it is logical to have some mechanism in place to detect whether the logged-in user is the same user in control of the user's session. Therefore, highly secure authentication methods must be used. We posit that each of us is unique in our use of computer systems. It is this uniqueness that is leveraged to "continuously authenticate users" while they use web software. To monitor user behavior, n-gram models are used to capture user interactions with web-based software. This statistical language model essentially captures sequences and sub-sequences of user actions, their orderings, and temporal relationships that make them unique by providing a model of how each user typically behaves. Users are then continuously monitored during software operations. Large deviations from "normal behavior" can possibly indicate malicious or unintended behavior. This approach is implemented in a system called Intruder Detector (ID) that models user actions as embodied in web logs generated in response to a user's actions. User identification through web logs is cost-effective and non-intrusive. We perform experiments on a large fielded system with web logs of approximately 4000 users. For these experiments, we use two classification techniques; binary and multi-class classification. We evaluate model-specific differences of user behavior based on coarse-grain (i.e., role) and fine-grain (i.e., individual) analysis. A specific set of metrics are used to provide valuable insight into how each model performs. Intruder Detector achieves accurate results when identifying legitimate users and user types. This tool is also able to detect outliers in role-based user behavior with optimal performance. In addition to web applications, this continuous monitoring technique can be used with other user-based systems such as mobile devices and the analysis of network traffic.

The dehydrogenation reactions between LiH and organic amines for solid state hydrogen storage systems

Hydrogen is considered as an appealing alternative to fossil fuels in the pursuit of sustainable, secure and prosperous growth in the UK and abroad. However there exists a persisting bottleneck in the effective storage of hydrogen for mobile applications in order to facilitate a wide implementation of hydrogen fuel cells in the fossil fuel dependent transportation industry. To address this issue, new means of solid state chemical hydrogen storage are proposed in this thesis. This involves the coupling of LiH with three different organic amines: melamine, urea and dicyandiamide. In principle, thermodynamically favourable hydrogen release from these systems proceeds via the deprotonation of the protic N-H moieties by the hydridic metal hydride. Simultaneously hydrogen kinetics is expected to be enhanced over heavier hydrides by incorporating lithium ions in the proposed binary hydrogen storage systems. Whilst the concept has been successfully demonstrated by the results obtained in this work, it was observed that optimising the ball milling conditions is central in promoting hydrogen desorption in the proposed systems. The theoretical amount of 6.97 wt% by dry mass of hydrogen was released when heating a ball milled mixture of LiH and melamine (6:1 stoichiometry) to 320 °C. It was observed that ball milling introduces a disruption in the intermolecular hydrogen bonding network that exists in pristine melamine. This effect extends to a molecular level electron redistribution observed as a function of shifting IR bands. It was postulated that stable phases form during the first stages of dehydrogenation which contain the triazine skeleton. Dehydrogenation of this system yields a solid product Li2NCN, which has been rehydrogenated back to melamine via hydrolysis under weak acidic conditions. On the other hand, the LiH and urea system (4:1 stoichiometry) desorbed approximately 5.8 wt% of hydrogen, from the theoretical capacity of 8.78 wt% (dry mass), by 270 °C accompanied by undesirable ammonia and trace amount of water release. The thermal dehydrogenation proceeds via the formation of Li(HN(CO)NH2) at 104.5 °C; which then decomposes to LiOCN and unidentified phases containing C-N moieties by 230 °C. The final products are Li2NCN and Li2O (270 °C) with LiCN and Li2CO3 also detected under certain conditions. It was observed that ball milling can effectively supress ammonia formation. Furthermore results obtained from energetic ball milling experiments have indicated that the barrier to full dehydrogenation between LiH and urea is principally kinetic. Finally the dehydrogenation reaction between LiH and dicyandiamide system (4:1 stoichiometry) occurs through two distinct pathways dependent on the ball milling conditions. When ball milled at 450 RPM for 1 h, dehydrogenation proceeds alongside dicyandiamide condensation by 400 °C whilst at a slower milling speed of 400 RPM for 6h, decomposition occurs via a rapid gas desorption (H2 and NH3) at 85 °C accompanied by sample foaming. The reactant dicyandiamide can be generated by hydrolysis using the product Li2NCN.

On the zeros of the Abelian integrals for a class of Liénard systems

A planar polynomial differential system has a finite number of limit cycles. However, finding the upper bound of the number of limit cycles is an open problem for the general nonlinear dynamical systems. In this paper, we investigated a class of Liénard systems of the form x'=y, y'=f(x)+y g(x) with deg f=5 and deg g=4. We proved that the related elliptic integrals of the Liénard systems have at most three zeros including multiple zeros, which implies that the number of limit cycles bifurcated from the periodic orbits of the unperturbed system is less than or equal to 3.