Sequential fusion of decisions from adaptive and random samples for controlled verification of errors

Fusion techniques have received considerable attention for achieving performance improvement with biometrics. While a multi-sample fusion architecture reduces false rejects, it also increases false accepts. This impact on performance also depends on the nature of subsequent attempts, i.e., random or adaptive. Expressions for error rates are presented and experimentally evaluated in this work by considering the multi-sample fusion architecture for text-dependent speaker verification using HMM based digit dependent speaker models. Analysis incorporating correlation modeling demonstrates that the use of adaptive samples improves overall fusion performance compared to randomly repeated samples. For a text dependent speaker verification system using digit strings, sequential decision fusion of seven instances with three random samples is shown to reduce the overall error of the verification system by 26% which can be further reduced by 6% for adaptive samples. This analysis novel in its treatment of random and adaptive multiple presentations within a sequential fused decision architecture, is also applicable to other biometric modalities such as finger prints and handwriting samples.

Sequential fusion of decisions with favorable dependence for controlled verification errors

Statistical dependence between classifier decisions is often shown to improve performance over statistically independent decisions. Though the solution for favourable dependence between two classifier decisions has been derived, the theoretical analysis for the general case of 'n' client and impostor decision fusion has not been presented before. This paper presents the expressions developed for favourable dependence of multi-instance and multi-sample fusion schemes that employ 'AND' and 'OR' rules. The expressions are experimentally evaluated by considering the proposed architecture for text-dependent speaker verification using HMM based digit dependent speaker models. The improvement in fusion performance is found to be higher when digit combinations with favourable client and impostor decisions are used for speaker verification. The total error rate of 20% for fusion of independent decisions is reduced to 2.1% for fusion of decisions that are favourable for both client and impostors. The expressions developed here are also applicable to other biometric modalities, such as finger prints and handwriting samples, for reliable identity verification.

A risk simulation framework for information infrastructure protection

Information communication and technology (ICT) systems are almost ubiquitous in the modern world. It is hard to identify any industry, or for that matter any part of society, that is not in some way dependent on these systems and their continued secure operation. Therefore the security of information infrastructures, both on an organisational and societal level, is of critical importance. Information security risk assessment is an essential part of ensuring that these systems are appropriately protected and positioned to deal with a rapidly changing threat environment. The complexity of these systems and their inter-dependencies however, introduces a similar complexity to the information security risk assessment task. This complexity suggests that information security risk assessment cannot, optimally, be undertaken manually. Information security risk assessment for individual components of the information infrastructure can be aided by the use of a software tool, a type of simulation, which concentrates on modelling failure rather than normal operational simulation. Avoiding the modelling of the operational system will once again reduce the level of complexity of the assessment task. The use of such a tool provides the opportunity to reuse information in many different ways by developing a repository of relevant information to aid in both risk assessment and management and governance and compliance activities. Widespread use of such a tool allows the opportunity for the risk models developed for individual information infrastructure components to be connected in order to develop a model of information security exposures across the entire information infrastructure. In this thesis conceptual and practical aspects of risk and its underlying epistemology are analysed to produce a model suitable for application to information security risk assessment. Based on this work prototype software has been developed to explore these concepts for information security risk assessment. Initial work has been carried out to investigate the use of this software for information security compliance and governance activities. Finally, an initial concept for extending the use of this approach across an information infrastructure is presented.

Numerical simulation of a new two-dimensional variable-order fractional percolation equation in non-homogeneous porous media

Percolation flow problems are discussed in many research fields, such as seepage hydraulics, groundwater hydraulics, groundwater dynamics and fluid dynamics in porous media. Many physical processes appear to exhibit fractional-order behavior that may vary with time, or space, or space and time. The theory of pseudodifferential operators and equations has been used to deal with this situation. In this paper we use a fractional Darcys law with variable order Riemann-Liouville fractional derivatives, this leads to a new variable-order fractional percolation equation. In this paper, a new two-dimensional variable-order fractional percolation equation is considered. A new implicit numerical method and an alternating direct method for the two-dimensional variable-order fractional model is proposed. Consistency, stability and convergence of the implicit finite difference method are established. Finally, some numerical examples are given. The numerical results demonstrate the effectiveness of the methods. This technique can be used to simulate a three-dimensional variable-order fractional percolation equation.

HMM triangle relative entropy concepts in sequential change detection applied to vision-based dim target manoeuvre detection

The quick detection of abrupt (unknown) parameter changes in an observed hidden Markov model (HMM) is important in several applications. Motivated by the recent application of relative entropy concepts in the robust sequential change detection problem (and the related model selection problem), this paper proposes a sequential unknown change detection algorithm based on a relative entropy based HMM parameter estimator. Our proposed approach is able to overcome the lack of knowledge of post-change parameters, and is illustrated to have similar performance to the popular cumulative sum (CUSUM) algorithm (which requires knowledge of the post-change parameter values) when examined, on both simulated and real data, in a vision-based aircraft manoeuvre detection problem.

Numerical simulation of a fractional mathematical model for epidermal wound healing

A number of mathematical models investigating certain aspects of the complicated process of wound healing are reported in the literature in recent years. However, effective numerical methods and supporting error analysis for the fractional equations which describe the process of wound healing are still limited. In this paper, we consider numerical simulation of fractional model based on the coupled advection-diffusion equations for cell and chemical concentration in a polar coordinate system. The space fractional derivatives are defined in the Left and Right Riemann-Liouville sense. Fractional orders in advection and diffusion terms belong to the intervals (0; 1) or (1; 2], respectively. Some numerical techniques will be used. Firstly, the coupled advection-diffusion equations are decoupled to a single space fractional advection-diffusion equation in a polar coordinate system. Secondly, we propose a new implicit difference method for simulating this equation by using the equivalent of the Riemann-Liouville and Gr¨unwald-Letnikov fractional derivative definitions. Thirdly, its stability and convergence are discussed, respectively. Finally, some numerical results are given to demonstrate the theoretical analysis.

Assessing of circuit breaker restrike risks using computer simulation and wavelet analysis

A breaker restrike is an abnormal arcing phenomenon, leading to a possible breaker failure. Eventually, this failure leads to interruption of the transmission and distribution of the electricity supply system until the breaker is replaced. Before 2008, there was little evidence in the literature of monitoring techniques based on restrike measurement and interpretation produced during switching of capacitor banks and shunt reactor banks in power systems. In 2008 a non-intrusive radiometric restrike measurement method and a restrike hardware detection algorithm were developed by M.S. Ramli and B. Kasztenny. However, the limitations of the radiometric measurement method are a band limited frequency response as well as limitations in amplitude determination. Current restrike detection methods and algorithms require the use of wide bandwidth current transformers and high voltage dividers. A restrike switch model using Alternative Transient Program (ATP) and Wavelet Transforms which support diagnostics are proposed. Restrike phenomena become a new diagnostic process using measurements, ATP and Wavelet Transforms for online interrupter monitoring. This research project investigates the restrike switch model Parameter „A. dielectric voltage gradient related to a normal and slowed case of the contact opening velocity and the escalation voltages, which can be used as a diagnostic tool for a vacuum circuit-breaker (CB) at service voltages between 11 kV and 63 kV. During current interruption of an inductive load at current quenching or chopping, a transient voltage is developed across the contact gap. The dielectric strength of the gap should rise to a point to withstand this transient voltage. If it does not, the gap will flash over, resulting in a restrike. A straight line is fitted through the voltage points at flashover of the contact gap. This is the point at which the gap voltage has reached a value that exceeds the dielectric strength of the gap. This research shows that a change in opening contact velocity of the vacuum CB produces a corresponding change in the slope of the gap escalation voltage envelope. To investigate the diagnostic process, an ATP restrike switch model was modified with contact opening velocity computation for restrike waveform signature analyses along with experimental investigations. This also enhanced a mathematical CB model with the empirical dielectric model for SF6 (sulphur hexa-fluoride) CBs at service voltages above 63 kV and a generalised dielectric curve model for 12 kV CBs. A CB restrike can be predicted if there is a similar type of restrike waveform signatures for measured and simulated waveforms. The restrike switch model applications are used for: computer simulations as virtual experiments, including predicting breaker restrikes; estimating the interrupter remaining life of SF6 puffer CBs; checking system stresses; assessing point-on-wave (POW) operations; and for a restrike detection algorithm development using Wavelet Transforms. A simulated high frequency nozzle current magnitude was applied to an Equation (derived from the literature) which can calculate the life extension of the interrupter of a SF6 high voltage CB. The restrike waveform signatures for a medium and high voltage CB identify its possible failure mechanism such as delayed opening, degraded dielectric strength and improper contact travel. The simulated and measured restrike waveform signatures are analysed using Matlab software for automatic detection. Experimental investigation of a 12 kV vacuum CB diagnostic was carried out for the parameter determination and a passive antenna calibration was also successfully developed with applications for field implementation. The degradation features were also evaluated with a predictive interpretation technique from the experiments, and the subsequent simulation indicates that the drop in voltage related to the slow opening velocity mechanism measurement to give a degree of contact degradation. A predictive interpretation technique is a computer modeling for assessing switching device performance, which allows one to vary a single parameter at a time; this is often difficult to do experimentally because of the variable contact opening velocity. The significance of this thesis outcome is that it is a non-intrusive method developed using measurements, ATP and Wavelet Transforms to predict and interpret a breaker restrike risk. The measurements on high voltage circuit-breakers can identify degradation that can interrupt the distribution and transmission of an electricity supply system. It is hoped that the techniques for the monitoring of restrike phenomena developed by this research will form part of a diagnostic process that will be valuable for detecting breaker stresses relating to the interrupter lifetime. Suggestions for future research, including a field implementation proposal to validate the restrike switch model for ATP system studies and the hot dielectric strength curve model for SF6 CBs, are given in Appendix A.

Physically sound vehicle-driver model for realistic microscopic simulation

In microscopic traffic simulators, the interaction between vehicles is considered. The dynamics of the system then becomes an emergent property of the interaction between its components. Such interactions include lane-changing, car-following behaviours and intersection management. Although, in some cases, such simulators produce realistic prediction, they do not allow for an important aspect of the dynamics, that is, the driver-vehicle interaction. This paper introduces a physically sound vehicle-driver model for realistic microscopic simulation. By building a nanoscopic traffic simulation model that uses steering angle and throttle position as parameters, the model aims to overcome unrealistic acceleration and deceleration values, as found in various microscopic simulation tools. A physics engine calculates the driving force of the vehicle, and the preliminary results presented here, show that, through a realistic driver-vehicle-environment simulator, it becomes possible to model realistic driver and vehicle behaviours in a traffic simulation.

A sequential Monte Carlo approach to the sequential design for discriminating between rival continuous data models

Here we present a sequential Monte Carlo approach to Bayesian sequential design for the incorporation of model uncertainty. The methodology is demonstrated through the development and implementation of two model discrimination utilities; mutual information and total separation, but it can also be applied more generally if one has different experimental aims. A sequential Monte Carlo algorithm is run for each rival model (in parallel), and provides a convenient estimate of the marginal likelihood (of each model) given the data, which can be used for model comparison and in the evaluation of utility functions. A major benefit of this approach is that it requires very little problem specific tuning and is also computationally efficient when compared to full Markov chain Monte Carlo approaches. This research is motivated by applications in drug development and chemical engineering.

Simulation-based comparison of pull-push system in motorcycle assembly line

To investigate the effects of adopting a pull system in assembly lines in contrast to a push system, simulation software called “ARENA” is used as a tool in order to present numerical results from both systems. Simulation scenarios are created to evaluate the effects of attributes changing in assembly systems, with influential factors including the change of manufacturing system (push system to pull system) and variation of demand. Moreover, pull system manufacturing consists of the addition attribute, which is the number of buffer storage. This paper will provide an analysis based on a previous case study, hence process time and workflow refer to the journal name “Optimising and simulating the assembly line balancing problem in a motorcycle manufacturing company: a case study” [2]. The implementation of the pull system mechanism is to produce a system improvement in terms of the number of Work-In-Process (WIP), total time of products in the system, and the number of finished product inventory, while retaining the same throughput.

Resource allocation in multiuser cooperative OFDM system using forced cost based decisions

A sub optimal resource allocation algorithm for Orthogonal Frequency Division Multiplexing (OFDM) based cooperative scheme is proposed. The system consists of multiple relays. Subcarrier space is divided into blocks and relays participating in cooperation are allocated specific blocks to be used with a user. To ensure unique subcarrier assignment system is constrained such that same block cannot be used by more than one user. Users are given fair block assignments while no restriction for maximum number of blocks a relay can employ is given. Forced cost based decisions [1] are used for block allocation. Simulation results show that this scheme outperforms a non cooperating scheme with sequential allocation with respect to power usage.

An assessment tool for selection of appropriate daylighting solutions for buildings in tropical and subtropical regions : Validation using radiance simulation

A new decision-making tool that will assist designers in the selection of appropriate daylighting solutions for buildings in tropical locations has been previously proposed by the authors. Through an evaluation matrix that prioritizes the parameters that best respond to the needs of tropical climates (e.g. reducing solar gain and protection from glare) the tool determines the most appropriate devices for specific climate and building inputs. The tool is effective in demonstrating the broad benefits and limitations of the different daylight strategies for buildings in the tropics. However for thorough analysis and calibration of the tool, validation is necessary. This paper presents a first step in the validation process. RADIANCE simulations were conducted to compare simulation performance with the performance predicted by the tool. To this end, an office building case study in subtropical Brisbane, Australia, and five different daylighting devices including openings, light guiding systems and light transport systems were simulated. Illuminance, light uniformity, daylight penetration and glare analysis were assessed for each device. The results indicate the tool can appropriately rank and recommend daylighting strategies based on specific building inputs for tropical and subtropical regions, making it a useful resource for designers.

A micro-simulation of airport passengers with advanced traits

An approach for modeling passenger flows in airport terminals by a set of devised advanced traits of passengers is proposed. Advanced traits take into account a passenger’s cognitive preferences which would be the underlying motivations of route-choice decisions. Basic traits are the status of passengers such as travel class. Although the activities of passengers are normally regarded as stochastic and sometimes unpredictable, we advise that real scenarios of passenger flows are basically feasible to be compared with virtual simulations in terms of tactical route-choice decision-making by individual personals. Inside airport terminals, passengers are goal-directed and not only use standard processing check points but also behave discretionary activities during the course. In this paper, we integrated discretionary activities in the study to fulfill full-range of passenger flows. In the model passengers are built as intelligent agents who possess a bunch of initial basic traits and then can be categorized into ten distinguish groups in terms of route-choice preferences by inferring the results of advanced traits. An experiment is executed to demonstrate the capability to facilitate predicting passenger flows.

Communication and organizational social networks : a simulation model

Recent management research has evidenced the significance of organizational social networks, and communication is believed to impact the interpersonal relationships. However, we have little knowledge on how communication affects organizational social networks. This paper studies the dynamics between organizational communication patterns and the growth of organizational social networks. We propose an organizational social network growth model, and then collect empirical data to test model validity. The simulation results agree well with the empirical data. The results of simulation experiments enrich our knowledge on communication with the findings that organizational management practices that discourage employees from communicating within and across group boundaries have disparate and significant negative effect on the social network’s density, scalar assortativity and discrete assortativity, each of which correlates with the organization’s performance. These findings also suggest concrete measures for management to construct and develop the organizational social network.