Condition monitoring and diagnosis of injector faults in a diesel engine using in-cylinder pressure and acoustic emission techniques

Failing injectors are one of the most common faults in diesel engines. The severity of these faults could have serious effects on diesel engine operations such as engine misfire, knocking, insufficient power output or even cause a complete engine breakdown. It is thus essential to prevent such faults from occurring by monitoring the condition of these injectors. In this paper, the authors present the results of an experimental investigation on identifying the signal characteristics of a simulated incipient injector fault in a diesel engine using both in-cylinder pressure and acoustic emission (AE) techniques. A time waveform event driven synchronous averaging technique was used to minimize or eliminate the effect of engine speed variation and amplitude fluctuation. It was found that AE is an effective method to detect the simulated injector fault in both time (crank angle) and frequency (order) domains. It was also shown that the time domain in-cylinder pressure signal is a poor indicator for condition monitoring and diagnosis of the simulated injector fault due to the small effect of the simulated fault on the engine combustion process. Nevertheless, good correlations between the simulated injector fault and the lower order components of the enveloped in-cylinder pressure spectrum were found at various engine loading conditions.

Abstracting and correlating heterogeneous events to detect complex scenarios

The research presented in this thesis addresses inherent problems in signaturebased intrusion detection systems (IDSs) operating in heterogeneous environments. The research proposes a solution to address the difficulties associated with multistep attack scenario specification and detection for such environments. The research has focused on two distinct problems: the representation of events derived from heterogeneous sources and multi-step attack specification and detection. The first part of the research investigates the application of an event abstraction model to event logs collected from a heterogeneous environment. The event abstraction model comprises a hierarchy of events derived from different log sources such as system audit data, application logs, captured network traffic, and intrusion detection system alerts. Unlike existing event abstraction models where low-level information may be discarded during the abstraction process, the event abstraction model presented in this work preserves all low-level information as well as providing high-level information in the form of abstract events. The event abstraction model presented in this work was designed independently of any particular IDS and thus may be used by any IDS, intrusion forensic tools, or monitoring tools. The second part of the research investigates the use of unification for multi-step attack scenario specification and detection. Multi-step attack scenarios are hard to specify and detect as they often involve the correlation of events from multiple sources which may be affected by time uncertainty. The unification algorithm provides a simple and straightforward scenario matching mechanism by using variable instantiation where variables represent events as defined in the event abstraction model. The third part of the research looks into the solution to address time uncertainty. Clock synchronisation is crucial for detecting multi-step attack scenarios which involve logs from multiple hosts. Issues involving time uncertainty have been largely neglected by intrusion detection research. The system presented in this research introduces two techniques for addressing time uncertainty issues: clock skew compensation and clock drift modelling using linear regression. An off-line IDS prototype for detecting multi-step attacks has been implemented. The prototype comprises two modules: implementation of the abstract event system architecture (AESA) and of the scenario detection module. The scenario detection module implements our signature language developed based on the Python programming language syntax and the unification-based scenario detection engine. The prototype has been evaluated using a publicly available dataset of real attack traffic and event logs and a synthetic dataset. The distinct features of the public dataset are the fact that it contains multi-step attacks which involve multiple hosts with clock skew and clock drift. These features allow us to demonstrate the application and the advantages of the contributions of this research. All instances of multi-step attacks in the dataset have been correctly identified even though there exists a significant clock skew and drift in the dataset. Future work identified by this research would be to develop a refined unification algorithm suitable for processing streams of events to enable an on-line detection. In terms of time uncertainty, identified future work would be to develop mechanisms which allows automatic clock skew and clock drift identification and correction. The immediate application of the research presented in this thesis is the framework of an off-line IDS which processes events from heterogeneous sources using abstraction and which can detect multi-step attack scenarios which may involve time uncertainty.

The failure of Australian legislation on indirect discrimination to detect the systemic racism which prevents Aboriginal people from fully participating in the workforce

Government figures put the current indigenous unemployment rate at around 23%, 3 times the unemployment rate for other Australians. This thesis aims to assess whether Australian indirect discrimination legislation can provide a remedy for one of the causes of indigenous unemployment - the systemic discrimination which can result from the mere operation of established procedures of recruitment and hiring. The impact of those practices on indigenous people is examined in the context of an analysis of anti-discrimination legislation and cases from all Australian jurisdictions from the time of the passing of the Racial Discrimination Act by the Commonwealth in 1975 to the present. The thesis finds a number of reasons why the legislation fails to provide equality of opportunity for indigenous people seeking to enter the workforce. In nearly all jurisdictions it is obscurely drafted, used mainly by educated middle class white women, and provides remedies which tend to be compensatory damages rather than change to recruitment policy. White dominance of the legal process has produced legislative and judicial definitions of "race" and "Aboriginality" which focus on biology rather than cultural difference. In the commissions and tribunals complaints of racial discrimination are often rejected on the grounds of being "vexatious" or "frivolous", not reaching the required standard of proof, or not showing a causal connection between race and the conduct complained of. In all jurisdictions the cornerstone of liability is whether a particular employment term, condition or practice is reasonable. The thesis evaluates the approaches taken by appellate courts, including the High Court, and concludes that there is a trend towards an interpretation of reasonableness which favours employer arguments such as economic rationalism, the maintenance of good industrial relations, managerial prerogative to hire and fire, and the protection of majority rights. The thesis recommends that separate, clearly drafted legislation should be passed to address indigenous disadvantage and that indigenous people should be involved in all stages of the process.

Comparison of molecular markers to detect fresh sewage in environmental waters

Human-specific Bacteroides HF183 (HS-HF183), human-specific Enterococci faecium esp (HS-esp), human-specific adenoviruses (HS-AVs) and human-specific polyomaviruses (HS-PVs) assays were evaluated in freshwater, seawater and distilled water to detect fresh sewage. The sewage spiked water samples were also tested for the concentrations of traditional fecal indicators (i.e., Escherichia coli, enterococci and Clostridium perfringens) and enteric viruses such as enteroviruses (EVs), sapoviruses (SVs), and torquetenoviruses (TVs). The overall host-specificity of the HS-HF183 marker to differentiate between humans and other animals was 98%. However, the HS-esp, HS-AVs and HS-PVs showed 100% hostspecificity. All the human-specific markers showed >97% sensitivity to detect human fecal pollution. E. coli, enterococci and, C. perfringens were detected up to dilutions of sewage 10_5, 10_4 and 10_3 respectively.HS-esp, HS-AVs, HS-PVs, SVs and TVs were detected up to dilution of sewage 10_4 whilst EVs were detected up to dilution 10_5. The ability of the HS-HF183 marker to detect freshsewagewas3–4 orders ofmagnitude higher than that of the HS-esp and viral markers. The ability to detect fresh sewage in freshwater, seawater and distilled water matrices was similar for human-specific bacterial and viral marker. Based on our data, it appears that human-specific molecular markers are sensitive measures of fresh sewage pollution, and the HS-HF183 marker appears to be the most sensitive among these markers in terms of detecting fresh sewage. However, the presence of the HS-HF183 marker in environmental waters may not necessarily indicate the presence of enteric viruses due to their high abundance in sewage compared to enteric viruses. More research is required on the persistency of these markers in environmental water samples in relation to traditional fecal indicators and enteric pathogens.

Rover autonomous integrity monitoring of GNSS RTK positioning solutions with multi-constellations

This paper studies receiver autonomous integrity monitoring (RAIM) algorithms and performance benefits of RTK solutions with multiple-constellations. The proposed method is generally known as Multi-constellation RAIM -McRAIM. The McRAIM algorithms take advantage of the ambiguity invariant character to assist fast identification of multiple satellite faults in the context of multiple constellations, and then detect faulty satellites in the follow-up ambiguity search and position estimation processes. The concept of Virtual Galileo Constellation (VGC) is used to generate useful data sets of dual-constellations for performance analysis. Experimental results from a 24-h data set demonstrate that with GPS&VGC constellations, McRAIM can significantly enhance the detection and exclusion probabilities of two simultaneous faulty satellites in RTK solutions.

Corneal confocal microscopy : a novel means to detect nerve fibre damage in idiopathic small fibre neuropathy

Patients with idiopathic small fibre neuropathy (ISFN) have been shown to have significant intraepidermal nerve fibre loss and an increased prevalence of impaired glucose tolerance (IGT). It has been suggested that the dysglycemia of IGT and additional metabolic risk factors may contribute to small nerve fibre damage in these patients. Twenty-five patients with ISFN and 12 aged-matched control subjects underwent a detailed evaluation of neuropathic symptoms, neurological deficits (Neuropathy deficit score (NDS); Nerve Conduction Studies (NCS); Quantitative Sensory Testing (QST) and Corneal Confocal Microscopy (CCM)) to quantify small nerve fibre pathology. Eight (32%) patients had IGT. Whilst all patients with ISFN had significant neuropathic symptoms, NDS, NCS and QST except for warm thresholds were normal. Corneal sensitivity was reduced and CCM demonstrated a significant reduction in corneal nerve fibre density (NFD) (Pb0.0001), nerve branch density (NBD) (Pb0.0001), nerve fibre length (NFL) (Pb0.0001) and an increase in nerve fibre tortuosity (NFT) (Pb0.0001). However these parameters did not differ between ISFN patients with and without IGT, nor did they correlate with BMI, lipids and blood pressure. Corneal confocal microscopy provides a sensitive non-invasive means to detect small nerve fibre damage in patients with ISFN and metabolic abnormalities do not relate to nerve damage.

Automatic generation of assertions to detect potential security vulnerabilities in C programs that use union and pointer types

Type unions, pointer variables and function pointers are a long standing source of subtle security bugs in C program code. Their use can lead to hard-to-diagnose crashes or exploitable vulnerabilities that allow an attacker to attain privileged access over classified data. This paper describes an automatable framework for detecting such weaknesses in C programs statically, where possible, and for generating assertions that will detect them dynamically, in other cases. Exclusively based on analysis of the source code, it identifies required assertions using a type inference system supported by a custom made symbol table. In our preliminary findings, our type system was able to infer the correct type of unions in different scopes, without manual code annotations or rewriting. Whenever an evaluation is not possible or is difficult to resolve, appropriate runtime assertions are formed and inserted into the source code. The approach is demonstrated via a prototype C analysis tool.