A sensor fault detection and isolation method in interior permanent-magnet synchronous motor drives based on an extended Kalman filter

Interior permanent-magnet synchronous motors (IPMSMs) become attractive candidates in modern hybrid electric vehicles and industrial applications. Usually, to obtain good control performance, the electric drives of this kind of motor require one position, one dc link, and at least two current sensors. Failure of any of these sensors might lead to degraded system performance or even instability. As such, sensor fault resilient control becomes a very important issue in modern drive systems. This paper proposes a novel sensor fault detection and isolation algorithm based on an extended Kalman filter. It is robust to system random noise and efficient in real-time implementation. Moreover, the proposed algorithm is compact and can detect and isolate all the sensor faults for IPMSM drives. Thorough theoretical analysis is provided, and the effectiveness of the proposed approach is proven by extensive experimental results.

A qualitative investigation of adolescents’ perceived mechanisms of change from a universal school-based depression prevention program

A recent meta-analysis provides evidence supporting the universal application of school-based prevention programs for adolescent depression. The mechanisms underlying such successful interventions, however, are largely unknown. We report on a qualitative analysis of 109 Grade 9 students’ beliefs about what they gained from an evidence-based depression prevention intervention, the Resourceful Adolescent Program (RAP-A). Fifty-four percent of interviewees articulated at least one specific example of program benefit. A thematic analysis of responses revealed two major themes, improved interpersonal relationships and improved self-regulation, both stronger than originally assumed. A more minor theme also emerged—more helpful cognitions. It is postulated that both improved interpersonal relationships and improved self-regulation are likely to enhance one another, and more helpful cognitions may express its contribution through enhanced self-regulation. These findings broaden our understanding of the impact of depression prevention programs, beginning to illuminate how such programs benefit participants.

A novel identification method for ultra trace detection of biomolecules using functionalised Surface Enhanced Raman Spectroscopy (SERS)

This thesis developed a new method for measuring extremely low amounts of organic and biological molecules, using Surface enhanced Raman Spectroscopy. This method has many potential applications, e.g. medical diagnosis, public health, food provenance, antidoping, forensics and homeland security. The method development used caffeine as the small molecule example, and erythropoietin (EPO) as the large molecule. This method is much more sensitive and specific than currently used methods; rapid, simple and cost effective. The method can be used to detect target molecules in beverages and biological fluids without the usual preparation steps.

Detection of object onset and offset in naturalistic scenes

The present study was conducted to investigate whether ob- servers are equally prone to overlook any kinds of visual events in change blindness. Capitalizing on the finding from visual search studies that abrupt appearance of an object effectively captures observers' attention, the onset of a new object and the offset of an existing object were contrasted regarding their detectability when they occurred in a naturalistic scene. In an experiment, participants viewed a series of photograph pairs in which layouts of seven or eight objects were depicted. One object either appeared in or disappeared from the layout, and participants tried to detect this change. Results showed that onsets were detected more quickly than offsets, while they were detected with equivalent ac- curacy. This suggests that the primacy of onset over offset is a robust phenomenon that likely makes onsets more resistant to change blindness under natural viewing conditions.

Nucleic acid hybridizations as radioactive tool for rapid detection of banana bunchy top virus

Banana bunchy top disease (BBTD) caused by banana bunchy top virus (BBTV) was radioactively detected by nucleic acid hybridization techniques. Results showed that, 32P-labelled insert of pBT338 was hybridized with nucleic acid extracts from BBTV-infected plants from Egypt and Australia but not with those from CMV-infected plants from Egypt. Results revealed that BBTV was greatly detected in midrib, roots, meristem, corm, leaves and pseudostem respectively. BBTV was also detected in symptomless young plants prepared from diseased plant materials grown under tissue culture conditions but was not present in those performed from healthy plant materials. The sensitivity of dot blot and Southern blot hybridizations for the detection of BBTV was also performed for the detection of BBTV.

Ultra sensitive label free surface enhanced Raman spectroscopy method for the detection of biomolecules

We present a proof of concept for a novel nanosensor for the detection of ultra-trace amounts of bio-active molecules in complex matrices. The nanosensor is comprised of gold nanoparticles with an ultra-thin silica shell and antibody surface attachment, which allows for the immobilization and direct detection of bio-active molecules by surface enhanced Raman spectroscopy (SERS) without requiring a Raman label. The ultra-thin passive layer (~1.3 nm thickness) prevents competing molecules from binding non-selectively to the gold surface without compromising the signal enhancement. The antibodies attached on the surface of the nanoparticles selectively bind to the target molecule with high affinity. The interaction between the nanosensor and the target analyte result in conformational rearrangements of the antibody binding sites, leading to significant changes in the surface enhanced Raman spectra of the nanoparticles when compared to the spectra of the un-reacted nanoparticles. Nanosensors of this design targeting the bio-active compounds erythropoietin and caffeine were able to detect ultra-trace amounts the analyte to the lower quantification limits of 3.5×10−13 M and 1×10−9 M, respectively.

Tunable “Nano-Shearing” : A physical mechanism to displace nonspecific cell adhesion during rare cell detection

We report a tunable alternating current electrohydrodynamic (ac-EHD) force which drives lateran fluid motion within a few nanometers of an electrode surface. Because the magnitude of this fluid shear force can be tuned externally (e.g., via the application of an ac electric field), it provides a new capability to physically displace weakly (nonspecifically) bound cellular analytes. To demonstrate the utility of the tunable nanoshearing phenomenon, we present data on purpose-built microfluidic devices that employ ac-EHD force to remove nonspecific adsorption of molecular and cellular species. Here, we show that an ac-EHD device containing asymmetric planar and microtip electrode pairs resulted in a 4-fold reduction in nonspecific adsorption of blood cells and also captured breast cancer cells in blood, with high efficiency (approximately 87%) and specificity. We therefore feel that this new capability of externally tuning and manipulating fluid flow could have wide applications as an innovative approach to enhance the specific capture of rare cells such as cancer cells in blood.

Improving the detection of donations within the RHD negative blood donor panel which weakly express the RHD antigen

This project improved the detection and classification of very weakly expressed RhD variants in the Australian blood donor panel and contributed to the knowledge of anti-D reactivity patterns of RHD alleles that are undescribed. As such, the management of donations possessing these RHD alleles can be improved upon and the overall safety of transfusion medicine pertaining to the Rh blood group system will be increased. Future projects at ARCBS will be able to utilise the procedures developed in this project, thereby decreasing throughput time. The specificity of current testing will be improved and the need for outsourced RHD testing diminished.

Managing clients’ expectations at the outset of online Cognitive Behavioural Therapy (CBT) for depression

Background Engaging clients in psychotherapy by managing their expectations is important for therapeutic success. Initial moments in first sessions of therapy are thought to afford an opportunity to establish a shared understanding of how therapy will proceed. However there is little evidence from analysis of actual sessions of therapy to support this. Objective This study utilised recordings to examine how therapists manage clients’ expectations during the first two sessions of online Cognitive Behavioural Therapy (CBT). Methods Expectation management was investigated through conversation analysis of sessions from 176 client-therapist dyads involved in online CBT. The primary focus of analysis was expectation management during the initial moments of first sessions, with a secondary focus on expectations at subsequent points. Analysis Clients’ expectations for therapy were most commonly managed during the initial moments of first sessions of therapy. At this point, most therapists either outlined the tasks of the first and subsequent sessions (n=36), or the first session only (n=108). On other occasions (n = 32), no attempt was made to manage clients’ expectations by outlining what would happen in therapy. Observations of the interactional consequences of such an absence suggest clients may struggle to engage with the therapeutic process in the absence of appropriate expectation management by therapists. Conclusion Clients may more readily engage from the outset of therapy when provided with an explanation that manages their expectation of what is involved. Therapists can accomplish this by projecting how therapy will proceed, particularly beyond the initial session.

Plasma-enabled graded nanotube biosensing arrays on a Si nanodevice platform : catalyst-free integration and in situ detection of nucleation events

Low-temperature plasmas in direct contact with arbitrary, written linear features on a Si wafer enable catalyst-free integration of carbon nanotubes into a Si-based nanodevice platform and in situ resolution of individual nucleation events. The graded nanotube arrays show reliable, reproducible, and competitive performance in electron field emission and biosensing nanodevices.

Asymptotic minimax robust and misspecified Lorden quickest change detection for dependent stochastic processes

The quick detection of an abrupt unknown change in the conditional distribution of a dependent stochastic process has numerous applications. In this paper, we pose a minimax robust quickest change detection problem for cases where there is uncertainty about the post-change conditional distribution. Our minimax robust formulation is based on the popular Lorden criteria of optimal quickest change detection. Under a condition on the set of possible post-change distributions, we show that the widely known cumulative sum (CUSUM) rule is asymptotically minimax robust under our Lorden minimax robust formulation as a false alarm constraint becomes more strict. We also establish general asymptotic bounds on the detection delay of misspecified CUSUM rules (i.e. CUSUM rules that are designed with post- change distributions that differ from those of the observed sequence). We exploit these bounds to compare the delay performance of asymptotically minimax robust, asymptotically optimal, and other misspecified CUSUM rules. In simulation examples, we illustrate that asymptotically minimax robust CUSUM rules can provide better detection delay performance at greatly reduced computation effort compared to competing generalised likelihood ratio procedures.

Detection of sinkhole attack in wireless sensor networks

Generally wireless sensor networks rely of many-to-one communication approach for data gathering. This approach is extremely susceptible to sinkhole attack, where an intruder attracts surrounding nodes with unfaithful routing information, and subsequently presents selective forwarding or change the data that carry through it. A sinkhole attack causes an important threat to sensor networks and it should be considered that the sensor nodes are mostly spread out in open areas and of weak computation and battery power. In order to detect the intruder in a sinkhole attack this paper suggests an algorithm which firstly finds a group of suspected nodes by analyzing the consistency of data. Then, the intruder is recognized efficiently in the group by checking the network flow information. The proposed algorithm's performance has been evaluated by using numerical analysis and simulations. Therefore, accuracy and efficiency of algorithm would be verified.

Telomerase activity : detection and clinical implications in human cancer

Telomerase is an extremely important enzyme required for the immortalisation of tumour cells. Because the gene is activated in the vast majority of tumour tissues and remains unused in most somatic cells, it represents a marker with huge diagnostic, prognostic and treatment implications in cancer. This article summarises the basic structure and functions of telomerase and considers its clinical implications in colorectal and other cancers.

Detection of dynamic primary user with cooperative spectrum sensing

In this paper we demonstrate that existing cooperative spectrum sensing formulated for static primary users cannot accurately detect dynamic primary users regardless of the information fusion method. Performance error occurs as the sensing parameters calculated by the conventional detector result in sensing performance that violates the sensing requirements. Furthermore, the error is accumulated and compounded by the number of cooperating nodes. To address this limitation, we design and implement the duty cycle detection model for the context of cooperative spectrum sensing to accurately calculate the sensing parameters that satisfy the sensing requirements. We show that longer sensing duration is required to compensate for dynamic primary user traffic.

Modelling total duration of traffic incidents including incident detection and recovery time

Traffic incidents are key contributors to non-recurrent congestion, potentially generating significant delay. Factors that influence the duration of incidents are important to understand so that effective mitigation strategies can be implemented. To identify and quantify the effects of influential factors, a methodology for studying total incident duration based on historical data from an ‘integrated database’ is proposed. Incident duration models are developed using a selected freeway segment in the Southeast Queensland, Australia network. The models include incident detection and recovery time as components of incident duration. A hazard-based duration modelling approach is applied to model incident duration as a function of a variety of factors that influence traffic incident duration. Parametric accelerated failure time survival models are developed to capture heterogeneity as a function of explanatory variables, with both fixed and random parameters specifications. The analysis reveals that factors affecting incident duration include incident characteristics (severity, type, injury, medical requirements, etc.), infrastructure characteristics (roadway shoulder availability), time of day, and traffic characteristics. The results indicate that event type durations are uniquely different, thus requiring different responses to effectively clear them. Furthermore, the results highlight the presence of unobserved incident duration heterogeneity as captured by the random parameter models, suggesting that additional factors need to be considered in future modelling efforts.