Recursive actuator fault detection and diagnosis for emergency landing of UASs

This paper presents a practical recursive fault detection and diagnosis (FDD) scheme for online identification of actuator faults for unmanned aerial systems (UASs) based on the unscented Kalman filtering (UKF) method. The proposed FDD algorithm aims to monitor health status of actuators and provide indication of actuator faults with reliability, offering necessary information for the design of fault-tolerant flight control systems to compensate for side-effects and improve fail-safe capability when actuator faults occur. The fault detection is conducted by designing separate UKFs to detect aileron and elevator faults using a nonlinear six degree-of-freedom (DOF) UAS model. The fault diagnosis is achieved by isolating true faults by using the Bayesian Classifier (BC) method together with a decision criterion to avoid false alarms. High-fidelity simulations with and without measurement noise are conducted with practical constraints considered for typical actuator fault scenarios, and the proposed FDD exhibits consistent effectiveness in identifying occurrence of actuator faults, verifying its suitability for integration into the design of fault-tolerant flight control systems for emergency landing of UASs.

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.

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.

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.

On the use of optical flow for scene change detection and description

We propose the use of optical flow information as a method for detecting and describing changes in the environment, from the perspective of a mobile camera. We analyze the characteristics of the optical flow signal and demonstrate how robust flow vectors can be generated and used for the detection of depth discontinuities and appearance changes at key locations. To successfully achieve this task, a full discussion on camera positioning, distortion compensation, noise filtering, and parameter estimation is presented. We then extract statistical attributes from the flow signal to describe the location of the scene changes. We also employ clustering and dominant shape of vectors to increase the descriptiveness. Once a database of nodes (where a node is a detected scene change) and their corresponding flow features is created, matching can be performed whenever nodes are encountered, such that topological localization can be achieved. We retrieve the most likely node according to the Mahalanobis and Chi-square distances between the current frame and the database. The results illustrate the applicability of the technique for detecting and describing scene changes in diverse lighting conditions, considering indoor and outdoor environments and different robot platforms.

A nationwide web-based automated system for early outbreak detection and rapid response in China

Timely reporting, effective analyses and rapid distribution of surveillance data can assist in detecting the aberration of disease occurrence and further facilitate a timely response. In China, a new nationwide web-based automated system for outbreak detection and rapid response was developed in 2008. The China Infectious Disease Automated-alert and Response System (CIDARS) was developed by the Chinese Center for Disease Control and Prevention based on the surveillance data from the existing electronic National Notifiable Infectious Diseases Reporting Information System (NIDRIS) started in 2004. NIDRIS greatly improved the timeliness and completeness of data reporting with real time reporting information via the Internet. CIDARS further facilitates the data analysis, aberration detection, signal dissemination, signal response and information communication needed by public health departments across the country. In CIDARS, three aberration detection methods are used to detect the unusual occurrence of 28 notifiable infectious diseases at the county level and to transmit that information either in real-time or on a daily basis. The Internet, computers and mobile phones are used to accomplish rapid signal generation and dissemination, timely reporting and reviewing of the signal response results. CIDARS has been used nationwide since 2008; all Centers for Disease Control and Prevention (CDC) in China at the county, prefecture, provincial and national levels are involved in the system. It assists with early outbreak detection at the local level and prompts reporting of unusual disease occurrences or potential outbreaks to CDCs throughout the country.

Redefining dermatologists’ role in skin cancer early detection and follow-up care

Early diagnosis of melanoma leads to the best prognosis for patients and may be more likely achieved when those who are at high risk for melanoma undergo regular and systematic monitoring. However, many people rarely or never see a dermatologist. Risk prediction models (recently reviewed by Usher-Smith et al ) could assist to triage people into preventive care appropriate for their risk profile. Most risk prediction models contain measures of phenotype including skin, eye and hair colour as well as genetic mutations. Almost all also contain the number and size of naevi, as well as the presence of naevi with atypical features which are independently associated with melanoma risk. In the absence of formal population-based screening programs for melanoma in most countries worldwide, people with high risk phenotypes may need to consider regular monitoring or self-monitoring of their naevi , especially since the vast majority of melanomas are found by people themselves or their friend and relatives. Another group of patients that will require regular monitoring are patients who have been successfully treated for their first melanoma, whose risk to develop a second melanoma is greatly increased . In a US study of 89,515 melanoma survivors those with a previous diagnosis of melanoma had a 9-fold increased risk of developing subsequent melanoma compared with the general population, equating to a rate of 3.76 per 1000 person-years, while in an Australian study, risk of subsequent melanoma was 6 per 1000 person-years. Regular follow-up is therefore essential for melanoma survivors, especially during the first few years after initial melanoma diagnosis.

Effectiveness of in-office blood pressure measurement by eye care practitioners in early detection and management of hypertension

AIM To investigate the number of hypertensive patients, the optometrist is able to identify by routinely taking blood pressure (BP) measurements for patients in "at -risk" groups, and to sample patients' opinions regarding in -office BP measurement. Many of the optometrists in Saudi Arabia practice in optical stores. These stores are wide spread, easily accessible and seldom need appointments. The expanding role of the optometrist as a primary health care provider (PHCP) and the increasing global prevalence of hypertension, highlight the need for an integrated approach towards detecting and monitoring hypertension. METHODS Automated BP measurements were made twice (during the same session) at five selected optometry practices using a validated BP monitor (Omron M6) to assess the number of patients with high BP (HBP) - in at -risk groups -visiting the eye clinic routinely. Prior to data collection, practitioners underwent a two-day training workshop by a cardiologist on hypertension and how to obtain accurate BP readings. A protocol for BP measurement was distributed and retained in all participating clinics. The general attitude towards cardiovascular health of 480 patients aged 37.2 (依12.4)y and their opinion towards in-office BP measurement was assessed using a self -administered questionnaire. RESULTS A response rate of 83.6% was obtained for the survey. Ninety -three of the 443 patients (21.0% ) tested for BP in this study had HBP. Of these, (62 subjects) 67.7% were unaware of their HBP status. Thirty of the 105 subjects (28.6%) who had previously been diagnosed with HBP, still had HBP at the time of this study, and only 22 (73.3%) of these patients were on medication. Also, only 25% of the diagnosed hypertensive patients owned a BP monitor. CONCLUSION Taking BP measurements in optometry practices, we were able to identify one previously undiagnosed patient with HBP for every 8 adults tested. We also identified 30 of 105 previously diagnosed patients whose BP was poorly controlled, twenty-two of whom were on medication. The patients who participated in this study were positively disposed toward the routine measurement of BP by optometrists.

A student-centred approach to support, reward and recognition of student peer ‘learnership’

The benefits for university graduates in growing skills and capabilities through volunteering experiences are gaining increased attention. Building leadership self-efficacy supports students develop their capacity for understanding, articulating and evidencing their learning. Reward and recognition is fundamental in the student’s journey to build self-efficacy. Through this research, concepts of reward and recognition have been explored and articulated through the experiences and perceptions of actively engaged student peer leaders. The research methodology has enabled a collaborative, student-centred approach in shaping an innovative Rewards Framework, which supports, recognises and rewards the learning journey from beginning peer leader to competent and confident graduate.

Robotic detection and tracking of Crown-Of-Thorns starfish

This paper presents a novel vision-based underwater robotic system for the identification and control of Crown-Of-Thorns starfish (COTS) in coral reef environments. COTS have been identified as one of the most significant threats to Australia's Great Barrier Reef. These starfish literally eat coral, impacting large areas of reef and the marine ecosystem that depends on it. Evidence has suggested that land-based nutrient runoff has accelerated recent outbreaks of COTS requiring extensive use of divers to manually inject biological agents into the starfish in an attempt to control population numbers. Facilitating this control program using robotics is the goal of our research. In this paper we introduce a vision-based COTS detection and tracking system based on a Random Forest Classifier (RFC) trained on images from underwater footage. To track COTS with a moving camera, we embed the RFC in a particle filter detector and tracker where the predicted class probability of the RFC is used as an observation probability to weight the particles, and we use a sparse optical flow estimation for the prediction step of the filter. The system is experimentally evaluated in a realistic laboratory setup using a robotic arm that moves a camera at different speeds and heights over a range of real-size images of COTS in a reef environment.

Hot spot detection and spatio-temporal dynamics of dengue in Queensland, Australia

Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992-1993. This study explored spatio-temporal distribution and clustering of locally-acquired dengue cases in Queensland State, Australia and identified target areas for effective interventions. A computerised locally-acquired dengue case dataset was collected from Queensland Health for Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. Dengue hot spots were detected using SatScan method. Descriptive spatial analysis showed that a total of 2,398 locally-acquired dengue cases were recorded in central and northern regions of tropical Queensland. A seasonal pattern was observed with most of the cases occurring in autumn. Spatial and temporal variation of dengue cases was observed in the geographic areas affected by dengue over time. Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in tropical Queensland, Australia. There is a clear evidence for the existence of statistically significant clusters of dengue and these clusters varied over time. These findings enabled us to detect and target dengue clusters suggesting that the use of geospatial information can assist the health authority in planning dengue control activities and it would allow for better design and implementation of dengue management programs.

A Bayesian Framework for the Assessment of Vision-based Weed and Fruit Detection and Classification Algorithms

This paper proposes new metrics and a performance-assessment framework for vision-based weed and fruit detection and classification algorithms. In order to compare algorithms, and make a decision on which one to use fora particular application, it is necessary to take into account that the performance obtained in a series of tests is subject to uncertainty. Such characterisation of uncertainty seems not to be captured by the performance metrics currently reported in the literature. Therefore, we pose the problem as a general problem of scientific inference, which arises out of incomplete information, and propose as a metric of performance the(posterior) predictive probabilities that the algorithms will provide a correct outcome for target and background detection. We detail the framework through which these predicted probabilities can be obtained, which is Bayesian in nature. As an illustration example, we apply the framework to the assessment of performance of four algorithms that could potentially be used in the detection of capsicums (peppers).

Multiplex real-time PCR for the detection and differentiation of equid herpesvirus 1 (EHV-1) and equid herpesvirus 4 (EHV-4).

A multiplex real-time PCR was designed to detect and differentiate equid herpesvirus 1 (EHV-1) and equid herpesvirus 4 (EHV-4). The PCR targets the glycoprotein B gene of EHV-1 and EHV-4. Primers and probes were specific to each equine herpesvirus type and can be used in monoplex or multiplex PCRs, allowing the differentiation of these two closely related members of the Alphaherpesvirinae. The two probes were minor-groove binding probes (MGB?) labelled with 6-carboxy-fluorescein (FAM?) and VIC® for detection of EHV-1 and EHV-4, respectively. Ten EHV-1 isolates, six EHV-1 positive clinical samples, one EHV-1 reference strain (EHV-1.438/77), three EHV-4 positive clinical samples, two EHV-4 isolates and one EHV-4 reference strain (EHV-4 405/76) were included in this study. EHV-1 isolates, clinical samples and the reference strain reacted in the EHV-1 real-time PCR but not in the EHV-4 real-time PCR and similarly EHV-4 clinical samples, isolates and the reference strain were positive in the EHV-4 real-time PCR but not in the EHV-1 real-time PCR. Other herpesviruses, such as EHV-2, EHV-3 and EHV-5 were all negative when tested using the multiplex real-time PCR. When bacterial pathogens and opportunistic pathogens were tested in the multiplex real-time PCR they did not react with either system. The multiplex PCR was shown to be sensitive and specific and is a useful tool for detection and differentiation of EHV-1 and EHV-4 in a single reaction. A comprehensive equine herpesvirus disease investigation procedure used in our laboratory is also outlined. This procedure describes the combination of alphaherpesvirus multiplex real-time PCR along with existing gel-based PCRs described by other authors.