Time correlated anomaly detection based on inferences

Anomaly detection techniques are used to find the presence of anomalous activities in a network by comparing traffic data activities against a "normal" baseline. Although it has several advantages which include detection of "zero-day" attacks, the question surrounding absolute definition of systems deviations from its "normal" behaviour is important to reduce the number of false positives in the system. This study proposes a novel multi-agent network-based framework known as Statistical model for Correlation and Detection (SCoDe), an anomaly detection framework that looks for timecorrelated anomalies by leveraging statistical properties of a large network, monitoring the rate of events occurrence based on their intensity. SCoDe is an instantaneous learning-based anomaly detector, practically shifting away from the conventional technique of having a training phase prior to detection. It does acquire its training using the improved extension of Exponential Weighted Moving Average (EWMA) which is proposed in this study. SCoDe does not require any previous knowledge of the network traffic, or network administrators chosen reference window as normal but effectively builds upon the statistical properties from different attributes of the network traffic, to correlate undesirable deviations in order to identify abnormal patterns. The approach is generic as it can be easily modified to fit particular types of problems, with a predefined attribute, and it is highly robust because of the proposed statistical approach. The proposed framework was targeted to detect attacks that increase the number of activities on the network server, examples which include Distributed Denial of Service (DDoS) and, flood and flash-crowd events. This paper provides a mathematical foundation for SCoDe, describing the specific implementation and testing of the approach based on a network log file generated from the cyber range simulation experiment of the industrial partner of this project.

Structural damage identification based on self-fitting ARMAX model and multi-sensor data fusion

Statistical time series methods have proven to be a promising technique in structural health monitoring, since it provides a direct form of data analysis and eliminates the requirement for domain transformation. Latest research in structural health monitoring presents a number of statistical models that have been successfully used to construct quantified models of vibration response signals. Although a majority of these studies present viable results, the aspects of practical implementation, statistical model construction and decision-making procedures are often vaguely defined or omitted from presented work. In this article, a comprehensive methodology is developed, which essentially utilizes an auto-regressive moving average with exogenous input model to create quantified model estimates of experimentally acquired response signals. An iterative self-fitting algorithm is proposed to construct and fit the auto-regressive moving average with exogenous input model, which is capable of integrally finding an optimum set of auto-regressive moving average with exogenous input model parameters. After creating a dataset of quantified response signals, an unlabelled response signal can be identified according to a 'closest-fit' available in the dataset. A unique averaging method is proposed and implemented for multi-sensor data fusion to decrease the margin of error with sensors, thus increasing the reliability of global damage identification. To demonstrate the effectiveness of the developed methodology, a steel frame structure subjected to various bolt-connection damage scenarios is tested. Damage identification results from the experimental study suggest that the proposed methodology can be employed as an efficient and functional damage identification tool. © The Author(s) 2014.

The incidence of V˙O2 plateau at V˙O2max in a cardiac-diseased population

We sought to determine the incidence of V˙O(2) plateau at V˙O(2)max in a cardiovascular-diseased (CVD) population using 4 different sampling intervals (15-breath moving average, 15 s, 30 s, and 60 s) and 3 different V˙O(2) plateau criteria (≤50 mL · min(-1), ≤80 mL · min(-1), and ≤150 mL · min(-1)). A total of 69 people (62 ± 10 yrs.) with recently diagnosed CVD performed a maximal exercise test (10:07 ± 2:24 min) on a treadmill. The test was classified as maximal (n = 57, 2 430 ± 605 mL · min(-1)) if self-terminated due to fatigue or classified as symptom-limited (n = 12, 1 683 ± 438 mL · min(-1)) if symptoms presented. Chi-square analysis revealed a significant (p < 0.05) effect of sampling interval on incidence of V˙O(2) plateau at V˙O(2)max across all 3 V˙O(2) plateau criteria. The sampling interval had an increasingly stronger influence on the incidence of V˙O(2) plateau at V˙O(2)max with smaller criterion thresholds as evidenced by the Cramer's V statistics: [≤50 mL · min(-1) (Cramer's V = 0.548, p < 0.05], ≤80 mL · min(-1) [Cramer's V = 0.489, p < 0.05], ≤150 mL · min(-1) [Cramer's V = 0.214, p < 0.05]. Incidence of V˙O(2) plateau at V˙O(2)max in CVD individuals is significantly influenced by the sampling interval applied. Based on our findings we recommend a15 breath moving average and V˙O(2) plateau criterion of ≤50 mL · min(-1).

RSSI-based localization of a wireless sensor node with a flying robot

We consider the problem of navigating a ying robot to a specific sensor node within a wireless sensor network. This target sensor node periodically sends out beacons. The robot is capable of sensing the received signal strength of each received beacon (RSSI measurements). Existing approaches for solving the sensor spotting problem with RSSI measurements do not deal with noisy channel conditions and/or heavily depend on additional hardware capabilities. In this work we reduce RSSI uctuations due to noise by continuously sampling RSSI values and maintaining an exponential moving average (EMA). The EMA values enable us to detect significant decrease of the received signal strength. In this case it is reasoned that the robot is moving away from the sensor. We present two basic variants to decide a new moving direction when the robot moves away from the sensor. Our simulations show that our approaches outperform competing algorithms in terms of success rate and ight time. Infield experiments with real hardware, a ying robocopter successfully and quickly landed near a sensor placed in an outdoor test environment. Traces show robustness to additional environmental factors not accounted for in our simulations.

Multivariate adaptive autoregressive modeling and kalman filtering for motor imagery BCI

Adaptive autoregressive (AAR) modeling of the EEG time series and the AAR parameters has been widely used in Brain computer interface (BCI) systems as input features for the classification stage. Multivariate adaptive autoregressive modeling (MVAAR) also has been used in literature. This paper revisits the use of MVAAR models and propose the use of adaptive Kalman filter (AKF) for estimating the MVAAR parameters as features in a motor imagery BCI application. The AKF approach is compared to the alternative short time moving window (STMW) MVAAR parameter estimation approach. Though the two MVAAR methods show a nearly equal classification accuracy, the AKF possess the advantage of higher estimation update rates making it easily adoptable for on-line BCI systems.

Moving beyond mateship:reconstructing Australian men's practices

In this chapter I will explore the implications of the definitively Australian
style of masculine behaviour called 'mateship' for gender relations in
Australia. Mateship is part of the Australian male heritage; it originated in
colonial days and was glorified in war and sport. The feminist movement
in Australia has challenged the dominant form of masculinity inherent in
mateship and the basic rationale for gender relations that flow from it. In
this context, I will discuss Australian profeminist men's attempts to challenge patriarchal gender relations and construct non-patriarchal subjectivities and practices. Theorizing about masculinity in Australia has tended to be derivative of overseas literature. This is partly because publishers are looking for overseas markets for their books so they discourage writers on masculinity from grounding men's practices in a specifically Australian context. While there are benefits in generalizing about western masculinities, such writing misses the uniqueness of the lived experiences of Australian men. It is this uniqueness that I will address in this chapter. As McGrane and Patience (1995: 15) note, 'Australian masculinism has a history of its own that needs to be recognized at the same time as it can be usefully compared to the masculinisms of similar cultures'.

Visual perception of movement kinematics and the acquisition of "action prototypes"

Recognizing a class of movements as belonging to a "nominal" action category, such as walking, running, or throwing, is a fundamental human ability. Three experiments were undertaken to test the hypothesis that common ("prototypical") features of moving displays could be learned by observation. Participants viewed moving stick-figure displays resembling forearm flexion movements in the saggital plane. Four displays (presentation displays) were first presented in which one or more movement dimensions were combined with 2 respective cues: direction (up, down), speed (fast, slow), and extent (long, short). Eight test displays were then shown, and the observer indicated whether each test display was like or unlike those previously seen. The results showed that without corrective feedback, a single cue (e.g., up or down) could be correctly recognized, on average, with the proportion correct between .66 and .87. When two cues were manipulated (e.g., up and slow), recognition accuracy remained high, ranging between .72 and .89. Three-cue displays were also easily identified. These results provide the first empirical demonstration of action-prototype learning for categories of human action and show how apparently complex kinematic patterns can be categorized in terms of common features or cues. It was also shown that probability of correct recognition of kinematic properties was reduced when the set of 4 presentation displays were more variable with respect to their shared kinematic property, such as speed or amplitude. Finally, while not conclusive, the results (from 2 of the 3 experiments) did suggest that similarity (or "likeness") with respect to a common kinematic property (or properties) is more easily recognized than dissimilarity.

Moving personal tax online: the Australian Taxation Office's E-Tax initiative

In exploiting the capabilities of online technologies, governments have developed policies and launched projects to conduct transactions and deliver their services through the Internet. The motivations for this include cost cutting, efficiency improvements, service enhancements, and leadership in business transformation. However, these diverse goals are not necessarily consistent, especially in the early stages of implementation. The e-government initiative discussed in this case study (E-Tax) provided an additional service to individual Australian taxpayers by enabling them to file their tax returns online. This case study provides an analysis of the E-Tax implementation in the first three years of its operation. Data on E-Tax use compared to other filing methods show that the package worked well technically, was favorably received by users, and was consistent with policy on e-government. However, adoption levels in the early stages did not meet government targets. The analysis suggests that impediments to a greater level of E-Tax use included entrenched patterns of filing, the nature of the taxation system, and political sensitivities. The E-Tax case demonstrates how complex e-government projects can be and the need to take contextual factors into account in planning and evaluating e-government implementation.

Moving from the quality of life concept to a theory

BACKGROUND: The Special Interest Quality of Life Group has updated its set of statements defining the quality of life (QOL) construct to reflect emerging areas of agreement and the framework for understanding better the QOL construct.
METHOD: This article examines the major areas currently under discussion involving the objective-subjective dichotomy, needs, and core domains.
RESULTS: It is concluded that while the new statements constitute a significant advance, further progress requires testable theory. In order to facilitate such future research, a conceptual model is proposed that distinguishes causal and indicator variables within the framework of a homeostatic management system.
CONCLUSION: Several lines of empirical investigation are suggested to test this and similar theoretical models with a view to taking our conceptualization of QOL to the next level.

Moving towards a model of professional identity formation in midwifery through conversations and positioning theory

The disciplines of nursing and midwifery both uphold a powerful oral tradition that can impact upon student learning. Students enrolled in a Graduate Diploma of Midwifery are supervised and assessed by midwives during their placements in midwifery practice settings by a program of 'preceptorship' support and where conversations are innate. Positioning theory, eveloped by Harre and others, is a metaphorical concept in which an individual 'positions' herself/himself within entities of encompassing people, institutions and societies where conversations are conducted either privately or publicly. As construction sites of professional learning, conversations are underpinned by reflective practices.In unravelling conversations, positioning may be applied as an analytical tool by educators to interpret the emerging meanings and themes in their discussions with students, reflective journals by students and in meetings with preceptors/midwives.

How ophthlamic day surgery patients convalesce at home : an exploration of the salient issues

Cataract surgery is the most commonly performed surgical procedure in Australia. In the next 10-15 years, the number of people needing this surgery is expected to double, This article is based on a study, which explored the types and levels of symptoms experienced by patients post-ophthalmic surgery. Patients were asked to complete two instruments: a 'Postoperative Symptoms Diary' and a follow up 'Telephone Survey Questionnaire'. Eight males and 15 females (n = 23) with a mean age of 80.5 years were recruited. The findings revealed that patients' symptom levels decreased over time, except for tiredness and moving around which increased slightly on Day 4 post-operatively. A carer was required for an average of 2.3 days. This study highlighted the discrepancies in current day surgery literature, which recommend that a carer is needed during only the first 24 hours post-operatively.

Robust control applied to metal spraying for rapid tooling

The spray forming process is a novel method of rapidly manufacturing tools and dies for stamping and injection operations. The process sprays molten tool steel from a set of arc spray guns onto a ceramic former to build up a thick steel shell. The volumetric contraction that occurs as the steel cools is offset by a volumetric expansion taking place within the sprayed steel, which allows the dimensional accurate tools to be produced. To ensure that the required phase transformation takes place, the temperature of the steel is regulated during spraying. The sprayed metal acts both as a source of mass and a source of heat and by adjusting the rate at which metal is sprayed; the surface temperature profile over the surface of the steel can be controlled. The temperature profile is measured using a thermal imaging camera and regulated by adjusting the rate at which the guns spray the steel. Because the temperature is regulated by adjusting the feed rate to an actuator that is moving over the surface, this is an example of mobile control, which is a class of distributed parameter control. The dynamic system has been controlled using a PI controller before. The paper describes the application of H∞ tracking type controller as the desire was for the average temperature to follow a desired profile. A study on the controllability of the underlying system was aimed at.

A preliminary meta-analysis of SME ebusiness journal publications: current trends and future research opportunities moving beyond adoption factor studies

Previous meta-analyses of SME-eBusiness journal research focuses on analysing adoption factors, pre-2000 articles and a small number of journals. This paper departs from this research by analysing 100 articles published between 2003 and 2006 in 41 journals on the basis of the research approaches employed, countries and eBusiness technologies studied, and research objectives focused upon. The paper presents preliminary insights into current major research trends based on this analysis, such as the predominant focus on adoption factor by many studies. It also identifies future research opportunities, and proposes a research agenda which aims to progress SME-eBusiness research beyond adoption factor studies by outlining research objectives to help SMEs overcome barriers and exploit drivers.