Design of light gauge steel roofing systems subject to high wind forces

Light gauge steel roofing systems made of thin profiled roof sheeting and battens are used commonly in residential, industrial and commercial buildings. Their critical design load combination is that due to wind uplift forces that occur during high wind events such as tropical cyclones and thunderstorms. However, premature local failures at their screw connections have been a concern for many decades since cyclone Tracy that devastated Darwin in 1974. Extensive research that followed cyclone Tracy on the pull-through and pull-out failures of roof sheeting to batten connections has significantly improved the safety of roof sheeting. However, this has made the batten to rafter/truss connection the weakest, and recent wind damage investigations have shown the failures of these connections and the resulting loss of entire roof structures. Therefore an experimental research program using both small scale and full scale air-box tests is currently under way to investigate the pull-through failures of thin-walled steel battens under high wind uplift forces. Tests have demonstrated that occurrence of pull-through failures in the bottom flanges of steel batttens and the need to develop simple test and design methods as a function of many critical parameters such as steel batten geometry, thickness and grade, screw fastener sizes and other fastening details. This paper presents the details of local failures that occur in light fauge roofing systems, a review of the current design and test methods for steel battens and associated short comings, and the test results obtained to date on pull-through failures of battens from small scale and full scale tests. Finally, it proposes the use of suitable small scale test methods that can be used by both researchers and manufacturers of such screw-fastened light gauge steel batten systems.

Beyond tasks and gateways: discovering BPMN models with subprocesses, boundary events and activity markers

Existing techniques for automated discovery of process models from event logs largely focus on extracting flat process models. In other words, they fail to exploit the notion of subprocess, as well as structured error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of BPMN models containing subprocesses, interrupting and non-interrupting boundary events, and loop and multi-instance markers. The technique analyzes dependencies between data attributes associated with events, in order to identify subprocesses and to extract their associated logs. Parent process and subprocess models are then discovered separately using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. A validation with one synthetic and two real-life logs shows that process models derived using the proposed technique are more accurate and less complex than those derived with flat process model discovery techniques.

High-frequency global navigation satellite system’s receivers for airborne gravimetry

The development of global navigation satellite systems (GNSS) provides a solution of many applied problems with increasingly higher quality and accuracy nowadays. Researches that are carried out by the Bavarian Academy of Sciences and Humanities in Munich (BAW) in the field of airborne gravimetry are based on sophisticated data processing from high frequency GNSS receiver for kinematic aircraft positioning. Applied algorithms for inertial acceleration determination are based on the high sampling rate (50Hz) and on reducing of such factors as ionosphere scintillation and multipath at aircraft /antenna near field effects. The quality of the GNSS derived kinematic height are studied also by intercomparison with lift height variations collected by a precise high sampling rate vertical scale [1]. This work is aimed at the ways of more accurate determination of mini-aircraft altitude by means of high frequency GNSS receivers, in particular by considering their dynamic behaviour.

Further development of discrete computational techniques for calculation of restricted diffusion propagators in porous media

Magnetic resonance is a well-established tool for structural characterisation of porous media. Features of pore-space morphology can be inferred from NMR diffusion-diffraction plots or the time-dependence of the apparent diffusion coefficient. Diffusion NMR signal attenuation can be computed from the restricted diffusion propagator, which describes the distribution of diffusing particles for a given starting position and diffusion time. We present two techniques for efficient evaluation of restricted diffusion propagators for use in NMR porous-media characterisation. The first is the Lattice Path Count (LPC). Its physical essence is that the restricted diffusion propagator connecting points A and B in time t is proportional to the number of distinct length-t paths from A to B. By using a discrete lattice, the number of such paths can be counted exactly. The second technique is the Markov transition matrix (MTM). The matrix represents the probabilities of jumps between every pair of lattice nodes within a single timestep. The propagator for an arbitrary diffusion time can be calculated as the appropriate matrix power. For periodic geometries, the transition matrix needs to be defined only for a single unit cell. This makes MTM ideally suited for periodic systems. Both LPC and MTM are closely related to existing computational techniques: LPC, to combinatorial techniques; and MTM, to the Fokker-Planck master equation. The relationship between LPC, MTM and other computational techniques is briefly discussed in the paper. Both LPC and MTM perform favourably compared to Monte Carlo sampling, yielding highly accurate and almost noiseless restricted diffusion propagators. Initial tests indicate that their computational performance is comparable to that of finite element methods. Both LPC and MTM can be applied to complicated pore-space geometries with no analytic solution. We discuss the new methods in the context of diffusion propagator calculation in porous materials and model biological tissues.

Retrieving trip information from a discrete detectors network : The case of Brisbane Bluetooth detectors

Automatic Vehicle Identification Systems are being increasingly used as a new source of travel information. As in the last decades these systems relied on expensive new technologies, few of them were scattered along a networks making thus Travel-Time and Average Speed estimation their main objectives. However, as their price dropped, the opportunity of building dense AVI networks arose, as in Brisbane where more than 250 Bluetooth detectors are now installed. As a consequence this technology represents an effective means to acquire accurate time dependant Origin Destination information. In order to obtain reliable estimations, however, a number of issues need to be addressed. Some of these problems stem from the structure of a network made out of isolated detectors itself while others are inherent of Bluetooth technology (overlapping detection area, missing detections,\...). The aim of this paper is threefold: First, after having presented the level of details that can be reached with a network of isolated detectors we present how we modelled Brisbane's network, keeping only the information valuable for the retrieval of trip information. Second, we give an overview of the issues inherent to the Bluetooth technology and we propose a method for retrieving the itineraries of the individual Bluetooth vehicles. Last, through a comparison with Brisbane Transport Strategic Model results, we highlight the opportunities and the limits of Bluetooth detectors networks. The aim of this paper is twofold. We first give a comprehensive overview of the aforementioned issues. Further, we propose a methodology that can be followed, in order to cleanse, correct and aggregate Bluetooth data. We postulate that the methods introduced by this paper are the first crucial steps that need to be followed in order to compute accurate Origin-Destination matrices in urban road networks.

Evolution of self-reporting methods for identifying discrete emotions in science classrooms

Emotion researchers have grappled with challenging methodological issues in capturing emotions of participants in naturalistic settings such as school or university classrooms. Self-reporting methods have been used frequently, yet these methods are inadequate when used alone. We argue that the self-reporting methods of emotion diaries and cogenerative dialogues can be helpful in identifying in-the-moment emotions when used in conjunction with the microanalysis of video recordings of classroom events. We trace the evolution of our use of innovative self-reporting methods through three cases from our research projects, and propose new directions for our ongoing development and application of these methods in both school and university classrooms.

Design of steel roof and wall cladding systems for pull-out failures

When thin steel roof and wall cladding systems are subjected to wind uplift/suction forces, local pull-through or pull-out failures occur prematurely at their screwed connections. During high wind events such as stom1s and cyclones, these localized failures then lead to severe damage to buildings and their contents. In recent times, the use of thin steel battens, purlins and girts has increased considerably, which has made the pull-out failures more critical in the design of steel cladding systems. An experimental investigation was therefore carried out to study the pull-out failure using both static and cyclic tests for a range of commonly used screw fasteners and steel battens, purlins and girts. This paper presents the details ofthis experimental investigation and its results.

A process mining-based investigation of adverse events in care processes

This paper proposes the Clinical Pathway Analysis Method (CPAM) approach that enables the extraction of valuable organisational and medical information on past clinical pathway executions from the event logs of healthcare information systems. The method deals with the complexity of real-world clinical pathways by introducing a perspective-based segmentation of the date-stamped event log. CPAM enables the clinical pathway analyst to effectively and efficiently acquire a profound insight into the clinical pathways. By comparing the specific medical conditions of patients with the factors used for characterising the different clinical pathway variants, the medical expert can identify the best therapeutic option. Process mining-based analytics enables the acquisition of valuable insights into clinical pathways, based on the complete audit traces of previous clinical pathway instances. Additionally, the methodology is suited to assess guideline compliance and analyse adverse events. Finally, the methodology provides support for eliciting tacit knowledge and providing treatment selection assistance.

Tracking the patient journey by combining multiple hospital database systems

With new national targets for patient flow in public hospitals designed to increase efficiencies in patient care and resource use, better knowledge of events affecting length of stay will support improved bed management and scheduling of procedures. This paper presents a case study involving the integration of material from each of three databases in operation at one tertiary hospital and demonstrates it is possible to follow patient journeys from admission to discharge. What is known about this topic? At present, patient data at one Queensland tertiary hospital are assembled in three information systems: (1) the Hospital Based Corporate Information System (HBCIS), which tracks patients from in-patient admission to discharge; (2) the Emergency Department Information System (EDIS) containing patient data from presentation to departure from the emergency department; and (3) Operation Room Management Information System (ORMIS), which records surgical operations. What does this paper add? This paper describes how a new enquiry tool may be used to link the three hospital information systems for studying the hospital journey through different wards and/or operating theatres for both individual and groups of patients. What are the implications for practitioners? An understanding of the patients’ journeys provides better insight into patient flow and provides the tool for research relating to access block, as well as optimising the use of physical and human resources.

Runoff, soil loss, and nutrient transport from cropping systems on Red Ferrosols in tropical northern Australia.

Runoff, soil loss, and nutrient loss were assessed on a Red Ferrosol in tropical Australia over 3 years. The experiment was conducted using bounded, 100-m(2) field plots cropped to peanuts, maize, or grass. A bare plot, without cover or crop, was also instigated as an extreme treatment. Results showed the importance of cover in reducing runoff, soil loss, and nutrient loss from these soils. Runoff ranged from 13% of incident rainfall for the conventional cultivation to 29% under bare conditions during the highest rainfall year, and was well correlated with event rainfall and rainfall energy. Soil loss ranged from 30 t/ha. year under bare conditions to <6 t/ha. year under cropping. Nutrient losses of 35 kg N and 35 kg P/ha. year under bare conditions and 17 kg N and 11 kg P/ha. year under cropping were measured. Soil carbon analyses showed a relationship with treatment runoff, suggesting that soil properties influenced the rainfall runoff response. The cropping systems model PERFECT was calibrated using runoff, soil loss, and soil water data. Runoff and soil loss showed good agreement with observed data in the calibration, and soil water and yield had reasonable agreement. Longterm runs using historical weather data showed the episodic nature of runoff and soil loss events in this region and emphasise the need to manage land using protective measures such as conservation cropping practices. Farmers involved in related, action-learning activities wished to incorporate conservation cropping findings into their systems but also needed clear production benefits to hasten practice change.

Detecting rare events using Kullback-Leibler divergence: A weakly supervised approach

Video surveillance infrastructure has been widely installed in public places for security purposes. However, live video feeds are typically monitored by human staff, making the detection of important events as they occur difficult. As such, an expert system that can automatically detect events of interest in surveillance footage is highly desirable. Although a number of approaches have been proposed, they have significant limitations: supervised approaches, which can detect a specific event, ideally require a large number of samples with the event spatially and temporally localised; while unsupervised approaches, which do not require this demanding annotation, can only detect whether an event is abnormal and not specific event types. To overcome these problems, we formulate a weakly-supervised approach using Kullback-Leibler (KL) divergence to detect rare events. The proposed approach leverages the sparse nature of the target events to its advantage, and we show that this data imbalance guarantees the existence of a decision boundary to separate samples that contain the target event from those that do not. This trait, combined with the coarse annotation used by weakly supervised learning (that only indicates approximately when an event occurs), greatly reduces the annotation burden while retaining the ability to detect specific events. Furthermore, the proposed classifier requires only a decision threshold, simplifying its use compared to other weakly supervised approaches. We show that the proposed approach outperforms state-of-the-art methods on a popular real-world traffic surveillance dataset, while preserving real time performance.

Population genetics of Australian white sharks reveals fine-scale spatial structure, transoceanic dispersal events and low effective population sizes

Despite international protection of white sharks Carcharodon carcharias, important conservation parameters such as abundance, population structure and genetic diversity are largely unknown. The tissue of 97 predominately juvenile white sharks sampled from spatially distant eastern and southwestern Australian coastlines was sequenced for the mitochondrial DNA (mtDNA) control region and genotyped with 6 nuclear-encoded microsatellite loci. MtDNA population structure was found between the eastern and southwestern coasts (F-ST = 0.142, p < 0.0001), implying female reproductive philopatry. This concurs with recent satellite and acoustic tracking findings which suggest the sustained presence of discrete east coast nursery areas. Furthermore, population subdivision was found between the same regions with biparentally inherited micro satellite markers (F-ST = 0.009, p < 0.05), suggesting that males may also exhibit some degree of reproductive philopatry; 5 sharks captured along the east coast had mtDNA haplotypes that resembled western Indian Ocean sharks more closely than Australian/New Zealand sharks, suggesting that transoceanic dispersal, or migration resulting in breeding, may occur sporadically. Our most robust estimate of contemporary genetic effective population size was low and close to thresholds at which adaptive potential may be lost. For a variety of reasons, these contemporary estimates were at least 1, possibly 2, orders of magnitude below our historical effective size estimates. Population decline could expose these genetically isolated populations to detrimental genetic effects. Regional Australian white shark conservation management units should be implemented until genetic population structure, size and diversity can be investigated in more detail.

Periodic oscillations in feedback systems with combined pulse modulation

This paper presents a systematic method of investigating the existence of limit cycle oscillations in feedback systems with combined integral pulse frequency-pulse width (IPF-P/V) modulation. The method is based on the non-linear discrete equivalence of the continuous feedback system containing the IPF-PW modulator.

Output feedback control of networked systems with a stochastic communication protocol

This paper addresses an output feedback control problem for a class of networked control systems (NCSs) with a stochastic communication protocol. Under the scenario that only one sensor is allowed to obtain the communication access at each transmission instant, a stochastic communication protocol is first defined, where the communication access is modelled by a discrete-time Markov chain with partly unknown transition probabilities. Secondly, by use of a network-based output feedback control strategy and a time-delay division method, the closed-loop system is modeled as a stochastic system with multi time-varying delays, where the inherent characteristic of the network delay is well considered to improve the control performance. Then, based on the above constructed stochastic model, two sufficient conditions are derived for ensuring the mean-square stability and stabilization of the system under consideration. Finally, two examples are given to show the effectiveness of the proposed method.

Lipid assisted membrane entry in specific phospholipid targeted protein systems

The purpose of this thesis project is to study changes in the physical state of cell membranes during cell entry, including how these changes are connected to the presence of ceramide. The role of enzymatical manipulation of lipids in bacterial internalization is also studied. A novel technique, where a single giant vesicle is chosen under the microscope and an enzyme coupled-particle attached to the micromanipulator pipette towards the vesicle, is used. Thus, the enzymatic reaction on the membrane of the giant vesicle can be followed in real-time. The first aim of this study is to develop a system where the localized sphingomyelinase membrane interaction could be observed on the surface of the giant vesicle and the effects could be monitored with microscopy. Domain formation, which resembles acid sphingomyelinase (ASMase), causes CD95 clustering in the cell membrane due to ceramide production (Grassmé et al., 2001a; Grassmé et al., 2001b) and the formation of small vesicles inside the manipulated giant vesicle is observed. Sphingomyelinase activation has also been found to be an important factor in the bacterial and viral invasion process in nonphagocytic cells (Grassmé et al., 1997; Jan et al., 2000). Accordingly, sphingomyelinase reactions in the cell membrane might also give insight into bacterial or viral cellular entry events. We found sphingomyelinase activity in Chlamydia pneumonia elementarybodies (EBs). Interestingly, the bacterium enters host cells by endocytosis but the internalization mechanism of Chlamydia is unknown. The hypothesis is that sphingomyelin is needed for host cell entry in the infection of C. pneumonia. The second project focuses on this subject. The goal of the third project is to study a role of phosphatidylserine as a target for a membrane binding protein. Phosphatidylserine is chosen because of its importance in fusion processes. This will be another example for the importance of lipids in cell targeting, internalization, and externalization.